Device for identification or auxiliary identification of acute chest pain type and use thereof

Abstract

Provided are a device for identification or auxiliary identification of an acute chest pain type and the use thereof in the field of medical care informatics. The technical problem to be solved is to quickly identify a chest pain type of a patient with acute chest pain. The device for identification or auxiliary identification of the acute chest pain type is provided, which device comprises the following modules: a data receiving module for receiving the content of a protein in the serum of a test subject, wherein the protein is soluble ST2, D-dimer and cardiac troponin I, and the test subject is a patient with acute chest pain; and a result output module for outputting the acute chest pain type from a computer on the basis of the concentration of the protein. The acute chest pain type is acute aortic dissection, acute myocardial infarction, acute pulmonary embolism or another type of acute chest pain, wherein the another type of acute chest pain is acute chest pain other than acute aortic dissection, acute myocardial infarction and acute myocardial infarction. The provided device for identification or auxiliary identification of the acute chest pain type has a certain application prospect.

Description

Device for identifying or assisting in identifying the type of acute chest pain and its application Technical Field

[0001] The present invention relates to a device for identifying or assisting in identifying the type of acute chest pain in the field of medical care informatics and an application thereof. Background Art

[0002] Acute chest pain is non-traumatic pain or other chest discomfort that occurs within 24 hours of onset. Cardiovascular-related acute chest pain, including acute myocardial infarction (AMI), acute aortic dissection (AAD), and acute pulmonary embolism (APE), is a serious condition with a high mortality rate. Clinically, all present with acute chest pain symptoms, but their different mechanisms require different treatments. Acute myocardial infarction is caused by coronary thrombosis, leading to myocardial ischemia. Acute pulmonary embolism is caused by internal or external emboli obstructing the pulmonary artery, resulting in pulmonary circulation and right heart dysfunction. Both conditions require rapid diagnosis and treatment with anticoagulants and thrombolytics. Acute aortic dissection is caused by various causes, resulting in a tear in the aortic intima and media. This separation allows blood to flow in, dividing the aortic lumen into the true and false lumen. Misdiagnosis and treatment with thrombolytics can exacerbate the disease and endanger the patient's life. Therefore, there is an urgent need for biomarkers that can provide additional information in addition to existing clinical diagnostic methods to help differentiate patients with acute fatal chest pain.

[0003] AMI, AAD, and APE can all induce chest pain, complicating clinical diagnosis and differential diagnosis, leading to missed and misdiagnoses. D-dimer is a specific degradation product produced by the hydrolysis of cross-linked fibrin by plasmin. A blood test value below the positive threshold indicates the absence of thrombus formation and lysis. AMI is triggered by a thrombus obstructing the coronary artery lumen. Because arterial thrombosis initiates platelet aggregation (white thrombus), the elevation of D-dimer levels in patients is less pronounced. In AAD, blood in the aorta enters the media through a tear in the intima, causing media separation and potential thrombus formation. Consequently, D-dimer levels are generally elevated. In patients with acute pulmonary embolism, once a thrombus forms in the pulmonary artery, it stimulates the body's fibrinolytic system, resulting in a significant increase in D-dimer levels within a short period of time. Thus, D-dimer biomarkers are elevated in both acute aortic dissection and acute pulmonary embolism.

[0004] ST2 is a receptor for interleukin-33 (IL-33), including the soluble ST2 receptor (sST2) and the membrane-bound functional receptor (ST2L). Previous research has shown that among patients with aortic dissection, sST2 levels are higher within 24 hours of symptom onset compared with those with acute myocardial infarction; and higher levels are found in patients with acute aortic dissection compared with those with acute pulmonary embolism, indicating its significant diagnostic value as an auxiliary indicator for aortic dissection.

