Thromboelastography generation method based on magnetic bead method and related device

Abstract

The embodiment of the application discloses a thromboelastography generation method based on a magnetic bead method, and the method is characterized in that the method comprises the following steps: acquiring magnetic bead oscillation waveform data detected based on the magnetic bead method; and performing conversion calculation based on the magnetic bead oscillation waveform data to obtain the thromboelastography. The thromboelastography generation method greatly reduces the cost, and greatly improves the timeliness due to the simple detection method. In addition, a thromboelastography generation device based on the magnetic bead method, a sample analyzer and a storage medium are also provided.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical detection, and in particular to a thromboelastography generation method and device based on a magnetic bead method, a sample analyzer and a storage medium. BACKGROUND

[0002] A traditional thromboelastogram is generated by a thromboelastograph (TEG), which is an analyzer for detecting the coagulation process from the whole dynamic process of platelet aggregation, coagulation and fibrinolysis, and is used for monitoring and analyzing the coagulation state of a blood sample. The principle is to simulate the viscoelasticity of a blood clot formed during the blood clotting process, which changes over time, and to draw a thromboelastogram using mechanical principles. The generation of a traditional thromboelastogram requires a special thromboelastograph, i.e., a special thromboelastograph needs to be purchased for detection, resulting in high cost, and the thromboelastograph has a slow detection speed and needs to be manually operated by a special person, which not only has low timeliness but also cannot meet the high timeliness demand in emergency situations. SUMMARY

[0003] Therefore, it is necessary to propose a thromboelastography generation method and device based on a magnetic bead method, a sample analyzer and a storage medium, which have high timeliness and can greatly save costs.

[0004] A thromboelastography generation method based on a magnetic bead method, the method comprising:

[0005] obtaining magnetic bead oscillation waveform data detected based on the magnetic bead method;

[0006] performing conversion calculation based on the magnetic bead oscillation waveform data to obtain the thromboelastogram.

[0007] A thromboelastography generation device based on a magnetic bead method, the device comprising:

[0008] an obtaining module configured to obtain magnetic bead oscillation waveform data detected based on the magnetic bead method;

[0009] a calculation module configured to perform conversion calculation based on the magnetic bead oscillation waveform data to obtain the thromboelastogram.

[0010] A sample analyzer comprising a memory and a processor, the memory storing a computer program, and the computer program being executed by the processor to cause the processor to perform the following steps:

[0011] obtaining magnetic bead oscillation waveform data detected based on the magnetic bead method;

[0012] performing conversion calculation based on the magnetic bead oscillation waveform data to obtain the thromboelastogram.

[0013] A computer readable storage medium has a computer program stored, the computer program is executed by a processor, so that the processor executes the following steps:

[0014] Obtain the magnetic bead oscillation waveform data detected based on the magnetic bead method;

[0015] Based on the magnetic bead oscillation waveform data, conversion calculation is carried out to obtain the thromboelastogram.

[0016] The above-mentioned thromboelastogram generation method, device, sample analyzer and storage medium based on the magnetic bead method, the magnetic bead oscillation waveform data in the coagulation analysis is used for conversion calculation, and the thromboelastogram can be obtained. In this method, a special thromboelastogram instrument is not needed to realize, and the existing sample analyzer can be used to realize. The magnetic bead method is a common detection method in the sample analyzer, and only the corresponding conversion calculation method needs to be added in the sample analyzer to draw the thromboelastogram. The thromboelastogram generation method not only greatly reduces the cost, but also greatly improves the timeliness due to the simple detection method. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0018] Among them:

[0019] Figure 1 It is a flow chart of the thromboelastogram detection method based on the magnetic bead method in an embodiment;

[0020] Figure 2A It is a schematic diagram of the first type of elastic diagram in an embodiment;

[0021] Figure 2B It is a schematic diagram of the second type of elastic diagram in an embodiment;

[0022] Figure 3 It is a detection flowchart of a sample analyzer in an embodiment;

[0023] Figure 4 It is a flow chart of the thromboelastogram generation method based on the magnetic bead method in an embodiment;

[0024] Figure 5 It is a method flowchart for conversion calculation to obtain the thromboelastogram in an embodiment;

[0025] Figure 6Fig. 1 is a schematic diagram of the magnetic bead oscillation waveform data in one embodiment;

[0026] Figure 7 Fig. 2 is a flowchart of calculating the peak baseline and the trough baseline of the first derivative in one embodiment;

[0027] Figure 8 Fig. 3 is a schematic diagram of the peak baseline and the trough baseline obtained in one embodiment;

[0028] Figure 9 Fig. 4 is a schematic diagram of the initial thrombelastogram obtained by inverse transformation in one embodiment;

[0029] Figure 10 Fig. 5 is a schematic diagram of the thrombelastogram obtained after fitting in one embodiment;

[0030] Figure 11 Fig. 6 is a flowchart of calculating the peak baseline and the trough baseline of the first derivative in one embodiment;

[0031] Figure 12 Fig. 7 is a flowchart of the heparinase detection method based on the magnetic bead method in one embodiment;

[0032] Figure 13 Fig. 8 is a schematic diagram of the thrombelastogram in one embodiment;

[0033] Figure 14 Fig. 9 is a structural block diagram of the thrombelastogram detection device based on the magnetic bead method in one embodiment;

[0034] Figure 15 Fig. 10 is a structural block diagram of the thrombelastogram generation device based on the magnetic bead method in one embodiment;

[0035] Figure 16 Fig. 11 is a structural block diagram of the calculation module in one embodiment;

[0036] Figure 17 Fig. 12 is a structural block diagram of the heparinase detection device based on the magnetic bead method in one embodiment;

[0037] Figure 18 Fig. 13 is an internal structural diagram of the sample analyzer in one embodiment. DETAILED DESCRIPTION

[0038] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0039] The magnetic bead method refers to putting a magnetic bead in a detection cup (i.e. a reaction cup), and there is a set of drive coils on both sides of the detection cup, which generates a constant alternating electromagnetic field, so that the specially designed demagnetization small steel bead in the detection cup maintains an equal amplitude oscillation movement. After the coagulation activator is added, as the amount of fibrin produced increases, the viscosity of the plasma increases, and the movement amplitude of the small steel bead gradually decreases. The instrument collects the movement changes of the small steel bead to obtain the magnetic bead oscillation waveform data according to the changes of the small steel bead movement sensed by another set of measurement coils.

[0040] As shown in Figure 1 , a thrombelastogram detection method based on the magnetic bead method is proposed, which is applied to a sample analyzer. The method comprises:

[0041] Step 102: When it is detected that the to-be-detected item contains thrombelastogram detection, the magnetic bead method is used to detect the sample to obtain magnetic bead oscillation waveform data.

[0042] Among the to-be-detected items, there can be one or more detection items. Thrombelastogram detection is one of the detection items. There are various ways to obtain the to-be-detected items, one of which is to directly receive a detection instruction, and the detection instruction contains information of the to-be-detected items. Another way is to obtain the to-be-detected items by scanning a code, that is, to store the to-be-detected item information in the form of a bar code.

