Myocardial injury evaluation method, apparatus, sample analysis system, and its applications

Abstract

This application relates to a method, apparatus, and sample analysis system for evaluating myocardial injury and its applications. The method, apparatus, and sample analysis system can rapidly and accurately assess the etiology and risk of myocardial injury in an individual and guide diagnostic and treatment decisions.

Description

[Technical Field]

[0001] This application is based on and claims priority to the application with CN application number 202311024062.1, filed on 14 August 2023, and the disclosures of said CN application are incorporated into this application as a whole.

[0002] (Technical field) This application belongs to the field of disease diagnosis and specifically relates to the manufacture of kits for a method of in vitro evaluation of myocardial damage in a subject, an apparatus for acquiring characteristic parameters for evaluating myocardial damage in a subject, a sample analysis system, and reagents for quantitative detection of large cardiac troponin ternary complex and / or reagents for quantitative detection of total cardiac troponin ternary complex. [Background technology]

[0003] Cardiovascular disease poses a serious threat to human health. In China, the incidence and mortality rates of cardiovascular disease are increasing year by year. Chest pain is a common symptom of various cardiovascular diseases, accompanied by diverse clinical manifestations and usually associated with shortness of breath. The risk of acute, fatal chest pain is extremely high. Accurate risk stratification and diagnosis of chest pain patients in emergency departments, and the establishment of rapid and rational diagnostic procedures, are crucial for proper management and customized treatment decisions. Differentiating the causes of chest pain, particularly acute and non-acute myocardial injury, has significant clinical importance and is an urgent clinical need.

[0004] Cardiac troponin (cTn) is a highly specific and sensitive biomarker for myocardial injury and is widely used to detect myocardial injury after or during myocardial infarction.

[0005] Cardiac troponin consists of three subunits: cardiac troponin I (cTnI), cardiac troponin T (cTnT), and troponin C (TnC). Serum concentrations of cTnI and cTnT are strongly associated with the severity of myocardial injury. Troponin normally binds to actin filaments in the form of a ternary complex (cTnITC). During myocardial injury, troponin is broken down from myofilaments and released into the bloodstream. Intracellularly and in the blood circulation, cTnITC is broken down into different forms by proteases. Studies have shown that the form of troponin present in the blood may be related to the physiological and pathological state of an individual.

[0006] A deep understanding of the different forms of troponin and their association with disease, correctly deciphering the causes of elevated cTn levels, and distinguishing between acute and nonacute myocardial injury are crucial for rapid stratification and accurate clinical diagnosis of chest pain patients. [Overview of the project]

[0007] To solve the above technical problems, in a first aspect, the present application provides a method for evaluating myocardial damage in a subject in vitro, the method being: To detect the content of one or more myocardial injury markers in a sample from the subject, Based on the content of one or more of the aforementioned myocardial injury markers, characteristic parameters for evaluating myocardial injury are obtained. The characteristic parameter is compared with a reference value for the characteristic parameter, This includes evaluating the myocardial damage of the subject based on the results of the comparison, Here, the one or more myocardial injury markers include the large-size cardiac troponin ternary complex (large-size cTnITC, large-size ITC complex) and / or the total cardiac troponin ternary complex (total cTnITC, total ITC complex). The large-size cardiac troponin ternary complex may also be called the long cardiac troponin ternary complex (long cTnITC, long ITC complex).

[0008] In a second aspect, the present application provides an apparatus for acquiring characteristic parameters for evaluating myocardial damage in a subject, the apparatus comprising: A data receiving module configured to receive the content of one or more myocardial injury markers obtained from a sample from a subject, wherein the one or more myocardial injury markers include large cardiac troponin ternary complex and / or total cardiac troponin ternary complex, A data processing module is configured to process the content data of one or more myocardial injury markers received by the receiving module and to obtain characteristic parameters for evaluating myocardial injury. It includes an output module configured to output the aforementioned feature parameters.

[0009] In a third aspect, the present application provides a sample analysis system, the system is A sample placement section for placing a container containing a sample of the subject, A sample dispensing unit for drawing up the subject's sample from the sample placement unit and discharging it into the cuvette where the sample should be placed, A reagent placement section for placing detection reagents, A reagent dispensing section for drawing detection reagent from the reagent placement section and discharging it into the cuvette to which the reagent should be added, a reaction section for placing a cuvette and incubating a test solution obtained by a reaction between a sample of a subject in the cuvette and a detection reagent, a detection section which comprises a signal detector, detects a signal of the test solution in the cuvette, and measures and outputs the content of one or more myocardial injury markers in the sample of the subject, wherein the one or more myocardial injury markers comprise a large cardiac troponin ternary complex and / or a total cardiac troponin ternary complex, a data processing section comprising a processor and a computer-readable storage medium storing computer-readable instructions, wherein when the computer-readable instructions are executed by the processor, the instructions cause the processor to perform: receiving and processing the content of said one or more myocardial injury markers to obtain characteristic parameters for evaluating myocardial injury; and outputting said characteristic parameters.

[0010] In a fourth aspect, the present application provides use of a reagent for quantitative detection of large cardiac troponin ternary complex and / or a reagent for quantitative detection of total cardiac troponin ternary complex in a sample in manufacture of a kit, wherein said kit is used for evaluating myocardial injury in a subject.

[0011] In a fifth aspect, the present application provides a reagent for quantitative detection of large cardiac troponin ternary complex and / or a reagent for quantitative detection of total cardiac troponin ternary complex in a sample, which is used for evaluating myocardial injury in a subject.

[0012] In each aspect of the present application, the characteristic parameters obtained based on the content of large cardiac troponin ternary complex and / or total cardiac troponin ternary complex can be used to evaluate myocardial injury more rapidly and more accurately. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The drawings described herein are for further understanding of the present invention, and constitute a part of the present application. The exemplary embodiments of the present invention and the description thereof are for interpreting the present invention, and do not improperly limit the present invention. In the drawings, [Figure 1] it is a schematic block diagram of an apparatus for acquiring characteristic parameters for evaluating myocardial injury in a subject provided according to an embodiment of the present application. [Figure 2] it is a schematic diagram of a sample analysis system according to an embodiment of the present application. [Figure 3] it is a signal-to-noise ratio analysis for large cTnITC detection kits, and the signal-to-noise ratio data of samples in each group corresponds to Kit 1 to Kit 8 in order from left to right. [Figure 4] it is a signal-to-noise ratio analysis for total cTnITC detection kits, and the signal-to-noise ratio data of samples in each group corresponds to Kit 1 to Kit 12 in order from left to right. [Figure 5] this is the result of verifying the specificity of the large cTnITC detection kit using serum samples. [Figure 6] this is the result of verifying the specificity of the total cTnITC detection kit using serum samples. [Figure 7] it is a linear analysis for large cTnITC detection kit 3. [Figure 8] it is a linear analysis for large cTnITC detection kit 4. [Figure 9] it is a linear analysis for total cTnITC detection kit 3. [Figure 10] it is a linear analysis for total cTnITC detection kit 4. [Figure 11] it is the enrollment and test flow of patients with early myocardial infarction. [Figure 12] it shows the ratios of large cTnITC / total complex, total cTnITC / total complex, and cTnT / total complex in patients with different chest pain durations. P values between groups were compared by the Kruskal-Wallis test. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001, ns, no significant difference. [Figure 13]These are the ratios of large cTnITC / total complex, total cTnITC / total complex, cTnT / total complex, large cTnITC / cTnT, and total cTnITC / cTnT in patients with type 1 and type 2 myocardial infarction. P-values ​​between type 1 and type 2 myocardial infarction were compared using the Mann-Whitney U test. *P<0.05, **P<0.01, ns, no significant difference. [Figure 14] This is the participation and trial flow for a patient with acute myocardial infarction (type 1) in Example 3-1. [Figure 15] This is the participation and trial flow for patients with chronic cardiac events (cardiomyopathy or chronic heart failure) in Example 3-1. [Figure 16] This is the participation and trial flow for a patient with a chronic cardiac event (pneumonia) in Example 3-1. [Figure 17] These are the ratios of large cTnITC / total complex, total cTnITC / total complex, cTnT / total complex, large cTnITC / cTnT, and total cTnITC / cTnT in acute myocardial infarction (type 1) and chronic cardiac event samples. Values ​​are shown as median ± interquartile range. P-values ​​between patients with acute myocardial infarction (type 1), cardiomyopathy or chronic heart failure, and pneumonia were compared using the Kruskal-Wallis test. **P<0.01, ***P<0.001, ****P<0.0001, ns, no significant difference. [Figure 18] This is the participation and trial flow for patients undergoing invasive procedures. [Figure 19] This is the participation and trial flow for patients with chronic cardiac events. [Figure 20] These are the ratios of large cTnITC / total complex, total cTnITC / total complex, cTnT / total complex, large cTnITC / cTnT, and total cTnITC / cTnT in patients with myocardial injury due to invasive treatment and patients with chronic cardiac events. Values ​​are shown as median ± interquartile range. P-values ​​between patients with chronic cardiac events, surgical patients, and interventional surgery patients were compared using the Kruskal-Wallis test. **P<0.01, ***P<0.001, ****P<0.0001, ns, no significant difference. [Figure 21] This is the participation and trial flow for patients undergoing cardiac surgery. [Figure 22] These are survival curves for cardiac surgery patients in different troponin fragment concentration groups. [Figure 23] This is the participation and trial flow for patients with acute myocardial infarction (type 1). [Figure 24] These are survival curves for patients with acute myocardial infarction (type 1) in different troponin fragment concentration groups. [Figure 25] This is the participation and trial flow for patients with chronic cardiac events (cardiomyopathy or chronic heart failure). [Figure 26] These are survival curves for patients with chronic cardiac events (cardiomyopathy or chronic heart failure) in different troponin fragment concentration groups. [Figure 27] This is the participation and trial flow for patients with acute chest pain suspected to be coronary artery syndrome.

[0014] The technical solutions in the embodiments are described clearly and completely below with reference to the drawings. Clearly, the embodiments described are only a part of the embodiments of the present invention, not all embodiments. The following descriptions of the embodiments are for illustrative purposes only and do not limit the present invention in any way. All other embodiments obtained based on the embodiments, without requiring any creative effort from those skilled in the art, are all within the scope of the protection of the present invention.

[0015] In this specification, unless otherwise specified, scientific and technical terms used have meanings generally understood by those skilled in the art. Furthermore, the immunological laboratory procedures used herein are all common procedures widely used in the relevant fields. In addition, to better understand the embodiments of the present invention, definitions and interpretations of relevant terms are provided below.

[0016] As used herein, the terms “include,” “incorporate,” or any other variation thereof encompass non-exclusive inclusion, thereby including not only the explicitly stated elements but also other elements not explicitly listed, or elements specific to carrying out the method or apparatus. Unless further limited, an element limited by the phrase “includes one…” does not preclude the existence of other related elements in the method or apparatus containing that element.

[0017] As used herein, the term “at least one” means one or more in reasonable terms, for example, two, three, four, five or ten.

[0018] As used herein, the terms “First” and “Second” are merely for distinguishing similar subjects and do not represent a particular order of subjects, and it should be understood that “First” and “Second” can be replaced in any particular order or sequence where permitted. Subjects distinguished by “First” and “Second” can be replaced where appropriate, and therefore, it should be understood that the embodiments of this application described herein can be carried out in a different order than those illustrated or described herein.

[0019] As used herein, the terms “individual” and “subject” preferably refer to a mammal. Mammals include, but are not limited to, domesticated animals (e.g., cattle, sheep, cats, dogs, and horses), primates (e.g., humans and non-human primates such as monkeys), rabbits, and rodents (e.g., mice and rats), but preferably humans. In some embodiments, in particular, there are patients with specific clinical symptoms, such as patients with chest pain.

[0020] As used herein, the term “specifically binding” refers to a non-random binding reaction between two molecules (i.e., a binding molecule and a target molecule), such as the reaction between an antibody and its target antigen. The binding affinity between the two molecules is K Dmay be described by a value. K D value refers to the dissociation constant obtained from the ratio of kd (the dissociation rate of a specific binding molecule-target molecule interaction, also called koff) to ka (the association rate of a specific binding molecule-target molecule interaction, also called kon), or refers to kd / ka expressed as molar concentration (M). K D the smaller the value is, the tighter the binding between the two molecules is, and the higher the affinity is. In some embodiments, an antibody that specifically binds to an antigen (or an antibody having specificity for an antigen) has about 10 -5 less than M, for example about 10 -6 less than M, 10 -7 less than M, 10 -8 less than M, 10 -9 less than M or 10 -10 less than M or lower K D refers to an antibody that binds to the antigen. Relevant methods for analyzing antibody specificity are described, for example, in the documents Harlow & Lane (1988) Antibodies: A Laboratory Manual, Cold Spring Harbor Laboratory Press and Harlow & Lane (1999) Using Antibodies: A Laboratory Manual, Cold Spring Harbor Laboratory Press. Non-limiting examples of applicable studies include binding studies using molecules that are structurally and / or functionally closely related, blocking studies and competition studies. These studies may be performed by methods such as fluorescence activated cell sorting (FACS) analysis, flow cytometry titration (FACS titration) analysis, surface plasmon resonance technology (e.g., SPR), isothermal titration calorimetry (ITC), fluorescence titration or radiolabeled ligand binding assay. More methods include, for example, Western Blot, ELISA (including competitive ELISA) assay, RIA assay, ECL assay and IRMA assay.

[0021] As used herein, the term “diagnosis” refers to a method by which a patient can be estimated and / or determined whether or not he or she suffers from a particular disease or condition.

[0022] As used herein, the term “prognosis” is typically determined by one or more markers or characteristic parameters. These markers or characteristic parameters indicate the probability of a particular outcome or process occurring.

[0023] As used herein, the terms “sample” refer to a body fluid or tissue sample of a subject, such as whole blood, serum, plasma (including heparinized lithium plasma and EDTA plasma), urine, saliva, biological tissue, or cells, and preferably whole blood, serum, or plasma.

[0024] As used herein, the terms “troponin” and “Tn” refer to proteins that regulate the calcium-mediated interaction between actin and myosin on actin filaments within muscle cells, are present in cardiac and skeletal muscle, and consist of three subunits: troponin T (TnT), troponin I (TnI), and troponin C (TnC). Here, TnT is the tropomyosin-binding subunit, which interacts with actin and tropomyosin; TnI is the inhibitory subunit, which inhibits the ATP enzyme activity of actomyosin; and TnC is the calcium-binding subunit, which enables the contraction of skeletal or cardiac muscle. The terms “cardiac troponin” and “cTn” refer to all troponin isoforms expressed in cardiac cells, preferably subendocardial cells. These isoforms have already been well characterized in this field, for example, as described by Anderson 1995, Circulation Research, vol. 76, no. 4: 681-686 and Ferrieres 1998, Clinical Chemistry, 44: 487-493. The term “cardiac troponin” further includes variants of a particular cardiac troponin, such variants possessing at least the same fundamental biological and immunological properties as the particular cardiac troponin. In particular, they share the same fundamental biological and immunological properties when detected by the same specific detection methods referred to herein. It should be understood that troponin isoforms may be measured together (simultaneously or sequentially) or individually (i.e., without measuring any other isoforms).

[0025] As used herein, the terms “cardiac troponin T” and “cTnT” refer to the cardiac troponin T subunit, whose amino acid sequence is disclosed in the UniProt database and is number P45379.

[0026] As used herein, the terms “cardiac troponin I” and “cTnI” refer to the cardiac troponin I subunit, whose amino acid sequence is disclosed in the UniProt database and is number P19429.

[0027] As used herein, the terms “troponin C” and “TnC” refer to the troponin C subunit, whose amino acid sequence is disclosed in the UniProt database and is number P63316.

[0028] As used herein, the term “cardiac troponin binary complex” includes a binary complex comprising the full-length protein of troponin C or any amino acid fragment thereof and the full-length protein of cardiac troponin I or any amino acid fragment thereof.

[0029] As used herein, the terms “large-size cardiac troponin ternary complex” or “large-size cTnITC (large-size ITC complex)” are interchangeable herein and are intended to include complexes formed from any full-length protein or fragment of any TnC, a full-length protein or fragment of cTnI, one or more segments of cTnT at amino acid residues 223–287, and one or more segments of cTnT at amino acid residues 1–222.

[0030] As used herein, the terms “total cardiac troponin ternary complex” or “total cTnITC (total ITC complex)” are interchangeable herein and are intended to include complexes formed from full-length proteins or fragments of all TnC, full-length proteins or fragments of cTnI, one or more segments of cTnT at amino acid residues 223–287, and one or more segments of optional cTnT at amino acid residues 1–222.

[0031] As used herein, the terms “total cardiac troponin complex” and “total complex” include the total cardiac troponin ternary complex, the full-length protein of troponin C or any amino acid fragment thereof, and the binary complex consisting of the full-length protein of cardiac troponin I or any amino acid fragment thereof.

[0032] Differential evaluation and diagnostic methods Cardiac troponin is a highly specific and sensitive biomarker for myocardial injury and is widely used to detect myocardial damage after or during myocardial infarction. However, current troponin analysis cannot distinguish between different types of myocardial injury, and there is still a lack of effective means in this field to evaluate myocardial injury, differentiate between different types of myocardial injury, and enable clinicians to rapidly and accurately diagnose an individual's pathological state and guide their prognosis.

[0033] A first aspect of this application provides a method for evaluating myocardial damage in a subject in vitro, the method being: To detect the content of one or more myocardial injury markers in a sample from the subject, Based on the content of one or more of the aforementioned myocardial injury markers, characteristic parameters for evaluating myocardial injury are obtained. The characteristic parameter is compared with a reference value for the characteristic parameter, This includes evaluating the myocardial damage of the subject based on the results of the comparison, Here, the one or more myocardial injury markers include the large cardiac troponin ternary complex and / or the total cardiac troponin ternary complex.

[0034] The term "myocardial injury" is well known in this field and refers to a pathological change in cardiac cells that results in abnormal findings in the heart. Patients may present with symptoms such as chest pain, palpitations, shortness of breath, and tachycardia. cTn is 99 th A value higher than the URL is diagnosed as myocardial injury; if accompanied by an increase or decrease, it is considered acute myocardial injury; and if the value is persistently elevated and the increase is <20%, it may indicate chronic myocardial injury. Myocardial injury can be observed in various cardiac and noncardiac diseases.

[0035] In this specification, the evaluation of myocardial injury includes diagnosis (e.g., diagnosis of etiology or type), classification (e.g., classification of the severity or stage of progression of myocardial injury), or monitoring (e.g., prognosis).

[0036] Differential assessment or diagnosis refers to a method of diagnosing a specific disease and / or condition in a particular individual based on a comparison of the observable characteristic properties of the individual with the characteristic properties of a potential disease, where the disease and / or condition underlies the symptoms of the particular individual. Depending on the range of diseases and conditions that must be considered in differential assessment or diagnosis, the types and number of experimental analyses that a physician must perform can be very numerous. For example, in the case of chest pain, a physician may select experimental analyses including physical examination, echocardiography, electrocardiogram recording, high-sensitivity troponin I detection, high-sensitivity troponin T detection, and coronary angiography. However, the physician must integrate the information obtained from a series of experiments to obtain a clinical diagnosis that most faithfully represents the range of symptoms and / or the results of the diagnostic experiments from the subject.

[0037] This application describes markers and characteristic parameters that can be used or supplementally used for the assessment of myocardial injury. By detecting the content of one or more myocardial injury markers in a sample and further obtaining characteristic parameters for assessing myocardial injury, the values ​​of these characteristic parameters are compared to those of individuals suffering from or at risk of a particular condition, or to those of individuals with known characteristics who do not suffer from the particular condition. Such comparison results are associated with a single assessment or diagnosis, thereby enabling corresponding action.

[0038] Myocardial injury markers and characteristic parameters In this application, the markers for evaluating myocardial injury include at least the large cardiac troponin ternary complex and / or the total cardiac troponin ternary complex. Depending on the diagnostic scenario applied, the markers may further include one or more of cTnI, cTnT, TnC, cardiac troponin binary complex and the total cardiac troponin complex.

[0039] The marker content is particularly preferably a concentration and may be determined by an immunoassay. Examples of such immunoassays include enzyme-linked immunosorbent assay (ELISA), enzyme-mediated immunoassay (EIA), radioimmunoassay (RIA), or immunoassays based on luminescence, fluorescence, chemiluminescence, or electrochemical emission. In some embodiments, quantitative detection of each marker is particularly preferably performed by an ELISA method, for example, using a commercially available ELISA kit.

[0040] Comparison with reference values "Comparison" refers to comparing a characteristic parameter obtained from a subject with its reference value. As used herein, "comparison" should generally refer to a comparison of the values ​​of the relevant characteristic parameter. Such comparison may be performed manually or with computer assistance. Therefore, the comparison may be performed by a computer device (e.g., an apparatus or analysis system disclosed herein). The characteristic parameter and the reference value may be compared with each other, for example, and such comparison may be performed automatically by a computer program that executes an algorithm for comparison. The computer program performing the evaluation provides the desired evaluation in an appropriate output format. In the case of computer-assisted comparison, the characteristic parameter may also be compared with a corresponding appropriate reference value, which is stored in a database by the computer program. The computer program can further evaluate the comparison results, i.e., automatically provide the desired evaluation in an appropriate output format.

[0041] Reference values ​​can be used to define and establish thresholds. Thresholds are preferably used for the evaluation / diagnosis of a subject, as described herein. The diagnosis or evaluation may be provided based on the calculated “value” and reference value or threshold by the data processing module of the apparatus or system described herein. For example, the data processing module of the system may provide an indicator that indicates the diagnosis or evaluation in the form of letters, symbols or numbers. The reference value applied to a subject is variable and is determined by the selected marker and its measurement method. Appropriate reference values ​​may be determined (i.e., simultaneously or sequentially) from the reference sample to be analyzed together with the test sample.

[0042] In principle, a reference level for a group of patients suffering from a specific disease or at least one abnormality, or those not suffering from the disease or abnormality, can be calculated using standard statistical methods based on the mean or median values ​​of specific markers. In some embodiments, statistical analysis is performed using Graphpad Prism, SPSS, and Excel software. Statistical significance between different subgroups is determined by analyzing the Mann-Whitney U test (used for comparisons between two groups) and the Kruskal-Wallis test (used for comparisons between multiple groups). A p-value < 0.05 indicates that the variable is significant.

[0043] Specifically, the accuracy of a test method (e.g., for a diagnostic event) is preferably described by a receiver operator characteristic curve (ROC) (see Zweig 1993, Clin. Chem. 39:561-577). The ROC curve is a curve plotted with true positive rate (TPR) on the y-axis and false positive rate (FPR) on the y-axis, based on a set of different binary classification schemes (cutoff thresholds). ROC_AUC (area under the curve) represents the area enclosed by the ROC curve and the horizontal axis. In some embodiments, the ROC curve is created using SPSS software, and the area under the curve (AUC) is obtained. Different TPRs and FPRs can be obtained by adjusting the threshold in the ROC curve. A larger threshold results in a smaller FPR and a larger TPR, and conversely, a larger FPR and a smaller TPR. The Youden's J statistic is a statistic used to evaluate the performance of a classifier, and is equal to TPR-FPR, i.e., sensitivity. The larger this value, the better the classifier's performance. In the ROC curve, the point where the Youden's J statistic takes its maximum value is called the Youden point, and the corresponding threshold is called the Youden threshold. In some embodiments, the Youden threshold is used as the optimal threshold point (CUTOFF value).

[0044] Depending on the desired confidence interval, the threshold may be derived from the ROC curve, which allows for diagnosing or predicting a given event using an appropriate balance of sensitivity and specificity. Therefore, the reference value used in the present invention may preferably be a threshold or a cutoff value, and preferably can be generated by establishing an ROC for the group as described above and deriving a threshold value therefrom. Depending on the desired sensitivity and specificity for the diagnostic method, the ROC plot allows for the deriving of an appropriate threshold.

[0045] The effectiveness of a diagnostic method and the predictive value of marker parameters for the primary endpoint event are described by a Subject Action Characteristic (ROC) curve. The ROC curve is plotted based on sensitivity and specificity obtained by continuously changing the judgment threshold within the observed data range. The Y-axis represents sensitivity, and the X-axis represents 1-specificity. The closer the curve is to the upper left corner, the higher the diagnostic accuracy. The area under the subject action curve (AUC) indicates the effectiveness or accuracy of the diagnosis. A significance test p-value < 0.05 indicates that the variable is significant. Since the ROC curve consists of multiple critical values ​​representing each sensitivity and specificity, the ROC curve can be used to select the optimal diagnostic boundary value for a given diagnostic method. The closer the ROC curve is to the upper left corner, the higher the sensitivity of the test, the lower the misjudgment rate, and the better the performance of the diagnostic method. For the point on the ROC curve closest to the upper left corner, the sum of sensitivity and specificity is maximized. The value corresponding to this point or a nearby point is often used as a diagnostic criterion (also called a diagnostic threshold, judgment threshold, or a set condition or set range).