[0005] Troponin (Tn) is a regulatory protein for muscle contraction, located on the thin filaments of the contractile proteins and playing a crucial role in regulating muscle contraction and relaxation. It consists of three isoforms: fast-acting, slow-acting, and cardiac troponin (cTn). The first two are associated with skeletal muscle, while cardiac troponin is present only in cardiomyocytes. It is a complex composed of three subunits: troponin T (cTnT), troponin I (cTnI), and troponin C (cTnC). cTnT and cTnI are cardiomyocyte-specific antigens. cTnI has a molecular weight of approximately 23.88 kDa and is degraded from myocardial fibers upon cardiomyocyte injury. Elevated serum cTn levels reflect cardiomyocyte damage, with higher specificity and sensitivity than the commonly used myocardial enzyme profile. In myocardial infarction, severe myocardial ischemia due to vascular occlusion or near-occlusion leads to cardiomyocyte necrosis. Intracellular cTnI is released into the blood, resulting in elevated serum cTnI levels. It is a marker of myocardial structural damage and a diagnostic marker of pathological diagnosis.

[0006] For the differential diagnosis of patients with acute fatal chest pain, the current clinical practice is mainly based on the patient's known biomarkers, imaging and onset characteristics. Only D-dimer has clinical significance in the diagnosis of suspected AAD patients, but it can only differentiate patients with acute myocardial infarction and cannot distinguish AAD patients from patients with pulmonary embolism. In addition, the detection process requires the use of large instruments in the laboratory for detection, and the entire detection process takes about 4 hours or more. Other metabolite detection also needs to be carried out in the laboratory and takes even longer. In addition, a single biomarker can only reflect part of the disease information from one aspect and cannot fully and accurately assess the cause, pathology and pathophysiological changes of acute chest pain and possible accompanying dyspnea. Therefore, there is an urgent need for combined biomarkers that can provide additional information in addition to existing clinical diagnostic methods to help differentiate patients with chest pain. In response to the needs of rapid differential diagnosis of people with acute chest pain, a new strategy for rapid differential diagnosis of acute fatal chest pain is established, and a test kit that can be used for rapid diagnosis is developed. Technical issues

[0007] The technical problem to be solved by the present invention is how to quickly identify the chest pain type of patients with acute chest pain so as to provide an effective treatment strategy. Technical Solutions

[0008] In order to solve the above technical problems, the present invention provides a device for identifying or assisting in identifying the type of acute chest pain.

[0009] The device for identifying or assisting in identifying the type of acute chest pain provided by the present invention includes the following modules:

[0010] M1, data receiving module: used to receive the protein content in the serum of the subject, wherein the proteins are soluble ST2, D-dimer and cardiac troponin I; the subject is a patient with acute chest pain;

[0011] M2. Result output module: used for outputting the acute chest pain type from a computer based on the protein concentration.

[0012] The type of acute chest pain may be acute aortic dissection, acute myocardial infarction, acute pulmonary embolism or other acute chest pain, and the other acute chest pain may be acute chest pain of non-acute aortic dissection, non-acute myocardial infarction and non-acute myocardial infarction.

[0013] The soluble ST2 may be a protein having an amino acid sequence of sequence 1 in the sequence list. The cardiac troponin I may be a protein having an amino acid sequence of sequence 2 in the sequence list.

[0014] In the above device, the result output module includes a model construction submodule, which is used to construct the model using the protein concentration in the serum of patients with acute chest pain as input data of the model and the type of acute chest pain as output data.

[0015] The aforementioned device may be a computer device, comprising a memory, a processor, and a computer program stored in the memory.

[0016] The memory is used to store a program. Specifically, the program may include a program code, and the program code includes computer program instructions.

[0017] The memory may include a main memory and a nonvolatile memory, and provides instructions and data to the processor.

[0018] The processor reads the corresponding computer program from the non-volatile memory into the internal memory and then runs it, forming a screening device for acute chest pain types at a logical level.

[0019] The processor executes the computer program to implement the following steps:

[0020] N1. Receive data: Receive serum protein levels of subjects, including soluble ST2, D-dimer, and cardiac troponin I; the subjects are patients with acute chest pain;

[0021] N2. Output result: Output the acute chest pain type from the computer based on the protein concentration.

[0022] The type of acute chest pain may be acute aortic dissection, acute myocardial infarction, acute pulmonary embolism or other acute chest pain, and the other acute chest pain may be acute chest pain of non-acute aortic dissection, non-acute myocardial infarction and non-acute myocardial infarction.