[0043] When it is detected that the to-be-detected item contains thrombelastogram detection, the magnetic bead method needs to be used to detect the sample to collect the magnetic bead oscillation waveform data. The to-be-detected item can contain multiple detection items at the same time. For example, the to-be-detected item contains thrombelastogram detection and four coagulation items, including prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), and fibrinogen (FIB). The detection of the four coagulation items can be performed by the magnetic bead method or the optical method. When the four coagulation items are detected by the magnetic bead method, the thrombelastogram detection and the four coagulation items can be detected simultaneously by the magnetic bead method. In an embodiment, each magnetic bead method detection item can correspond to a thrombelastogram. For example, the TT item detected by the magnetic bead method can correspond to a TT thrombelastogram, and the APTT item detected by the magnetic bead method can correspond to an APTT thrombelastogram.

[0044] Since the detection of the four coagulation items requires a plasma sample, the thrombelastogram obtained based on the plasma sample is not a standard thrombelastogram. In order to distinguish, the thrombelastogram obtained based on the plasma sample is called "second type thrombelastogram", that is, the TT thrombelastogram and the APTT thrombelastogram actually belong to the second type thrombelastogram.

[0045] That is, the elasticogram detection is actually divided into two types, the first type elasticogram detection and the second type elasticogram detection. The first type elasticogram is a standard elasticogram detected based on a whole blood sample, and the second type elasticogram detection is a non-standard elasticogram detected based on a plasma sample.

[0046] Therefore, when the to-be-detected item contains elasticogram detection, it is further necessary to distinguish which type of elasticogram detection is contained, so as to determine the sample type required for detection, that is, whether to use a plasma sample or a whole blood sample.

[0047] In step 104, the elasticogram is drawn according to the magnetic bead oscillation waveform data, and a thrombus elasticogram is generated.

[0048] Among them, the magnetic bead oscillation waveform data is converted to draw a thrombus elasticogram. There are many methods for converting and calculating the magnetic bead oscillation waveform data.

[0049] In one embodiment, the conversion calculation can be calculated by the following method: first, the magnetic bead oscillation waveform data is subjected to first-order derivation to obtain first-order derivation graph data, then the first-order derivation graph data is subjected to second-order derivation to obtain second-order derivation graph data, the wave peaks and wave troughs of the first-order derivation graph data are determined according to the second-order derivation graph data, then the wave peak baseline and the wave trough baseline are extracted, and the initial elasticogram is obtained by inverse transformation based on the wave peak baseline and the wave trough baseline, and then the fitting calculation is performed to draw the thrombus elasticogram.

[0050] In another embodiment, the conversion calculation can also be calculated by the following method: first, the magnetic bead oscillation waveform data is subjected to inverse transformation to obtain inverse transformed magnetic bead oscillation waveform data, then the transformed magnetic bead oscillation waveform data is subjected to first-order derivation and second-order derivation, the wave peaks and wave troughs of the first-order derivation are determined based on the second-order derivation, the wave peak baseline and the wave trough baseline are extracted, and then the fitting calculation is performed to obtain the thrombus elasticogram.

[0051] The above-mentioned elasticogram detection method based on the magnetic bead method, when the to-be-detected item contains elasticogram detection, the sample is detected by the magnetic bead method to obtain magnetic bead oscillation waveform data, and the elasticogram is drawn according to the magnetic bead oscillation waveform data to generate a thrombus elasticogram. In this method, a special thrombus elasticogram instrument is not required to realize, and the existing sample analyzer can be used to realize, the magnetic bead method is a common detection method in the sample analyzer, and only the corresponding elasticogram drawing method needs to be added in the sample analyzer to draw the thrombus elasticogram. The thrombus elasticogram detection method not only greatly reduces the cost, but also greatly improves the timeliness due to the simple detection method.

[0052] In one embodiment, when the elastography detection included in the test item is a first type of elastography detection, the sample is a whole blood sample and the thromboelastography is a first type of thromboelastography; when the elastography detection included in the test item is a second type of elastography detection, the sample is a plasma sample and the thromboelastography is a second type of thromboelastography.

[0053] The first type of elasticity diagram is a standard elasticity diagram, which includes the entire force curve. The second type of elasticity diagram is a non-standard elasticity diagram, which only includes half of the force curve (i.e., only the first half). For example... Figure 2A The diagram shown is a schematic of the first type of elastic force diagram. Figure 2B This is a schematic diagram of the second type of elasticity map. Different samples are used for different types of elasticity maps, which allows for the determination of the items to be tested based on actual needs, and provides greater flexibility and variety in the selection of testable items.

[0054] In one embodiment, when the test item only includes the first type of elastogram test, the magnetic bead method is used to test the sample and obtain magnetic bead oscillation waveform data. This includes: controlling the sampling needle to draw whole blood sample and add it to the magnetic bead reaction cup; transferring the magnetic bead reaction cup with the whole blood sample added to the reagent addition position; adding whole blood reagent to the reagent addition position; transferring the magnetic bead reaction cup with the whole blood reagent added to the magnetic bead detection position; and using the magnetic bead method to test the sample at the magnetic bead detection position and collecting magnetic bead oscillation waveform data.

[0055] When performing tests in the sample analyzer, if the test item only includes the first type of elastogram detection, a whole blood sample is used directly. That is, the provided sample is a whole blood sample. The whole blood sample is directly drawn up using a sampling needle, and then the magnetic bead reaction cup with the whole blood sample is transferred to the reagent addition position. Whole blood reagent is added to the reagent addition position, and then transferred to the magnetic bead detection position. This facilitates the subsequent detection of the whole blood sample using the magnetic bead method to obtain the magnetic bead oscillation waveform data. The sample analyzer provides a method for realizing the above-mentioned elastogram detection, and the detection of the first type of elastogram can be achieved using the sample analyzer.

[0056] In one embodiment, when the test item includes more than just the first type of elastogram test, the magnetic bead method is used to test the sample and obtain magnetic bead oscillation waveform data. This includes: controlling the sampling needle to mix the centrifuged whole blood sample, and adding the mixed whole blood sample to the magnetic bead reaction cup; transferring the magnetic bead reaction cup with the added whole blood sample to the reagent addition position, adding whole blood reagent to the reagent addition position, transferring the magnetic bead reaction cup with the added whole blood reagent to the magnetic bead detection position; transferring the magnetic bead reaction cup with the added mixed whole blood sample to the magnetic bead detection position, and using the magnetic bead method to perform the test and collect the magnetic bead oscillation waveform data.

[0057] When the tests to be performed include more than just Type I elastography, it indicates that other tests are required. These other tests often require plasma samples. Therefore, to ensure that both Type I and other tests can be performed using the same sample, centrifuged whole blood is provided, with plasma as the supernatant. For other tests, the plasma supernatant is used. For Type I elastography, the centrifuged whole blood is first mixed, and then the mixed whole blood sample is used. When both tests are performed simultaneously, since a centrifuged whole blood sample is provided, the tests requiring plasma are performed first. This involves first collecting the plasma sample, then mixing it, and finally collecting the mixed whole blood sample. This saves time and reduces the physical and financial burden on patients and medical staff caused by repeated blood draws for multiple tests.