[0046] In one embodiment, the term “reference value” may be a predetermined value. As those skilled in the art will understand, the reference value is predetermined and set to satisfy general requirements, for example, in terms of specificity and / or sensitivity. These requirements may vary, for example, between different administrative departments. For example, to measure sensitivity or specificity, several limit values ​​must be set, for example, 80%, 90%, 95%, or 98%, respectively. These requirements may impose limitations in terms of positive or negative predictive values. Nevertheless, based on the teachings of the present invention, it is easy to reach a reference value that satisfies these requirements. The reference value is taken from patients suffering from the disease or abnormality referred to herein, or from a severe or mild form thereof.

[0047] In some embodiments, the baseline was predetermined in a reference sample of the disease the subject was suffering from. In some embodiments, the baseline may be set to any percentage between 25% and 75% of the overall distribution of the characteristic parameter in the disease under study, for example. In some other embodiments, the baseline may be set to the median, ternary, or quartile determined based on the overall distribution of the reference sample of the disease under study, for example. In some embodiments, the baseline may be set to the median determined based on the overall distribution of the characteristic parameter in the disease under study. In some embodiments, continuous variables are shown as medians (25-75th percentiles), and taxonomic variables are shown as numbers (percentages).

[0048] In this application, characteristic parameters for evaluating myocardial damage may be selected from the content of large cardiac troponin ternary complex, the content of total cardiac troponin ternary complex, and combinations of the content of large cardiac troponin ternary complex and / or total cardiac troponin ternary complex with the content of other myocardial damage markers (e.g., cTnI, cTnT, or total cardiac troponin complex).

[0049] In some embodiments, obtaining characteristic parameters for evaluating myocardial damage based on the content of detected markers is possible. To determine the content of the aforementioned large cardiac troponin ternary complex or total cardiac troponin ternary complex as a characteristic parameter for evaluating myocardial damage, or Based on the content of the large cardiac troponin ternary complex and the content of the total cardiac troponin ternary complex, characteristic parameters for evaluating myocardial damage are obtained. For example, this includes determining characteristic parameters for evaluating myocardial damage based on changes (including differences and ratios) in the content of the large cardiac troponin ternary complex or total cardiac troponin ternary complex before and after an event.

[0050] In some embodiments, the one or more myocardial injury markers preferably further include at least one of cTnI, cTnT, and the total cardiac troponin complex.

[0051] In some embodiments, obtaining feature parameters for evaluating myocardial injury based on the content of one or more myocardial injury markers includes inputting the content of the multiple myocardial injury markers into a predefined function model and obtaining the output of the predefined function model as feature parameters for evaluating myocardial injury. The predefined function model may be, for example, a linear function model, a nonlinear function model, or a machine learning model. In some embodiments, a binary logistic regression model is used to construct combinations of variables and establish combination parameters. In some embodiments, binary classification logistic regression analysis is used to analyze the correlation between marker parameters and the occurrence of primary endpoint events. A p-value < 0.05 is considered significant for the variable. Cox regression analysis is used to determine the relationship between marker parameters or combinations thereof and outcomes in research subjects, calculate hazard ratios (HR) based on a Cox proportional hazards model, analyze the risk levels of risk groups with different marker parameter values, and analyze the multiples of the risk of endpoint event occurrence compared to the control group. A p-value < 0.05 is considered significant for the variable.

[0052] In one example, the content of multiple myocardial injury markers may be directly input as variables into a pre-defined function model. For example, the content of large cardiac troponin ternary complex or total cardiac troponin ternary complex and the content of at least one of cTnI, cTnT, and total cardiac troponin complex may be input as variables into a pre-defined function model, and the output of the pre-defined function model may be obtained as a feature parameter for evaluating myocardial injury.

[0053] In another example, the ratio of the contents of multiple myocardial injury markers may be input as a variable into a pre-defined function model. For example, the ratio of the contents of large cardiac troponin ternary complex and / or total cardiac troponin ternary complex to the contents of at least one of cTnI, cTnT, and total cardiac troponin complex may be input as a variable into a pre-defined function model, and the output of the pre-defined function model may be obtained as a feature parameter for evaluating myocardial injury.

[0054] In this specification, when describing the ratio of the content of one myocardial injury marker to the content of another myocardial injury marker, this includes the ratio obtained by dividing the content of the myocardial injury marker by the content of the other myocardial injury marker, and the ratio obtained by dividing the content of the other myocardial injury marker by the content of the other myocardial injury marker.

[0055] In some embodiments, the characteristic parameter is obtained by the ratio of the contents of a plurality of myocardial injury markers, that is, obtaining a characteristic parameter for evaluating myocardial injury based on the contents of one or more myocardial injury markers includes determining one of the following ratio parameters as a characteristic parameter for evaluating myocardial injury, or obtaining a characteristic parameter for evaluating myocardial injury based on at least two of the following ratio parameters, or obtaining a characteristic parameter for evaluating myocardial injury based on at least one of the following ratio parameters and the ratio of the cTnT content to the total cardiac troponin complex content. The aforementioned ratio parameters include the ratio of the content of large cardiac troponin ternary complex to the content of cTnI, the ratio of the content of large cardiac troponin ternary complex to the content of cTnT, the ratio of the content of large cardiac troponin ternary complex to the content of total cardiac troponin complex, the ratio of the content of total cardiac troponin ternary complex to the content of cTnI, the ratio of the content of total cardiac troponin ternary complex to the content of cTnT, the ratio of the content of total cardiac troponin ternary complex to the content of total cardiac troponin complex, and the ratio of the content of large cardiac troponin ternary complex to the content of total cardiac troponin ternary complex.

[0056] In some embodiments, the ratio parameter is the ratio of the content of large cardiac troponin ternary complex to the content of cTnI, cTnT, or total cardiac troponin complex, and optionally, the ratio parameter further includes the ratio of the content of total cardiac troponin ternary complex to the content of cTnI, cTnT, or total cardiac troponin complex, and / or the ratio of the content of cTnT to the content of cTnI or total cardiac troponin complex.

[0057] For example, the ratio of the content of large cardiac troponin ternary complex or total cardiac troponin ternary complex to the content of one of cTnI, cTnT, and total cardiac troponin complex may be established as a characteristic parameter for evaluating myocardial damage.

[0058] Based on the information above, this application is applicable to the evaluation of myocardial damage.

[0059] Large cardiac troponin ternary complexes or total cardiac troponin ternary complexes are used in the diagnosis of myocardial injury. Specifically, they can be used in the following clinical scenarios:

[0060] (1) Diagnosis of early acute myocardial infarction (stage determination of myocardial infarction patients) Existing literature has reported that the ternary troponin complex is more concentrated and represents a larger proportion of total troponin I in patients with acute myocardial infarction, particularly in those in the early stages of myocardial infarction. However, there are currently no relevant studies that have used the analysis of large cardiac troponin ternary complex or total cardiac troponin ternary complex as an aid in the diagnosis of myocardial infarction. Large cardiac troponin ternary complex or total cardiac troponin ternary complex, either alone or in combination with other clinical myocardial injury indicators, can provide information for the acute phase assessment of myocardial infarction, enabling rapid identification of high-risk patients and supporting the customization of clinical decision-making.

[0061] In this specification, markers for the diagnosis of early acute myocardial infarction include the large cardiac troponin ternary complex and / or the total cardiac troponin ternary complex, and one or more of cTnI, cTnT, TnC, cardiac troponin binary complex, and the total cardiac troponin complex.

[0062] In some embodiments, markers for the diagnosis of early acute myocardial infarction include the large cardiac troponin ternary complex, or a combination thereof with cTnI, cTnT, or total cardiac troponin complex.

[0063] In some embodiments, the marker for the diagnosis of early acute myocardial infarction includes the large cardiac troponin ternary complex and / or the total cardiac troponin ternary complex, and one or more of the following: cTnI, cTnT, TnC, cardiac troponin binary complex and the total cardiac troponin complex, particularly the large cardiac troponin ternary complex and / or the total cardiac troponin ternary complex, and one or two of the following: cTnT and the total cardiac troponin complex.

[0064] In some embodiments, obtaining characteristic parameters for evaluating myocardial damage based on the content of one or more myocardial damage markers is possible. The content of the aforementioned large cardiac troponin ternary complex is determined as a characteristic parameter for evaluating myocardial damage, or Characteristic parameters for evaluating myocardial damage are obtained based on the content of the large cardiac troponin ternary complex and the content of at least one of cTnI, cTnT, total cardiac troponin ternary complex, and total cardiac troponin complex, and preferably, characteristic parameters for evaluating myocardial damage are calculated based on the content of the total cardiac troponin ternary complex and the content of cTnT. Characteristic parameters for evaluating myocardial damage are obtained based on the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex and the ratio of the content of at least one of cTnI, cTnT, and the total cardiac troponin complex, and the ratio of the content of an optional cTnT to the content of cTnI or the total cardiac troponin complex, for example, determining the ratio of the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex to the content of cTnT as a characteristic parameter for evaluating myocardial damage.

[0065] In some embodiments, feature parameters are constructed based on a logistic regression algorithm, using combinations of multiple myocardial injury markers. Examples include combinations of macrocardial troponin ternary complex content, total cardiac troponin ternary complex content, cTnT content, or total cardiac troponin complex content, or combinations of macrocardial troponin ternary complex content, total cardiac troponin ternary complex content, cTnT content, and total cardiac troponin complex content; or, for example, a ratio of macrocardial troponin ternary complex content to total cardiac troponin complex content, a ratio of total cardiac troponin ternary complex content to total cardiac troponin complex content, and a ratio of cTnT content to total cardiac troponin complex content; or a ratio of macrocardial troponin ternary complex content to cTnT content, and a ratio of total cardiac troponin ternary complex content to cTnT content.

[0066] In some embodiments, an ROC curve is created, a predictive model for the feature parameters is established, and an optimal threshold (cutoff) is calculated using the cutoff as a reference value.

[0067] In some embodiments, evaluating the myocardial damage of the subject based on the results of the comparison described above is possible. This includes determining the stage of myocardial infarction for the subject based on the results of the comparison described above.

[0068] In some embodiments, if the characteristic parameter is higher than the reference value of the characteristic parameter, it is determined that the subject is in the early stages of acute myocardial infarction, for example, myocardial infarction with chest pain onset within 72 hours, 30 to 72 hours, 10 to 30 hours, 10 to 72 hours, or within 10 hours.

[0069] In one embodiment, the method further includes hospitalizing a subject who is judged to be in the early stages of acute myocardial infarction.

[0070] The term "higher than" a reference value refers to a level of such parameter in a sample that is higher than the level of such parameter in a reference value or reference sample. For example, a higher amount of a marker, or an elevated marker level, may be detected in a sample from one individual with a given disease compared to the same sample from individuals without the disease.

[0071] (2) Distinguishing between acute myocardial infarction (type 1) and chronic cardiac events Current troponin I and troponin T are specific markers of myocardial injury, but when myocardial injury occurs, the marker levels simply rise, and this does not allow for differentiation between acute and chronic injury. Identifying acute myocardial injury usually requires continuous monitoring of troponin levels, and a single test is difficult to interpret, potentially leading to delayed diagnosis and treatment.

[0072] In this specification, “acute cardiac event” refers to an acute condition, disease, or dysfunction of the heart, particularly acute heart failure, such as myocardial infarction (MI) or arrhythmia. Depending on the severity of the MI, LVD and CHF may follow. “Chronic cardiac event” refers to a decline in cardiac function, such as due to cardiac ischemia, coronary artery disease, or a previous, particularly minor, myocardial infarction (which may be followed by progressive LVD). This decline may also be caused by inflammatory diseases, cardiac valve defects (e.g., mitral valve defects), dilated cardiomyopathy, hypertrophic cardiomyopathy, cardiac rhythm defects (arrhythmias), and chronic obstructive pulmonary disease. Thus, obvious chronic cardiac events may further include patients who have already suffered from acute coronary syndrome, such as MI, but are not currently suffering from an acute cardiac event.

[0073] Distinguishing between acute and chronic cardiac events is crucial because they may require entirely different treatment regimens. For example, early reperfusion may be extremely important for patients presenting with acute myocardial infarction. However, performing reperfusion on patients with chronic heart failure is, at best, harmless to these patients, or causes only minor harm.

[0074] In this specification, markers for distinguishing between acute myocardial infarction and chronic cardiac events include the large cardiac troponin ternary complex and / or total cardiac troponin ternary complex, and one or more of cTnI, cTnT, TnC, cardiac troponin binary complex, and total cardiac troponin complex.

[0075] In some embodiments, markers for distinguishing between acute myocardial infarction and chronic cardiac events include large cardiac troponin ternary complex, total cardiac troponin ternary complex, or a combination of large cardiac troponin ternary complex and cTnT.

[0076] In some embodiments, markers for distinguishing between acute myocardial infarction and chronic cardiac events include one or more combinations of the large cardiac troponin ternary complex, total cardiac troponin ternary complex, cTnT, and total cardiac troponin complex.

[0077] In some embodiments, obtaining characteristic parameters for evaluating myocardial damage based on the content of one or more myocardial damage markers is possible. To determine the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex as a characteristic parameter for evaluating myocardial damage, or Based on the content of the large cardiac troponin ternary complex and the content of the total cardiac troponin ternary complex, characteristic parameters for evaluating myocardial damage are calculated, or This includes obtaining characteristic parameters for evaluating myocardial damage based on the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex and the content of cTnT or total cardiac troponin complex.

[0078] In one embodiment, characteristic parameters for evaluating myocardial damage are obtained based on the ratio of the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex to the content of at least one of cTnI, cTnT, and the total cardiac troponin complex, and the ratio of the content of an optional cTnT to the content of cTnI or the total cardiac troponin complex.

[0079] In one example, the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex and the content of cTnT or total cardiac troponin complex may be directly used as variables to calculate characteristic parameters for evaluating myocardial damage.

[0080] In another example, the content of the large cardiac troponin ternary complex and / or the ratio of the total cardiac troponin ternary complex content to the content of cTnT or total cardiac troponin complex may be used as variables to calculate characteristic parameters for evaluating myocardial damage.

[0081] In some embodiments, feature parameters are constructed based on a logistic regression algorithm, using combinations of multiple myocardial injury markers. Examples include combinations of macrocardial troponin ternary complex content, total cardiac troponin ternary complex content, cTnT content, or total cardiac troponin complex content, or combinations of macrocardial troponin ternary complex content, total cardiac troponin ternary complex content, cTnT content, and total cardiac troponin complex content; or, for example, a ratio of macrocardial troponin ternary complex content to total cardiac troponin complex content, a ratio of total cardiac troponin ternary complex content to total cardiac troponin complex content, and a ratio of cTnT content to total cardiac troponin complex content; or a ratio of macrocardial troponin ternary complex content to cTnT content, and a ratio of total cardiac troponin ternary complex content to cTnT content.

[0082] In some embodiments, an ROC curve is created, a predictive model for the feature parameters is established, and an optimal threshold (cutoff) is calculated using the cutoff as a reference value.

[0083] In some embodiments, the aforementioned comparison is performed, and based on the results of the comparison, an evaluation is made regarding myocardial damage in the subject. This includes determining, based on the results of the comparison, whether a type I myocardial infarction or a chronic cardiac event occurred in the subject.

[0084] In some embodiments, if the characteristic parameter is higher than a reference value for the characteristic parameter, it is determined that the subject has suffered a type I myocardial infarction.

[0085] In some embodiments, this further includes hospitalizing a subject who is determined to have suffered a type I myocardial infarction.

[0086] By using large cardiac troponin ternary complexes and / or total cardiac troponin ternary complexes, the type of myocardial injury can be more rapidly differentiated in a single-time-point study, accelerating the treatment of acute injury patients, rapidly excluding chronic injury patients, and speeding up clinical turnover.

[0087] (3) Exclusion of individuals who have not suffered myocardial damage Current research focuses on excluding patients without myocardial injury through continuous monitoring using troponin I and troponin T. Even in patients with chest pain lasting less than 3 hours, continuous monitoring of troponin levels is necessary, even if troponin levels are very low. Using the large cardiac troponin ternary complex and / or total cardiac troponin ternary complex, a single-time-point study can optimize the diagnostic flow by excluding patients without myocardial injury, such as those with chest pain onset within 24 hours, or even within 12 hours.

[0088] In this specification, markers for ruling out the absence of myocardial injury in a chest pain subject include the large cardiac troponin ternary complex and / or total cardiac troponin ternary complex, and one or more of cTnI, cTnT, TnC, cardiac troponin binary complex and total cardiac troponin complex, preferably the large cardiac troponin ternary complex.

[0089] Based on the method described above, distinguishing feature parameters are obtained, and based on the results of the comparison described above, patients who have not experienced myocardial damage (e.g., myocardial infarction, especially NSTEMI) are excluded.

[0090] In some embodiments, if the characteristic parameter is lower than a reference value for the characteristic parameter, the occurrence of a myocardial injury event in a chest pain subject is ruled out.

[0091] In some embodiments, the system further includes notifying patients who have been ruled out of myocardial injury to leave the emergency room.

[0092] In some embodiments, obtaining characteristic parameters for evaluating myocardial damage based on the content of one or more myocardial damage markers is possible. To determine the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex as a characteristic parameter for evaluating myocardial damage, or This includes obtaining characteristic parameters for evaluating myocardial damage based on the content of the large cardiac troponin ternary complex or the content of the total cardiac troponin ternary complex and the total cardiac troponin complex.

[0093] In some embodiments, an ROC curve is created, a predictive model for the feature parameters is established, and an optimal threshold (cutoff) is calculated using the cutoff as a reference value.

[0094] (4) Distinguishing between Type I and Type II myocardial infarction Distinguishing between type I and type II myocardial infarction is of significant importance, and early differentiation between type I and type II myocardial infarction can provide information for subsequent treatment decisions. Currently, the distinction between type I and type II myocardial infarction is mainly achieved through imaging tests, and there are no markers that can effectively differentiate between type I and type II myocardial infarction. Large cardiac troponin ternary complex and / or total cardiac troponin ternary complex can rapidly differentiate between type I and type II myocardial infarction, support the customization of clinical decision-making, and reduce unnecessary medical tests.

[0095] In this specification, markers for distinguishing between type I and type II myocardial infarction include the large cardiac troponin ternary complex and / or total cardiac troponin ternary complex, and one or more of cTnI, cTnT, TnC, cardiac troponin binary complex, and total cardiac troponin complex.

[0096] Based on the method described above, distinguishing feature parameters are obtained, and based on the results of the comparison described above, an evaluation is performed on the myocardial damage of the subject to determine whether a type I myocardial infarction or a type II myocardial infarction occurred in the subject.

[0097] In some embodiments, if the characteristic parameter is higher than a reference value for the characteristic parameter, it is determined that the subject has suffered a type I myocardial infarction.

[0098] In some embodiments, subjects diagnosed with type I myocardial infarction receive thrombolytic therapy, while subjects diagnosed with type II myocardial infarction receive oxygen supplementation without thrombolytic therapy.

[0099] (5) Distinguishing between myocardial injury caused by invasive procedures and chronic cardiac events. Current troponin I and troponin T are specific markers of myocardial injury; however, when myocardial injury occurs, only the marker levels rise, failing to distinguish between different types of injury. To identify myocardial injury resulting from invasive procedures, continuous monitoring of troponin concentration changes is usually necessary. Using large cardiac troponin ternary complex and / or total cardiac troponin ternary complex allows for more rapid differentiation of different types of injury in a single-time-point study.

[0100] In this specification, markers for distinguishing between myocardial injury resulting from invasive procedures and chronic cardiac events include the large cardiac troponin ternary complex and / or total cardiac troponin ternary complex, and one or more of cTnI, cTnT, TnC, cardiac troponin binary complex, and total cardiac troponin complex.

[0101] In some embodiments, obtaining characteristic parameters for evaluating myocardial damage based on the content of one or more myocardial damage markers is possible. This includes determining the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex as characteristic parameters for evaluating myocardial damage.

[0102] In some embodiments, characteristic parameters for evaluating myocardial damage are obtained based on the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex to the ratio of the content of at least one of cTnI, cTnT, and the total cardiac troponin complex, and the ratio of the content of an optional cTnT to the content of cTnI or the total cardiac troponin complex.

[0103] In some embodiments, feature parameters are constructed based on a logistic regression algorithm, using combinations of multiple myocardial injury markers. Examples include combinations of macrocardial troponin ternary complex content, total cardiac troponin ternary complex content, cTnT content, or total cardiac troponin complex content, or combinations of macrocardial troponin ternary complex content, total cardiac troponin ternary complex content, cTnT content, and total cardiac troponin complex content; or, for example, a ratio of macrocardial troponin ternary complex content to total cardiac troponin complex content, a ratio of total cardiac troponin ternary complex content to total cardiac troponin complex content, and a ratio of cTnT content to total cardiac troponin complex content; or a ratio of macrocardial troponin ternary complex content to cTnT content, and a ratio of total cardiac troponin ternary complex content to cTnT content.

[0104] In some embodiments, an ROC curve is created, a predictive model for the feature parameters is established, and an optimal threshold (cutoff) is calculated using the cutoff as a reference value.

[0105] In some embodiments, the comparisons described above are performed, and based on the results of the comparisons, an evaluation is made regarding myocardial damage in the subject to determine whether myocardial damage caused by the invasive procedure or a chronic cardiac event occurred in the subject.

[0106] In some embodiments, if the characteristic parameter is higher than a reference value for the characteristic parameter, it is determined that myocardial damage caused by the invasive procedure has occurred in the subject.

[0107] In some embodiments, subjects who are determined to have suffered myocardial damage as a result of invasive surgery will have their hospital stay extended or their cardiac monitoring will be intensified.

[0108] In some embodiments, the method can accurately distinguish between myocardial injury resulting from an invasive procedure and chronic cardiac-related diseases (e.g., cardiomyopathy, chronic heart failure, structural heart disease, invasive disease, stable coronary artery disease, persistent arrhythmias). In some other embodiments, the method can accurately distinguish between myocardial injury resulting from an invasive procedure and non-cardiac-related diseases (e.g., pneumonia, renal failure).

[0109] Furthermore, large cardiac troponin ternary complexes or total cardiac troponin ternary complexes are also used to assess the prognosis of myocardial injury. Specifically, they can be used in the following clinical scenarios.

[0110] (6) Evaluation of the prognosis of acute myocardial injury Current research focuses on evaluating the prognosis of myocardial infarction patients using troponin I and troponin T. Evaluation using the large cardiac troponin ternary complex and / or total cardiac troponin ternary complex is expected to improve the accuracy of predicting future cardiac events or death related to myocardial injury in patients with acute myocardial injury, such as the prognosis of myocardial injury in patients who have undergone cardiac surgery or in patients who have experienced myocardial infarction.

[0111] In this specification, markers for evaluating the prognostic risk in patients with myocardial infarction include the large cardiac troponin ternary complex and / or the total cardiac troponin ternary complex, and one or more of cTnI, cTnT, TnC, cardiac troponin binary complex, and the total cardiac troponin complex.

[0112] Based on the method described above, distinguishing characteristic parameters are obtained, and based on the results of the comparison described above, an evaluation is performed on the myocardial damage of the subject, and the prognosis of the myocardial infarction subject is determined, for example, within one year, within six months, or within three months.

[0113] In some embodiments, if the characteristic parameter is higher than a reference value for the characteristic parameter, it is determined that the prognosis is poor.

[0114] In some embodiments, obtaining characteristic parameters for evaluating myocardial damage based on the content of one or more myocardial damage markers is possible. This includes determining the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex as a characteristic parameter for evaluating myocardial damage.

[0115] In some embodiments, changes in the content of large cardiac troponin ternary complex or total cardiac troponin ternary complex in the plasma of the subject before and after cardiac surgery are identified as characteristic parameters for evaluating the prognostic risk of undergoing surgery.

[0116] Evaluation of myocardial injury prognosis in patients undergoing surgical procedures (e.g., coronary artery bypass grafting (CABG) or heart valve replacement). Based on the content or change therein of the large cardiac troponin ternary complex or total cardiac troponin ternary complex before and after surgery (e.g., the difference or ratio of the content of the large cardiac troponin ternary complex or total cardiac troponin ternary complex postoperatively and preoperatively), characteristic parameters for evaluating myocardial damage are determined. In some embodiments, characteristic parameters based on a combination of multiple myocardial damage markers are constructed based on a logistic regression algorithm. For example, a combination of the content of the large cardiac troponin ternary complex and the content of cTnT.

[0117] In some embodiments, an ROC curve is created, a predictive model for the feature parameters is established, and an optimal threshold (cutoff) is calculated using the cutoff as a reference value.

[0118] In some embodiments, binary classification logistic regression analysis is used to assess the risk of a patient developing a composite endpoint event (selected from major clinical events, including a composite event of all-cause mortality, myocardial infarction, and unplanned coronary revascularization, and any combination of secondary clinical events, including cardiovascular death, components of the major clinical events, stroke, hospitalization for heart failure or emergency treatment observation for 24 hours or more, cardiac arrest or malignant arrhythmia, and hospitalization for other cardiovascular diseases).

[0119] In some embodiments, COX regression is used to assess the risk of a patient developing a composite endpoint event (selected from major clinical events, including a composite event of all-cause mortality, myocardial infarction, and unplanned coronary revascularization, and any combination of secondary clinical events, including cardiovascular death, components of the major clinical events, stroke, hospitalization for heart failure or emergency treatment observation for 24 hours or more, cardiac arrest or malignant arrhythmia, and hospitalization for other cardiovascular disease).