[0023] The computer program instructions may be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0024] The computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0025] The present invention also provides a method for constructing a prediction model for acute chest pain types, the method comprising receiving the protein content in the serum of an acute chest pain patient, the proteins being soluble ST2, D-dimer, and cardiac troponin I, using the protein content as model input data, and using the acute chest pain type as output data to construct an acute chest pain type prediction model.

[0026] The present invention also provides a method for identifying or assisting in identifying the type of acute chest pain, the method comprising receiving the protein content in the serum of a patient with acute chest pain, wherein the proteins are soluble ST2, D-dimer and cardiac troponin I, and outputting the type of acute chest pain from a computer based on the protein concentration; the acute chest pain type is acute aortic dissection, acute myocardial infarction, acute pulmonary embolism or other acute chest pain, and the other acute chest pain is acute chest pain other than acute aortic dissection, non-acute myocardial infarction and non-acute myocardial infarction.

[0027] In the above method, the method also includes the step of constructing a model, which includes receiving the soluble ST2, D-dimer, and cardiac troponin I levels in the serum of patients with acute chest pain as model input data, and using the acute chest pain type as output data to construct an acute chest pain type prediction model.

[0028] The present invention also provides a computer program product or a computer-readable storage medium, wherein the computer program product includes a computer program, and the computer-readable storage medium stores a computer program, which, when executed by a processor, implements the method steps described above for identifying or assisting in identifying the type of acute chest pain.

[0029] The computer program product may be a software product that primarily implements its solution through a computer program.

[0030] Computer-readable storage media refers to a medium for storing data, including permanent and non-permanent, removable and non-removable media. Information storage can be achieved using any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Computer-readable storage media can be magnetic tape, magnetic disk, floppy disk, optical disk, magneto-optical disk, ROM, PROM, VCD, DVD, hard disk, flash memory, USB flash drive, CF card, SD card, MMC card, SM card, Memory Stick, or xD card, etc.

[0031] The present invention also provides a product for identifying or assisting in identifying the type of acute chest pain, the product comprising a device and a reagent, the device being the device described above, the reagent being a protein and / or a substance for detecting the protein, the protein being soluble ST2, D-dimer and cardiac troponin I; the type of acute chest pain being acute aortic dissection, acute myocardial infarction, acute pulmonary embolism or other acute chest pain, the other acute chest pain being non-acute aortic dissection, non-acute myocardial infarction and acute chest pain of non-acute myocardial infarction.

[0032] The substance may include a substance for detecting the content of the protein in serum by enzyme-linked immunosorbent assay, immunofluorescence, flow cytometry, radioimmunoassay, immunocoprecipitation, immunoblotting, high performance liquid chromatography, capillary gel electrophoresis, near-infrared spectroscopy, mass spectrometry, immunochemiluminescence, colloidal gold immunoassay, fluorescent immunochromatography, surface plasmon resonance, immuno-PCR or biotin-avidin technology.

[0033] The product may be a reagent and / or an instrument. The product may also be a system.

[0034] The present invention also provides the use of proteins in preparing products for identifying or assisting in identifying the type of acute chest pain, wherein the proteins are soluble ST2, D-dimer and cardiac troponin I; the acute chest pain type is acute aortic dissection, acute myocardial infarction, acute pulmonary embolism or other acute chest pain, and the other acute chest pain is acute chest pain other than acute aortic dissection, non-acute myocardial infarction and non-acute myocardial infarction.

[0035] The use of substances for detecting the aforementioned proteins in the preparation of products for identifying or assisting in identifying the type of acute chest pain also falls within the scope of protection of the present invention.

[0036] In the above application, the proteins are soluble ST2, D-dimer and cardiac troponin I; the types of acute chest pain are acute aortic dissection, acute myocardial infarction, acute pulmonary embolism or other acute chest pain, and the other acute chest pain is acute chest pain other than acute aortic dissection, non-acute myocardial infarction and non-acute myocardial infarction.