[0058] In one embodiment, when the test item includes a second type of elastography test, the magnetic bead method is used to test the sample and obtain magnetic bead oscillation waveform data. This includes: controlling the sampling needle to draw up a plasma sample and add it to a magnetic bead reaction cup; transferring the magnetic bead reaction cup with the added plasma sample to a reagent addition position; adding plasma reagent to the reagent addition position; transferring the magnetic bead reaction cup with the added plasma reagent to a magnetic bead detection position; and using the magnetic bead method to test the plasma sample at the magnetic bead detection position to collect magnetic bead oscillation waveform data.

[0059] The second type of elastography uses plasma samples, and other tests (such as the four coagulation tests) also primarily use plasma samples. Therefore, regardless of whether the test includes other tests besides the second type of elastography, plasma samples are always used. Similarly, the plasma sample is tested using the magnetic bead method to obtain the corresponding magnetic bead oscillation waveform data.

[0060] In one embodiment, the above-mentioned elastogram detection method based on magnetic beads further includes: when the item to be detected does not include elastogram detection, controlling the sampling needle to draw plasma into the reaction cup, and transferring the reaction cup after adding the sample to the detection position, which is a magnetic bead detection position or an optical detection position.

[0061] In addition to detecting items that include elastography, this sample analyzer can also perform tests that do not include elastography, such as the standard coagulation panel. In other words, this sample analyzer can perform both standard coagulation panel and elastography tests. The analysis method employed by this sample analyzer can utilize both magnetic bead and optical methods; that is, the analyzer has both magnetic bead and optical method detection channels. It should be noted that a coagulation activator must be added to the sample before performing magnetic bead or optical method tests to initiate a coagulation reaction. This is fundamental to sample testing and will not be elaborated upon here.

[0062] In one embodiment, when the items to be tested include both elastography and optical testing, the method further includes: controlling the sampling needle to draw a sample into an optical reaction cup; transferring the optical reaction cup with the sample added to an optical detection position; and using optical methods to test the sample at the optical detection position.

[0063] When the tests include both elastography and optical testing, the optical tests require adding the sample to an optical reaction cup and then performing optical testing at the optical detection site. In other words, multiple tests can be performed using the same method or different methods.

[0064] In one embodiment, when the items to be tested include more than just elastography, the method further includes: obtaining the test results of other items besides elastography; and generating a test report based on the test results of other items and thromboelastography.

[0065] In order to comprehensively reflect the coagulation status, the test results of multiple tests are combined into a single test report. For example, the coagulation four items and the elastography test are combined into one test report for doctors' reference.

[0066] like Figure 3The diagram illustrates the detection process of a sample analyzer (e.g., a coagulation analyzer) implementing the above-described thromboelastography detection method based on the magnetic bead method in one embodiment. First, the coagulation test sample (centrifuged whole blood) is placed in the sample position. Then, the barcode is scanned to obtain the test item. It is determined whether any test item requires plasma. If not, the centrifuged whole blood is remixed using vibration or suction, and then the whole blood is drawn into a magnetic bead reaction cup and transferred to the magnetic bead detection position for magnetic bead detection. Magnetic bead oscillation waveform data is collected, thus obtaining the first type of thromboelastography. If plasma is required, the sampling needle is controlled to draw plasma, which is then transferred to the detection module (including magnetic bead detection and optical detection). Depending on the type of test item, the detection module uses either the magnetic bead method or the optical method for detection (if the second type of elastography detection is included, the magnetic bead method is used to obtain the second type of thromboelastography). Then, it is determined whether there are any items that require whole blood testing (Type I thromboelastography testing) in the test items. If so, the centrifuged whole blood is remixed into whole blood by vibration or suction. Then, the whole blood is drawn into the magnetic bead reaction cup and transferred to the magnetic bead detection position for magnetic bead detection. The magnetic bead oscillation waveform data is collected, and then the Type I thromboelastography is obtained.

[0067] like Figure 4 As shown, a method for generating thromboelastography based on magnetic beads is proposed. This method includes:

[0068] Step 402: Obtain the magnetic bead oscillation waveform data obtained based on the magnetic bead method.

[0069] The magnetic bead method involves placing a magnetic bead (which can be pre-placed in the test cup or added during the test; the test cup can also be sealed) in a test cup (reaction cup). At the test position, a set of driving coils and a set of receiving coils on both sides of the test cup generate a constant, alternating electromagnetic field, causing a specially designed demagnetized steel bead inside the test cup to maintain a constant amplitude oscillation. After the addition of a coagulation activator, as fibrin production increases, plasma viscosity increases, and the amplitude of the steel bead's movement gradually weakens. The instrument collects the changes in the steel bead's movement based on the sensing of these changes by another set of measuring coils, obtaining the magnetic bead oscillation waveform data.

[0070] Step 404: Based on the magnetic bead oscillation waveform data, perform conversion calculations to obtain the thromboelastography.

[0071] One method involves converting the magnetic bead oscillation waveform data to generate a thromboelastography map. There are several methods for converting and calculating using magnetic bead oscillation waveform data.

[0072] In one embodiment, the transformation calculation can be performed as follows: First, the first derivative of the magnetic bead oscillation waveform data is obtained to obtain the first derivative graphic data. Then, the first derivative graphic data is differentiated again to obtain the second derivative graphic data. Based on the second derivative graphic data, the peaks and troughs of the first derivative graphic data are determined. Then, the peak baseline and trough baseline are extracted. Based on the peak baseline and trough baseline, an inverse transformation is performed to obtain the initial elasticity map. Then, a fitting calculation is performed to draw the thromboelastography map.

[0073] In another embodiment, the transformation calculation can also be performed as follows: first, the magnetic bead oscillation waveform data is inversely transformed to obtain the inversely transformed magnetic bead oscillation waveform data; then, the first-order derivative and second-order derivative of the transformed magnetic bead oscillation waveform data are performed; based on the second-order derivative, the peak and trough of the first-order derivative are determined; the peak baseline and trough baseline are extracted; and then, the fitting calculation is performed to obtain the thromboelastography map.

[0074] The aforementioned method for generating thromboelastography based on the magnetic bead method can obtain the thromboelastography map by converting and calculating the oscillation waveform data of the magnetic beads. This method does not require a dedicated thromboelastography instrument and can be implemented using existing sample analyzers. The magnetic bead method is a common detection method in sample analyzers. Only the corresponding conversion and calculation method needs to be added to the sample analyzer to generate the thromboelastography map. This method not only greatly reduces costs but also significantly improves timeliness due to the simplicity of the detection method.

[0075] like Figure 5 As shown, in one embodiment, step 404, which involves converting and calculating data based on the magnetic bead oscillation waveform to obtain the thromboelastography, includes:

[0076] Step 404A: Calculate the peak baseline and trough baseline of the first derivative based on the oscillation waveform data of the magnetic bead.

[0077] The first-order derivative peak baseline refers to the peak baseline in the first-order derivative graphical data obtained by taking the first derivative of the magnetic bead oscillation waveform data. The peak baseline is a line composed of multiple extracted peaks, i.e., a straight line connecting multiple peaks. The first-order derivative trough baseline refers to the trough baseline in the first-order derivative graphical data obtained by taking the first derivative of the magnetic bead oscillation waveform data. The trough baseline is a line composed of multiple extracted troughs, i.e., a straight line connecting multiple troughs. As can be seen from the above, thromboelastography is divided into type I thromboelastography and type II thromboelastography, which are thromboelastography obtained based on whole blood and plasma, respectively.