[0120] Evaluation of myocardial injury prognosis in patients with myocardial infarction The content of the large cardiac troponin ternary complex or total cardiac troponin ternary complex is determined as a characteristic parameter for evaluating myocardial damage.

[0121] In some embodiments, an ROC curve is created, a predictive model for the feature parameters is established, and an optimal threshold (cutoff) is calculated using the cutoff as a reference value.

[0122] In some embodiments, binary classification logistic regression analysis is used to assess the risk of a patient developing a composite endpoint event (selected from major clinical events, including a composite event of all-cause mortality, myocardial infarction, and unplanned coronary revascularization, and any combination of secondary clinical events, including cardiovascular death, components of the major clinical events, stroke, hospitalization for heart failure or emergency treatment observation for 24 hours or more, cardiac arrest or malignant arrhythmia, and hospitalization for other cardiovascular diseases).

[0123] In some embodiments, COX regression is used to assess the risk of a patient experiencing a composite endpoint event.

[0124] (7) Assessment of prognostic risk in patients with chronic myocardial injury Current research focuses on evaluating the prognosis of patients with chronic myocardial injury using troponin I and troponin T, and evaluation using the large cardiac troponin ternary complex and / or total cardiac troponin ternary complex is expected to improve predictive accuracy.

[0125] In this specification, markers for evaluating prognostic risk in patients with chronic myocardial injury include the large cardiac troponin ternary complex and / or total cardiac troponin ternary complex, and one or more of cTnI, cTnT, TnC, cardiac troponin binary complex, and total cardiac troponin complex.

[0126] Based on the method described above, characteristic parameters for differentiation are obtained, and based on the results of the comparison described above, a prognostic risk assessment is performed for subjects with chronic myocardial injury (e.g., cardiomyopathy, chronic heart failure, structural heart disease, invasive disease, stable coronary artery disease, persistent arrhythmia).

[0127] In some embodiments, if the characteristic parameter is higher than a reference value for the characteristic parameter, it is determined that the prognosis is poor.

[0128] In some embodiments, obtaining characteristic parameters for evaluating myocardial damage based on the content of one or more myocardial damage markers is possible. This includes determining the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex as a characteristic parameter for evaluating myocardial damage.

[0129] The content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex is determined as a characteristic parameter for evaluating myocardial damage. In some embodiments, a characteristic parameter based on a combination of multiple myocardial damage markers is constructed based on a logistic regression algorithm. For example, a combination of the content of the large cardiac troponin ternary complex and the content of the total cardiac troponin complex, or a combination of the content of the large cardiac troponin ternary complex and the content of cTnT.

[0130] In some embodiments, an ROC curve is created, a predictive model for the feature parameters is established, and an optimal threshold (cutoff) is calculated using the cutoff as a reference value.

[0131] In some embodiments, binary classification logistic regression analysis is used to assess the risk of a patient experiencing a composite endpoint event.

[0132] In some embodiments, COX regression is used to assess the risk of a patient experiencing a composite endpoint event.

[0133] The method of this application is preferably an ex vivo or in vitro method. It may include steps other than those explicitly mentioned above. For example, further steps may relate to sample preparation and obtaining an evaluation of the results obtained by the method. The method may be performed manually or assisted by automation. Preferably, the detection step, calculation step and comparison step may be assisted in whole or in part by automation, for example, by appropriate robots and sensing devices for detection, a calculation algorithm performed by a computer on a data processing device in the calculation step, or a comparison and / or diagnostic algorithm on a data processing device in the comparison step.

[0134] Apparatus and sample analysis system In a second aspect, the present application provides an apparatus for acquiring characteristic parameters for evaluating myocardial damage in a subject, and as shown in Figure 1, the apparatus 100 is A data receiving module 110 configured to receive the content of one or more myocardial injury markers obtained from a sample from a subject, wherein the one or more myocardial injury markers include large cardiac troponin ternary complex and / or total cardiac troponin ternary complex, A data processing module 120 is configured to process the content data of one or more myocardial injury markers received by the receiving module and obtain characteristic parameters for evaluating myocardial injury. The system includes an output module 130 configured to output the aforementioned feature parameters.

[0135] In some embodiments, the data processing module processes the content of one or more myocardial injury markers and obtains characteristic parameters for evaluating myocardial injury. The data processing module determines the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex as a characteristic parameter for evaluating myocardial damage, or The data processing module includes obtaining characteristic parameters for evaluating myocardial damage based on the content of the large cardiac troponin ternary complex and the content of the total cardiac troponin ternary complex.

[0136] In some embodiments, the myocardial injury marker further comprises one or more of cTnI, cTnT, TnC, the cardiac troponin binary complex, and the total cardiac troponin complex.

[0137] In some embodiments, the one or more myocardial injury markers further include at least one of cTnI, cTnT, and the total cardiac troponin complex.

[0138] In some embodiments, the data processing module processing the content of one or more myocardial injury markers and obtaining feature parameters for evaluating myocardial injury includes the data processing module inputting the content of the multiple myocardial injury markers into a pre-defined function model and obtaining the output of the pre-defined function model as feature parameters for evaluating myocardial injury.

[0139] In some embodiments, the data processing module processing the content of one or more myocardial injury markers and obtaining characteristic parameters for evaluating myocardial injury includes the data processing module determining one of the following ratio parameters as a characteristic parameter for evaluating myocardial injury, or obtaining characteristic parameters for evaluating myocardial injury based on at least two of the following ratio parameters, or obtaining characteristic parameters for evaluating myocardial injury based on at least one of the following ratio parameters and the ratio of the cTnT content to the total cardiac troponin complex content. The aforementioned ratio parameters include the ratio of the content of large cardiac troponin ternary complex to the content of cTnI, the ratio of the content of large cardiac troponin ternary complex to the content of cTnT, the ratio of the content of large cardiac troponin ternary complex to the content of total cardiac troponin complex, the ratio of the content of total cardiac troponin ternary complex to the content of cTnI, the ratio of the content of total cardiac troponin ternary complex to the content of cTnT, the ratio of the content of total cardiac troponin ternary complex to the content of total cardiac troponin complex, and the ratio of the content of large cardiac troponin ternary complex to the content of total cardiac troponin ternary complex.

[0140] In some embodiments, the ratio parameter is the ratio of the content of large cardiac troponin ternary complex to the content of cTnI, cTnT, or total cardiac troponin complex, and optionally, the ratio parameter further includes the ratio of the content of total cardiac troponin ternary complex to the content of cTnI, cTnT, or total cardiac troponin complex, and / or the ratio of the content of cTnT to the content of cTnI or total cardiac troponin complex.

[0141] In a third aspect, the present application provides a sample analysis system, the system is A sample placement section for placing a container containing a sample of the subject, A sample dispensing unit for drawing up the subject's sample from the sample placement unit and discharging it into the cuvette where the sample should be placed, A reagent placement section for placing detection reagents, A reagent dispensing section for drawing detection reagent from the reagent placement section and discharging it into the cuvette to which the reagent should be added, A reaction section for placing a cuvette and incubating the test solution obtained by the reaction between the sample of the subject in the cuvette and the detection reagent, A detection unit having a signal detector for detecting the signal of a test solution in a cuvette, for measuring and outputting the content of one or more myocardial injury markers in a sample of a subject, wherein the one or more myocardial injury markers include a large cardiac troponin ternary complex and / or total cardiac troponin ternary complex, The system includes a data processing unit which includes a processor and a computer-readable storage medium in which computer-readable instructions are stored, and when the computer-readable instructions are executed by the processor, the processor The steps include receiving and processing the content of one or more myocardial injury markers to obtain characteristic parameters for evaluating myocardial injury, The system is characterized by performing the step of outputting the aforementioned characteristic parameters.

[0142] Figure 2 shows a sample analysis system 200 according to an embodiment of the present application, which is configured to include a chemiluminescence analyzer or a chemiluminescence analyzer. As shown in Figure 2, the sample analysis system 200 includes a sample placement section 210, a sample dispensing section 220, a reagent placement section 230, a reagent dispensing section 240, a reaction section 250, a detection section 260, and a second embodiment of the apparatus 270.

[0143] The sample placement section 210 is used to place a container containing a blood sample from a subject. For example, the sample placement section 210 may be configured as a sample tray, which includes a plurality of sample positions on which the container 10 can be placed, and the sample tray can be rotated to schedule the container containing the blood sample to the appropriate position, for example, a position on which the sample dispensing section 220 can draw up the blood sample.

[0144] The sample dispensing unit 220 is used to draw a blood sample, such as serum, from the sample placement unit 210 and discharge it into a cuvette into which the sample is to be placed. For example, the sample dispensing unit 112 may include a sample needle, which can perform two-dimensional or three-dimensional spatial motion by a two-dimensional or three-dimensional drive mechanism, thereby allowing the sample needle to move to a position to draw the blood sample, move to a cuvette into which the sample is to be placed, and discharge the drawn blood sample into the cuvette.

[0145] The reagent placement section 230 is used to place detection reagents, for example, reagents for measuring the content of one or more myocardial damage markers. For example, the reagent placement section 230 may be configured as a reagent tray having a disc-shaped structure, the reagent tray having multiple positions for placing reagent containers, the reagent placement section 230 can rotate and rotate the reagent container placed on it, thereby facilitating the rotation of the reagent container to a specific position, for example, a position from which the reagent can be drawn up by the reagent dispensing section 240. The number of reagent placement components 230 may be one or more.

[0146] The reagent dispensing unit 240 is used to draw up the detection reagent from the reagent placement unit 230 and discharge it into the cuvette to which the reagent is to be added. For example, the reagent dispensing unit 240 may include a reagent needle, which can perform two-dimensional or three-dimensional spatial motion by a two-dimensional or three-dimensional drive mechanism, thereby moving the reagent needle to a position to draw up the reagent, to the cuvette to which the reagent is to be added, and discharging the drawn-up reagent into the cuvette.

[0147] The reaction unit 250 is used to place cuvettes and incubate the test solution obtained by the reaction of the subject's blood sample in the cuvette with the detection reagent. For example, the reaction unit 250 may be configured as a reaction tray having a disc-shaped structure, the reaction tray having one or more resting positions for resting cuvettes, the reaction tray can rotate and move the cuvettes in the resting positions, thereby scheduling the cuvettes within the reaction tray and facilitating the incubation of the test solution in the cuvettes.

[0148] The detection unit 260 has a signal detector, such as an optical detector, and is used to detect the signal of the test solution in the cuvette to measure and output the content of one or more myocardial damage markers in the subject sample. The detection unit 260 is installed, for example, outside the reaction unit 250, which rotates to move the container containing the test solution towards the detection unit 260 for detection. In some embodiments, the detection unit 260 is configured as a photometric device.

[0149] For example, if the sample analysis system is configured as a chemiluminescence analyzer or including a chemiluminescence analyzer, the detection unit 260 is configured as a photometric device. One specific detection flow for a chemiluminescence analyzer is as follows: The sample dispensing unit 220 draws the test sample from the sample placement unit 210 and adds it to the cuvette; the reagent dispensing unit 240 draws the enzyme-labeled reagent and magnetic bead reagent from the reagent placement unit 230 and adds them to the cuvette containing the sample, mixing them uniformly with the sample; the cuvette is then left in the reaction unit 250 for reaction, incubation, and magnetic separation washing; a luminescent substrate is added to the cuvette after reaction, incubation, and magnetic separation washing are completed, and it is incubated for a certain period of time; and finally, the detection unit 260 detects the photons emitted by the test substance in the test sample under the action of the luminescent substrate and calculates the concentration level of the test substance from the measured number of photons. For other embodiments and advantages of the sample analysis system, refer to the above description for apparatus 100.

[0150] Detection kits and applications In a fourth aspect, the application provides an application in the manufacture of a kit for the quantitative detection of large cardiac troponin ternary complex and / or total cardiac troponin ternary complex in a sample, wherein the kit is used for the evaluation of myocardial injury as described in the application. Accordingly, the application provides a kit containing the reagent for the quantitative detection of large cardiac troponin ternary complex and / or total cardiac troponin ternary complex in a sample.

[0151] In some embodiments, the kit further includes a reagent for quantitative detection of total cardiac troponin complex, a reagent for quantitative detection of cTnI, and / or a reagent for quantitative detection of cTnT.

[0152] According to the research, it was found that applying the kit for detecting large cardiac troponin ternary complex and total cardiac troponin ternary complex of this application is beneficial in obtaining the content of the myocardial damage marker more rapidly and accurately, and in obtaining characteristic parameters for evaluating the myocardial damage.

[0153] In some embodiments, the reagent for quantitative detection of large cardiac troponin ternary complex in the sample comprises a first group antibody and a second group antibody, where, The antibody of the first group comprises one or more antibodies 1-1, each antibody 1-1 independently selected from antibodies that specifically bind to any one segment in the amino acid sequence of cTnT between positions 67 and 222. The second group of antibodies comprises one or more antibodies 1-2, each antibody 1-2 being independently selected from antibodies that specifically bind to any one segment in the TnC amino acid sequence.

[0154] In some embodiments, the antibodies in the first group do not include antibodies that specifically bind to any one segment in the amino acid sequence between positions 223 and 287 of cTnT.

[0155] In some embodiments, the antibodies of the second group are Independently, one or more antibodies 1-3 selected from antibodies that specifically bind to cTnIC, and / or The solution further comprises one or more antibodies 1-4 selected from antibodies that independently specifically bind to any single segment in the amino acid sequence of cTnI between positions 18 and 210.

[0156] In some embodiments, the first group of antibodies comprises one or more antibodies 1-1, and the second group of antibodies comprises one or more antibodies 1-2 and one or more antibodies 1-3.

[0157] In some embodiments, each antibody 1-1 is independently selected from antibodies that specifically bind to the amino acids at positions 67-86, 119-138, 132-151, 145-164, or 171-190 of cTnT.

[0158] In some embodiments, each of the antibodies 1-4 is independently selected from antibodies that specifically bind to the amino acids at positions 1-15, 13-22, 18-22, 18-28, 18-35, 22-31, 22-40, 23-29, 24-40, 25-40, 26-35, 34-37, 41-49, 83-89, 86-90, 87-90, 117-126, 130-145, 169-178, 186-192, 190-196, or 195-209 of cTnI. In some embodiments, each of the antibodies 1-4 is independently selected from antibodies that specifically bind to the amino acids at positions 22-40, 41-49, or 83-89 of cTnI.

[0159] In some embodiments, the antibodies of group 1 are capture antibodies, and the antibodies of group 2 are detection antibodies.

[0160] In some embodiments, the reagent for quantitative detection of total cardiac troponin ternary complex in the sample comprises a first detection reagent and a second detection reagent, where, The first detection reagent comprises one or more antibodies 2-1, each antibody 2-1 independently selected from antibodies that specifically bind to any one segment in the amino acid sequence of cTnT between positions 223 and 287. The second detection reagent comprises one or more antibodies 2-2, each antibody 2-2 independently selected from antibodies that specifically bind to any one segment in the TnC amino acid sequence.

[0161] In some embodiments, the first detection reagent further comprises one or more antibodies 2-3, each of which is independently selected from antibodies that specifically bind to any one segment in the amino acid sequence of cTnT between positions 67 and 222.

[0162] In some embodiments, the second detection reagent is Independently, one or more antibodies 2-4 selected from antibodies that specifically bind to cTnIC, and / or The solution further comprises one or more antibodies 2-5 independently selected from antibodies that specifically bind to any single segment in the amino acid sequence of cTnI between positions 18 and 210.

[0163] In some embodiments, the first detection reagent comprises one or more antibodies 2-1 and one or more antibodies 2-3, and the second detection reagent comprises one or more antibodies 2-2 and one or more antibodies 2-4 and / or one or more antibodies 2-5.

[0164] In some embodiments, each antibody 2-1 is independently selected from antibodies that specifically bind to the amino acids at positions 223-242 and 262-281 of cTnT. In some embodiments, antibody 2-1 is an antibody that specifically binds to the amino acids at positions 223-242 of cTnT.

[0165] In some embodiments, each of the antibodies 2-3 is independently selected from antibodies that specifically bind to the amino acids at positions 67-86, 119-138, 132-151, 145-164, or 171-190 of cTnT. In some embodiments, each of the antibodies 2-3 is independently selected from antibodies that specifically bind to the amino acids at positions 119-138 or 132-151 of cTnT.

[0166] In some embodiments, each of the antibodies 2-5 is independently selected from antibodies that specifically bind to the amino acids at positions 1-15, 13-22, 18-22, 18-28, 18-35, 22-31, 22-40, 23-29, 24-40, 25-40, 26-35, 34-37, 41-49, 83-89, 86-90, 87-90, 117-126, 130-145, 169-178, 186-192, 190-196, or 195-209 of cTnI. In some embodiments, each of the antibodies 2-5 is independently selected from antibodies that specifically bind to the amino acids at positions 22-40, 41-49, or 83-89 of cTnI.

[0167] In some embodiments, the first detection reagent is a capture reagent, and the second detection reagent is a detection reagent.

[0168] In some embodiments, the kit is 1) Determination of the stage of myocardial infarction, in particular, determination of whether the subject is in the early stage of myocardial infarction, 2) Distinguishing between type 1 myocardial infarction and chronic cardiac events, 3) Exclusion of subjects with chest pain who have not experienced myocardial injury. 4) Distinguishing between type I myocardial infarction and type II myocardial infarction, 5) Distinguishing between myocardial injury caused by invasive procedures and chronic cardiac events. 6) Evaluation of the prognosis of acute myocardial injury, 7) It is used in one or more of the assessments of the prognosis of chronic myocardial injury.

[0169] (Effects of the invention) 1) Detection of troponin complexes and fragments in patient samples enables the assessment of the etiology and risk of myocardial injury in individuals when troponin levels are elevated.

[0170] 2) This will avoid the difficulties associated with continuous monitoring of troponin levels, improve clinical turnover, and contribute to the establishment of a faster diagnostic flow.

[0171] 3) Contribute to the stratification of chest pain patients and provide guidance in diagnosis and treatment decisions. [Modes for carrying out the invention]

[0172] Example 1. Detection kit and analysis of signal-to-noise ratio 1. Kit Construction Those skilled in the art will understand that kits for quantitatively detecting the myocardial damage markers include commercially available kits, all of which can be used to determine the content of the myocardial damage markers. For an unrestrictive purpose, the following descriptions exemplify kits for detecting cTnI, cTnT, total cardiac troponin complex, large cTnITC, and total cTnITC.

[0173] We constructed each kit by applying a capture antibody-detection antibody (all antibodies used herein are from Hytest) to a dual antibody sandwich chemiluminescence immunoassay method.

[0174] 1. Development of a detection kit for myocardial damage markers cTnI, cTnT, and total cardiac troponin complex. (1) Total complex detection kit: Capture antibody: 19C7cc, an antibody that specifically binds to cTnI amino acid fragments 41-49. Detection antibody: 20C6cc antibody, which specifically binds to the cTnIC complex epitope.

[0175] (2) cTnT detection kit: Capture antibody: 329cc of antibody that specifically binds to cTnT amino acid fragments 119-138. Detection antibody: 406cc of antibody that specifically binds to cTnT amino acid fragments 132-151.

[0176] (3) cTnI detection kit: Capture antibody: 19C7cc, an antibody that specifically binds to cTnI amino acid fragments 41-49. Detection antibody: RecR33, an antibody that specifically binds to 24-40 fragments of cTnI amino acids.

[0177] 2. Construction of a large-scale cTnITC detection kit (1) Large-scale cTnITC detection kit 1 Capture antibody: Antibody 1-1: 329cc of antibody that specifically binds to cTnT amino acid fragments 119-138. Detected antibodies: Antibodies 1-3: 20C6cc of antibodies that specifically bind to the cTnIC complex epitope.

[0178] (2) Large-scale cTnITC detection kit 2 Capture antibody: Antibody 1-1: 329cc of antibody that specifically binds to cTnT amino acid fragments 119-138. Detected antibodies: Antibodies 1-4: Antibodies 19C7cc that specifically bind to cTnI amino acid fragments 41-49.

[0179] (3) Large-scale cTnITC detection kit 3 Capture antibody: Antibody 1-1: 329cc of antibody that specifically binds to cTnT amino acid fragments 119-138. Detected antibodies: Antibodies 1-2: Antibody 7B9cc that specifically binds to TnC, and Antibodies 1-3: Antibody 20C6cc that specifically binds to the cTnIC complex epitope.

[0180] (4) Large cTnITC detection kit 4 Capture antibody: Antibody 1-1: 329cc of antibody that specifically binds to cTnT amino acid fragments 119-138. Detected antibodies: Antibodies 1-2: Antibody 7B9cc that specifically binds to TnC, and Antibodies 1-4: Antibody 19C7cc that specifically binds to cTnI amino acid fragments 41-49.

[0181] (5) Large-scale cTnITC detection kit 5 Capture antibody: Antibody 1-1: 329cc of antibody that specifically binds to cTnT amino acid fragments 119-138. Detected antibody: Antibody 1-2: Antibody 7B9cc that specifically binds to TnC.

[0182] (6) Large cTnITC detection kit 6 Capture antibody: Antibody 1-1: Antibody 1C11cc that specifically binds to cTnT amino acid fragments 171-190. Detected antibodies: Antibodies 1-2: Antibody 7B9cc, which specifically binds to TnC, and Antibodies 1-3: Antibody Tcom8, which specifically binds to the cTnIC complex epitope.

[0183] (7) Large-scale cTnITC detection kit 7 Capture antibody: Antibody 1-1: 406cc of antibody that specifically binds to cTnT amino acid fragments 132-151. Detected antibodies: Antibodies 1-2: Antibody 7B9cc that specifically binds to TnC, and Antibodies 1-3: Antibody 20C6cc that specifically binds to the cTnIC complex epitope.

[0184] (8) Large-scale cTnITC detection kit 8 Capture antibody: Antibody 1-1: 300cc of antibody that specifically binds to cTnT amino acid fragments 119-138. Detected antibodies: Antibodies 1-2: Antibody 7B9cc that specifically binds to TnC, and Antibodies 1-3: Antibody 20C6cc that specifically binds to the cTnIC complex epitope.

[0185] In addition to the kits described above, the experiment also used a kit obtained by replacing antibody 1-1, used in the large cTnITC detection kits 3-8, with antibody 7F4 or 7G7, whose specific binding site is cTnT amino acid fragments 67-86, or antibody 2F3, 1A11, or 1F11cc, whose specific binding site is cTnT amino acid fragments 145-164. The experiment also used a kit obtained by replacing antibody 1-4, used in the large cTnITC detection kit 4, with antibody M18cc, whose specific binding site is cTnI amino acid fragments 18-28, antibody 16A11cc, 16A12cc, or 8E10cc, whose specific binding site is cTnI amino acid fragments 86-90, antibody M46, whose specific binding site is cTnI amino acid fragments 130-145, or antibody MF4cc, whose specific binding site is cTnI amino acid fragments 190-196, to create antibody 1-4.

[0186] 3. Development of a total cardiac troponin ternary complex detection kit. A capture antibody-detection antibody was applied to a dual antibody sandwich chemiluminescence immunoassay method to construct a detection kit, which was used to detect total ternary troponin complex cTnITC in samples.

[0187] Total cTnITC Detection Kit 1: Capture antibodies: Antibody 2-1: 7E7 (specifically binds to cTnT amino acid fragments 223-242), Antibody 2-3: 329cc (specifically binds to cTnT amino acid fragments 119-138).

[0188] Detected antibody: Antibody 2-4: 20C6cc (specifically binds to the cTnIC complex epitope).

[0189] Total cTnITC Detection Kit 2: Capture antibodies: Antibody 2-1: 7E7 (specifically binds to cTnT amino acid fragments 223-242), Antibody 2-3: 329cc (specifically binds to cTnT amino acid fragments 119-138).

[0190] Detected antibody: Antibody 2-5: 19C7cc (specifically binds to cTnI amino acid fragments 41-49).

[0191] Total cTnITC Detection Kit 3: Capture antibodies: Antibody 2-1: 7E7 (specifically binds to cTnT amino acid fragments 223-242), Antibody 2-3: 329cc (specifically binds to cTnT amino acid fragments 119-138).

[0192] Detected antibodies: Antibody 2-2: 7B9cc (specifically binds to TnC), Antibody 2-4: 20C6cc (specifically binds to the cTnIC complex epitope),

[0193] Total cTnITC Detection Kit 4: Capture antibodies: Antibody 2-1: 7E7 (specifically binds to cTnT amino acid fragments 223-242), Antibody 2-3: 329cc (specifically binds to cTnT amino acid fragments 119-138).

[0194] Detected antibodies: Antibody 2-2: 7B9cc (specifically binds to TnC), Antibody 2-5: 19C7cc (specifically binds to cTnI amino acid fragments 41-49).

[0195] Total cTnITC Detection Kit 5: Capture antibodies: Antibody 2-1: 7E7 (specifically binds to cTnT amino acid fragments 223-242), Antibody 2-3: 329cc (specifically binds to cTnT amino acid fragments 119-138).

[0196] Detected antibody: Antibody 2-2: 7B9cc (specifically binds to TnC).

