Blood coagulation time calculation method and coagulation analyzer

Abstract

An embodiment of the present invention discloses a blood coagulation time calculation method and a coagulation analyzer. By obtaining characteristic parameters of a blood sample, the characteristic parameters are used to evaluate the accuracy of the coagulation time obtained by processing the coagulation curve of the blood sample according to the derivative detection method; when the characteristic parameters meet the first characteristic condition, the coagulation time is obtained by processing the coagulation curve according to the derivative detection method; when the characteristic parameters meet the second characteristic condition, the coagulation curve is processed according to the derivative detection method and the threshold detection method respectively, and a weighted operation is performed on the processing results to obtain the coagulation time; and when the characteristic parameters meet the third characteristic condition, the coagulation curve is processed according to the threshold detection method to obtain the coagulation time. It can be seen that since the characteristic parameters can evaluate the accuracy of the coagulation time obtained by processing the coagulation curve of the blood sample according to the derivative detection method, different methods for processing the coagulation curve of the blood sample are selected according to the magnitude of the characteristic parameters, effectively improving the accuracy of the obtained blood coagulation time.

Description

Technical Field

[0001] The present invention relates to the technical field of blood testing, and particularly to a method for calculating blood coagulation time and a coagulation analyzer. Background Art

[0002] The optical coagulation method is a common method for detecting coagulation items, and is mainly divided into transmission turbidimetry and scattering turbidimetry according to different optical measurement principles. The basic principle of the optical method is: adding a detection reagent to the sample plasma and irradiating it with analysis light, and forming a coagulation curve according to the change in light flux or absorbance reflected during the coagulation process to determine the detection coagulation end point and calculate the coagulation time.

[0003] According to the waterfall effect theory of blood coagulation, within a period of time after adding the reagent, due to the cascade reaction of coagulation factors, the change in light flux is small at this time, forming the "baseline period" of the light flux. After fibrin rapidly forms large fibrin molecules, within a very short time, blood coagulation is completed, and at this time, it is manifested as a rapid increase in turbidity and absorbance. When the coagulation reaction ends, the light flux enters the "plateau period", and at this time, the change in light flux tends to be stable.

[0004] The existing technologies for determining the coagulation time through the coagulation curve include two types, the threshold detection method (also known as the percentage detection method) and the derivative detection method. The specific principles are as Figure 1 and Figure 2 shown, Figure 1 is a schematic diagram of calculating by the threshold detection method, Figure 2 is a schematic diagram of calculating by the derivative detection method; the threshold detection method defines the "baseline period" of the coagulation curve as 0% and the "plateau period" as 100% according to a certain detection standard, and calculates the position of a set percentage (such as 50%) to determine the coagulation time. The derivative detection method is to first perform differential processing (first-order differential or second-order differential, etc.) on the coagulation curve, and calculate the coagulation time through the main peak value of the differential curve. Among them, the corresponding position of the main peak value on the coagulation curve is the coagulation point, and the corresponding time is the coagulation time.

[0005] Although using the derivative detection method to calculate the coagulation time can obtain more clinical information for assisting clinical diagnosis compared with the threshold detection method. However, referring to Figure 3 , Figure 3 is a schematic diagram of the light flux curve and the first-order derivative curve of a strongly chylous sample; when the dH of the coagulation curve (dH is the total change of the whole coagulation curve, that is, the difference in light flux between the "baseline period" and the "plateau period" of the curve, see specifically Figure 1When it is too small (commonly found in strong chylomicron samples or low fibrinogen samples, etc.), the first-order or second-order differential curves often show noise-like curves (since dH is actually the integral of the first-order differential curve in the interval from the starting point to the ending point of the coagulation reaction, when dH is too small, that is, the integral of the first-order differential curve is too small, generally it will show that the ordinate of the differential curve is too small, and the difference in curve data within adjacent time is very small). At this time, it is often impossible to find the main peak of the differential curve, and the accuracy of the calculated coagulation time cannot be guaranteed. Summary of the Invention

[0006] An embodiment of the present invention provides a method for calculating blood coagulation time and a coagulation analyzer, which can effectively improve the accuracy of blood coagulation time.

[0007] In a first aspect, an embodiment of the present invention provides a method for calculating blood coagulation time, including:

[0008] Obtain characteristic parameters of a blood sample, where the characteristic parameters are used to evaluate the accuracy of the coagulation time obtained by processing the coagulation curve of the blood sample according to the derivative detection method, and the coagulation curve is a curve of the optical detection value of the blood sample changing with the detection time;

[0009] When the characteristic parameters meet the first characteristic condition, the coagulation time of the blood sample is obtained by processing the coagulation curve according to the derivative detection method;

[0010] When the characteristic parameters meet the second characteristic condition, the coagulation curve is processed according to the derivative detection method and the threshold detection method respectively, and a weighted operation is performed on the processing results to obtain the coagulation time;

[0011] When the characteristic parameters meet the third characteristic condition, the coagulation time is obtained by processing the coagulation curve according to the threshold detection method.