[0078] The following example, using a type II thromboelastography (TEE) of a plasma sample, illustrates the entire calculation process of the thromboelastography. Figure 6The image shown is a graphical representation of the oscillation waveform data of the collected magnetic beads. Figure 7 The image shown is a graphical representation of the first-order derivative obtained by taking the first-order derivative of the oscillation waveform data of the magnetic bead. Figure 8 The figure shows a schematic diagram of the peak and trough baselines obtained based on the first-order derivative graphical data.

[0079] Step 404B: Obtain the initial elasticity diagram by performing an inverse transformation based on the peak and trough baselines of the first-order derivative.

[0080] Among them, such as Figure 9 As shown, the initial elasticity map is obtained by inversely transforming the peak and trough baselines of the first-order derivative relative to the zero baseline. From Figure 9 The signal can be emitted, and after inverse transformation, the original peak baseline and trough baseline become 0 baseline, and then the 0 baseline after the peak baseline and trough baseline becomes the original peak baseline and trough baseline.

[0081] Step 404C: Fit the initial elasticity map to obtain the thromboelastography map.

[0082] Among them, such as Figure 10 The image shown is the thromboelastography map obtained after fitting. Figure 9 The initial elasticity map obtained is not a smooth curve. Therefore, to obtain a smooth curve, the initial elasticity map is fitted to obtain a smoothed thromboelastography map. The initial elasticity map can be fitted using four-parameter fitting, three-parameter fitting, or five-parameter fitting.

[0083] Thromboelastography (TEG) was obtained through the conversion and calculation of the aforementioned magnetic bead oscillation waveform data, realizing the function of detecting TEG using the magnetic bead method. This not only reduces costs but also improves the timeliness of detection. Furthermore, existing sample analyzers often have multiple channels capable of simultaneous detection, further enhancing the efficiency of detecting multiple samples. In addition, using the magnetic bead method for TEG detection allows for the simultaneous testing of multiple items to generate a single report; for example, the magnetic bead method can be used to detect coagulation parameters while simultaneously performing TEG detection.

[0084] like Figure 11 As shown, in one embodiment, the peak baseline and trough baseline of the first derivative are calculated based on the oscillation waveform data of the magnetic bead, including:

[0085] Step 1102: Perform first-order differentiation on the magnetic bead oscillation waveform data to obtain first-order derivative graphical data.

[0086] Among them, reference Figure 6 The image shown is a graphical schematic diagram of the oscillation waveform data of a magnetic bead in one embodiment. (Refer to...)Figure 7 This is the first-order derivative graphical data obtained by taking the first-order derivative of the oscillation waveform data of the magnetic bead.

[0087] Step 1104: Differentiate the first-order derivative graphical data to obtain the second-order derivative graphical data.

[0088] In order to obtain the peak and trough data in the first-order derivative graph data, the second-order derivative graph data is obtained by taking the derivative again based on the first-order derivative graph data.

[0089] Step 1106: Determine multiple peaks and multiple troughs in the first-order derivative graph data based on the second-order derivative graph data.

[0090] Specifically, the peaks and troughs in the first-order derivative graph data are determined using the extremum method based on the second-order derivative graph data. The maxima in the second-order derivative graph data are taken as troughs, and the minima are taken as peaks.

[0091] Step 1108: Determine the peak baseline of the first derivative based on multiple peaks, and determine the trough baseline of the first derivative based on multiple troughs.

[0092] Among them, after determining multiple peaks and troughs, the peak baseline is further determined based on the multiple peaks, and the trough baseline is further determined based on the multiple troughs.

[0093] The above process demonstrates how to determine the peak and trough baselines of the first derivative based on the second-order obtained graphical data. This method is simple to calculate and does not require complex calculations to determine the peak and trough baselines, thus improving the efficiency of thromboelastography generation.

[0094] In one embodiment, determining the peak baseline of the first derivative based on multiple peaks and the trough baseline of the first derivative based on multiple troughs includes: determining the endpoint of the peak baseline of the first derivative and extracting the peak baseline of the first derivative based on the endpoint of the peak baseline of the first derivative; determining the endpoint of the trough baseline of the first derivative and extracting the trough baseline of the first derivative based on the endpoint of the trough baseline of the first derivative.

[0095] Extracting the peak baseline essentially involves determining its endpoint, since the starting point is already determined—the position of the first peak. Similarly, extracting the trough baseline also involves determining its endpoint, with the starting point being the position of the first trough. Determining the endpoints of the peak and trough baselines is crucial. Not all peak data obtained using the second-order derivative graphs mentioned above falls within the baseline range. After adding coagulation reagent, during the detection process, as the coagulation reaction occurs, the amplitude of the magnetic bead oscillation data decreases. After the coagulation time is reached, the amplitude becomes very small. Peaks and troughs after the coagulation time are not within the range for peak and trough baseline extraction. Therefore, it is necessary to find the endpoint of the peak and trough baselines, which corresponds to the coagulation time; that is, to find the coagulation time reached by the sample for baseline extraction.

[0096] In one embodiment, determining the endpoint of the first derivative peak baseline and extracting the first derivative peak baseline based on the endpoint of the first derivative peak baseline includes: calculating the mean of the first N peaks; when the value of the (N+1)th peak is less than a preset proportion of the mean of the first N peaks, the first N+1 peaks are taken as the endpoint of the first derivative peak baseline; and extracting the first derivative peak baseline based on the endpoint and starting point of the first derivative peak baseline, wherein the starting point of the first derivative peak baseline refers to the position of the first peak in the first derivative graph.

[0097] The determination of the endpoint of the peak baseline requires dynamic calculation. The average of the first two peaks is calculated sequentially, from smallest to largest N. The value of the third peak is compared with the average of the first two peaks. If the value of the third peak is not less than a preset percentage (e.g., 98%) of the average of the first two peaks, the average of the first three peaks is calculated again. Then, the value of the fourth peak is checked to see if it meets the above condition. This process continues until the value of the (N+1)th peak is found to be less than a preset percentage of the average of the first N peaks. The (N+1)th peak is then taken as the endpoint of the first-order derivative peak baseline. (Reference) Figure 8 The upper part is the extracted peak baseline.

[0098] In one embodiment, determining the endpoint of the first derivative's valley baseline and extracting the first derivative's valley baseline based on the endpoint of the first derivative's valley baseline includes: calculating the mean of the absolute values ​​of the first N valleys; when the absolute value of the (N+1)th valley is less than a preset proportion of the mean of the absolute values ​​of the first N valleys, the (N+1)th valley is taken as the endpoint of the first derivative's valley baseline; and extracting the first derivative's valley baseline based on the endpoint and starting point of the first derivative's valley baseline, wherein the starting point of the first derivative's valley baseline refers to the position of the first valley in the first derivative graph.