[0197] Total cTnITC Detection Kit 6: Capture antibody: Antibody 2-1:7E7 (specifically binds to cTnT amino acid fragments 223-242).

[0198] Detected antibody: Antibody 2-2: 7B9cc (specifically binds to TnC).

[0199] Total cTnITC Detection Kit 7: Capture antibody: Antibody 2-1:155 (specifically binds to cTnT amino acid fragments 262-281).

[0200] Detected antibodies: Antibody 2-2: 7B9cc (specifically binds to TnC), Antibody 2-4: Tcom8 (specifically binds to the cTnIC complex epitope).

[0201] Total cTnITC Detection Kit 8: Capture antibodies: Antibody 2-1: 7E7 (specifically binds to cTnT amino acid fragments 223-242), Antibody 2-3: 406cc (specifically binds to cTnT amino acid fragments 132-151).

[0202] Detected antibodies: Antibody 2-2: 7B9cc (specifically binds to TnC), Antibody 2-4: 20C6cc (specifically binds to the cTnIC complex epitope),

[0203] Total cTnITC Detection Kit 9: Capture antibodies: Antibody 2-1: 7E7 (specifically binds to cTnT amino acid fragments 223-242), Antibody 2-3: 300cc (specifically binds to cTnT amino acid fragments 119-138).

[0204] Detected antibodies: Antibody 2-2: 7B9cc (specifically binds to TnC), Antibody 2-4: 20C6cc (specifically binds to the cTnIC complex epitope),

[0205] Total cTnITC detection kit 10: Capture antibodies: Antibody 2-1: 155cc (specifically binds to cTnT amino acid fragments 262-281), Antibody 2-3: 406cc (specifically binds to cTnT amino acid fragments 132-151).

[0206] Detected antibodies: Antibody 2-2: 7B9cc (specifically binds to TnC), Antibody 2-4: 20C6cc (specifically binds to the cTnIC complex epitope),

[0207] Total cTnITC detection kit 11: Capture antibodies: Antibody 2-1: 7E7 (specifically binds to cTnT amino acid fragments 223-242), Antibody 2-3: 7G7 (specifically binds to cTnT amino acid fragments 67-86).

[0208] Detected antibodies: Antibody 2-2: 7B9cc (specifically binds to TnC), Antibody 2-4: 20C6cc (specifically binds to the cTnIC complex epitope),

[0209] Total cTnITC detection kit 12: Capture antibodies: Antibody 2-1: 7E7 (specifically binds to cTnT amino acid fragments 223-242), Antibody 2-3: 1C11cc (specifically binds to cTnT amino acid fragments 171-190).

[0210] Detected antibodies: Antibody 2-2: 7B9cc (specifically binds to TnC), Antibody 2-4: Tcom8 (specifically binds to the cTnIC complex epitope).

[0211] In addition to the above kits, the experiments also used kits in which antibodies 2-3 used in the total cTnITC detection kits 3-5 and 8-12 were replaced with antibodies 7F4, whose specific binding site is cTnT amino acid fragments 67-86, and antibodies 2F3, 1A11, or 1F11cc, whose specific binding site is cTnT amino acid fragments 145-164. In the experiments, the experiments also used kits in which antibodies 2-5 used in the total cTnITC detection kit 4 were replaced with antibodies M18cc, whose specific binding site is cTnI amino acid fragments 18-28, antibodies 16A11cc, 16A12cc, or 8E10cc, whose specific binding site is cTnI amino acid fragments 86-90, antibodies M46, whose specific binding site is cTnI amino acid fragments 130-145, and antibodies MF4cc, whose specific binding site is cTnI amino acid fragments 190-196.

[0212] Each detection kit includes the following:

[0213] A. A magnetic bead-coated working fluid for capturing myocardial damage markers in a sample. The magnetic bead-coated working fluid comprises a mixture of superparamagnetic microparticles coated with a capture antibody.

[0214] B. An enzyme-labeled working solution for detecting myocardial damage markers captured by superparamagnetic nanoparticles. The enzyme-labeled working solution contains a detection antibody labeled with alkaline phosphatase.

[0215] 4. Method for detecting myocardial damage markers The detection method is as follows:

[0216] Step 1: The sample, magnetic bead coating solution, and enzyme-labeled solution were added to the reaction tube and incubated. The target protein in the sample bound to the antibody coated on the magnetic beads, and the antibody-alkaline phosphatase label bound to the target protein in the sample. After the reaction was complete, the solid phase was placed in a magnetic field. The magnetic field adsorbed the magnetic beads, retaining the substances bound to the solid phase while washing away the unbound substances.

[0217] Step 2: The chemiluminescent substrate was added to the reaction tube. The luminescent substrate (3-(2-spiroadamantan)-4-methoxy-4-(3-phosphoryl)-phenyl-1,2-dioxetane, AMPPD) was decomposed by alkaline phosphatase, one phosphate group was removed, and an unstable intermediate product was purified. This intermediate product produced a methyl metaoxybenzoate anion through intramolecular electron transfer. When the excited methyl metaoxybenzoate anion returned from the excited state to the ground state, it produced chemiluminescence. The number of photons produced during the reaction was then measured using a photomultiplier tube. The number of photons produced was proportional to the concentration of the target protein in the sample. The amount of analyte in the sample was determined by a calibration curve.

[0218] The above detection kit can be used in combination with Mairui fully automatic chemiluminescence systems such as the CL2000i, CL6000i, and CL8000i.

[0219] 2. Analysis of the signal-to-noise ratio of the detection kit 1. Analysis of the signal-to-noise ratio of a large cTnITC detection kit Samples containing antigens of different concentrations were prepared, including two high-concentration samples and two low-concentration samples, where the antigen was recombinant cardiac troponin ternary complex (Hytest, 8ITCR). Each sample was analyzed using large cTnITC detection kits 1-8. Simultaneously, the signal from a blank sample without the antigen was recorded, and the signal-to-noise ratio was calculated.

[0220] The test results can be seen in Figure 3. As can be seen from Figure 3, all of the large cTnITC detection kits 1-8 had good signal-to-noise ratios and met clinical needs. Here, the signal-to-noise ratio of large cTnITC detection kit 3 was significantly higher than that of large cTnITC detection kits 1 and 5. Here, the signal-to-noise ratio of large cTnITC detection kit 4 was significantly higher than that of large cTnITC detection kits 2 and 5. This indicates that the combination of antibodies 1-2, which specifically bind to TnC, with antibodies 1-3 or 1-4 can significantly increase the signal-to-noise ratio. Large cTnITC detection kits 3, 7, and 8 had high signal-to-noise ratios, and it was shown that antibodies 1-1, whose specific binding sites are located at positions 119-138 and 132-151 of cTnT amino acids, clearly contribute to the improvement of the signal-to-noise ratio.

[0221] Furthermore, replacing antibodies 1-1 used in large-scale cTnITC detection kits 3-8 with antibodies 7F4 or 7G7 (specifically binding to cTnT amino acid fragments 67-86) or 2F3, 1A11, or 1F11cc (specifically binding to cTnT amino acid fragments 145-164), and replacing antibodies 1-4 used in large-scale cTnITC detection kit 4 with antibodies M18cc (specifically binding to cTnI amino acid fragments 18-28), 16A11cc, 16A12cc, or 8E10cc (specifically binding to cTnI amino acid fragments 86-90), M46 (specifically binding to cTnI amino acid fragments 130-145), or MF4cc (specifically binding to cTnI amino acid fragments 190-196) effectively reflects the signal differences of the samples.

[0222] 2. Analysis of the signal-to-noise ratio of the total cTnITC detection kit The signal-to-noise ratio analysis of all cTnITC detection kits (1-12) was performed by referring to the signal-to-noise ratio analysis method for large-scale cTnITC detection kits.

[0223] The test results can be seen in Figure 4. As can be seen from Figure 4, all total cTnITC detection kits 1-12 had good signal-to-noise ratios and met clinical needs. Here, the signal-to-noise ratio of total cTnITC detection kit 5 was higher than that of total cTnITC detection kit 6, indicating that the addition of antibodies 2-3, which specifically bind to cTnT amino acid fragments 67-222, improved the signal-to-noise ratio. The signal-to-noise ratio of total cTnITC detection kit 3 was significantly higher than that of total cTnITC detection kit 1 and total cTnITC detection kit 5, and the signal-to-noise ratio of total cTnITC detection kit 4 was significantly higher than that of total cTnITC detection kit 2 and total cTnITC detection kit 5, indicating that the combination of antibodies 2-2, which specifically bind to TnC, and antibodies 2-4 or 2-5 can significantly increase the signal-to-noise ratio. The signal-to-noise ratios (SNRs) of total cTnITC detection kits 3, 8, and 9 were similar, indicating that kits obtained by selecting antibodies 2-3 that specifically bind to different amino acid fragments between positions 67 and 222 of cTnT had similar SNRs. The signal-to-noise ratio of total cTnITC detection kit 8 was significantly better than that of total cTnITC detection kit 10, demonstrating that selecting an antibody 2-1 that specifically binds to amino acids between positions 223 and 242 of cTnT resulted in a better SNR compared to selecting an antibody that specifically binds to amino acids between positions 262 and 281 of cTnT. The signal-to-noise ratio of total cTnITC detection kit 3 was significantly higher than that of total cTnITC detection kits 11 and 12, demonstrating that antibodies specifically binding to cTnT at positions 119-138 (as antibodies 2-3) are superior to antibodies specifically binding to cTnT at positions 67-86 or 171-190.

[0224] It should be noted that if the antibody 2-3 used in the total cTnITC detection kits 3-5, 8-12 is replaced with antibody 7F4 (specific binding site is the cTnT amino acid 67-86 fragment), antibody 2F3, 1A11 or 1F11cc (specific binding site is the cTnT amino acid 145-164 fragment), and the antibody 2-5 used in the total cTnITC detection kit 4 is replaced with antibody M18cc (specific binding site is the cTnI amino acid 18-28 fragment), antibody 16A11cc, 16A12cc or 8E10cc (specific binding site is the cTnI amino acid 86-90 fragment), antibody M46 (specific binding site is the cTnI amino acid 130-145 fragment), or antibody MF4cc (specific binding site is the cTnI amino acid 190-196 fragment), any of these replacements can effectively reflect the signal difference of the sample.

[0225] III. Specificity Analysis of Detection Kits 1. Specificity Analysis of Large-format cTnITC Detection Kits Antigens of different equal concentrations were added into serum of healthy humans, and analysis was performed respectively by the chemiluminescence immunoassay method using the large-format cTnITC detection kits 1-8. The analyzed antigens include cTnT (Hytest, 8RTT5), cTnI (Hytest, 8RT17), cTnIC (Hytest, 8ICR3), and cTnITC (Hytest, 8ITCR).

[0226] For the experimental results, please refer to Figure 5. All of the large cTnITC detection kits 1 to 8 can only recognize the cTnITC antigen, but cannot recognize cTnT, cTnI and binary cTnIC. When antibody 1-1 used in large cTnITC detection kits 3 to 8 is replaced with antibody 7F4 or 7G7 whose specific binding site is the fragment of amino acids 67 to 86 of cTnT, or with antibody 2F3, 1A11 or 1F11cc whose specific binding site is the fragment of amino acids 145 to 164 of cTnT, and antibody 1-4 used in large cTnITC detection kit 4 is replaced with antibody M18cc whose specific binding site is the fragment of amino acids 18 to 28 of cTnI, 16A11cc, 16A12cc or 8E10cc whose specific binding site is the fragment of amino acids 86 to 90 of cTnI, antibody M46 whose specific binding site is the fragment of amino acids 130 to 145 of cTnI, or antibody MF4cc whose specific binding site is the fragment of amino acids 190 to 196 of cTnI, all of the replacement kits can effectively recognize the cTnITC antigen.

[0227] 2. Specificity analysis of total cTnITC detection kits With reference to the specificity analysis method for large cTnITC detection kits, analysis was performed on the specificity of total cTnITC detection kits 1 to 9.

[0228] The experimental results, as shown in Figure 6, show that all total cTnITC detection kits 1-9 can recognize only the cTnITC antigen, but cannot recognize cTnT, cTnI, or binary cTnIC. Furthermore, if antibodies 2-3 used in the total cTnITC detection kits 3-5 and 8-12 are replaced with antibodies 7F4, whose specific binding site is cTnT amino acid fragments 67-86, or antibodies 2F3, 1A11, or 1F11cc, whose specific binding site is cTnT amino acid fragments 145-164, and if antibodies 2-5 used in the total cTnITC detection kit 4 are replaced with antibodies M18cc, whose specific binding site is cTnI amino acid fragments 18-28, antibodies 16A11cc, 16A12cc, or 8E10cc, whose specific binding site is cTnI amino acid fragments 86-90, antibodies M46, whose specific binding site is cTnI amino acid fragments 130-145, or antibodies MF4cc, whose specific binding site is cTnI amino acid fragments 190-196, then the cTnITC antigen can be effectively recognized in all cases.

[0229] IV. Establishment of the blank limit and detection limit of the detection kit. Based on the guidelines of the Clinical Laboratory Standardization Council (CLSI) (EP-17A2 Protocols for Determination of Limits of Detection and Limits of Quantitation), we established the blank limit (LoB) and the limit of detection (LoD).

[0230] LoB (Lot of Balance) test results were obtained from 5 blank samples, which ran for 4 days, and each test was repeated 4 times. The general formula is LoB = mean + 1.65 * SD.

[0231] The LoD test results were obtained from five low-concentration samples, run for four days, and each test was repeated four times. The general formula is LoD = LoB + 1.65 * SD.

[0232] Refer to Tables 1-1 and 1-2 for the test results.

[0233] [Table 1]

[0234] [Table 2]

[0235] The blank limits and detection limits of large cTnITC detection kits 1-8 all met clinical needs. Here, the blank limits and detection limits of large cTnITC detection kit 3 were significantly lower than those of large cTnITC detection kits 1 and 5, and the blank limits and detection limits of large cTnITC detection kit 4 were significantly lower than those of large cTnITC detection kits 2 and 5. It was shown that the sensitivity of the kits could be significantly increased by adding antibodies 1-2 that specifically bind to TnC, or by using them in combination with antibodies 1-3 or 1-4. Furthermore, when antibodies 1-1 used in large cTnITC detection kits 3-8 were replaced with antibodies 7F4 or 7G7, whose specific binding site is cTnT amino acid fragments 67-86, or antibodies 2F3, 1A11, or 1F11cc, whose specific binding site is cTnT amino acid fragments 145-164, and when antibodies 1-4 used in large cTnITC detection kit 4 were replaced with antibodies M18cc, whose specific binding site is cTnI amino acid fragments 18-28, 16A11cc, 16A12cc, or 8E10cc, whose specific binding site is cTnI amino acid fragments 86-90, antibody M46, whose specific binding site is cTnI amino acid fragments 130-145, or antibody MF4cc, whose specific binding site is cTnI amino acid fragments 190-196, all of these resulted in low LoB and LoD values.

[0236] The blank limits and detection limits of total cTnITC detection kits 1-9 all met clinical needs. Here, the blank limits and detection limits of total cTnITC detection kit 5 were lower than those of total cTnITC detection kit 6, and the addition of antibodies 2-3, which specifically bind to cTnT amino acid fragments 119-138, was shown to increase sensitivity. The blank limits and detection limits of total cTnITC detection kit 3 were significantly lower than those of total cTnITC detection kits 1 and 5, and the blank limits and detection limits of total cTnITC detection kit 4 were significantly lower than those of total cTnITC detection kits 2 and 5. The addition of antibodies 2-2, which specifically bind to TnC, and their use in combination with antibodies 2-4 or 2-5, was shown to significantly increase the sensitivity of the kits. Furthermore, when antibodies 2-3 used in the total cTnITC detection kits 3-5 and 8-12 were replaced with antibodies 7F4 (specifically binding to cTnT amino acid fragments 67-86) and 2F3, 1A11, or 1F11cc (specifically binding to cTnT amino acid fragments 145-164), and antibodies 2-5 used in the total cTnITC detection kit 4 were replaced with antibodies M18cc (specifically binding to cTnI amino acid fragments 18-28), 16A11cc, 16A12cc, or 8E10cc (specifically binding to cTnI amino acid fragments 86-90), M46 (specifically binding to cTnI amino acid fragments 130-145), and MF4cc (specifically binding to cTnI amino acid fragments 190-196), all of these kits exhibited low LoB and LoD values.

[0237] 5. Linear analysis of detection kits 1. Linear analysis of large-scale cTnITC detection kits Large cTnITC detection kit 3 and large cTnITC kit 4 were used in linear analysis.

[0238] Clinical serum samples were selected as high-concentration samples, and these high-concentration samples were diluted at a fixed ratio to obtain serially diluted samples. The concentration range of the serially diluted samples was 0 to 6000 ng / L.

[0239] A sample was analyzed by chemiluminescence immunoassay using the large cTnITC detection kit 3. Linear fitting was performed on the average value of the test concentration results and the theoretical concentration, and the correlation coefficient within the linear range was calculated.

[0240] Refer to Figure 7 for the experimental results. The test concentration and theoretical concentration of the diluted sample showed linearity. The R² value within the linear range (0~6000ng / L) was 0.9982.

[0241] A sample was analyzed by chemiluminescence immunoassay using the large cTnITC detection kit 4. Linear fitting was performed on the average value of the test concentration results and the theoretical concentration, and the correlation coefficient within the linear range was calculated. Refer to Figure 8 for the experimental results. The test concentration and theoretical concentration of the diluted sample showed linearity. The R² value within the linear range (0~6000ng / L) was 0.9995.

[0242] 2. Linear analysis of total cTnITC detection kits Detection kit 3 and kit 4 were used for linear analysis.

[0243] Two clinical serum samples with different concentrations were selected as high-concentration samples, and the high-concentration samples were diluted at a certain ratio to obtain serially diluted samples. The concentration ranges of the serial samples were 0~120ng / L and 0~6000ng / L. A sample was analyzed by chemiluminescence immunoassay using detection kit 3. Linear fitting was performed on the average value of the test concentration results and the theoretical concentration, and the correlation coefficient within the linear range was calculated. Refer to Figure 9 for the experimental results. The test concentration and theoretical concentration of the diluted sample showed linearity. Within the linear range, the R² value for the low concentration range (0~120ng / L) was 0.9990, and the R² value for the high concentration range (0~6000ng / L) was 0.9992.

[0244] The samples were analyzed using chemiluminescence immunoassay with detection kit 4. Linear fitting was performed on the mean values ​​of the test concentrations and the theoretical concentrations, and the correlation coefficient within the linear range was calculated. See Figure 10 for the experimental results, and the test concentrations and theoretical concentrations of the diluted samples showed a linear relationship. Within the linear range, the R2 value for the low concentration range (0-120 ng / L) was 0.9979, and the R2 value for the high concentration range (0-6000 ng / L) was 0.9988.

[0245] In the following examples, the concentrations of each marker in the sample were detected using the cTnI detection kit, cTnT detection kit, total cardiac troponin complex detection kit, large cTnITC detection kit 7, and total cTnITC detection kit 8.

[0246] Example 2. Diagnosis of early myocardial infarction (stage determination of myocardial infarction patients) 1. Patient participation Patients selected for inclusion were those diagnosed with type 1 acute myocardial infarction at admission and at the time of final diagnosis, and all patients were 18 years of age or older. All patients were diagnosed with myocardial infarction and subsequently received interventional treatment. Acute myocardial infarction was independently determined by the hospital's cardiologist based on the definition of acute myocardial infarction. Clinical examinations, including physical examination, echocardiography, electrocardiogram recording, high-sensitivity troponin I detection, high-sensitivity troponin T detection, and coronary angiography, were used to complete the determination of acute myocardial infarction. Patients whose final diagnosis was not acute myocardial infarction or whose diagnostic information was incomplete were excluded. Patients under 18 years of age and pregnant women were excluded. Heparinized lithium plasma samples were collected prior to interventional treatment and used for troponin complex and fragment composition analysis. Refer to Figure 11 for the patient inclusion flow.

[0247] Patient information was recorded, including age, sex, symptoms (chest pain, chest tightness, shortness of breath, etc.), time of onset, medical history, hypertension, diabetes, smoking status, creatinine, and glomerular filtration rate. Samples meeting the eligibility criteria were selected, and relevant marker tests were performed. A total of 61 patients with acute myocardial infarction were accepted, of which 49 were male, representing 80%. See Table 2-1 for patient information.

[0248] [Table 3]

[0249] 2. Analysis of the relationship between troponin marker concentration and chest pain duration in patients with acute myocardial infarction. After sample inclusion, troponin markers, including total complex, large cTnITC, total cTnITC, cTnT, and cTnI, were tested in the participating patient samples using a Maizuru chemiluminescence instrument. Patients were divided into different subgroups based on the duration of their chest pain (≤10 hours, 10–30 hours, 30–72 hours, and >72 hours). Table 2-2 shows the concentrations of total complex, large cTnITC, total cTnITC, cTnT, and cTnI in the patients' blood. Here, the concentrations of total complex, large cTnITC, total cTnITC, cTnT, and cTnI were significantly higher in patients with chest pain durations of 10–72 hours than in patients with chest pain durations of >72 hours. The cTnI kit and total complex measurements were similar, indicating a certain degree of clinical equivalence between the two.

[0250] [Table 4]

[0251] Figure 12 shows the ratio of troponin complexes and fragments in patients with different chest pain durations, including the ratio of large cTnITC concentration to total complex concentration, the ratio of total cTnITC concentration to total complex concentration, and the ratio of cTnT concentration to total complex concentration. Here, the proportion of ternary cTnITCs (including large cTnITCs and total cTnITCs) was high in early acute myocardial infarction patients with short chest pain durations, and the proportion of cTnTs was high in patients with chest pain durations shorter than 10 hours and longer than 72 hours. These results indicate that in patients diagnosed with acute myocardial infarction, the complex and fragment composition of cardiac troponin is strongly correlated with the time from symptom onset to blood sampling. In early acute myocardial infarction patients with short chest pain onset times, the proportion of large cTnITCs or total cTnITCs was high, and in patients with chest pain durations shorter than 10 hours and longer than 72 hours, the proportion of cTnTs was high. The correlation between troponin complex and fragment composition and the duration of chest pain in patients with acute myocardial infarction showed that using a single marker, such as cTnT alone, makes it difficult to accurately determine the stage of disease development, especially in patients where chest pain is not apparent (e.g., when taking analgesics). Specific recognition of different troponin fragments may be useful for diagnosing acute myocardial infarction and confirming the disease state, and in particular, the ternary complex (including large cTnITC and total cTnITC) shows a more pronounced continuous downward trend and may be more suitable for early diagnosis.

[0252] 3. Diagnostic effectiveness of concentration and concentration ratio characteristic parameters used to predict early myocardial infarction. Table 2-3 shows the diagnostic effectiveness of the concentration and concentration ratio characteristic parameters. In this example, patients with chest pain onset within 72 hours were selected as early myocardial infarction patients. Here, the P values ​​for total complex concentration, large cTnITC concentration, total cTnITC concentration, cTnI concentration, concentration ratio of large cTnITC to total complex, concentration ratio of total cTnITC to total complex, concentration ratio of cTnT to total complex, concentration ratio of large cTnITC to cTnT, concentration ratio of total cTnITC to cTnT, and concentration ratio of large cTnITC to cTnI were all less than 0.05, indicating that the variables were statistically significant. ROC curves were created using SPSS software, and the area under the curve (AUC) was obtained. Here, the area under the curve (AUC) for large cTnITC concentration was 0.833, the AUC for the concentration ratio of large cTnITC to total complex was 0.883, and the AUC for the concentration ratio of large cTnITC to cTnT was 0.923, indicating good diagnostic efficacy. The measured values ​​for the cTnI kit and total complex were similar, and the two had a certain degree of clinical equivalence. These results suggest that using the concentration of large cTnITC or total cTnITC alone, or using the ratio of large cTnITC concentration or total cTnITC concentration to total complex concentration, cTnT concentration or cTnI concentration as a characteristic parameter, is more effective in predicting early myocardial infarction than using the concentration of total complex, cTnT, or cTnI alone.

[0253] [Table 5]

[0254] Using sensitivity and specificity corresponding to different cutoff values ​​with the total complex concentration, large cTnITC concentration, total cTnITC concentration, cTnI concentration, concentration ratio of large cTnITC to total complex, concentration ratio of total cTnITC to total complex, concentration ratio of cTnT to total complex, concentration ratio of large cTnITC to cTnT, concentration ratio of total cTnITC to cTnT, and concentration ratio of large cTnITC to cTnI as characteristic parameters, the Iorden index is calculated, and the optimal cutoff value for diagnosis is determined based on the maximum Iorden index, referring to Table 2-4.

[0255] [Table 6]

[0256] 4. Diagnostic effectiveness of combinations of multiple concentration-based parameters used to predict early myocardial infarction. The characteristic parameters of the marker concentration include total complex concentration, large cTnITC concentration, total cTnITC concentration, cTnT concentration, and cTnI concentration. In this example, patients with chest pain onset within 72 hours were selected as early myocardial infarction patients.