[0037] The above applications or methods may be non-disease diagnosis applications or methods. The above applications or methods are not directly intended to obtain disease diagnosis results or health status of living human or animal bodies.

[0038] The above-mentioned application or method may be an application or method for disease diagnosis.

[0039] The above-mentioned application or method may be an application or method for non-disease treatment purposes. The above-mentioned application or method is not intended to restore or obtain health or alleviate suffering in living human or animal bodies.

[0040] The above-mentioned application or method may be an application or method for the purpose of treating a disease. Beneficial effects

[0041] The present invention combines serum soluble ST2, D-dimer, and cardiac troponin I as indicators for differential diagnosis of acute chest pain, and can be used to prepare products for differential diagnosis or auxiliary differential diagnosis of patients with acute chest pain. By detecting serum soluble ST2, D-dimer, and cardiac troponin I, patients with acute chest pain can be differentially diagnosed. This invention can improve the ability to differentially diagnose acute chest pain based on known biomarkers, and can be used in clinical practice to accurately stratify patient risk and improve patient survival rates. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] FIG1 is a computer flow chart for implementing the method for identifying or assisting in identifying the type of acute chest pain according to the present invention.

[0043] Figure 2 shows the levels of three markers in the discovery cohort. A represents serum sST2 levels; B represents serum D-dimer levels; and C represents serum cardiac troponin I levels. The vertical axis represents serum sST2 levels, serum D-dimer levels, and serum cardiac troponin I levels, respectively, in ng / mL. Modes for Carrying Out the Invention

[0044] The present invention will be further described in detail below in conjunction with specific embodiments. The examples provided are only for illustrating the present invention and are not intended to limit the scope of the present invention. The examples provided below can serve as a guide for further improvements by those skilled in the art and are not intended to limit the present invention in any way.

[0045] Unless otherwise specified, the experimental methods in the following examples are conventional methods and were performed according to the techniques or conditions described in the literature in the field or according to the product instructions. The materials and reagents used in the following examples, unless otherwise specified, were all commercially available.

[0046] The Human ST2 / IL-33R serum soluble ST2 detection kit used in the following examples was purchased from R&D Company, catalog number DY523B-05. D-dimer was measured using an ACL TOP550CTS fully automated coagulation analyzer; cardiac troponin I was measured using a Beckman fully automated luminescence analyzer. (Hereinafter, "cardiac troponin" refers to "cardiac troponin I").

[0047] The following examples were analyzed using Stata / SE 15.1 statistical software. Results for normally distributed continuous variables are expressed as mean ± standard deviation and tested using a one-way ANOVA. Results for non-normally distributed continuous variables are expressed as medians (25%-75%) and tested using a rank sum test. Results for categorical variables were tested using a chi-square test. P < 0.05 (*) indicates a significant difference, P < 0.01 (**) indicates a very significant difference, and P < 0.001 (***) indicates a very significant difference.

[0048] The present invention first provides a method for identifying or assisting in identifying the type of acute chest pain ( FIG. 1 ), comprising the following steps:

[0049] Step S1: receiving the serum soluble ST2, D-dimer and cardiac troponin levels of patients with known acute chest pain types to obtain model input data;

[0050] Step S2: constructing a multivariate logistic regression model using model input data;

[0051] Step S3: receiving the soluble ST2, D-dimer and cardiac troponin levels in the serum of the subject to obtain the subject's data;

[0052] Step S4: Input the subject's data into a multivariate logistic regression model, and output the prediction results of the acute chest pain type from the computer.

[0053] Example 1: Combined Differential Diagnosis of Chest Pain Types by Soluble ST2 (sST2), D-Dimer, and Cardiac Troponin

[0054] Ethics Statement

[0055] The experimental protocols in the examples of the present invention were approved by the Ethics Committee of Beijing Anzhen Hospital Affiliated to Capital Medical University, and the studies were conducted in accordance with the principles of the Declaration of Helsinki.

[0056] Research subjects

[0057] All study subjects were Chinese adults.