[0099] The determination of the endpoint of the trough baseline requires dynamic calculation. The average of the first two troughs is calculated sequentially, starting with the smallest N value. The value of the third trough is compared to the average of the first two troughs. If the value of the third trough is not less than a preset percentage (e.g., 98%) of the average of the first two troughs, the average of the first three troughs is calculated again. Then, the value of the fourth trough is checked to see if it meets the above condition. This process is repeated until the value of the (N+1)th trough is found to be less than a preset percentage of the average of the first N troughs. The (N+1)th trough is then taken as the endpoint of the first-order derivative trough baseline. (Reference) Figure 8 The lower part is the extracted trough baseline.

[0100] In one embodiment, determining the endpoint of the peak baseline of the first derivative and extracting the peak baseline of the first derivative based on the endpoint of the peak baseline of the first derivative includes: differentiating multiple peaks of the first derivative and taking the point with the fastest rate change as the endpoint of the peak baseline of the first derivative; differentiating multiple troughs of the first derivative and taking the point with the fastest rate change as the endpoint of the trough baseline of the first derivative.

[0101] During the detection process, as the coagulation reaction occurs, the amplitude of the magnetic bead oscillation data will become smaller and smaller. When the coagulation time is reached, the amplitude will suddenly become very small. Therefore, we can differentiate the multiple peaks of the first derivative and take the point with the fastest rate change as the endpoint of the peak baseline of the first derivative. Similarly, we can differentiate the multiple troughs of the first derivative and take the point with the fastest rate change as the endpoint of the trough baseline of the first derivative.

[0102] In one embodiment, the method of obtaining first-order derivative graphic data by performing first-order derivative on the magnetic bead oscillation waveform data includes: determining the amplitude pattern of the magnetic bead oscillation based on the magnetic bead oscillation waveform data; and performing first-order derivative on the amplitude pattern to obtain first-order derivative graphic data.

[0103] Before performing the first derivative, the amplitude graph of the magnetic bead oscillation waveform data is determined, that is, the magnetic bead oscillation waveform data is represented in the form of an amplitude graph. Then, the first derivative of the amplitude graph is performed to determine the first derivative graph data obtained after the derivative is obtained.

[0104] In one embodiment, fitting the initial elasticity map to obtain a thromboelastography map includes: fitting the initial elasticity map using a four-parameter fitting method to obtain the thromboelastography map, wherein the four parameters in the four-parameter fitting method are obtained experimentally.

[0105] The four-parameter fitting formula is as follows: F(x)=D+(AD) / (1+(x / C)^B), where A, B, C, and D are the four parameters, which are empirical values ​​obtained through experiments. x represents the independent variable (the coordinates of a point on the elasticity map), and F(x) represents the fitted result. The thromboelastography obtained by fitting the initial elasticity map with four parameters is smoother and closer to the actual situation, meaning the detection results are more accurate.

[0106] In addition, the magnetic bead method can also be used to detect heparinase. Traditional heparinase comparative testing is based on thromboelastography (TEG). This involves simultaneously testing the same whole blood sample using both a standard cup and a heparinase cup. The heparinase cup contains heparinase, which degrades heparin in the blood, unaffected by residual heparin. The standard cup does not contain heparinase. Kaolin is added to both samples to activate the coagulation process, and TEG records the clotting time (R time). The elastography curves from the standard cup and the heparinase cup are overlaid and compared. If they are similar, it indicates no heparin effect in the body, or that heparin treatment has not been effective. If the R time is significantly prolonged in the group without heparinase, it indicates that residual heparin in the body is affecting the coagulation process, or that resistance exists. Traditional heparinase comparative testing requires a specialized thromboelastography instrument, resulting in high costs. Furthermore, thromboelastography is slow and lacks timeliness, failing to meet the high-time requirements of emergency situations. Therefore, using the magnetic bead method for heparinase detection can solve the above problems, which not only improves timeliness but also greatly saves detection costs.

[0107] like Figure 12 As shown, a heparinase detection method based on magnetic beads is proposed and applied to a sample analyzer. The method includes:

[0108] Step 1202: The magnetic bead method is used to detect the sample containing heparinase. The first coagulation time corresponding to the sample with added heparinase is determined based on the collected first magnetic bead oscillation waveform data.

[0109] In one embodiment, a magnetic bead method is used to detect samples containing heparinase, an elasticity map is plotted based on the oscillation waveform data of the first magnetic bead, and the corresponding first clotting time is determined based on the elasticity map.

[0110] In another embodiment, it is not necessary to draw an elasticity diagram. Instead, the coagulation time point can be found directly by calculating based on the oscillation waveform data of the first magnetic bead, and then the corresponding first coagulation time can be determined.

[0111] The magnetic bead method for detecting heparinase allows for the use of either plasma or whole blood samples, providing greater flexibility and variety compared to traditional methods that only allow whole blood.

[0112] Step 1204: The magnetic bead method is used to test the samples that do not contain heparinase. The second coagulation time corresponding to the samples without heparinase is determined based on the collected second magnetic bead oscillation waveform data.

[0113] In this embodiment, as a comparison with heparinase detection, a magnetic bead method is used to detect samples that do not contain heparinase. An elasticity map or similar elasticity map is plotted based on the oscillation waveform data of the second magnetic bead, and the corresponding second clotting time is determined based on the elasticity map. In another embodiment, it is not necessary to plot an elasticity map; the clotting time point can also be found by calculation based on the oscillation waveform data of the second magnetic bead, i.e., the second clotting time can be determined.

[0114] It should be noted that the order of steps 1202 and 1204 can be interchanged, and they can also be performed simultaneously.

[0115] Step 1206: Determine the test result based on the first coagulation time and the second coagulation time.

[0116] Among them, comparing the first coagulation time and the second coagulation time, if they are similar, it means that there is no heparin effect in the body, or that heparin has not yet taken effect; if the coagulation time is significantly prolonged in the group without heparinase, it means that residual heparin in the body affects the coagulation process, or there is resistance, etc.

[0117] The aforementioned heparinase detection method based on magnetic beads uses magnetic beads to detect samples containing heparinase and samples without heparinase, respectively. It collects first and second magnetic bead oscillation waveform data. Then, it determines the first clotting time based on the first magnetic bead oscillation waveform data and the second clotting time based on the second magnetic bead oscillation waveform data. Finally, it compares the first and second clotting times to determine the detection result. This method does not require a dedicated thromboelastography instrument; it can be implemented using existing sample analyzers. The magnetic bead method is a common detection method in sample analyzers. Only the calculation method for determining the clotting time based on the magnetic bead oscillation waveform data needs to be added to the sample analyzer. This method not only significantly reduces costs but also greatly improves timeliness due to its simplicity.

[0118] In one embodiment, a magnetic bead method is used to detect samples containing heparinase, and the first clotting time corresponding to the sample containing heparinase is determined based on the collected first magnetic bead oscillation waveform data, including: plotting an image based on the first magnetic bead oscillation waveform data to obtain a first thromboelastography; and determining the corresponding first clotting time based on the first thromboelastography.

[0119] The magnetic bead method was used to detect samples that did not contain heparinase. The second coagulation time corresponding to the sample without heparinase was determined based on the collected second magnetic bead oscillation waveform data. This included: plotting the second magnetic bead oscillation waveform data to obtain a second thromboelastography; and determining the corresponding second coagulation time based on the second thromboelastography.