[0257] Large cTnITC concentration and cTnT concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for calculating the feature parameter, namely Logit(P) = 0.0661 * (large cTnITC concentration) - 0.0012 * (cTnT concentration) - 0.4725. The method for calculating the predicted probability (feature parameter 1) is P = 1 / (1 + e -logit )*100%.

[0258] Large cTnITC concentration and total complex concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for calculating the feature parameter, namely Logit(P) = 0.0313 * (large cTnITC concentration) - 0.0009 * (total complex concentration) - 0.8964. The method for calculating the predicted probability (feature parameter 2) is P = 1 / (1 + e -logit )*100%.

[0259] Large cTnITC concentration and total cTnITC concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for calculating the feature parameter, namely Logit(P) = 0.0224 * (large cTnITC concentration) - 0.0013 * (total cTnITC concentration) - 1.2990. The method for calculating the predicted probability (feature parameter 3) is P = 1 / (1 + e -logit )*100%.

[0260] Large cTnITC concentration, total cTnITC concentration, total complex concentration, and cTnT concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for the feature parameter, namely Logit(P) = 0.0615*(large cTnITC concentration) - 0.0002*(total cTnITC concentration) + 0.0003*(total complex concentration) - 0.0013*(cTnT concentration) - 0.4727. The method for calculating the predicted probability (feature parameter 4) is P = 1 / (1+e-logit)*100%.

[0261] Here, the area under the curve (AUC) for feature parameter 1, feature parameter 2, feature parameter 3, and feature parameter 4 are 0.923, 0.880, 0.858, and 0.920, respectively, indicating good diagnostic effectiveness; see Table 2-5. Based on the maximum value of the Yoden index, the optimal CUTOFF values ​​for diagnosis are determined to be 0.3829, 0.2949, 0.2249, and 0.3592, respectively; see Table 2-6.

[0262] [Table 7]

[0263] [Table 8]

[0264] Furthermore, other combinations of concentration characteristic parameters include total cTnITC concentration + total complex concentration, total cTnITC concentration + cTnT concentration, large cTnITC concentration + total cTnITC concentration + total complex concentration, large cTnITC concentration + total cTnITC concentration + cTnT concentration, large cTnITC concentration + total complex concentration + cTnT concentration, and total cTnITC concentration + total complex concentration + cTnT concentration. When these combinations were used for the diagnosis of early myocardial infarction, they all showed good diagnostic effectiveness. These results indicate that using large cTnITC concentration and / or total cTnITC concentration in combination with other troponin fragment concentrations to predict early myocardial infarction yields good performance.

[0265] 5. Diagnostic effectiveness of combinations of concentration ratio characteristic parameters used to predict early myocardial infarction. The concentration ratio characteristic parameters include the ratio of the concentration of large cTnITC or total cTnITC to the concentration of the total complex, cTnT, or cTnI, i.e., large cTnITC concentration / total complex concentration, total cTnITC concentration / total complex concentration, cTnT concentration / total complex or concentration, large cTnITC concentration / cTnT concentration, total cTnITC concentration / cTnT concentration, large cTnITC concentration / cTnI concentration, and total cTnITC concentration / cTnI concentration. In this example, patients with chest pain onset within 72 hours were selected as early myocardial infarction patients.

[0266] Large cTnITC concentration / total complex concentration, total cTnITC concentration / total complex concentration, and cTnT concentration / total complex concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for calculating the feature parameter, namely Logit(P) = 27.708 * (large cTnITC concentration / total complex concentration) + 9.322 * (total cTnITC / total complex) - 0.558 * (cTnT concentration / total complex concentration) - 1.456. The method for calculating the predicted probability (feature parameter 5) is P = 1 / (1 + e -logit )*100%.

[0267] Large cTnITC concentration / cTnT concentration and total cTnITC concentration / cTnT concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for calculating the feature parameter, namely Logit(P) = 78.924 * (large cTnITC concentration / cTnT concentration) + 21.483 * (total cTnITC concentration / cTnT concentration) - 3.004. The method for calculating the prediction probability (feature parameter 6) is P = 1 / (1 + e -logit )*100%.

[0268] Here, the area under the curve (AUC) for feature parameter 5 and feature parameter 6 are 0.945 and 0.938, respectively, indicating good diagnostic effectiveness; see Table 2-7. Based on the maximum value of the Yoden index, the optimal CUTOFF values ​​for diagnosis are determined to be 0.2729 and 0.2031, respectively; see Table 2-8.

[0269] [Table 9]

[0270] [Table 10]

[0271] Furthermore, other combinations of concentration ratio parameters, including large cTnITC concentration / total complex concentration + total cTnITC concentration / total complex concentration, large cTnITC concentration / total complex concentration + cTnT concentration / total complex concentration, total cTnITC concentration / total complex concentration + cTnT concentration / total complex concentration, large cTnITC concentration / total complex concentration + total cTnITC concentration / total complex concentration + large cTnITC concentration / cTnT concentration, and large cTnITC concentration / total complex concentration + total cTnITC concentration / total complex concentration + total cTnITC concentration / cTnT concentration, all of which, when used in combination in the above manner for the diagnosis of early myocardial infarction, showed good diagnostic effect. The results showed that combinations of ratios of large cTnITCs to other troponin fragments, ratios of total cTnITCs to other troponin fragments, and ratios of at least one of these to other troponin fragments performed well when used to predict early myocardial infarction.

[0272] The above data demonstrates that large cTnITC concentration and total cTnITC concentration can be used individually as characteristic parameters to predict early myocardial infarction. The ratio of large cTnITC concentration or total cTnITC concentration to total complex concentration, cTnT, or cTnI can also be used to predict early myocardial infarction, preferably using large cTnITC concentration / total complex concentration, large cTnITC concentration / cTnT concentration, or large cTnITC concentration / cTnI concentration. Furthermore, the use of combinations of multiple parameters, such as a combination of large cTnITC concentration and cTnT concentration, a combination of large cTnITC concentration and total complex concentration, a combination of large cTnITC concentration and total cTnITC concentration, or a combination of large cTnITC concentration, total cTnITC concentration, total complex concentration and cTnT concentration, or a combination of large cTnITC concentration / total complex concentration, total cTnITC concentration / total complex concentration and cTnT concentration / total complex concentration, or a combination of large cTnITC concentration / cTnT concentration and total cTnITC concentration / cTnT concentration, can further improve diagnostic effectiveness. Although not subject to theoretical constraints, large cTnITC or characteristic parameters obtained based on large cTnITC may be more suitable for the diagnosis of early myocardial infarction.

[0273] Example 3.1 Distinction between type 1 and type 2 myocardial infarction 1. Patient participation Patients selected for this study had a diagnosis of type 1 or type 2 acute myocardial infarction at admission or at the time of final diagnosis, and all patients were 18 years of age or older. All patients were diagnosed with either type 1 or type 2 acute myocardial infarction and had a symptom onset time of less than 72 hours. Acute myocardial infarction was independently determined by the hospital's cardiologist based on the definition of acute myocardial infarction. Clinical tests, including physical examination, echocardiography, electrocardiogram recording, high-sensitivity troponin I detection, high-sensitivity troponin T detection, and coronary angiography, were used to complete the determination of acute myocardial infarction. Patients whose final diagnosis was not type 1 or type 2 acute myocardial infarction, or whose diagnostic information was incomplete, were excluded. Patients under 18 years of age and pregnant women were excluded. Heparinized lithium plasma samples were collected from patients before treatment and used for troponin complex and fragment composition analysis.

[0274] We admitted a total of 24 patients with type 1 acute myocardial infarction and 6 patients with type 2 acute myocardial infarction.

[0275] 2. Analysis of the content of myocardial damage markers in patients with type 2 myocardial infarction and type 2 myocardial infarction. After sample ingestion, troponin markers, including total complex, large cTnITC, total cTnITC, cTnT, and cTnI, were tested in the participating patient samples using a Maizuru chemiluminescence device. Differences in troponin composition were analyzed between patients with acute myocardial infarction, patients with cardiomyopathy or chronic heart failure, and patients with pneumonia. Table 3-1 shows the concentrations of total complex, large cTnITC, total cTnITC, cTnT, and cTnI in the patients' blood. Here, the concentrations of total complex, large cTnITC, total cTnITC, and cTnI were significantly higher in patients with type 1 myocardial infarction than in patients with type 2 myocardial infarction. Here, the measured values ​​of the cTnI kit and the total complex kit were similar, and the two had a certain degree of clinical equivalence.

[0276] [Table 11]

[0277] Figure 13 shows the ratio relationship between troponin complexes and fragments in patients with type 1 and type 2 myocardial infarction, including the ratio of large cTnITC concentration to total complex concentration, the ratio of total cTnITC concentration to total complex concentration, the ratio of cTnT concentration to total complex concentration, the ratio of large cTnITC concentration to cTnT concentration, and the ratio of total cTnITC concentration to cTnT concentration. Here, the ratio of large cTnITC concentration to total complex concentration, the ratio of total cTnITC concentration to total complex concentration, the ratio of large cTnITC concentration to cTnT concentration, and the ratio of total cTnITC concentration to cTnT concentration were high in patients with type 1 myocardial infarction and low in patients with type 2 myocardial infarction.

[0278] The above data demonstrates that large cTnITC concentration or total cTnITC concentration can be used to distinguish between type 1 and type 2 myocardial infarction. Here, large cTnITC is preferred.

[0279] Example 4-1. Distinction between acute myocardial infarction (type 1) and chronic cardiac events. 1. Patient participation (1) Acute Myocardial Infarction (Type 1) Patient Group: Patients selected for inclusion were those diagnosed with type 1 acute myocardial infarction at admission and at the time of final diagnosis, and all patients were 18 years of age or older. All patients were diagnosed with acute myocardial infarction and the symptom onset time was less than 72 hours. These patients subsequently received interventional treatment. Acute myocardial infarction was independently determined by the hospital's cardiologist based on the definition of acute myocardial infarction. The determination of acute myocardial infarction was completed by clinical examinations including physical examination, echocardiography, electrocardiogram recording, high-sensitivity troponin I detection, high-sensitivity troponin T detection, and coronary angiography. Patients whose final diagnosis was not acute myocardial infarction or whose diagnostic information was incomplete were excluded. Patients under 18 years of age and pregnant female patients were excluded. Heparinized lithium plasma samples were collected before interventional treatment and used for troponin complex and fragment composition analysis. Refer to Figure 14 for the patient participation flow.

[0280] (2) Patients with chronic cardiac events: a) Patients were selected to participate if their admission diagnosis and final diagnosis was chronic heart failure or cardiomyopathy, and their age was 18 years or older. Patients whose final diagnosis was not chronic heart failure or cardiomyopathy were excluded. Patients who were simultaneously diagnosed with acute myocardial infarction were excluded. Patients under 18 years of age and pregnant women were excluded. Cardiomyopathy and chronic heart failure were independently determined by hospital clinicians. Acute myocardial infarction was independently determined by hospital cardiologists based on the definition of acute myocardial infarction. Initial heparinized lithium plasma samples were collected from these patients after admission and used for troponin complex and fragment composition analysis. Refer to Figure 15 for the patient participation flow.

[0281] b) Patients were selected to participate if their diagnosis at admission and final diagnosis was pneumonia, and their age was 18 years or older. Patients whose final diagnosis was not pneumonia were excluded. Patients who were also diagnosed with acute myocardial infarction were excluded. Patients under 18 years of age and pregnant women were excluded. Pneumonia was independently determined by hospital clinicians. Acute myocardial infarction was independently determined by hospital cardiologists based on the definition of acute myocardial infarction. Initial heparinized lithium plasma samples were collected from these patients after admission and used for troponin complex and fragment composition analysis. Refer to Figure 16 for the patient participation flow.

[0282] Patient information was recorded, including age, sex, medical history, hypertension, diabetes, smoking status, creatinine, and glomerular filtration rate. Samples meeting the eligibility criteria were selected, and relevant marker tests were performed. A total of 24 patients with acute myocardial infarction (type 1) and 145 patients with chronic cardiac events were admitted. From these, a total of 94 samples of hospitalized patients with cardiomyopathy or chronic heart failure and 51 samples of patients with pneumonia were collected. See Table 4-1-1 for patient information.

[0283] [Table 12]

[0284] Continuous variables are shown using the median (25th to 75th percentile), while categorical variables are shown using numbers (percentages).

[0285] 2. Troponin composition analysis in acute myocardial infarction (type 1) and chronic cardiac event samples After sample ingestion, troponin markers, including total troponin complex, large cTnITC, total cTnITC, and cTnT, were tested in the samples using a Maizuru chemiluminescence apparatus and corresponding reagents. Differences in troponin composition were analyzed between patients with acute myocardial infarction (type 1), patients with cardiomyopathy or chronic heart failure, and patients with pneumonia. See Table 4-1-2 for the concentrations of total troponin complex, large cTnITC, total cTnITC, and cTnT in the patients' blood.

[0286] [Table 13]

[0287] Figure 17 shows the ratio relationship between troponin complexes and fragments in patients with acute myocardial infarction (type 1) and patients with chronic cardiac events, including the ratios of large cTnITC / total complex, total cTnITC / total complex, cTnT / total complex, large cTnITC / cTnT, and total cTnITC / cTnT. Here, the proportions of large cTnITC / total complex, large cTnITC / cTnT, and total cTnITC / cTnT were low in patients with chronic cardiac events (including patients with cardiomyopathy or chronic heart failure and patients with pneumonia), while the proportions were high in patients with acute myocardial infarction (type 1). The proportion of cTnT / total complex was high in patients with chronic cardiac events, while the proportion was low in patients with acute myocardial infarction (type 1).

[0288] The correlation between troponin complex and fragment composition and disease type demonstrated that specific recognition of different troponin fragments can be used in the diagnosis and differentiation of acute myocardial infarction (type 1) and chronic cardiac events.

[0289] 3. Diagnostic effectiveness of concentration-specific parameters and concentration-ratio-specific parameters used to differentiate between acute myocardial infarction (type 1) and chronic cardiac events. Table 4-1-3 shows the diagnostic efficacy of the troponin complex and fragment markers used. In this example, patients had either acute myocardial infarction (type 1) or a chronic cardiac event, and patients with chronic cardiac events had cardiomyopathy, chronic heart failure, or pneumonia. To facilitate ratio analysis between complexes, the total complex concentration in the patient samples accepted for analysis was higher than 0.1 pmol / L.

[0290] Here, the P-values ​​for total complex concentration, large cTnITC concentration, total cTnITC concentration, cTnT concentration, cTnI concentration, large cTnITC / total complex ratio, total cTnITC / total complex ratio, cTnT / total complex ratio, large cTnITC / cTnT ratio, total cTnITC / cTnT ratio, and large cTnITC / cTnI ratio were all less than 0.05, indicating that the variables were statistically significant. Here, the area under the curve AUC for large cTnITC concentration was 0.929, the area under the curve AUC for total cTnITC concentration was 0.869, and the AUC for the large cTnITC / cTnT ratio was 0.870, indicating good diagnostic efficacy. The measured values ​​for the cTnI kit and total complex were similar, and the two had a certain degree of clinical equivalence. The results showed that using the concentration of large cTnITC or total cTnITC alone, or using the ratio of large cTnITC to cTnT, was more effective in differentiating acute myocardial infarction (type 1) from chronic cardiac events compared to using the concentration of troponin total complex, cTnT, or cTnI alone.

[0291] [Table 14]

[0292] The Yoden index was calculated using the sensitivity and specificity corresponding to different cutoff values ​​for characteristic parameters, and the optimal CUTOFF value for diagnosis (Table 4-1-4) was determined based on the maximum value of the Yoden index. The cutoff value for total complex concentration was 247.7, the cutoff value for large cTnITC concentration was 1.9, the cutoff value for total cTnITC concentration was 13.6, the cutoff value for cTnT concentration was 754.7, the cutoff value for cTnI concentration was 278.8, the cutoff value for large cTnITC / total complex was 0.0498, the cutoff value for total cTnITC / total complex was 0.1779, the cutoff value for cTnT / total complex was 3.4450, the cutoff value for large cTnITC / cTnT was 0.0165, the cutoff value for total cTnITC / cTnT was 0.0365, and the cutoff value for large cTnITC / cTnI was 0.0705.

[0293] [Table 15]

[0294] 4. Diagnostic effectiveness of integrated analysis of multiple concentration-characteristic parameters used to differentiate between acute myocardial infarction (type 1) and chronic cardiac events. The diagnostic effectiveness of a combination analysis of multiple concentration feature parameters for differentiating between acute myocardial infarction (type 1) and chronic cardiac events was evaluated. The feature parameters included concentrations of troponin complexes and fragments, i.e., total complex concentration, large cTnITC concentration, total cTnITC concentration, cTnT concentration, and cTnI concentration. In this example, patients had either acute myocardial infarction (type 1) or a chronic cardiac event, and patients with chronic cardiac events had cardiomyopathy, chronic heart failure, or pneumonia. The total complex concentration in patient samples was higher than 0.1 pmol / L.

[0295] Large cTnITC concentration + cTnT concentration were selected as features, and an integrated analysis was performed. Based on the logistic regression algorithm, combined prediction parameters were constructed, and the coefficients of each feature were estimated by logistic regression. The formula for calculating the predicted value was output: Logit(P) = 0.0484 * (large cTnITC concentration) - 0.0003 * (cTnT concentration) - 2.3441. The method for calculating the prediction probability (prediction parameter 1) is P = 1 / (1 + e -logit )*100%.

[0296] Large cTnITC concentration + total complex concentration were selected as features, and an integrated analysis was performed. Based on the logistic regression algorithm, combined prediction parameters were constructed, and the coefficients of each feature were estimated by logistic regression. The formula for calculating the predicted value was output: Logit(P) = 0.0266 * (large cTnITC concentration) - 0.00004 * (total complex concentration) - 2.3382. The method for calculating the prediction probability (prediction parameter 2) is P = 1 / (1 + e -logit )*100%.

[0297] Large cTnITC concentration + total cTnITC concentration were selected as features, and an integrated analysis was performed. Based on the logistic regression algorithm, combined prediction parameters were constructed, and the coefficients of each feature were estimated by logistic regression. The formula for calculating the predicted value was output: Logit(P) = 0.0315 * (large cTnITC concentration) - 0.0016 * (total cTnITC concentration) - 2.3538. The method for calculating the prediction probability (prediction parameter 3) is P = 1 / (1 + e -logit )*100%.

[0298] Large cTnITC concentration + total cTnITC concentration + total complex + cTnT concentration were selected as features, and an integrated analysis was performed. Based on the logistic regression algorithm, combined prediction parameters were constructed, and the coefficients of each feature were estimated by logistic regression. The formula for calculating the predicted value was output: Logit(P) = 0.0523 * (large cTnITC concentration) + 0.0221 * (total cTnITC concentration) + 0.0001 * (total complex concentration) - 0.0019 * (cTnT concentration) - 2.0412. The method for calculating the prediction probability (prediction parameter 4) is P = 1 / (1 + e - logit) * 100%.

[0299] Here, the area under the curve AUC for predictor parameter 1, predictor parameter 2, predictor parameter 3, and predictor parameter 4 were 0.870, 0.928, 0.845, and 0.960, respectively, indicating good diagnostic effectiveness (Table 4-1-5). Based on the maximum value of the Yoden index, the optimal CUTOFF values ​​for diagnosis were determined to be 0.1150, 0.0920, 0.1828, and 0.1077, respectively (Table 4-1-6).

[0300] [Table 16]

[0301] [Table 17]

[0302] Furthermore, when other combinations, including total cTnITC concentration + total complex concentration, total cTnITC concentration + cTnT concentration, large cTnITC concentration + total cTnITC concentration + total complex concentration, large cTnITC concentration + total cTnITC concentration + cTnT concentration, large cTnITC concentration + total complex concentration + cTnT concentration, and total cTnITC concentration + total complex concentration + cTnT concentration, were combined using the above method and used to distinguish between acute myocardial infarction (type 1) and chronic cardiac events, all showed good diagnostic effectiveness. These results indicate that integrated analysis of large cTnITC concentration or total cTnITC concentration and other troponin fragment concentrations performs well when used to distinguish between acute myocardial infarction (type 1) and chronic cardiac events.

[0303] 6. Diagnostic effectiveness of integrated analysis of multiple concentration ratio characteristic parameters used to differentiate between acute myocardial infarction (type 1) and chronic cardiac events. The diagnostic effectiveness of differentiating between acute myocardial infarction (type 1) and chronic cardiac events was evaluated using a pooled analysis of multiple concentration ratio parameters. Concentration ratio characteristic parameters included the ratios of troponin complexes and fragments to total troponin complex, cTnT, or cTnI, i.e., large cTnITC / total complex, total cTnITC / total complex, cTnT / total complex, large cTnITC / cTnT, total cTnITC / cTnT, large cTnITC / cTnI, and total cTnITC / cTnI. In this example, patients had either acute myocardial infarction (type 1) or a chronic cardiac event, and patients with chronic cardiac events had cardiomyopathy, chronic heart failure, or pneumonia. The concentration of the total complex in the patient samples was higher than 0.1 pmol / L.

[0304] Large cTnITC / total complex + total cTnITC / total complex + cTnT / total complex were selected as features, and an integrated analysis was performed. Based on the logistic regression algorithm, combined prediction parameters were constructed, and the coefficients of each feature were estimated by logistic regression. The formula for calculating the predicted value was output: Logit(P) = 10.532 * (large cTnITC / total complex) + 24.346 * (total cTnITC / total complex) - 1.076 * (cTnT / total complex) - 1.099. The method for calculating the prediction probability (prediction parameter 5) is P = 1 / (1 + e-logit )*100%.

[0305] Large cTnITC / cTnT and total cTnITC / cTnT were selected as features, and a combined analysis was performed. Based on the logistic regression algorithm, combined prediction parameters were constructed, and the coefficients of each feature were estimated by logistic regression. The formula for calculating the predicted value was output: Logit(P) = 16.149 * (large cTnITC / cTnT) + 62.770 * (total cTnITC / cTnT) - 4.041. The method for calculating the prediction probability (prediction parameter 6) is P = 1 / (1 + e -logit )*100%.

[0306] Here, the area under the curve AUC for predictive parameter 5 and predictive parameter 6 were 0.961 and 0.892, respectively, indicating good diagnostic effectiveness (Table 4-1-7). Based on the maximum value of the Yoden index, the optimal CUTOFF values ​​for diagnosis were determined to be 0.1562 and 0.2286, respectively (Table 4-1-8).

[0307] [Table 18]

[0308] [Table 19]

[0309] Furthermore, when other combinations, including large cTnITC / total complex + total cTnITC / total complex, large cTnITC / total complex + cTnT / total complex, total cTnITC / total complex + cTnT / total complex, large cTnITC / total complex + total cTnITC / total complex + large cTnITC / cTnT, and large cTnITC / total complex + total cTnITC / total complex + total cTnITC / cTnT, were combined using the above method and used to distinguish between acute myocardial infarction (type 1) and chronic cardiac events, all showed good diagnostic effectiveness. According to these results, when a combined analysis of the ratio of large cTnITC to other troponin fragments, the ratio of total cTnITC to other troponin fragments, and the ratio of at least one of these to other troponin fragments was performed and used to distinguish between acute myocardial infarction (type 1) and chronic cardiac events, it was shown to have good performance.

[0310] The data above demonstrates that troponin large cTnITC complexes and total cTnITC complexes, when used alone, can be used to differentiate between acute myocardial infarction (type 1) and chronic cardiac events. The ratio of large cTnITC complexes or total cTnITC complexes to total complexes, and the ratio of large cTnITC concentration or total cTnITC concentration to cTnT concentration, can also be used to differentiate between acute myocardial infarction (type 1) and chronic cardiac events. The use of combinations of concentrations of multiple markers, such as troponin large cTnITC complex + total complex concentration, large cTnITC concentration + cTnT concentration, large cTnITC concentration + total cTnITC concentration, or large cTnITC concentration + total cTnITC concentration + total complex concentration + cTnT concentration, or the use of combinations of ratios of multiple markers, such as large cTnITC / total complex, total cTnITC / total complex, cTnT / total complex, or large cTnITC concentration / cTnT concentration, total cTnITC concentration / cTnT concentration, can further enhance the diagnostic effect.

[0311] Example 4-2. Distinction between acute myocardial infarction (type 1) and chronic cardiac events (patients under observation). 1. Patient participation Patients whose troponin I levels were between the 99th and 5th percentiles in their initial blood test at the time of their visit were admitted. According to the 0-3 hour rapid diagnostic flow using high-sensitivity cardiac troponin, these patients could not be admitted or excluded and were referred to as patients under observation. A total of 84 patients were admitted, of which 9 were type 1 acute myocardial infarction patients with symptom onset time of less than 72 hours, and 75 were patients with other chronic cardiac events.

[0312] Refer to Table 4-2-1 for patient information.

[0313] [Table 20]

[0314] After sample collection, troponin markers, including total troponin complex, large cTnITC, total cTnITC, and cTnT, were tested in the samples using a Maizuru chemiluminescence apparatus and corresponding reagents. Differences in troponin composition between patients with acute myocardial infarction (type 1) and patients with chronic cardiac events were analyzed. See Table 4-2-2 for the concentrations of total complex, large cTnITC, total cTnITC, and cTnT in the patients' blood.