[0058] Patient diagnostic criteria

[0059] Patients included in the study must meet the following criteria:

[0060] Acute chest pain: The latest management consensus released by the European Society of Cardiology (ESC) and the Acute Cardiovascular Care Association (ACCA) in 2020 clearly stated that acute chest pain is non-traumatic pain or other chest discomfort within 24 hours of onset.

[0061] Acute myocardial infarction (AMI) refers to acute myocardial injury [serum cardiac troponin (cTn) increases and / or decreases, and is higher than the upper limit of normal (99th percentile of the upper limit of the reference value) at least once], accompanied by clinical evidence of acute myocardial ischemia, including: (1) symptoms of acute myocardial ischemia; (2) new ischemic electrocardiographic changes; (3) new pathological Q waves; (4) imaging evidence of new loss of viable myocardium or ventricular wall segment motion abnormalities; (5) coronary artery thrombosis confirmed by coronary angiography or intravascular imaging examination or autopsy.

[0062] Acute aortic dissection (AAD) is caused by various reasons, such as tearing of the aortic intima and media, separation of the aortic intima and media, and blood inflow, resulting in the aortic cavity being divided into true cavity and false cavity. The acute stage is when the onset time is ≤ 2 weeks.

[0063] Acute pulmonary embolism (APE) is a clinical syndrome characterized by pulmonary circulation and right heart dysfunction caused by endogenous or exogenous emboli blocking the pulmonary artery.

[0064] Other acute chest pain refers to non-acute aortic dissection, non-acute myocardial infarction, and acute chest pain associated with non-acute myocardial infarction. This includes unstable angina and other chest pain conditions. The diagnostic criteria for unstable angina are a group of clinical angina syndromes that fall between stable angina and acute myocardial infarction.

[0065] Discovery Cohort: A total of 326 patients with acute chest pain were enrolled. The mean age of these 326 patients was 53 years, and 219 (68.4%) were male. Baseline characteristics of this discovery cohort, stratified by disease type, are shown in Table 1. The 326 patients included 109 patients with acute adrenal infarction (AAD), 72 patients with acute myocardial infarction (AMI), 24 patients with acute periarthritis (APE), and 121 patients with other acute chest pain. Among the 109 patients with AAD, the mean age was 51 years, 68.9% were male, the median body mass index (BMI) was 26.6, the median left ventricular ejection fraction (LVEF) was 63.0%, 69.4% had hypertension (HBP), and 3.5% had diabetes mellitus (DM). Among the 72 patients with AMI, the mean age was 54 years, 84.7% were male, the median BMI was 25.8, the median LVEF was 55.0%, 59.4% had hypertension, and 26.1% had DM. Among the 24 patients with acute pulmonary embolism (APE), the mean age was 62 years, 50% were male, the median BMI was 23.8, the median LVEF was 62.0%, 58.3% had hypertension, and 20.8% had diabetes. Among the 121 patients with other acute chest pain, the mean age was 53 years, and 62.0% were male.

[0066]

[0067] Validation Cohort: A total of 217 patients with acute chest pain were enrolled. The mean age of these 217 patients was 53 years, and 163 (75.1%) were male. The baseline characteristics of this discovery cohort, stratified by disease type, are shown in Table 2. Among the 217 patients, there were 120 patients with acute adrenal infarction (AAD), 70 with acute myocardial infarction (AMI), and 27 with acute periarthritis (APE). Among the 120 patients with AAD, the mean age was 48 years, 77.5% were male, the median BMI was 26.1, the median LVEF was 63.0%, 76.7% had hypertension, and 8.3% had diabetes. Among the 70 patients with AMI, the mean age was 57 years, 85.7% were male, 58.6% had hypertension, and 28.6% had diabetes. Among the 27 patients with APE, the mean age was 66 years, 37.0% were male, 59.3% had hypertension, and 14.8% had diabetes.

[0068]

[0069] 1. Detection of serum soluble ST2, D-dimer, and cardiac troponin levels

[0070] Serum sample processing: After collecting blood, centrifuge at 1200 rpm at 4°C for 10 minutes and collect the supernatant for testing.