[0120] To determine clotting time, a thromboelastography (TEE) method is used. This involves plotting the TEE based on the waveform data of the magnetic bead oscillations, and then determining the corresponding clotting time based on the plotted TEE. Figure 13 The diagram shown is a schematic of a thromboelastography in one embodiment. Based on the characteristics of the thromboelastography, the clotting time can be determined from the diagram.

[0121] In one embodiment, a magnetic bead method is used to detect a sample containing heparinase. The first clotting time corresponding to the sample containing heparinase is determined based on the acquired first magnetic bead oscillation waveform data. This includes: controlling the sampling needle to aspirate the sample into a first magnetic bead reaction vessel; transferring the first magnetic bead reaction vessel to a reagent addition position; adding heparinase and a coagulation activator to the first magnetic bead reaction vessel at the reagent addition position; detecting the sample using the magnetic bead method at the magnetic bead detection position to acquire the first magnetic bead oscillation waveform data; and determining the corresponding first clotting time based on the first magnetic bead oscillation waveform data.

[0122] The magnetic bead method was used to detect samples that did not contain heparinase. The second coagulation time corresponding to the sample without heparinase was determined based on the collected second magnetic bead oscillation waveform data. The process included: controlling the sampling needle to aspirate the sample into the first magnetic bead reaction cup; transferring the first magnetic bead reaction cup to the reagent addition position; adding only the coagulation activator to the first magnetic bead reaction cup at the reagent addition position; detecting the sample using the magnetic bead method at the magnetic bead detection position and collecting the second magnetic bead oscillation waveform data; and determining the corresponding second coagulation time based on the second magnetic bead oscillation waveform data.

[0123] For comparison, the same sample was added to both the first and second magnetic bead reaction cups. Heparinase and a coagulation activator were added to the first cup, while only the coagulation activator was added to the second cup. Kaolin or similar materials can be used as the coagulation activator. After the reagents were added, as fibrin production increased, plasma viscosity increased, and the amplitude of the small steel beads' movement gradually decreased. The instrument, based on changes in the small steel bead movement sensed by another set of measuring coils, used software to convert the magnetic bead motion pattern into a thromboelastography-like pattern, comparing the coagulation time of the cups with and without heparinase.

[0124] In one embodiment, adding heparinase and coagulation activator to the first magnetic bead reaction vessel at the reagent addition site includes: adding heparinase to the first magnetic bead reaction vessel at the reagent addition site and mixing and incubating; adding coagulation activator to the first magnetic bead reaction vessel after mixing and incubation.

[0125] Among them, the magnetic bead method for heparinase detection can use ordinary magnetic bead reaction cups, which is more convenient and cost-effective than the traditional method that requires special heparinase cups.

[0126] When performing heparinase testing, there is a specific order in which heparinase and coagulation activator are added. Heparinase is added first, and after mixing and incubation, the coagulation activator is added. This is because the coagulation reaction begins after the coagulation activator is added, and the coagulation activator is added later to facilitate timely detection of coagulation changes.

[0127] In one embodiment, the sample analyzer includes multi-channel detection and uses a magnetic bead method to perform parallel detection of samples with added heparinase and samples without added heparinase.

[0128] The sample analyzer includes multi-channel detection. To accelerate the detection speed, samples with added heparinase and samples without added heparinase are detected in parallel.

[0129] In one embodiment, the sample is plasma or whole blood.

[0130] The sample used for heparinase detection can be either plasma or whole blood, offering flexibility in selection. When using whole blood samples, the sample can be directly aspirated using a syringe for testing; that is, the sample provided from the beginning is whole blood. If a centrifuged whole blood sample is initially provided, it needs to be mixed thoroughly before aspirating the mixed whole blood sample.

[0131] In one embodiment, when the sample is whole blood, controlling the sampling needle to aspirate the sample and add it to the first magnetic bead reaction cup includes: controlling the sampling needle to mix the centrifuged whole blood sample and aspirating the mixed whole blood sample into the first magnetic bead reaction cup; controlling the sampling needle to aspirate the sample and add it to the second magnetic bead reaction cup includes: controlling the sampling needle to mix the centrifuged whole blood sample and aspirating the mixed whole blood sample into the second magnetic bead reaction cup.

[0132] If a centrifuged whole blood sample is provided, it needs to be mixed before aspiration to obtain a whole blood sample.

[0133] like Figure 14 As shown, in one embodiment, a thromboelastography detection device based on the magnetic bead method is proposed, the device comprising:

[0134] The detection module 1402 is used to detect the sample using the magnetic bead method when the item to be detected includes elasticity map detection, and to obtain magnetic bead oscillation waveform data.

[0135] The generation module 1404 is used to draw an elasticity map based on the magnetic bead oscillation waveform data to generate a thrombus elasticity map.

[0136] In one embodiment, when the elastogram detection included in the test item is a first type of elastogram detection, the sample is a whole blood sample, and the thromboelastogram is a first type of thromboelastogram; when the elastogram detection included in the test item is a second type of elastogram detection, the sample is a plasma sample, and the thromboelastogram is a second type of thromboelastogram.

[0137] In one embodiment, when the test item only includes the first type of elastogram detection, the detection module 1402 is further configured to control the sampling needle to mix the centrifuged whole blood sample, aspirate the mixed whole blood sample and add it to the magnetic bead reaction cup; transfer the magnetic bead reaction cup with the added whole blood sample to the reagent addition position, add whole blood reagent to the reagent addition position, transfer the magnetic bead reaction cup with the added whole blood reagent to the magnetic bead detection position; transfer the magnetic bead reaction cup with the added mixed whole blood sample to the magnetic bead detection position, perform detection using the magnetic bead method, and acquire the magnetic bead oscillation waveform data.

[0138] In one embodiment, when the test item includes more than just the first type of elastogram detection, the detection module 1402 is further configured to control the sampling needle to mix the centrifuged whole blood sample, aspirate the mixed whole blood sample and add it to the magnetic bead reaction cup; transfer the magnetic bead reaction cup with the added whole blood sample to the reagent addition position, add whole blood reagent to the reagent addition position, transfer the magnetic bead reaction cup with the added whole blood reagent to the magnetic bead detection position; transfer the magnetic bead reaction cup with the added mixed whole blood sample to the magnetic bead detection position, perform detection using the magnetic bead method, and acquire the magnetic bead oscillation waveform data.

[0139] In one embodiment, when the item to be tested includes a second type of elastogram detection, the detection module 1402 is further configured to control the sampling needle to draw up a plasma sample and add it to the magnetic bead reaction cup, transfer the magnetic bead reaction cup after adding the plasma sample to the reagent addition position, add plasma reagent to the reagent addition position, transfer the magnetic bead reaction cup after adding the plasma reagent to the magnetic bead detection position, and use the magnetic bead method to detect the plasma sample at the magnetic bead detection position to collect magnetic bead oscillation waveform data.