[0315] [Table 21]

[0316] The ratio of large cTnITC concentration to total complex concentration, the ratio of large cTnITC concentration to cTnT concentration, and the ratio of total cTnITC concentration to cTnT concentration were low in patients with chronic cardiac events, while they were high in patients with acute myocardial infarction (type 1). The ratio of cTnT / total complex was high in patients with chronic cardiac events, while it was low in patients with acute myocardial infarction (type 1). The correlation between troponin complex and fragment composition and disease type indicated that specific recognition of different troponin fragments can be used to distinguish between acute myocardial infarction (type 1) and chronic cardiac events in patients whose troponin I measurements are between the 99th percentile and five times the 99th percentile.

[0317] Table 4-2-3 shows the diagnostic effectiveness of the concentration and concentration ratio characteristic parameters used to distinguish between acute myocardial infarction (type 1) and chronic cardiac events in patients whose troponin I measurements were between the 99th percentile and five times the 99th percentile.

[0318] [Table 22]

[0319] Here, the P-values ​​for large cTnITC concentration, total cTnITC concentration, cTnT concentration, the ratio of large cTnITC concentration to total complex concentration, the ratio of cTnT concentration to total complex concentration, the ratio of large cTnITC concentration to cTnT concentration, and the ratio of total cTnITC concentration to cTnT concentration were all less than 0.05, indicating that the variables were statistically significant. Here, the AUC of the area under the curve for large cTnITC concentration was 0.842, the AUC of the ratio of large cTnITC concentration to total complex concentration was 0.852, the AUC of the ratio of large cTnITC concentration to cTnT concentration was 0.875, and the AUC of the ratio of total cTnITC concentration to cTnT concentration was 0.842, indicating good diagnostic efficacy. The results indicate that using large cTnITC concentration, or the ratio of large cTnITC concentration to total complex concentration, the ratio of large cTnITC concentration to cTnT concentration, or the ratio of total cTnITC concentration to cTnT concentration as characteristic parameters, can more effectively distinguish between acute myocardial infarction (type 1) and chronic cardiac events.

[0320] Using the sensitivity and specificity corresponding to different cutoff values ​​for the characteristic parameters, calculate the Iorden index, determine the optimal cutoff value for diagnosis based on the maximum Iorden index, and refer to 4-2-4.

[0321] [Table 23]

[0322] The diagnostic effectiveness of a combination of concentration-specific parameters of multiple myocardial injury markers, used to distinguish between acute myocardial infarction (type 1) and chronic cardiac events in patients whose troponin I measurements were between the 99th percentile and five times the 99th percentile, was analyzed. The concentration-specific parameters of myocardial injury markers include the concentrations of the troponin complex and fragments, i.e., total complex concentration, large cTnITC concentration, total cTnITC concentration, cTnT concentration, and cTnI concentration.

[0323] Large cTnITC concentration and cTnT concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for calculating the feature parameter, namely Logit(P) = 0.1593 * (large cTnITC concentration) - 0.0052 * (cTnT concentration) - 1.3890. The method for calculating the predicted probability (feature parameter 1) is P = 1 / (1 + e -logit )*100%.

[0324] Large cTnITC concentration and total complex concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for calculating the feature parameter, namely Logit(P) = 0.1722 * (large cTnITC concentration) + 0.0066 * (total complex concentration) - 3.2247. The method for calculating the predicted probability (feature parameter 2) is P = 1 / (1 + e -logit )*100%.

[0325] Large cTnITC concentration and total cTnITC concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for calculating the feature parameter, namely Logit(P) = 0.1761 * (large cTnITC concentration) + 0.0608 * (total cTnITC concentration) - 3.2829. The method for calculating the predicted probability (feature parameter 3) is P = 1 / (1 + e -logit )*100%.

[0326] Large cTnITC concentration, total cTnITC concentration, total complex, and cTnT concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for calculating the feature parameter, namely Logit(P) = 0.1450*(large cTnITC concentration) + 0.2588*(total cTnITC concentration) + 0.0086*(total complex concentration) - 0.0160*(cTnT concentration) - 1.048. The method for calculating the predicted probability (feature parameter 4) is P = 1 / (1+e-logit)*100%.

[0327] Here, the area under the curve (AUC) for feature parameter 1, feature parameter 2, feature parameter 3, and feature parameter 4 are 0.880, 0.809, 0.803, and 0.899, respectively, indicating good diagnostic effectiveness; refer to Table 4-2-5. Based on the maximum value of the Yoden index, the optimal CUTOFF value for diagnosis is determined for each, refer to Table 4-2-6.

[0328] [Table 24]

[0329] [Table 25]

[0330] Furthermore, other combinations of concentration parameters, including total cTnITC concentration + total complex concentration, total cTnITC concentration + cTnT concentration, large cTnITC concentration + total cTnITC concentration + total complex concentration, large cTnITC concentration + total cTnITC concentration + cTnT concentration, large cTnITC concentration + total complex concentration + cTnT concentration, and total cTnITC concentration + total complex concentration + cTnT concentration, all showed good diagnostic effectiveness when used in combination in the above manner to distinguish between acute myocardial infarction (type 1) and chronic cardiac events. According to these results, the use of a combination of large cTnITC concentration and total cTnITC concentration, or an integrated analysis of at least one of these and other troponin fragment concentrations, has been shown to perform well when used to distinguish between acute myocardial infarction (type 1) and chronic cardiac events.

[0331] The diagnostic effectiveness of characteristic parameters obtained by combining ratio parameters of multiple myocardial injury markers was analyzed for differentiating between acute myocardial infarction (type 1) and chronic cardiac events in patients whose troponin I measurements were between the 99th percentile and five times the 99th percentile. The ratio parameters of myocardial injury markers include the ratio of large cTnITC concentration or total cTnITC concentration to total complex concentration, cTnT concentration or cTnI concentration, i.e., large cTnITC concentration / total complex concentration, total cTnITC concentration / total complex concentration, cTnT concentration / total complex concentration, large cTnITC concentration / cTnT concentration, total cTnITC concentration / cTnT concentration, large cTnITC concentration / cTnI concentration, and total cTnITC concentration / cTnI concentration.

[0332] Large cTnITC concentration / total complex concentration, total cTnITC concentration / total complex concentration, and cTnT concentration / total complex concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for calculating the feature parameter, namely Logit(P) = 6.880 * (large cTnITC concentration / total complex concentration) + 13.985 * (total cTnITC concentration / total complex concentration) - 0.619 * (cTnT concentration / total complex concentration) - 1.201. The method for calculating the predicted probability (feature parameter 5) is P = 1 / (1 + e-logit )*100%.

[0333] Large cTnITC concentration / cTnT concentration and total cTnITC concentration / cTn concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for calculating the predicted value, namely Logit(P) = 30.283 * (large cTnITC concentration / cTnT concentration) + 68.804 * (total cTnITC concentration / cTnT concentration) - 4.519. The method for calculating the predicted probability (feature parameter 6) is P = 1 / (1 + e -logit )*100%.

[0334] Here, the area under the curve (AUC) for feature parameter 5 and feature parameter 6 are 0.875 and 0.854, respectively, indicating good diagnostic effectiveness; see Table 4-2-7. Based on the maximum value of the Yoden index, the optimal CUTOFF value for diagnosis is determined; see Table 4-2-8.

[0335] [Table 26]

[0336] [Table 27]

[0337] Furthermore, other combinations of ratio parameters, including large cTnITC concentration / total complex concentration + total cTnITC concentration / total complex concentration, large cTnITC concentration / total complex concentration + cTnT concentration / total complex concentration, total cTnITC concentration / total complex concentration + cTnT concentration / total complex concentration, large cTnITC concentration / total complex concentration + total cTnITC concentration / total complex concentration + large cTnITC concentration / cTnT concentration, and large cTnITC concentration / total complex concentration + total cTnITC concentration / total complex concentration + total cTnITC concentration / cTnT concentration, all of which, when used in combination in the above manner to distinguish between acute myocardial infarction (type 1) and chronic cardiac events, showed good diagnostic effectiveness. The results showed that combinations of ratios of large cTnITCs to other troponin fragments, and ratios of total cTnITCs to other troponin fragments, or combinations of ratios of at least one of these to other troponin fragments, performed well when used to distinguish between acute myocardial infarction (type 1) and chronic cardiac events.

[0338] Based on the data above, it was shown that large cTnITC concentration or total cTnITC concentration, particularly large cTnITC concentration, can be used alone to differentiate between acute myocardial infarction (type 1) and chronic cardiac events in patients whose troponin I measurements are between the 99th percentile and five times the 99th percentile. Furthermore, the ratio of large cTnITC concentration or total cTnITC concentration to total complex concentration, and the ratio of large cTnITC concentration or total cTnITC concentration to cTnT concentration, can also be used to differentiate between acute myocardial infarction (type 1) and chronic cardiac events, and in particular, the ratio of large cTnITC concentration or total cTnITC concentration to cTnT concentration, or the ratio of large cTnITC concentration to total complex concentration, showed better diagnostic efficacy. The use of combinations of multiple parameters, such as large cTnITC concentration + total complex concentration, large cTnITC concentration + cTnT concentration, large cTnITC concentration + total cTnITC concentration, or combinations of large cTnITC concentration + total cTnITC concentration + total complex concentration + cTnT concentration, or combinations of large cTnITC concentration / total complex concentration, total cTnITC concentration / total complex concentration, cTnT concentration / total complex concentration, or combinations of large cTnITC concentration / cTnT concentration, total cTnITC concentration / cTnT concentration, can further enhance diagnostic effectiveness.

[0339] In summary, Examples 4-1 and 4-2 represent a secondary analysis of patients in Example 4-1 who showed mild troponin elevation. In Example 4-2, the study found that, in patients with mild troponin elevation, characteristic parameters obtained based on large cTnITC concentration and / or total cTnITC concentration showed superior diagnostic efficacy in acute myocardial infarction (type 1) and chronic cardiac events. Preferably, large cTnITC concentration or characteristic parameters obtained therefrom had better diagnostic efficacy. Furthermore, the ratio of total cTnITC concentration to cTnT concentration, or characteristic parameters obtained therefrom, also showed good diagnostic efficacy.

[0340] Example 5. Distinguishing between myocardial injury caused by invasive procedures and chronic cardiac events. 1. Patient participation (1) Patients undergoing invasive procedures: Patients who had undergone invasive treatment were selected for inclusion, and their age was 18 years or older. Patients who had undergone coronary artery bypass grafting (CABG) or heart valve replacement were placed in the surgical group. Patients diagnosed with myocardial infarction and who underwent percutaneous coronary intervention (PCI) were placed in the interventional surgery group. Patients under 18 years of age and pregnant women were excluded. Heparinized lithium plasma samples were collected and analyzed before invasive treatment and the first heparinized lithium plasma sample after invasive treatment. Patients with elevated postoperative total complex levels that were above the upper reference limit (URL) of the sex-specific 99th percentile were included in subsequent analyses. See Figure 18 for the patient inclusion flow.

[0341] (2) Patients with chronic cardiac events: Patients were selected to participate if their admission-based and final diagnoses were chronic heart failure, cardiomyopathy, or pneumonia, and their age was 18 years or older. Patients whose final diagnosis was not chronic heart failure, cardiomyopathy, or pneumonia were excluded. Patients who were simultaneously diagnosed with acute myocardial infarction were also excluded. Patients under 18 years of age and pregnant women were excluded. Cardiomyopathy, chronic heart failure, and pneumonia were independently determined by hospital clinicians. Acute myocardial infarction was independently determined by hospital cardiologists based on the definition of acute myocardial infarction. Initial heparinized lithium plasma samples were collected from these patients after admission and used for troponin complex and fragment composition analysis. See Figure 19 for the patient participation flow.

[0342] Patient information was recorded, including age, sex, medical history, hypertension, diabetes, smoking status, creatinine, and glomerular filtration rate. Samples meeting the eligibility criteria were selected, and relevant marker tests were performed. A total of 82 patients who had undergone invasive treatment were accepted, of which 48 underwent surgery, 34 underwent interventional treatment, and 145 had chronic cardiac events. See Table 5-1 for patient information.

[0343] [Table 28]

[0344] 2. Analysis of troponin composition fragments and complexes in myocardial injury and chronic cardiac events resulting from invasive procedures. After sample ingestion, troponin markers, including total troponin complex, large cTnITC, total cTnITC, and cTnT, were tested in the samples using the Mairui chemiluminescence apparatus and corresponding reagents. Differences in troponin composition between patients with myocardial injury due to invasive procedures and patients with chronic cardiac events were analyzed. Table 5-2 shows the concentrations of total complex, large cTnITC, total cTnITC, cTnT, and cTnI in the patients' blood. Here, the measurements from the cTnI kit and the total complex kit were similar, indicating a certain degree of clinical equivalence between the two.

[0345] [Table 29]

[0346] Figure 20 shows the ratio relationship between troponin complexes and fragments in patients with myocardial injury due to invasive treatment and patients with chronic cardiac events, including the ratio of large cTnITC concentration to total complex concentration, the ratio of total cTnITC concentration to total complex concentration, the ratio of cTnT concentration to total complex concentration, the ratio of large cTnITC concentration to cTnT concentration, and the ratio of total cTnITC concentration to cTnT concentration. Here, the ratio of large cTnITC concentration to total complex concentration, the ratio of total cTnITC concentration to total complex concentration, the ratio of large cTnITC concentration to cTnT concentration, and the ratio of total cTnITC concentration to cTnT concentration were high in patients with myocardial injury due to invasive treatment and low in patients with chronic cardiac events, while the ratio of cTnT concentration to total complex concentration was high in patients with chronic cardiac events and low in patients with myocardial injury due to invasive treatment.

[0347] The concentrations of troponin complexes and fragments, and the ratios between them, are associated with the type of injury. Specific detection of different troponin complexes contributed to the differentiation and diagnosis of myocardial injury resulting from chronic cardiac events and invasive treatments.

[0348] 3. Diagnostic effectiveness of myocardial injury used to differentiate between myocardial injury caused by invasive procedures and chronic cardiac events. Table 5-3 shows the diagnostic effectiveness of the myocardial injury markers used. In this example, the patients had experienced myocardial injury due to invasive treatment or suffered from a chronic cardiac event, and the patients with a chronic cardiac event suffered from cardiomyopathy, chronic heart failure, or pneumonia, and the concentration of troponin complex in the patient samples was higher than the upper limit of the 99th percentile.

[0349] Here, the P-values ​​for total complex concentration, large cTnITC concentration, total cTnITC concentration, cTnT concentration, cTnI concentration, the ratio of large cTnITC concentration to total complex concentration, the ratio of total cTnITC concentration to total complex concentration, the ratio of cTnT concentration to total complex concentration, the ratio of large cTnITC concentration to cTnT concentration, the ratio of total cTnITC concentration to cTnT concentration, and the ratio of large cTnITC concentration to cTnI concentration were all less than 0.05, indicating that the variables were statistically significant. Here, the area under the curve AUC for large cTnITC concentration was 0.952, the area under the curve AUC for total cTnITC concentration was 0.940, and the AUC for the ratio of total cTnITC concentration to cTnT concentration was 0.913, indicating good diagnostic effectiveness. The results indicate that, compared to using the concentrations of total complex, cTnT, or cTnI alone, the characteristic parameters obtained based on the concentration of large cTnITC or total cTnITC can more effectively distinguish between myocardial injury caused by invasive procedures and chronic cardiac events. Thus, the concentration of large cTnITC or total cTnITC has a good diagnostic effect.

[0350] [Table 30]

[0351] Using the sensitivity and specificity corresponding to different cutoff values ​​for the characteristic parameters, calculate the Iorden index, and determine the optimal cutoff value for diagnosis based on the maximum Iorden index value, referring to Table 5-4.

[0352] [Table 31]

[0353] 4. Diagnostic effectiveness of combinations of concentration parameters of multiple myocardial injury markers used to differentiate between myocardial injury caused by invasive procedures and chronic cardiac events. The concentration parameters for myocardial injury markers include the concentrations of troponin complexes and fragments, i.e., total complex concentration, large cTnITC concentration, total cTnITC concentration, cTnT concentration, and cTnI concentration. In this example, the patients had experienced myocardial injury due to invasive treatment or suffered from a chronic cardiac event, and the patients with chronic cardiac events suffered from cardiomyopathy, chronic heart failure, or pneumonia, and the concentration of troponin complexes in the patient samples was higher than the upper limit of the 99th percentile.

[0354] Large cTnITC concentration and cTnT concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for calculating the feature parameter, namely Logit(P) = 0.0417 * (large cTnITC concentration) - 0.0001 * (cTnT concentration) - 1.346. The method for calculating the predicted probability (feature parameter 1) is P = 1 / (1 + e -logit )*100%.

[0355] Large cTnITC concentration + total complex concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for calculating the feature parameter, namely Logit(P) = 0.0522 * (large cTnITC concentration) - 0.0009 * (total complex concentration) - 1.2682. The method for calculating the predicted probability (feature parameter 2) is P = 1 / (1 + e -logit )*100%.

[0356] Large cTnITC concentration and total cTnITC concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for calculating the feature parameter, namely Logit(P) = 0.0217 * (large cTnITC concentration) + 0.0040 * (total cTnITC concentration) - 1.3428. The method for calculating the predicted probability (feature parameter 3) is P = 1 / (1 + e -logit )*100%.

[0357] Large cTnITC concentration and total cTnITC concentration + total complex + cTnT concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for the feature parameter, namely Logit(P) = 0.0375*(large cTnITC concentration) + 0.0053*(total cTnITC concentration) - 0.0007*(total complex concentration) - 0.0001*(cTnT concentration) - 1.3256. The method for calculating the predicted probability (feature parameter 4) is P = 1 / (1+e-logit)*100%.

[0358] Here, the area under the curve AUC for feature parameter 1, feature parameter 2, feature parameter 3, and feature parameter 4 are 0.940, 0.921, 0.955, and 0.937, respectively, indicating good diagnostic effectiveness; see Table 5-5. Based on the maximum value of the Yoden index, the optimal CUTOFF values ​​for diagnosis are determined to be 0.4163, 0.3081, 0.3169, and 0.2827, respectively; see Table 5-6.

[0359] [Table 32]

[0360] [Table 33]

[0361] Furthermore, other combinations of concentration parameters include total cTnITC concentration + total complex concentration, total cTnITC concentration + cTnT concentration, large cTnITC concentration + total cTnITC concentration + total complex concentration, large cTnITC concentration + total cTnITC concentration + cTnT concentration, large cTnITC concentration + total complex concentration + cTnT concentration, and total cTnITC concentration + total complex concentration + cTnT concentration. When these combinations were used to differentiate between myocardial injury caused by invasive procedures and chronic cardiac events, they all showed good diagnostic effectiveness. According to these results, integrated analysis of large cTnITC concentration or total cTnITC concentration and other troponin fragment concentrations showed good performance when used to differentiate between myocardial injury caused by invasive procedures and chronic cardiac events.

[0362] 5. Diagnostic effectiveness of combinations of ratio parameters of multiple myocardial injury markers used to differentiate between myocardial injury caused by invasive procedures and chronic cardiac events. The ratio parameters for myocardial injury markers include the ratio of large cTnITC concentration to total complex, the ratio of total cTnITC concentration to total complex concentration, the ratio of cTnT concentration to total complex concentration, the ratio of large cTnITC concentration to cTnT concentration, the ratio of total cTnITC concentration to cTnT concentration, the ratio of large cTnITC concentration to cTnI concentration, and the ratio of total cTnITC concentration to cTnI concentration. In the example, the patients had experienced myocardial injury due to invasive treatment or suffered from a chronic cardiac event, and the patients with a chronic cardiac event suffered from cardiomyopathy, chronic heart failure, or pneumonia, and the troponin complex concentration in the patient samples was higher than the upper limit of the 99th percentile.

[0363] Large cTnITC concentration / total complex concentration, total cTnITC concentration / total complex concentration, and cTnT concentration / total complex concentration were selected as features, and an integrated analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression. This yielded the formula for calculating the feature parameter, namely Logit(P) = 4.775 * (large cTnITC concentration / total complex concentration) + 10.015 * (total cTnITC concentration / total complex concentration) - 0.413 * (cTnT concentration / total complex concentration) - 0.251. The method for calculating the predicted probability (feature parameter 5) is P = 1 / (1 + e -logit )*100%.

[0364] Large cTnITC concentration / cTnT concentration and total cTnITC concentration / cTnT concentration were selected as features, and a combined analysis was performed. Feature parameters were constructed based on a logistic regression algorithm, and the coefficients of each feature were estimated by logistic regression, thereby obtaining the formula for calculating the feature parameters: Logit(P) = 9.933 * (large cTnITC concentration / cTnT concentration) + 40.395 * (total cTnITC concentration / cTnT concentration) - 2.094. The method for calculating the predicted probability (feature parameter 6) is P = 1 / (1 + e -logit )*100%.

[0365] Here, the area under the curve (AUC) for feature parameter 5 and feature parameter 6 are 0.926 and 0.921, respectively, indicating good diagnostic effectiveness; see Table 5-7. Based on the maximum value of the Yoden index, the optimal CUTOFF values ​​for diagnosis are determined to be 0.6594 and 0.6053, respectively; see Table 5-8.

[0366] [Table 34]

[0367] [Table 35]

[0368] Furthermore, other combinations of ratio parameters, including large cTnITC concentration / total complex concentration + total cTnITC concentration / total complex concentration, large cTnITC concentration / total complex concentration + cTnT concentration / total complex concentration, total cTnITC concentration / total complex concentration + cTnT concentration / total complex concentration, large cTnITC concentration / total complex concentration + total cTnITC concentration / total complex concentration + large cTnITC concentration / cTnT concentration, and large cTnITC concentration / total complex concentration + total cTnITC concentration / total complex concentration + total cTnITC concentration / cTnT concentration, all of which, when combined in the above manner and used to distinguish between myocardial injury caused by invasive procedures and chronic cardiac events, showed good diagnostic effectiveness. The results showed that combinations of ratios of large cTnITCs to other troponin fragments, ratios of total cTnITCs to other troponin fragments, and ratios of at least one of these to other troponin fragments performed well when used to distinguish between myocardial injury caused by invasive procedures and chronic cardiac events.

[0369] The data above demonstrates that large cTnITC concentration or total cTnITC concentration can be used alone to differentiate between myocardial injury caused by invasive procedures and chronic cardiac events. The ratio of large cTnITC concentration or total cTnITC concentration to total complex concentration, the ratio of large cTnITC concentration or total cTnITC concentration to cTnT concentration, and the ratio of large cTnITC concentration or total cTnITC concentration to cTnI concentration can also be used to differentiate between myocardial injury caused by invasive procedures and chronic cardiac events. The use of combinations of multiple parameters, such as large cTnITC concentration + total complex concentration, large cTnITC concentration + cTnT concentration, large cTnITC concentration + total cTnITC concentration, or combinations of large cTnITC concentration + total cTnITC concentration + total complex concentration + cTnT concentration, or combinations of large cTnITC concentration / total complex concentration, total cTnITC concentration / total complex concentration, cTnT concentration / total complex concentration, or combinations of large cTnITC concentration / cTnT concentration, total cTnITC concentration / cTnT concentration, and so on, can also be used to distinguish between myocardial injury resulting from invasive procedures and chronic cardiac events. While we do not wish to be constrained by theory, large cTnITC concentration or the characteristic parameters derived therefrom may be more suitable for distinguishing between myocardial injury resulting from invasive procedures and chronic cardiac events.

[0370] Example 6: Evaluation of Prognosis for Acute Myocardial Injury This embodiment will explain the application of the marker of this application to the prognosis of acute myocardial injury, divided into two parts: the prognosis of acute myocardial injury in patients who have undergone cardiac surgery and the prognosis of acute myocardial injury in patients with myocardial infarction.

[0371] (1) Surgical operation part 1. Patient participation and follow-up methods Patients who had undergone cardiac surgery were included, and their age was 18 years or older. Cardiac surgery included (1) coronary artery bypass grafting (CABG) or (2) heart valve replacement. Patients under 18 years of age and pregnant women were excluded. Heparinized lithium plasma samples were collected and analyzed before invasive treatment and after invasive treatment (within 48 hours). Refer to Figure 21 for the patient participation flow.

[0372] Patient information was recorded, including age, sex, medical history, and glomerular filtration rate. Samples meeting the eligibility criteria were selected, and relevant marker tests were performed. In this study, a total of 311 patients who had undergone cardiac surgery were included, of which 133 underwent coronary artery bypass grafting and 178 underwent heart valve replacement. See Table 6-1 for patient information.

[0373] [Table 36] Here, continuous variables are shown as medians (25th to 75th percentiles), and categorical variables are shown as numbers (percentages).

[0374] This study will track patients for 3 months and 1 year, recording information on clinical events through in-office follow-up, telephone follow-up, and / or electronic medical record collection. Major clinical events include all-cause mortality, myocardial infarction, and a composite event of unplanned coronary revascularization. Secondary clinical events include cardiovascular mortality, components of major clinical events, stroke, hospitalization for heart failure or observation for emergency treatment for 24 hours or more, hospitalization for cardiac arrest or malignant arrhythmias and other cardiovascular diseases, and composite endpoints of different combinations of the above events.