[0071] 1. Detection of soluble ST2 in serum

[0072] Detection kit: Human ST2 / IL-33R DuoSet (R&D, catalog number: DY523B-05). The ELISA method for detecting serum sST2 should be carried out according to the instructions in the kit.

[0073] 2. Detection of serum D-dimer

[0074] Detection kit: Catalog number REV202209, Instrument Laboratory Corporation. An ACL TOP550CTS fully automated coagulation analyzer was used. Serum D-dimer levels were measured according to the kit instructions.

[0075] 3. Detection of cardiac troponin I in serum

[0076] Detection kit: Catalog No. B52699, Manufacturer: ImmunoTech Co., Ltd. Serum cardiac troponin I levels were measured using a Beckman automated luminescence analyzer according to the kit instructions.

[0077] 2. Analysis of individual marker data for soluble ST2, D-dimer, and cardiac troponin levels in the discovery cohort

[0078] The results are shown in Figure 2A, B, and C and Table 1: Compared with other types of chest pain (except AAD), the serum sST2 level in patients with AAD was significantly higher, at 80.0 (median, IQR 49.2-143.8) (P<0.001).

[0079] Compared with other types of chest pain (except APE), the serum D-dimer level in patients with APE was significantly higher, at 2394 (median, IQR 1373-2991) (P<0.001).

[0080] Compared with other types of chest pain (except AMI), the serum cTNI level in patients with AMI was significantly higher, at 0.66 (median, IQR 0.13-3.88) (P<0.001).

[0081] 3. Differential diagnosis of different types of chest pain using three markers: soluble ST2, D-dimer, and cardiac troponin

[0082] To determine the optimal combination of three biomarkers (soluble ST2, D-dimer, and cardiac troponin), a multivariable logistic regression model was constructed using different combinations of variables (random combinations of ST2, D-dimer, and / or cardiac troponin). Data were processed and analyzed using Stata / SE 15.1 statistical software. A multivariable logistic regression model was used when multiple predictors were present. The area under the curve (AUC) was calculated based on the predicted probabilities generated by the multivariable logistic regression model. The cutoff value for the combined diagnosis of ST2, D-dimer, and cardiac troponin was determined by calculating the optimal threshold value using the Youden index (Youden index = sensitivity + specificity - 1).

[0083] The results are as follows: The combination of soluble ST2, D-dimer and cardiac troponin performed best in terms of diagnostic performance. In the above discovery cohort, the AUC of the combined diagnosis of AAD by soluble ST2, D-dimer and cardiac troponin was higher than that of each individual marker, at 0.9813, with a sensitivity of 98.06% and a specificity of 90.19%; the AUC of the combined diagnosis of AMI by soluble ST2, D-dimer and cardiac troponin was higher than that of each individual marker, at 0.9054, with a sensitivity of 76.39% and a specificity of 91.43%; the AUC of the combined diagnosis of APE by soluble ST2, D-dimer and cardiac troponin was higher than that of each individual marker, at 0.9554, with a sensitivity of 91.30% and a specificity of 90.11% (Table 3).

[0084]

[0085] 4. Biomarkers - Soluble ST2, D-dimer, and Cardiac Troponin Combined to Classify Different Types of Acute Chest Pain

[0086] The combined diagnostic results of the cohort's markers—soluble ST2, D-dimer, and cardiac troponin—were found (Table 4): when the sST2 level was ≥34.6 ng / mL, the diagnosis rate for acute aortic dissection was 92.7%; when the cTNI level was ≥0.04 ng / mL, the diagnosis rate for acute myocardial infarction was 93.1%; and when the sST2 level was <34.6 ng / mL and the D-dimer level was ≥500 ng / mL, the diagnosis rate for acute pulmonary embolism was 87.5%.

[0087]

[0088] In summary, the prediction model of different types of acute chest pain using soluble ST2, D-dimer, and cardiac troponin was constructed as follows:

[0089] 1) When the sST2 level is ≥34.6 ng / mL, it can assist in identifying the chest pain type as acute aortic dissection;

[0090] 2) When the cTNI level is ≥0.04 ng / mL, it can assist in identifying the chest pain type as acute myocardial infarction;

[0091] 3) When the sST2 level is <34.6 ng / mL and the D-Dimer level is ≥500 ng / mL, the chest pain type is diagnosed as acute pulmonary embolism.