[0140] In one embodiment, the detection module is further configured to control the sampling needle to draw plasma into the reaction cup and transfer the reaction cup after adding the sample to the detection position when the elastogram detection is not included in the test items, wherein the detection position is a magnetic bead detection position or an optical detection position.

[0141] In one embodiment, when the items to be tested include both elastogram testing and optical testing, the detection module is further configured to control the sampling needle to draw a sample into an optical reaction cup; transfer the optical reaction cup after adding the sample to an optical detection position; and use optical methods to detect the sample at the optical detection position.

[0142] In one embodiment, when the items to be tested include more than just the elastogram detection, the device further includes: a merging module, used to obtain the detection results of other items besides the elastogram detection, and generate a detection report based on the detection results of the other items and the thromboelastogram.

[0143] In one embodiment, the generation module is further configured to determine the peak baseline and trough baseline of the first derivative based on the magnetic bead oscillation waveform data; perform inverse transformation based on the peak baseline and trough baseline of the first derivative to obtain an initial elasticity map; and perform fitting processing on the initial elasticity map to obtain the thromboelastography map.

[0144] In one embodiment, the generation module is further configured to perform first-order differentiation on the amplitude graph to obtain a first-order derivative graph; perform second-order differentiation on the first-order derivative graph to obtain a second-order derivative graph; determine multiple peaks and multiple troughs in the first-order derivative graph based on the second-order derivative graph; determine the peak baseline of the first-order derivative based on the multiple peaks; and determine the trough baseline of the first-order derivative based on the multiple troughs.

[0145] In one embodiment, the generation module is further configured to determine the endpoint of the peak baseline of the first-order derivative, and extract the peak baseline of the first-order derivative based on the endpoint of the peak baseline of the first-order derivative; determine the endpoint of the trough baseline of the first-order derivative, and extract the trough baseline of the first-order derivative based on the endpoint of the trough baseline of the first-order derivative.

[0146] like Figure 15 As shown, a thromboelastography generation device based on the magnetic bead method is proposed. The device includes:

[0147] The acquisition module 1502 is used to acquire the magnetic bead oscillation waveform data detected based on the magnetic bead method;

[0148] The calculation module 1504 is used to perform conversion calculations based on the oscillation waveform data of the magnetic bead to obtain the thromboelastography.

[0149] like Figure 16As shown, in one embodiment, the computing module 1504 includes:

[0150] The baseline calculation module 1504A is used to calculate the peak baseline and trough baseline of the first derivative based on the oscillation waveform data of the magnetic bead;

[0151] The inverse transformation module 1504B is used to perform an inverse transformation based on the peak baseline and trough baseline of the first-order derivative to obtain the initial elasticity map.

[0152] The fitting module 1504C is used to perform fitting processing on the initial elasticity map to obtain the thromboelastography map.

[0153] In one embodiment, the baseline calculation module is further configured to perform first-order differentiation on the magnetic bead oscillation waveform data to obtain first-order derivative graphical data; perform second-order differentiation on the first-order derivative graphical data to obtain second-order derivative graphical data; determine multiple peaks and multiple troughs in the first-order derivative graphical data based on the second-order derivative graphical data; determine the peak baseline of the first-order derivative based on the multiple peaks; and determine the trough baseline of the first-order derivative based on the multiple troughs.

[0154] In one embodiment, the baseline calculation module is further configured to determine the endpoint of the peak baseline of the first derivative, extract the peak baseline of the first derivative based on the endpoint of the peak baseline of the first derivative; determine the endpoint of the trough baseline of the first derivative, extract the trough baseline of the first derivative based on the endpoint of the trough baseline of the first derivative.

[0155] In one embodiment, the baseline calculation module is further used to calculate the mean of the first N peaks. When the value of the (N+1)th peak is less than a preset proportion of the mean of the first N peaks, the (N+1)th peak is taken as the endpoint of the peak baseline of the first derivative, where N is a positive integer. The peak baseline of the first derivative is extracted based on the endpoint and the starting point of the peak baseline of the first derivative. The starting point of the peak baseline of the first derivative refers to the position of the first peak in the first derivative graph.

[0156] The baseline calculation module is also used to calculate the mean of the absolute values ​​of the first N troughs. When the absolute value of the (N+1)th trough is less than a preset proportion of the mean of the absolute values ​​of the first N troughs, the (N+1)th trough is taken as the endpoint of the first derivative trough baseline, where N is a positive integer. The first derivative trough baseline is extracted based on the endpoint and starting point of the first derivative trough baseline. The starting point of the first derivative trough baseline refers to the position of the first trough in the first derivative graph.

[0157] In one embodiment, the baseline calculation module is further configured to differentiate the multiple peaks of the first derivative and take the point with the fastest rate of change as the endpoint of the peak baseline of the first derivative; and to differentiate the multiple troughs of the first derivative and take the point with the fastest rate of change as the endpoint of the trough baseline of the first derivative.

[0158] In one embodiment, the baseline calculation module is further configured to determine the amplitude pattern of the magnetic bead's oscillation based on the magnetic bead oscillation waveform data; and to obtain the first-order derivative pattern data by performing a first-order derivative on the amplitude pattern.

[0159] In one embodiment, the fitting module is further configured to use a four-parameter fitting method to fit the initial elastic map to obtain the thromboelastography, wherein the four parameters in the four-parameter fitting method are obtained experimentally.

[0160] like Figure 17 As shown, in one embodiment, a heparinase detection device based on magnetic beads is proposed for use in a sample analyzer. The device includes:

[0161] The first detection module 1702 is used to detect samples containing heparinase using the magnetic bead method, and to determine the first coagulation time corresponding to the sample containing heparinase based on the collected first magnetic bead oscillation waveform data.

[0162] The second detection module 1704 is used as a comparison to detect samples without heparinase using the magnetic bead method. The second coagulation time corresponding to the sample without heparinase is determined based on the collected second magnetic bead oscillation waveform data.

[0163] The determination module 1706 is used to determine the test result based on the first coagulation time and the second coagulation time.

[0164] In one embodiment, the first detection module 1702 is further configured to draw an image based on the oscillation waveform data of the first magnetic bead to obtain a first thromboelastography; and determine the corresponding first clotting time based on the first thromboelastography.

[0165] The second detection module 1704 is also used to draw an image based on the oscillation waveform data of the second magnetic bead to obtain a second thromboelastography; and to determine the corresponding second coagulation time based on the second thromboelastography.

[0166] In one embodiment, the first detection module is further configured to control the sampling needle to draw a sample into a first magnetic bead reaction cup, transfer the first magnetic bead reaction cup to a reagent addition position, add heparinase and coagulation activator to the first magnetic bead reaction cup at the reagent addition position, detect the sample using the magnetic bead method at the magnetic bead detection position, and acquire the first magnetic bead oscillation waveform data; determine the corresponding first coagulation time based on the first magnetic bead oscillation waveform data;

[0167] The second detection module is also used to control the sampling needle to draw the sample and add it to the first magnetic bead reaction cup, transfer the first magnetic bead reaction cup to the reagent addition position, and add only the coagulation activator to the first magnetic bead reaction cup at the reagent addition position; detect the sample using the magnetic bead method at the magnetic bead detection position and collect the second magnetic bead oscillation waveform data; and determine the corresponding second coagulation time based on the second magnetic bead oscillation waveform data.