[0375] 3. Assessment of the predictive ability of troponin fragments and complexes to predict patient prognosis risk. In this study, a total of 311 patients underwent cardiac surgery, of which 133 (43%) underwent coronary artery bypass grafting. The overall mortality rate within 3 months post-surgery was 0.6% (2 / 311), and the incidence of the composite endpoint event of death and cardiovascular adverse events was 5.1% (16 / 311). The overall mortality rate within 1 year post-surgery was 1.0% (3 / 311), and the incidence of the composite endpoint event of death and cardiovascular adverse events was 7.7% (24 / 311).

[0376] ROC curve analysis was used to evaluate the effects of troponin complex and fragment markers used to predict patient prognosis risk (Table 6-2). The predictive event was the occurrence of a composite endpoint event of death and / or cardiovascular adverse events within one year post-surgery. Variables included total troponin complex concentration, large cTnITC concentration, total cTnITC concentration, and cTnT concentration within 24 hours post-surgery.

[0377] Here, the P-values ​​for total complex concentration, large cTnITC concentration, total cTnITC concentration, and cTnT concentration were all less than 0.05, indicating that the variables were statistically significant. The area under the curve (AUC) for total complex concentration and large cTnITC absolute concentration was 0.765, and the area under the curve (AUC) for total cTnITC absolute concentration was 0.771, indicating that these factors have a certain predictive ability for cardiovascular adverse events and mortality within one year of the patient's development. These results suggest that total troponin complex concentration, large cTnITC concentration, total cTnITC concentration, and cTnT concentration can be used to assess the prognostic risk of a patient.

[0378] [Table 37]

[0379] The total troponin complex concentration, large cTnITC concentration, total cTnITC concentration, and cTnT concentration were used as sensitivity and specificity corresponding to different cutoff values ​​of the marker. The Iodine index was calculated to ensure high sensitivity and specificity, and the optimal cutoff value was determined based on the maximum Iodine index (Table 6-3). When the total complex concentration was higher than 6848.6 ng / L, the predictive sensitivity was 66.7% and the specificity was 69.3%. When the large cTnITC concentration was higher than 1001.0 ng / L, the predictive sensitivity was 71.4% and the specificity was 78.7%. When the total cTnITC concentration was higher than 1897.1 ng / L, the predictive sensitivity was 81.0% and the specificity was 65.5%. When the cTnT concentration was higher than 738.9 ng / L, the predictive sensitivity was 66.7% and the specificity was 76.0%.

[0380] [Table 38]

[0381] Furthermore, the difference in troponin fragments and complexes (postoperative concentration - preoperative concentration) and the multiplier of change (postoperative concentration / preoperative concentration) between the patient's preoperative and postoperative levels were calculated and used to predict the patient's prognostic risk (Table 6-4). Variables include total troponin complex concentration (postoperative - preoperative), large cTnITC concentration (postoperative - preoperative), total cTnITC concentration (postoperative - preoperative), cTnT concentration (postoperative - preoperative), and total complex (postoperative / preoperative), large cTnITC (postoperative / preoperative), total cTnITC (postoperative / preoperative), and cTnT (postoperative / preoperative).

[0382] Here, the P-values ​​for the postoperative-preoperative concentration differences of total complex, large cTnITC, total cTnITC, and cTnT, and the postoperative-preoperative concentration ratios of large cTnITC, total cTnITC, and cTnT were all less than 0.05, indicating that the variables were statistically significant. The area under the curve AUC for large cTnITC (postoperative-preoperative) was 0.759, for total cTnITC (postoperative-preoperative) it was 0.774, for large cTnITC (postoperative / preoperative) it was 0.663, and for total cTnITC (postoperative / preoperative) it was 0.660, demonstrating predictive ability for cardiovascular adverse events and mortality within one year of the patient's death. The results showed that the difference or change multiplier between postoperative and preoperative values ​​for total complex, large cTnITC, total cTnITC, and cTnT can assess the patient's prognostic risk and predict the risk of postoperative myocardial injury in patients undergoing cardiac surgery.

[0383] [Table 39]

[0384] For total complex, large cTnITC, total cTnITC, and cTnT, the difference in concentration between postoperative and preoperative periods and the multiplier of change were used as sensitivity and specificity corresponding to different CUTOFF values ​​for the parameters. The Ioden index was calculated to ensure high sensitivity and specificity, and the optimal CUTOFF value was determined based on the maximum Ioden index (Table 6-5). When the postoperative increase in large cTnITC concentration was greater than 1008.0 ng / L compared to preoperative levels, the predictive sensitivity was 68.4% and the specificity was 77.8%. When the increase in total cTnITC concentration was greater than 1896.6 ng / L, the predictive sensitivity was 84.2% and the specificity was 65.4%. When the postoperative increase in large cTnITC concentration was greater than 3320 times compared to preoperative levels, the predictive sensitivity was 63.2% and the specificity was 67.3%. When the increase in total cTnITC concentration was greater than 970 times, the predictive sensitivity was 63.2% and the specificity was 55.3%.

[0385] [Table 40]

[0386] 4. Assessment of the predictive ability of integrated analysis of troponin fragment concentrations for patient prognosis risk. A pooled analysis of multiple marker parameters was used to predict patient prognosis risk. Parameters included the difference between postoperative and preoperative concentrations of troponin complexes and fragments (postoperative concentration - preoperative concentration) and the ratio (postoperative concentration / preoperative concentration).

[0387] Using the large cTnITC concentration + cTnT concentration as an example, an integrated analysis was performed, and combined prediction parameters were constructed based on the logistic regression algorithm. The coefficients of each feature were estimated by logistic regression. The formula for calculating the predicted value was output: Logit(P) = 0.0002 * (large cTnITC concentration) + 0.0002 * (cTnT concentration) - 3.103. The method for calculating the prediction probability (prediction parameter 1) is P = 1 / (1 + e -logit )*100%.

[0388] ROC curve analysis showed that the p-value for predictor parameter 1 was less than 0.05, indicating that the variable was significant. The area under the curve (AUC) was 0.789, indicating a slight improvement in diagnostic effectiveness compared to the use of a single marker (Table 6-6).

[0389] [Table 41]

[0390] Furthermore, other combinations, including concentrations of large cTnITC+ total complex, large cTnITC+total cTnITC, total cTnITC+total complex, total cTnITC+cTnT, large cTnITC+total cTnITC+total complex, large cTnITC+total cTnITC+cTnT, large cTnITC+total complex+cTnT, and total cTnITC+total complex+cTnT, as well as postoperative and preoperative concentration values ​​or ratios, were also used to assess the patient's prognostic risk. The results indicate that a combined analysis of large cTnITC and other troponin fragments can be used to predict the patient's prognostic risk.

[0391] 5. Risk of composite endpoint events in different troponin fragment concentration groups Using postoperative troponin concentration as an example, patients were divided into three subgroups based on their postoperative troponin concentration: Group 1 "<median concentration", Group 2 "median concentration - 75th percentile concentration", and Group 3 ">75th percentile concentration". Refer to Table 6-7 for the subgroup concentrations corresponding to each marker.

[0392] [Table 42]

[0393] Binary classification logistic regression analysis was used to analyze the risk of the composite endpoint event occurring in patients with different troponin fragment and complex concentration groups (Table 6-8). Binary classification logistic regression analysis is used to analyze the correlation between marker parameters and the occurrence of the primary endpoint event. A p-value < 0.05 indicates that the variable is statistically significant.

[0394] The analysis showed that the P-values ​​for total complex groups 2 and 3 were less than 0.05, with OR values ​​of 10.0 and 11.5, respectively. The P-value for large cTnITC group 3 was less than 0.05, with an OR value of 11.6. The P-values ​​for total cTnITC groups 2 and 3 were less than 0.05, with OR values ​​of 8.8 and 12.1, respectively. The P-values ​​for cTnT groups 2 and 3 were less than 0.05, with OR values ​​of 4.2 and 8.9, respectively. Based on these results, it was indicated that a total complex concentration higher than 2964 ng / L, a large cTnITC concentration higher than 997 ng / L, a total cTnITC concentration higher than 956 ng / L, and a cTnT concentration higher than 354 ng / L were risk factors for the occurrence of the composite endpoint event in patients.

[0395] [Table 43]

[0396] Using COX regression, the risk of occurrence of the composite endpoint event in patients with different troponin fragment and complex concentration groups (Table 6-9) was analyzed, and survival curves for different patient groups (Figure 22) were plotted. The Cox proportional hazards model is used to determine the relationship between marker parameters or combinations thereof and outcomes in the study subjects. Hazard ratios (HRs) are calculated based on the Cox proportional hazards model to analyze the risk levels of risk groups with different marker parameter values ​​and to analyze the multiple of the risk of occurrence of the endpoint event compared to the control group. A p-value < 0.05 indicates that the variable is significant.

[0397] According to the analysis, the p-values ​​for the total complex group 2 (median concentration ~75th percentile concentration, 2964~9605 ng / L) and group 3 (>75th percentile concentration 9605 ng / L) were less than 0.05, and the HR values ​​were 8.0 and 9.63, respectively. For the large cTnITC group 3 (>75th percentile concentration 997 ng / L), the p-value was less than 0.05, and the HR value was 9.9. For the total cTnITC group 2 (median concentration ~75th percentile concentration, 956~4220 ng / L) and group 3 (>75th percentile concentration 4220 ng / L), the p-values ​​were less than 0.05, and the HR values ​​were 7.8 and 10.1, respectively. For the cTnT group 3 (>75th percentile concentration 809 ng / L), the p-value was less than 0.05, and the HR value was 7.2. The results indicated that a total complex concentration higher than 2964 ng / L, a large cTnITC concentration higher than 997 ng / L, a total cTnITC concentration higher than 956 ng / L, and a cTnT concentration higher than 809 ng / L were risk factors for the occurrence of the composite endpoint event in patients.

[0398] [Table 44]

[0399] Based on the above data, large cTnITC or total cTnITC, preferably large cTnITC, can be used to assess the prognosis of postoperative myocardial injury in patients who have undergone cardiac surgery, and the data for each group also showed that the higher the concentration of the marker, the higher the risk and the worse the prognosis.

[0400] (ii) Myocardial infarction 1. Patient participation and follow-up methods For the participation of patients with acute myocardial infarction (type 1), patients were selected whose admission diagnosis and final diagnosis were type 1 acute myocardial infarction, and whose age was 18 years or older. Acute myocardial infarction was independently determined by the hospital's cardiologist based on the definition of acute myocardial infarction. The determination of acute myocardial infarction was completed through clinical examinations including physical examination, echocardiography, electrocardiogram recording, high-sensitivity troponin I detection, high-sensitivity troponin T detection, and coronary angiography. Patients whose final diagnosis was not acute myocardial infarction or whose diagnostic information was incomplete were excluded. Patients under 18 years of age and pregnant women were excluded. When these patients visited the hospital, an initial heparinized lithium plasma sample was collected before interventional treatment and used for troponin complex and fragment composition analysis. Refer to Figure 23 for the patient participation flow.

[0401] Patient information was recorded, including age, sex, medical history, and glomerular filtration rate. Samples meeting the eligibility criteria were selected, and relevant marker tests were performed. A total of 324 patients with acute myocardial infarction were accepted. See Table 6-10 for patient information.

[0402] [Table 45] Here, continuous variables are shown as medians (25th to 75th percentiles), and categorical variables are shown as numbers (percentages).

[0403] This study will track patients for 3 months and 1 year, recording information on clinical events through in-office follow-up, telephone follow-up, and / or electronic medical record collection. Major clinical events include all-cause mortality, myocardial infarction, and a composite event of unplanned coronary revascularization. Secondary clinical events include cardiovascular mortality, components of major clinical events, stroke, hospitalization for heart failure or observation for emergency treatment for 24 hours or more, hospitalization for cardiac arrest or malignant arrhythmias and other cardiovascular diseases, and composite endpoints of different combinations of the above events.

[0404] 2. Evaluation of the predictive ability of troponin fragments and complexes to predict patient prognosis risk. In this study, a total of 324 patients with acute myocardial infarction were admitted. The overall mortality rate within 3 months after discharge was 0.6% (2 / 324), and the incidence of the composite endpoint event of death and cardiovascular adverse events was 6.5% (21 / 324). The overall mortality rate within 1 year after discharge was 1.2% (4 / 324), and the incidence of the composite endpoint event of death and cardiovascular adverse events was 9.6% (31 / 324).

[0405] Patients were divided into different subgroups based on the median or 25th percentile troponin concentration. Refer to Table 6-11 for the subgroup concentrations corresponding to each troponin fragment or complex.

[0406] [Table 46]

[0407] Using COX regression, the risk of composite endpoint events occurring in patients with different troponin fragment and complex concentration groups (Table 6-12) was analyzed, and survival curves for different patient groups (Figure 24) were plotted. The analysis showed that large cTnITC concentration > 25th percentile concentration of 1.1 ng / L was associated with a P-value <0.05 and an HR value of 3.6, while cTnT concentration > median concentration of 136.8 ng / L was associated with a P-value <0.05 and an HR value of 2.2. These results indicate that high concentrations of large cTnITC and cTnT are risk factors for the occurrence of composite endpoint events in patients.

[0408] [Table 47]

[0409] Based on the data above, large cTnITCs can be used to assess the prognosis of myocardial damage in patients with myocardial infarction, and the data from each group also showed that higher concentrations of the marker were associated with increased risk and a worse prognosis.

[0410] Example 7: Evaluation of the prognosis of patients with chronic myocardial injury This embodiment illustrates the application of the marker of this application in the prognosis of myocardial injury in patients with chronic myocardial injury, such as chronic heart failure or cardiomyopathy.

[0411] 1. Patient participation and follow-up methods For the participation of patients with chronic cardiac events, patients with a diagnosis of chronic heart failure or cardiomyopathy at admission and at the time of admission were selected, and their age was 18 years or older. Patients whose final diagnosis was not chronic heart failure or cardiomyopathy were excluded. Patients who were simultaneously diagnosed with acute myocardial infarction were excluded. Patients under 18 years of age and pregnant women were excluded. Cardiomyopathy and chronic heart failure were independently determined by hospital clinicians. Acute myocardial infarction was independently determined by hospital cardiologists based on the definition of acute myocardial infarction. Initial heparinized lithium plasma samples were collected from these patients after admission and used for troponin complex and fragment composition analysis. Refer to Figure 25 for the patient participation flow.

[0412] Patient information was recorded, including age, sex, medical history, and glomerular filtration rate. Samples meeting the eligibility criteria were selected, and relevant marker tests were performed. A total of 179 patients with chronic cardiac events were admitted. Of these, 29 were diagnosed with chronic heart failure, 62 with cardiomyopathy, and 88 had both chronic heart failure and cardiomyopathy. See Table 7-1 for patient information.

[0413] [Table 48] Here, continuous variables are shown as medians (25th to 75th percentiles), and categorical variables are shown as numbers (percentages).

[0414] This study will track patients for 3 months and 1 year, recording information on clinical events through in-office follow-up, telephone follow-up, and / or electronic medical record collection. Major clinical events include all-cause mortality, myocardial infarction, and a composite event of unplanned coronary revascularization. Secondary clinical events include cardiovascular mortality, components of major clinical events, stroke, hospitalization for heart failure or observation for emergency treatment for 24 hours or more, hospitalization for cardiac arrest or malignant arrhythmias and other cardiovascular diseases, and composite endpoints of different combinations of the above events.

[0415] 2. Evaluation of the predictive ability of troponin fragments and complexes to predict patient prognosis risk. In this study, a total of 179 patients with chronic cardiac events were admitted. Of these, 29 (16%) had chronic heart failure, 62 (35%) had cardiomyopathy, and 88 (49%) had both chronic heart failure and cardiomyopathy. The overall mortality rate within 3 months after discharge was 0.6% (1 / 179), and the incidence of the composite endpoint of death and cardiovascular adverse events was 12.8% (23 / 179). The overall mortality rate within 1 year after discharge was 1.1% (2 / 179), and the incidence of the composite endpoint of death and cardiovascular adverse events was 24.0% (43 / 179).

[0416] ROC curve analysis was used to evaluate the effects of troponin complex and fragment markers used to predict patient prognosis risk (Table 7-2). In this example, patients with chronic cardiac events had cardiomyopathy or chronic heart failure. The predicted event was the occurrence of a composite endpoint event of death and adverse cardiovascular events within one year after discharge. Variables included total troponin complex concentration, large cTnITC concentration, total cTnITC concentration, and cTnT concentration.

[0417] Here, the P-values ​​for total troponin complex concentration, large cTnITC concentration, and cTnT concentration were all less than 0.05, indicating that the variables were statistically significant. The area under the curve (AUC) for the absolute concentration of large cTnITC was 0.614, indicating a certain predictive ability for cardiovascular adverse events and mortality within one year in patients. These results suggest that total troponin complex concentration, large cTnITC concentration, and cTnT concentration can be used to assess prognostic risk in patients.

[0418] [Table 49]

[0419] The total troponin complex concentration, large cTnITC concentration, and cTnT concentration were used as sensitivity and specificity corresponding to different cutoff values ​​of the marker. The Iodden index was calculated, and the optimal cutoff value was determined based on the maximum Iodden index (Table 7-3). When the total complex concentration was higher than 11.7 ng / L, the predictive sensitivity was 86% and the specificity was 42%. When the large cTnITC concentration was higher than 0.3 ng / L (approximately 2x LoD), the predictive sensitivity was 93% and the specificity was 30%. When the cTnT concentration was higher than 24.3 ng / L, the predictive sensitivity was 83% and the specificity was 63%.

[0420] [Table 50]

[0421] 3. Risk of composite endpoint events in different troponin fragment concentration groups Based on troponin levels, patients were divided into three subgroups: Group 1 (<25th percentile concentration), Group 2 (25th percentile concentration to median concentration), and Group 3 (>median concentration). See Table 7-4 for the subgroup concentrations corresponding to each marker.

[0422] [Table 51]

[0423] Using binary classification logistic regression analysis, the risk of occurrence of the patient composite endpoint event in different troponin fragment and complex concentration groups was analyzed (Table 7-5). The analysis showed that the total complex group 3 (>median concentration 19.5 ng / L) had a p-value of less than 0.05 and an OR value of 4.3. The large cTnITC group 2 (25th percentile concentration to median concentration, 0.3 to 0.7 ng / L) and group 3 (>median concentration 0.7 ng / L) also had p-values ​​of less than 0.05 and OR values ​​of 4.0 and 3.1, respectively. The cTnT group 3 (>median concentration 23.8 ng / L) also had a p-value of less than 0.05 and an OR value of 13.8. Based on these results, a total complex concentration higher than 19.5 ng / L, a large cTnITC concentration higher than 0.3 ng / L, and a cTnT concentration higher than 23.8 ng / L were identified as risk factors for the occurrence of the composite endpoint event in patients.

[0424] [Table 52]

[0425] Using COX regression, the risk of occurrence of the patient composite endpoint event in different troponin fragment and complex concentration groups (Table 7-6) was analyzed, and survival curves for different patient groups (Figure 26) were plotted. The analysis showed that the total complex group 3 (>median concentration 19.5 ng / L) had a p-value of <0.05 and an HR value of 3.8; the large cTnITC group 2 (25th percentile concentration to median concentration, 0.3 to 0.7 ng / L) and group 3 (>median concentration 0.7 ng / L) had p-values ​​of <0.05 and HR values ​​of 3.4 and 2.8, respectively; the total cTnITC group 2 (25th percentile concentration to median concentration, 1.4 to 2.7 ng / L) had a p-value of <0.05 and an HR value of 2.8; and the cTnT group 3 (>median concentration 23.8 ng / L) had a p-value of <0.05 and an HR value of 9.9. Based on these results, a total complex concentration higher than 19.5 ng / L, a large cTnITC concentration higher than 0.3 ng / L, a total cTnITC concentration of 1.4–2.7 ng / L, and a cTnT concentration higher than 23.8 ng / L were identified as risk factors for the occurrence of the composite endpoint event in patients.

[0426] [Table 53]

[0427] Based on the data above, large cTnITCs can be used to assess the prognosis of myocardial injury in patients with chronic cardiac events, such as chronic heart failure or cardiomyopathy, and the data from each group also showed that higher concentrations of the marker were associated with increased risk and a worse prognosis.

[0428] Example 8: Exclusion of subjects with chest pain who have not experienced a myocardial injury event. 1. Patient participation and diagnosis We established thresholds and flows for rapidly excluding non-ST-elevation myocardial infarction (NSTEMI) patients by admitting patients with acute chest pain suspected to be coronary artery syndrome who presented consecutively from the emergency department, and evaluated their safety and effectiveness. Inclusion criteria: (1) Chinese population 18 years of age or older, (2) presentation due to suspected symptoms or signs of acute myocardial infarction (possible cardiac symptoms including acute chest, upper abdomen, neck, jaw, or arm pain, discomfort, or pressure), (3) blood sample taken at the time of presentation. Exclusion criteria: patients with clear STEMI at the time of presentation, pregnant women, patients with a history of major surgery or trauma within the past four weeks, and patients with clear chest pain of non-cardiovascular cause.

[0429] Acute myocardial infarction was independently determined by the hospital's cardiologist based on the definition of acute myocardial infarction. The determination of acute myocardial infarction was completed through clinical examinations including physical examination, echocardiography, electrocardiogram recording, high-sensitivity troponin I detection, high-sensitivity troponin T detection, and coronary angiography. Heparinized lithium plasma samples were collected before the patient received treatment and used for troponin complex and fragment composition analysis. See Figure 27 for the patient participation flow.

[0430] Patient information was recorded, including age, sex, medical history, hypertension, diabetes, smoking status, creatinine, and glomerular filtration rate. Samples meeting the eligibility criteria were selected, and relevant marker tests were performed. A total of 1210 patients suspected of having acute myocardial infarction were admitted, of which 138 were diagnosed with NSTEMI and 1072 were non-myocardial infarction patients. See Table 8-1 for important patient information.

[0431] [Table 54] Here, continuous variables are shown as medians (25th to 75th percentiles), and categorical variables are shown as numbers (percentages).

[0432] 2. Evaluation of the effects of troponin fragments and complexes for NSTEMI exclusion In this example, all patients admitted with suspected acute coronary syndrome symptoms were selected for analysis, resulting in a total of 1210 suspected NSTEMI patients, of which 138 were confirmed to have NSTEMI. Table 8-2 shows the diagnostic effectiveness of the troponin complex and fragment markers used.

[0433] Here, the P-values ​​for the total complex absolute concentration, the absolute concentration of large cTnITCs, the absolute concentration of total cTnITCs, the absolute concentration of cTnTs, and the absolute concentration of cTnIs were all less than 0.05, indicating that the variables were statistically significant. The area under the curve (AUC) for the absolute concentration of large cTnITCs was 0.959, indicating good diagnostic efficacy. The measured values ​​for the cTnI kit and the total complex were similar, and the two had a certain degree of clinical equivalence. These results indicate that predictive NSTEMI can be predicted more effectively when using either the absolute concentration of large cTnITCs or the absolute concentration of total cTnITCs alone. Here, large cTnITCs are preferred.

[0434] [Table 55]

[0435] In patients suspected of having myocardial infarction, using an extremely low troponin threshold allows for early and safe exclusion of non-myocardial infarction patients at the time of presentation. Exclusion thresholds for troponin complexes and fragments were established based on the guideline-recommended myocardial infarction exclusion efficiency criteria (requiring a diagnostic sensitivity of ≥99% and a negative predictive value (NPV) of ≥99.5%). Based on the exclusion thresholds, the sensitivity and NPV for excluding NSTEMI patients were calculated, along with the proportion of excluded patients. See Table 8-3 for calculation methods. The established thresholds and diagnostic effect data are shown in Table 8-4. These data further demonstrate that large cTnITC absolute concentrations and total cTnITC can support the diagnosis of myocardial infarction and be used to exclude non-myocardial injury patients. Here, large cTnITC measurements could safely exclude non-myocardial infarction patients at a high proportion, with an effect close to that of the total complex and superior to that of cTnT.

[0436] [Table 56] Sensitivity = a / (a+c)×100% NPV = d / (c+d)×100%

[0437] [Table 57]

[0438] 3. Evaluation of the effects of troponin fragments and complexes for NSTEMI exclusion (in patients with early chest pain) In this example, patients with chest pain onset within 24 hours were selected as early chest pain patients for analysis. A total of 764 suspected NSTEMI patients were accepted, of which 88 were confirmed to be NSTEMI patients. Table 8-5 shows the diagnostic effectiveness of the troponin complex and fragment markers used. Here, the P values ​​for total complex absolute concentration, large cTnITC absolute concentration, total cTnITC absolute concentration, and cTnT absolute concentration were all less than 0.05, indicating that the variables were statistically significant. The area under the curve (AUC) for large cTnITC absolute concentration was 0.976, indicating a good diagnostic effect.

[0439] [Table 58]

[0440] In patients with early chest pain suspected to be myocardial infarction (chest pain duration ≤ 24 hours), using an extremely low troponin threshold allows for early and safe exclusion from non-myocardial infarction patients at the time of presentation. Based on the myocardial infarction exclusion efficiency criteria recommended by the guidelines (requiring a diagnostic sensitivity of ≥ 99% and a negative predictive value (NPV) of ≥ 99.5%), exclusion thresholds for troponin complexes and fragments were established. Based on the exclusion thresholds, the sensitivity and NPV for excluding NSTEMI patients were calculated, as well as the proportion of excluded patients. The established thresholds and diagnostic effect data are shown in Table 8-6.