[0092] 4) When the sST2 level is <34.6 ng / mL, the D-Dimer level is <500 ng / mL, and the TNI level is <0.04 ng / mL, the auxiliary identification of the chest pain type is other chest pain that excludes the above three types of acute and fatal chest pain.

[0093] The prediction model was subsequently validated in a validation cohort.

[0094] Example 2: Application of Soluble ST2, D-Dimer, and Cardiac Troponin Combined to Chest Pain Type Prediction Model

[0095] The levels of soluble ST2, D-dimer, and cardiac troponin in the serum of the validation cohort samples were detected according to the detection method described in Example 1 (see Table 7 for specific data), and then multivariate logistic regression was performed on the validation cohort using the prediction model in Example 1.

[0096] The results are as follows: In Table 5, sST2 represents sST2 alone, and sST2+D-Dimer+cTN1 represents the combined diagnosis of soluble ST2, D-dimer, and cardiac troponin. In the validation cohort, the combined diagnosis of soluble ST2, D-dimer, and cardiac troponin for ADD showed a higher AUC of 0.9534, with a sensitivity of 93.33% and a specificity of 84.54%, compared with the individual markers alone. The combined diagnosis of AMI showed a higher AUC of 0.9849, with a sensitivity of 97.14% and a specificity of 96.60%, compared with the individual markers alone. The combined diagnosis of APE showed a higher AUC of 0.9076, with a sensitivity of 92.59% and a specificity of 86.84%, compared with the individual markers alone (Table 5).

[0097]

[0098] When the sST2 level is ≥34.6 ng / mL, acute aortic dissection is diagnosed; when the cTNI level is ≥0.04 ng / mL, acute myocardial infarction is diagnosed; when the sST2 level is <34.6 ng / mL and the D-Dimer level is ≥500 ng / mL, acute pulmonary embolism is diagnosed.

[0099] The combined diagnostic results of the validation cohort markers—soluble ST2, D-dimer, and cardiac troponin—showed that when sST2 ≥ 34.6 ng / mL, the diagnosis rate for acute aortic dissection was 82.50%; when cTNI ≥ 0.04 ng / mL, the diagnosis rate for acute myocardial infarction was 88.57%; and when sST2 < 34.6 ng / mL and D-dimer ≥ 500 ng / mL, the diagnosis rate for acute pulmonary embolism was 85.19%.

[0100]

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[0107]

[0108] In summary, through rapid testing of three biomarkers—sST2, D-dimer, and cardiac troponin—and combined analysis of their levels, the following criteria are established: when sST2 ≥ 34.6 ng / mL, the auxiliary diagnosis is acute aortic dissection; when cTNI ≥ 0.04 ng / mL, the auxiliary diagnosis is acute myocardial infarction; when sST2 < 34.6 ng / mL and D-dimer ≥ 500 ng / mL, the auxiliary diagnosis is acute pulmonary embolism; and when sST2 < 34.6 ng / mL, D-dimer < 500 ng / mL, and cTNI < 0.04 ng / mL, the auxiliary diagnosis is other chest pain that excludes the three aforementioned acute, life-threatening conditions. By improving the differential diagnosis of patients with acute, life-threatening chest pain, we can accurately stratify their risk and, in the hope of improving their survival in clinical practice.

[0109] The present invention has been described in detail above. For those skilled in the art, without departing from the purpose and scope of the present invention, and without the need to carry out unnecessary experimental conditions, the present invention can be implemented in a wide range under equivalent parameters, concentrations and conditions. Although the present invention provides specific embodiments, it should be understood that further improvements can be made to the present invention. In short, according to the principles of the present invention, this application is intended to include any changes, uses or improvements to the present invention, including changes that depart from the disclosed scope in this application and are made using conventional techniques known in the art.