[0168] In one embodiment, the first detection module is further configured to add the heparinase to the first magnetic bead reaction cup at the reagent addition position and perform mixing and incubation; and add the coagulation activator to the first magnetic bead reaction cup after mixing and incubation.

[0169] In one embodiment, the sample analyzer includes multi-channel detection, and the magnetic bead method is used to perform parallel detection on samples with added heparinase and samples without added heparinase.

[0170] In one embodiment, the sample is plasma or whole blood.

[0171] In one embodiment, when the sample is whole blood, the first detection module is further configured to control the sampling needle to mix the centrifuged whole blood sample and add the mixed whole blood sample to the first magnetic bead reaction cup; the second detection module is further configured to control the sampling needle to mix the centrifuged whole blood sample and add the mixed whole blood sample to the second magnetic bead reaction cup.

[0172] In one embodiment, the first detection module is further configured to determine the peak baseline and trough baseline of the first derivative based on the oscillation waveform data of the first magnetic bead; perform inverse transformation based on the peak baseline and trough baseline of the first derivative to obtain an initial elasticity map; and perform fitting processing on the initial elasticity map to obtain the first thromboelastography map.

[0173] The second detection module is also used to determine the peak baseline and trough baseline of the first-order guide based on the oscillation waveform data of the second magnetic bead; to perform an inverse transformation based on the peak baseline and trough baseline of the first-order guide to obtain an initial elasticity map; and to perform fitting processing on the initial elasticity map to obtain the second thromboelastography map.

[0174] Figure 18An internal structural diagram of a sample analyzer in one embodiment is shown. Figure 18 As shown, the sample analyzer includes a processor, a magnetic bead detection module, and a memory connected via a system bus. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and may also store a computer program. When executed by the processor, this computer program enables the processor to implement the aforementioned magnetic bead-based thromboelastography detection method, magnetic bead-based thromboelastography generation method, or magnetic bead-based heparinase detection method. The internal memory may also store a computer program. When executed by the processor, this computer program enables the processor to implement the aforementioned magnetic bead-based thromboelastography detection method, magnetic bead-based thromboelastography generation method, or magnetic bead-based heparinase detection method. Those skilled in the art will understand that... Figure 18 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the sample analyzer to which the present application is applied. A specific sample analyzer may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0175] A computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the steps of the above-described thromboelastography detection method based on magnetic beads, or the thromboelastography generation method based on magnetic beads, or the heparinase detection method based on magnetic beads.

[0176] A sample analyzer includes a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the above-described thromboelastography detection method based on magnetic beads, the thromboelastography generation method based on magnetic beads, or the heparinase detection method based on magnetic beads.

[0177] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0178] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0179] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for generating thromboelastography based on magnetic beads, characterized in that, The method includes: Obtain the magnetic bead oscillation waveform data detected based on the magnetic bead method; The thromboelastography is obtained by performing conversion calculations based on the magnetic bead oscillation waveform data. The step of converting and calculating based on the magnetic bead oscillation waveform data to obtain the thromboelastography includes: calculating the peak baseline and trough baseline of the first derivative based on the magnetic bead oscillation waveform data; performing an inverse transformation based on the peak baseline and trough baseline of the first derivative to obtain an initial elasticity map; and fitting the initial elasticity map to obtain the thromboelastography. The step of calculating the peak and trough baselines of the first derivative based on the oscillation waveform data of the magnetic bead includes: performing first-order differentiation on the oscillation waveform data of the magnetic bead to obtain first-order derivative graphical data; performing second-order differentiation on the first-order derivative graphical data to obtain second-order derivative graphical data; determining multiple peaks and multiple troughs in the first-order derivative graphical data based on the second-order derivative graphical data; determining the peak baseline of the first derivative based on the multiple peaks; and determining the trough baseline of the first derivative based on the multiple troughs. The step of determining the peak baseline of the first derivative based on the plurality of peaks and the trough baseline of the first derivative based on the plurality of troughs includes: determining the endpoint of the peak baseline of the first derivative and extracting the peak baseline of the first derivative based on the endpoint of the peak baseline of the first derivative; determining the endpoint of the trough baseline of the first derivative and extracting the trough baseline of the first derivative based on the endpoint of the trough baseline of the first derivative. The process of determining the endpoint of the first-order derivative's peak baseline and extracting the first-order derivative's peak baseline based on the endpoint of the first-order derivative's peak baseline includes: Calculate the mean of the first N peaks. When the value of the (N+1)th peak is less than a preset proportion of the mean of the first N peaks, take the first (N+1)th peaks as the endpoint of the peak baseline of the first derivative, where N is a positive integer. Extract the peak baseline of the first derivative based on the endpoint and the starting point of the peak baseline of the first derivative. The starting point of the peak baseline of the first derivative refers to the position of the first peak in the first derivative graph. The step of determining the endpoint of the first-order derivative's trough baseline and extracting the first-order derivative's trough baseline based on the endpoint of the first-order derivative's trough baseline includes: Calculate the mean of the absolute values ​​of the first N troughs. When the absolute value of the (N+1)th trough is less than a preset proportion of the mean of the absolute values ​​of the first N troughs, the (N+1)th trough is taken as the endpoint of the trough baseline of the first derivative, where N is a positive integer. Extract the trough baseline of the first derivative based on the endpoint and the starting point of the trough baseline of the first derivative. The starting point of the trough baseline of the first derivative refers to the position of the first trough in the graph of the first derivative.

2. The method according to claim 1, characterized in that, The process of determining the endpoint of the first-order derivative's peak baseline and extracting the first-order derivative's peak baseline based on the endpoint of the first-order derivative's peak baseline includes: Differentiate the multiple peaks of the first derivative and take the point with the fastest rate of change as the endpoint of the peak baseline of the first derivative. Differentiate the multiple valleys of the first derivative and take the point with the fastest rate change as the endpoint of the valley baseline of the first derivative.

3. The method according to claim 1, characterized in that, The step of obtaining first-order derivative graphical data by taking the first-order derivative of the magnetic bead oscillation waveform data includes: The amplitude pattern of the magnetic bead's oscillation is determined based on the oscillation waveform data of the magnetic bead; The amplitude graph is differentiated by first order to obtain the first-order derivative graph data.

4. The method according to claim 1, characterized in that, The process of fitting the initial elasticity map to obtain the thromboelastography includes: The initial elasticity map was fitted using a four-parameter fitting method to obtain the thromboelastography map. The four parameters in the four-parameter fitting method were obtained experimentally.

5. A thromboelastography generation device based on magnetic beads, characterized in that, The apparatus includes a module for performing the steps of the thromboelastography generation method based on magnetic beads as described in any one of claims 1-4.

6. A computer-readable storage medium having a stored computer program, which, when executed by a processor, causes the processor to perform the steps of the thromboelastography generation method based on the magnetic bead method as described in any one of claims 1 to 4.

7. A sample analyzer, comprising a memory and a processor, the memory having a stored computer program, which, when executed by the processor, causes the processor to perform the steps of the thromboelastography generation method based on magnetic beads as described in any one of claims 1 to 4.

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