[0441] [Table 59]

[0442] In this example, patients with chest pain onset within 12 hours were selected as early chest pain patients for analysis. A total of 617 suspected NSTEMI patients were accepted, of which 59 were confirmed to be NSTEMI patients. Table 8-7 shows the diagnostic effectiveness of the troponin complex and fragment markers used. Here, the P-values ​​for total complex absolute concentration, large cTnITC absolute concentration, total cTnITC absolute concentration, and cTnT absolute concentration were all less than 0.05, indicating that the variables were statistically significant. The area under the curve (AUC) for large cTnITC absolute concentration was 0.972, indicating a good diagnostic effect.

[0443] [Table 60]

[0444] In patients with early chest pain suspected to be myocardial infarction (chest pain duration ≤ 12 hours), using an extremely low troponin threshold allows for early and safe exclusion from non-myocardial infarction patients at the time of presentation. Based on the myocardial infarction exclusion efficiency criteria recommended by the guidelines (requiring a diagnostic sensitivity of ≥ 99% and a negative predictive value (NPV) of ≥ 99.5%), exclusion thresholds for troponin complexes and fragments were established. Based on the exclusion thresholds, the sensitivity and NPV for excluding NSTEMI patients were calculated, as well as the proportion of excluded patients. The established thresholds and diagnostic effect data are shown in Table 8-8.

[0445] [Table 61]

[0446] The data above demonstrates that when troponin large cTnITC complexes and total cTnITC complexes are used alone, they can assist in the diagnosis of myocardial infarction in a queue of patients with chest pain suspected to be myocardial infarction, exclude patients without myocardial damage, allow patients to leave the emergency room earlier, reduce patient observation time, enable them to receive treatment for other illnesses, and accelerate emergency room turnover.

[0447] Furthermore, in patients with early-stage chest pain (chest pain duration ≤ 12 or 24 hours), large cTnITC measurements can safely exclude non-myocardial infarction patients with a high proportion of cases. Compared to the total composite and cTnT, the proportion of excluded patients relative to the total number of patients was higher, indicating superior diagnostic effectiveness. By comparing data from all chest pain patients within 24 hours of chest pain and within 12 hours of chest pain, it was shown that large cTnITCs could safely exclude patients with shorter chest pain durations, demonstrating increased superiority compared to the total composite.

[0448] 3. Evaluation of the effectiveness of integrated detection of troponin fragment concentrations for NSTEMI exclusion. Integrated detection of multiple troponin fragment concentrations was used to rapidly rule out NSTEMI.

[0449] The test markers included total complex concentration, large cTnITC concentration, total cTnITC concentration, and cTnT concentration. Large cTnITC concentration + total complex concentration were selected as features, and an integrated study was conducted to establish thresholds for each. Patients with both large cTnITC concentration and total complex concentration below the threshold were excluded to achieve the greatest safety. The established thresholds and diagnostic effect data are shown in Table 8-9. These data demonstrate that the integrated detection of multiple troponin fragment concentrations can support the rapid exclusion of myocardial infarction patients. Compared to the use of a single marker, integrated detection of multiple troponin fragments reduces the number of missed myocardial infarction patients to zero, achieving 100% sensitivity and 100% negative predictive value.

[0450] [Table 62]

[0451] As shown in the data in Table 8-9, a single marker cannot effectively solve the problem of missed diagnoses, but integrated detection can, and the reduction in the exclusion rate is also slight, indicating that it is the optimal solution for reconciling the contradiction between the ratio of missed diagnoses to excluded patients.

[0452] According to this embodiment, the troponin large cTnITC complex and the total cTnITC complex can exclude patients who clinically present with chest pain but have not experienced myocardial injury. Preferably, the large cTnITC complex is used, and its diagnostic effect is superior to that of cTnT. In particular, the superiority of the troponin large cTnITC complex is even greater in patients with early chest pain. It binds to the total complex, avoiding missed diagnoses and maintaining a good exclusion rate. This demonstrates excellent diagnostic efficacy in myocardial injury diagnosis, specifically in excluding cases where myocardial injury has occurred in chest pain subjects.

[0453] In addition to those described herein, various modifications of the invention will be apparent to those skilled in the art based on the foregoing description. Such modifications are also intended to be included within the claims. The entire scope of the invention is given by the appended claims and any equivalents thereof.

Claims

1. A method for evaluating myocardial damage in a subject in vitro, To detect the content of one or more myocardial injury markers in a sample from the subject, Based on the content of one or more of the aforementioned myocardial injury markers, characteristic parameters for evaluating myocardial injury are obtained. The characteristic parameter is compared with a reference value for the characteristic parameter, This includes evaluating the myocardial damage of the subject based on the results of the comparison, Here, the one or more myocardial injury markers include the large cardiac troponin ternary complex and / or the total cardiac troponin ternary complex. The aforementioned large cardiac troponin ternary complex is a complex formed from the full-length protein or any amino acid fragment of troponin C, the full-length protein or any amino acid fragment of cardiac troponin I, one or more segments of cardiac troponin T at amino acid residues 223-287, and one or more segments of cardiac troponin T at amino acid residues 1-222. A method for in vitro evaluating myocardial damage in a subject, wherein the total cardiac troponin ternary complex is a complex formed from the full-length protein or any amino acid fragment of troponin C, the full-length protein or any amino acid fragment of cardiac troponin I, one or more segments of cardiac troponin T at amino acid residues 223-287, and one or more segments of optionally selected cardiac troponin T at amino acid residues 1-222.

2. The aforementioned myocardial injury marker is cTnI containing the full-length protein of cardiac troponin I or any amino acid fragment thereof, cTnT comprising the full-length protein of cardiac troponin T or any amino acid fragment thereof, TnC containing the full-length protein of troponin C or any amino acid fragment thereof, A cardiac troponin binary complex comprising a binary complex consisting of a full-length protein of troponin C or any amino acid fragment thereof and a full-length protein of cardiac troponin I or any amino acid fragment thereof, The total cardiac troponin complex further comprises one or more of the total cardiac troponin ternary complex, the total cardiac troponin complex comprising the full-length protein of troponin C or any amino acid fragment thereof, and the total cardiac troponin complex comprising the full-length protein of cardiac troponin I or any amino acid fragment thereof, Preferably, the method according to claim 1, wherein the one or more myocardial injury markers further comprises at least one of cTnI, cTnT, and total cardiac troponin complex.

3. Obtaining characteristic parameters for evaluating myocardial damage based on the content of one or more of the aforementioned myocardial damage markers is possible. To determine the content of the aforementioned large cardiac troponin ternary complex or total cardiac troponin ternary complex as a characteristic parameter for evaluating myocardial damage, or The method according to claim 1 or 2, comprising obtaining characteristic parameters for evaluating myocardial damage based on the content of the large cardiac troponin ternary complex and the content of the total cardiac troponin ternary complex.

4. The method according to any one of claims 1 to 3, wherein obtaining characteristic parameters for evaluating myocardial damage based on the content of one or more myocardial damage markers includes inputting the content of the multiple myocardial damage markers into a preset function model and obtaining the output of the preset function model as characteristic parameters for evaluating myocardial damage.

5. Obtaining characteristic parameters for evaluating myocardial damage based on the content of one or more myocardial damage markers includes determining one of the following ratio parameters as a characteristic parameter for evaluating myocardial damage, or obtaining characteristic parameters for evaluating myocardial damage based on at least two of the following ratio parameters, or obtaining characteristic parameters for evaluating myocardial damage based on at least one of the following ratio parameters and the ratio of the cTnT content to the total cardiac troponin complex content. The aforementioned ratio parameters include the ratio of the content of large cardiac troponin ternary complex to the content of cTnI, the ratio of the content of large cardiac troponin ternary complex to the content of cTnT, the ratio of the content of large cardiac troponin ternary complex to the content of total cardiac troponin complex, the ratio of the content of total cardiac troponin ternary complex to the content of cTnI, the ratio of the content of total cardiac troponin ternary complex to the content of cTnT, the ratio of the content of total cardiac troponin ternary complex to the content of total cardiac troponin complex, and the ratio of the content of large cardiac troponin ternary complex to the content of total cardiac troponin ternary complex. Preferably, the ratio parameter is the ratio of the content of large cardiac troponin ternary complex to the content of cTnI, cTnT, or total cardiac troponin complex, and optionally, the ratio parameter further comprises the ratio of the content of total cardiac troponin ternary complex to the content of cTnI, cTnT, or total cardiac troponin complex, and / or the ratio of the content of cTnT to the content of cTnI or total cardiac troponin complex, according to any one of claims 1 to 4.

6. The method according to any one of claims 1 to 5, wherein the method is used to diagnose myocardial injury in a subject, and preferably, characteristic parameters for diagnosing myocardial injury in a subject are obtained based on the large cardiac troponin ternary complex.

7. The method according to any one of claims 1 to 5, wherein the method is used to evaluate the prognosis of myocardial injury in a subject, and preferably, characteristic parameters for evaluating the prognosis of myocardial injury in a subject are obtained based on the large cardiac troponin ternary complex.

8. Based on the results of the above comparison, evaluating the myocardial damage in the subject is, This includes classifying the subject's myocardial infarction stage based on the results of the comparison described above. Preferably, the method according to any one of claims 1 to 6, wherein if the characteristic parameter is higher than the reference value of the characteristic parameter, it is determined that the subject is in the early stages of acute myocardial infarction.

9. Obtaining characteristic parameters for evaluating myocardial damage based on the content of one or more of the aforementioned myocardial damage markers is possible. To determine the content of the aforementioned large cardiac troponin ternary complex as a characteristic parameter for evaluating myocardial damage, or Based on the content of the large cardiac troponin ternary complex and the content of at least one of cTnI, cTnT, total cardiac troponin ternary complex and total cardiac troponin complex, preferably based on the content of the large cardiac troponin ternary complex and the content of cTnT, characteristic parameters for evaluating myocardial damage can be obtained, or The method of claim 8, comprising obtaining characteristic parameters for evaluating myocardial damage based on the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex to the ratio of the content of at least one of cTnI, cTnT, and total cardiac troponin complex, and the ratio of the content of an optional cTnT to the content of cTnI or total cardiac troponin complex.

10. Based on the results of the above comparison, evaluating the myocardial damage in the subject is, Based on the results of the comparison, it is necessary to determine whether the subject developed a type I myocardial infarction or a type II myocardial infarction. Preferably, if the characteristic parameter is higher than the reference value of the characteristic parameter, it is determined that a type I myocardial infarction has occurred in the subject, or Preferably, the method according to any one of claims 1 to 6, wherein characteristic parameters for evaluating myocardial damage are obtained based on the content of the large cardiac troponin ternary complex or the ratio of the total cardiac troponin ternary complex content to the total cardiac troponin complex.

11. Based on the results of the above comparison, evaluating the myocardial damage in the subject is, Based on the results of the comparison, the procedure includes determining whether a type I myocardial infarction occurred in the subject or whether a chronic cardiac event occurred. Preferably, the method according to any one of claims 1 to 6, wherein it is determined that a type I myocardial infarction has occurred in the subject if the characteristic parameter is higher than a reference value for the characteristic parameter.

12. Obtaining characteristic parameters for evaluating myocardial damage based on the content of one or more of the aforementioned myocardial damage markers is possible. To determine the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex as a characteristic parameter for evaluating myocardial damage, or Based on the content of the large cardiac troponin ternary complex and the content of the total cardiac troponin ternary complex, characteristic parameters for evaluating myocardial damage can be obtained, or This includes obtaining characteristic parameters for evaluating myocardial damage based on the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex and the content of cTnT or total cardiac troponin complex, The method according to claim 11, preferably, obtaining characteristic parameters for evaluating myocardial damage based on the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex to the ratio of the content of at least one of cTnI, cTnT, and total cardiac troponin complex, and the ratio of the content of an optional cTnT to the content of cTnI or total cardiac troponin complex.

13. Based on the results of the above comparison, evaluating the myocardial damage in the subject is, Based on the results of the comparison, the procedure includes determining whether the subject suffered myocardial injury due to the invasive procedure or whether a chronic cardiac event occurred. Preferably, the method according to any one of claims 1 to 6, wherein it is determined that myocardial damage caused by an invasive procedure has occurred in the subject if the characteristic parameter is higher than a reference value for the characteristic parameter.

14. Obtaining characteristic parameters for evaluating myocardial damage based on the content of one or more of the aforementioned myocardial damage markers is possible. This includes determining the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex as a characteristic parameter for evaluating myocardial damage. The method according to claim 13, preferably, obtaining characteristic parameters for evaluating myocardial damage based on the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex to the ratio of the content of at least one of cTnI, cTnT, and total cardiac troponin complex, and the ratio of the content of an optional cTnT to the content of cTnI or total cardiac troponin complex.

15. Based on the above comparison results, subjects with chest pain who did not experience myocardial injury were excluded. Preferably, if the characteristic parameter is lower than the reference value of the characteristic parameter, subjects with chest pain who have not experienced a myocardial injury event are excluded. Preferably, the myocardial injury event is myocardial infarction or NSTEMI, according to any one of claims 1 to 6.

16. Obtaining characteristic parameters for evaluating myocardial damage based on the content of one or more of the aforementioned myocardial damage markers is possible. To determine the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex as a characteristic parameter for evaluating myocardial damage, or The method according to claim 15, comprising obtaining characteristic parameters for evaluating myocardial damage based on the content of the large cardiac troponin ternary complex or the content of the total cardiac troponin ternary complex and the total cardiac troponin complex.

17. Based on the results of the above comparison, the prognosis of myocardial injury in subjects who have suffered acute myocardial injury is evaluated, preferably, the subjects have undergone cardiac surgery or have suffered a myocardial infarction. Preferably, the method according to claim 7, wherein if the characteristic parameter is higher than a reference value for the characteristic parameter, it is determined that the prognosis is poor.

18. Obtaining characteristic parameters for evaluating myocardial damage based on the content of one or more of the aforementioned myocardial damage markers is possible. This includes determining the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex as a characteristic parameter for evaluating myocardial damage. Preferably, the method according to claim 17, wherein the change in the content of large cardiac troponin ternary complex or total cardiac troponin ternary complex in the plasma of the subject before and after cardiac surgery is determined as a characteristic parameter for evaluating the prognostic risk of undergoing surgery.

19. Based on the results of the above comparison, the prognosis of myocardial injury in chronic myocardial injury subjects was evaluated. Preferably, the subject is a patient with cardiomyopathy, chronic heart failure, structural heart disease, infiltrative disease, stable coronary artery disease, or persistent arrhythmia. Preferably, the method according to claim 7, wherein if the characteristic parameter is higher than a reference value for the characteristic parameter, it is determined that the prognosis is poor.

20. Obtaining characteristic parameters for evaluating myocardial damage based on the content of one or more of the aforementioned myocardial damage markers is possible. The method according to claim 19, comprising determining the content of the large cardiac troponin ternary complex or the total cardiac troponin ternary complex as a characteristic parameter for evaluating myocardial damage.

21. A device for acquiring characteristic parameters for evaluating myocardial damage in a subject, A data receiving module configured to receive the content of one or more myocardial injury markers obtained from a sample from a subject, wherein the one or more myocardial injury markers include large cardiac troponin ternary complex and / or total cardiac troponin ternary complex, A data processing module is configured to process the content data of one or more myocardial injury markers received by the receiving module and to obtain characteristic parameters for evaluating myocardial injury. Includes an output module configured to output the aforementioned feature parameters, Here, the large cardiac troponin ternary complex is a complex formed from the full-length protein or any amino acid fragment of troponin C, the full-length protein or any amino acid fragment of cardiac troponin I, one or more segments of cardiac troponin T at amino acid residues 223-287, and one or more segments of cardiac troponin T at amino acid residues 1-222. The apparatus is a complex formed by the total cardiac troponin ternary complex being a full-length protein or any amino acid fragment of troponin C, a full-length protein or any amino acid fragment of cardiac troponin I, one or more segments of cardiac troponin T at amino acid residues 223-287, and one or more segments of optionally selected cardiac troponin T at amino acid residues 1-222.

22. The data processing module processes the content of one or more myocardial injury markers and obtains characteristic parameters for evaluating myocardial injury. The data processing module determines the content of the cardiac troponin ternary complex or total cardiac troponin ternary complex as a characteristic parameter for evaluating myocardial damage, or The apparatus according to claim 21, wherein the data processing module includes obtaining characteristic parameters for evaluating myocardial damage based on the content of the cardiac troponin ternary complex and the total cardiac troponin ternary complex.

23. The aforementioned myocardial injury marker is cTnI containing the full-length protein of cardiac troponin I or any amino acid fragment thereof, cTnT comprising the full-length protein of cardiac troponin T or any amino acid fragment thereof, TnC containing the full-length protein of troponin C or any amino acid fragment thereof, A cardiac troponin binary complex comprising a binary complex consisting of a full-length protein of troponin C or any amino acid fragment thereof and a full-length protein of cardiac troponin I or any amino acid fragment thereof, The total cardiac troponin complex further comprises one or more of the total cardiac troponin ternary complex, the total cardiac troponin complex comprising the full-length protein of troponin C or any amino acid fragment thereof, and the total cardiac troponin complex comprising the full-length protein of cardiac troponin I or any amino acid fragment thereof, Preferably, the apparatus according to claim 21, wherein the one or more myocardial injury markers further comprises at least one of cTnI, cTnT, and total cardiac troponin complex.

24. The apparatus according to any one of claims 21 to 23, wherein the data processing module processes the content of one or more myocardial injury markers and obtains characteristic parameters for evaluating myocardial injury, the data processing module inputs the content of the multiple myocardial injury markers into a preset function model and obtains the output of the preset function model as characteristic parameters for evaluating myocardial injury.

25. The data processing module processing the content of one or more myocardial injury markers and obtaining characteristic parameters for evaluating myocardial injury includes the data processing module determining one of the following ratio parameters as a characteristic parameter for evaluating myocardial injury, or obtaining characteristic parameters for evaluating myocardial injury based on at least two of the following ratio parameters, or obtaining characteristic parameters for evaluating myocardial injury based on at least one of the following ratio parameters and the ratio of the cTnT content to the total cardiac troponin complex content. The aforementioned ratio parameters include the ratio of the content of large cardiac troponin ternary complex to the content of cTnI, the ratio of the content of large cardiac troponin ternary complex to the content of cTnT, the ratio of the content of large cardiac troponin ternary complex to the content of total cardiac troponin complex, the ratio of the content of total cardiac troponin ternary complex to the content of cTnI, the ratio of the content of total cardiac troponin ternary complex to the content of cTnT, the ratio of the content of total cardiac troponin ternary complex to the content of total cardiac troponin complex, and the ratio of the content of large cardiac troponin ternary complex to the content of total cardiac troponin ternary complex. Preferably, the ratio parameter is the ratio of the content of large cardiac troponin ternary complex to the content of cTnI, cTnT, or total cardiac troponin complex, and optionally, the ratio parameter further comprises the ratio of the content of total cardiac troponin ternary complex to the content of cTnI, cTnT, or total cardiac troponin complex, and / or the ratio of the content of cTnT to the content of cTnI or total cardiac troponin complex, according to any one of claims 21 to 24.

26. A sample placement section for placing a container containing a sample of the subject, A sample dispensing unit for drawing up the subject's sample from the sample placement unit and discharging it into the cuvette where the sample should be placed, A reagent placement section for placing detection reagents, A reagent dispensing section for drawing detection reagent from the reagent placement section and discharging it into the cuvette to which the reagent should be added, A reaction section for placing a cuvette and incubating the test solution obtained by the reaction between the sample of the subject in the cuvette and the detection reagent, A detection unit having a signal detector for detecting the signal of a test solution in a cuvette, measuring and outputting the content of one or more myocardial injury markers in a sample of a subject, wherein the one or more myocardial injury markers include a large cardiac troponin ternary complex and / or a total cardiac troponin ternary complex, where the large cardiac troponin ternary complex is a complex formed from the full-length protein or any amino acid fragment of troponin C, the full-length protein or any amino acid fragment of cardiac troponin I, one or more segments at amino acid residues 223-287 of cardiac troponin T, and one or more segments at amino acid residues 1-222 of cardiac troponin T, and the total cardiac troponin ternary complex is a complex formed from the full-length protein or any amino acid fragment of troponin C, the full-length protein or any amino acid fragment of cardiac troponin I, one or more segments at amino acid residues 223-287 of cardiac troponin T, and one or more segments at arbitrarily selected amino acid residues 1-222 of cardiac troponin T, A sample analysis system including a data processing unit including a processor and a computer-readable storage medium storing computer-readable instructions, wherein when the computer-readable instructions are executed by the processor, the processor: The steps include receiving and processing the content of one or more myocardial injury markers to obtain characteristic parameters for evaluating myocardial injury, A sample analysis system characterized by performing the step of outputting the aforementioned characteristic parameters.

27. Applications in the manufacture of a kit for the quantitative detection of large cardiac troponin ternary complex and / or total cardiac troponin ternary complex in a sample, wherein the kit is used to evaluate myocardial damage in a subject. Here, the large cardiac troponin ternary complex is a complex formed from the full-length protein or any amino acid fragment of troponin C, the full-length protein or any amino acid fragment of cardiac troponin I, one or more segments of cardiac troponin T at amino acid residues 223-287, and one or more segments of cardiac troponin T at amino acid residues 1-222. The total cardiac troponin ternary complex is a complex formed from the full-length protein or any amino acid fragment of troponin C, the full-length protein or any amino acid fragment of cardiac troponin I, one or more segments of cardiac troponin T at amino acid residues 223-287, and one or more segments of optionally selected cardiac troponin T at amino acid residues 1-222.

28. The kit further includes reagents for quantitative detection of total cardiac troponin complex, reagents for quantitative detection of cTnI, and / or reagents for quantitative detection of cTnT, where, The cTnI comprises the full-length protein of cardiac troponin I or any amino acid fragment thereof. The aforementioned cTnT comprises the full-length protein of cardiac troponin T or any amino acid fragment thereof. The use according to claim 27, wherein the total cardiac troponin complex comprises the total cardiac troponin ternary complex and a binary complex consisting of the full-length protein of troponin C or any amino acid fragment thereof and the full-length protein of cardiac troponin I or any amino acid fragment thereof.

29. The reagent for quantitative detection of large cardiac troponin ternary complex in the aforementioned sample comprises a group antibody and a group antibody, where, The first group of antibodies comprises one or more antibodies 1-1, each antibody 1-1 independently selected from antibodies that specifically bind to any one segment in the amino acid sequence of cTnT between positions 67 and 222. The second group of antibodies comprises one or more antibodies 1-2, each antibody 1-2 independently selected from antibodies that specifically bind to any one segment in the TnC amino acid sequence. The antibodies in the second group are, independently, one or more antibodies 1-3 selected from antibodies that specifically bind to cTnIC, and / or The present invention further comprises one or more antibodies 1-4 independently selected from antibodies that specifically bind to any single segment in the amino acid sequence of cTnI between positions 18 and 210, Preferably, the antibodies in the first group do not include antibodies that specifically bind to any one segment in the amino acid sequence between positions 223 and 287 of cTnT. Preferably, the antibody of the first group is a capture antibody, and the antibody of the second group is a detection antibody, according to the use of claim 27 or 28.

30. The reagent for quantitative detection of total cardiac troponin ternary complex in the aforementioned sample comprises a first antibody group and a second antibody group, where, The first detection reagent comprises one or more antibodies 2-1, each antibody 2-1 independently selected from antibodies that specifically bind to any one segment in the amino acid sequence of cTnT between positions 223 and 287. The second detection reagent comprises one or more antibodies 2-2, each antibody 2-2 independently selected from antibodies that specifically bind to any one segment in the TnC amino acid sequence. Optionally, the first detection reagent further comprises one or more antibodies 2-3, each antibody 2-3 independently selected from antibodies that specifically bind to any one segment in the amino acid sequence of cTnT between positions 67 and 222. Optionally, the second detection reagent is One or more antibodies 2-4, independently selected from antibodies that specifically bind to cTnIC, and / or The solution further comprises one or more antibodies 2-5 independently selected from antibodies that specifically bind to any one segment in the amino acid sequence of cTnI between positions 18 and 210, Preferably, the first antibody group is a capture antibody, and the second antibody group is a detection antibody, according to any one of claims 27 to 29.

31. The aforementioned kit is 1) Determination of the stage of myocardial infarction, in particular, determination of whether the subject is in the early stage of myocardial infarction, 2) Distinguishing between type I myocardial infarction and chronic cardiac events, 3) Exclusion of chest pain subjects who have not experienced myocardial injury. 4) Distinguishing between type I myocardial infarction and type II myocardial infarction, 5) Distinguishing between myocardial injury caused by invasive procedures and chronic cardiac events. 6) Evaluation of the prognosis of chronic myocardial injury, 7) The use described in any one of claims 27 to 30, which is used for one or more of the evaluations of the prognosis of acute myocardial injury.

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