[0110] CROSS-REFERENCE TO RELATED APPLICATIONS

[0111] This application claims priority to Chinese patent application No. 202410062876.2 filed with the Patent Office of China on January 17, 2024, entitled “Device for Identifying or Assisting in Identifying the Type of Acute Chest Pain and Its Application,” the entire contents of which are incorporated herein by reference. Industrial Applicability

[0112] The present invention can be used to accurately stratify the risks of patients with acute chest pain and improve their survival rates. Sequence Listing Free Content

[0113] SEQ ID No.1

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[0115] SEQ ID No. 2

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Claims

1. A device for identifying or assisting in the identification of the type of acute chest pain, characterized in that, The device includes the following modules: M1, a data receiving module: used to receive the protein content in the serum of the subject, where the proteins are soluble ST2, D-dimer, and cardiac troponin I; the subject is a patient with acute chest pain; M2, a result output module: used to output the type of acute chest pain from a computer based on the protein concentration; The type of acute chest pain is acute aortic dissection, acute myocardial infarction, acute pulmonary embolism, or other acute chest pain, and the other acute chest pain is acute chest pain that is not acute aortic dissection, not acute myocardial infarction, and not acute myocardial infarction.

2. The device according to claim 1, wherein The result output module includes a model construction sub-module, and the model construction sub-module is used to use the protein concentration in the serum of a patient with acute chest pain as the input data of the model and the type of acute chest pain as the output data to construct a model.

3. A method for constructing a model for identifying or assisting in identifying the types of acute chest pain, characterized in that, The method includes receiving the protein content in the serum of a patient with acute chest pain, where the proteins are soluble ST2, D-dimer, and cardiac troponin I, using the protein content as the input data of the model, and using the type of acute chest pain as the output data to construct a prediction model for the type of acute chest pain.

4. A method for identifying or assisting in the identification of the type of acute chest pain, characterized in that, The method includes receiving the protein content in the serum of a patient with acute chest pain, where the proteins are soluble ST2, D-dimer, and cardiac troponin I, and outputting the type of acute chest pain from a computer based on the protein concentration; the type of acute chest pain is acute aortic dissection, acute myocardial infarction, acute pulmonary embolism, or other acute chest pain, and the other acute chest pain is acute chest pain that is not acute aortic dissection, not acute myocardial infarction, and not acute myocardial infarction.

5. The method according to claim 4, wherein The method includes constructing a model, and the constructing of the model includes receiving the contents of soluble ST2, D-dimer, and cardiac troponin I in the serum of a patient with acute chest pain as the input data of the model and the type of acute chest pain as the output data to construct a prediction model for the type of acute chest pain.

6. A computer-readable storage medium storing a computer program, characterized in that, The computer program causes the computer to execute the steps of the method according to any one of claims 3-5.

7. A product for identifying or assisting in the identification of the type of acute chest pain, characterized in that, The product includes a device and a reagent, the device is the device according to claim 1 or 2, the reagent is a protein and / or a substance for detecting the protein, and the proteins are soluble ST2, D-dimer, and cardiac troponin I; the type of acute chest pain is acute aortic dissection, acute myocardial infarction, acute pulmonary embolism, or other acute chest pain, and the other acute chest pain is acute chest pain that is not acute aortic dissection, not acute myocardial infarction, and not acute myocardial infarction.

8. Use of a protein in the preparation of a product for identifying or assisting in the identification of the type of acute chest pain, characterized in that, The proteins are soluble ST2, D-dimer, and cardiac troponin I; the type of acute chest pain is acute aortic dissection, acute myocardial infarction, acute pulmonary embolism, or other acute chest pain, and the other acute chest pain is acute chest pain that is not acute aortic dissection, not acute myocardial infarction, and not acute myocardial infarction.

9. Use of a substance for detecting proteins in the preparation of a product for identifying or assisting in the identification of types of acute chest pain, characterized in that, The proteins are soluble ST2, D-dimer, and cardiac troponin I; the type of acute chest pain is acute aortic dissection, acute myocardial infarction, acute pulmonary embolism, or other acute chest pain, and the other acute chest pain is acute chest pain that is not acute aortic dissection, not acute myocardial infarction, and not acute myocardial infarction.

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