[0012] Optionally, the characteristic parameter is the curve characteristic of the coagulation curve or the degree of chylomicron interference of the blood sample.

[0013] Optionally, the curve characteristic includes any one of the estimated total change value of the optical detection value of the blood sample, the difference between the maximum value and the minimum value of the derivative curve of the coagulation curve of the blood sample during the blood coagulation process, and the number of peaks of the derivative curve of the coagulation curve of the blood sample during the blood coagulation process.

[0014] Optionally, when the curve characteristic is the estimated total change value of the optical detection value, the obtaining of the characteristic parameters of the blood sample includes:

[0015] Obtain the coagulation curve of the optical detection value of the blood sample changing with the detection time;

[0016] Determine the minimum optical detection value and the maximum optical detection value in the coagulation curve;

[0017] Determine an estimated total change in the optical detection value based on the maximum optical detection value and the minimum optical detection value.

[0018] Optionally, the optical detection value is luminous flux, the minimum optical detection value is the minimum luminous flux, and the maximum optical detection value is the maximum luminous flux;

[0019] The determination of the minimum optical detection value and the maximum optical detection value in the solidification curve includes:

[0020] Determine a first search interval for searching for the maximum luminous flux and a second search interval for searching for the minimum luminous flux in the solidification curve; the first search interval is the time range from the effective start time of the solidification curve to a first preset search upper limit, and the second search interval is the time range from the time point corresponding to the maximum luminous flux determined in the first search interval to a second preset search upper limit, and the first preset search upper limit is less than the second preset search upper limit;

[0021] Determine the maximum luminous flux of the solidification curve in the first search interval;

[0022] Determine the minimum luminous flux of the solidification curve in the second search interval.

[0023] Optionally, the optical detection value is absorbance, the minimum optical detection value is the minimum absorbance, and the maximum optical detection value is the maximum absorbance;

[0024] The determination of the minimum optical detection value and the maximum optical detection value in the solidification curve includes:

[0025] Determine a first search interval for searching for the minimum absorbance and a second search interval for searching for the maximum absorbance in the solidification curve. The first search interval is the time range from the effective start time of the solidification curve to a first preset search upper limit, and the second search interval is the time range from the time point corresponding to the minimum absorbance determined in the first search interval to a second preset search upper limit, and the first preset search upper limit is less than the second preset search upper limit;

[0026] Determine the minimum absorbance of the solidification curve in the first search interval;

[0027] Determine the maximum absorbance of the solidification curve in the second search interval.

[0028] Optionally, when the curve feature is the estimated total change value of the optical detection value or the difference between the maximum value and the minimum value, the first feature condition is the first feature parameter range, the second feature condition is the second feature parameter range, and the third feature condition is the third feature parameter range;

[0029] The value of the third feature parameter range is less than the value of the second feature parameter range, and the value of the second feature parameter range is less than the value of the first feature parameter range.

[0030] Optionally, when the feature parameter is the number of peaks or the degree of chyle interference, the first feature condition is the first feature parameter range, the second feature condition is the second feature parameter range, and the third feature condition is the third feature parameter range;

[0031] The value of the first feature parameter range is less than the value of the second feature parameter range, and the value of the second feature parameter range is less than the value of the third feature parameter range.

[0032] Optionally, processing the solidification curve according to the derivative detection method and the threshold detection method respectively, and performing a weighted operation on the processing results to obtain the solidification time, includes:

[0033] Processing the solidification curve according to the derivative detection method to obtain a first solidification time;

[0034] Processing the solidification curve according to the threshold detection method to obtain a second solidification time;

[0035] Calibrating the second solidification time according to a calibration model, where the calibration model is used to calibrate the solidification time of the derivative detection method and the solidification time of the threshold detection method;

[0036] Performing a weighted operation on the first solidification time and the calibrated second solidification time to obtain the solidification time.

[0037] Optionally, performing a weighted operation on the first solidification time and the calibrated second solidification time to obtain the solidification time, includes:

[0038] Determining a first weight of the first solidification time and a second weight of the second solidification time according to the feature parameter and the second feature condition.

[0039] Optionally, processing the solidification curve according to the threshold detection method to obtain the solidification time, includes:

[0040] Processing the solidification curve according to the threshold detection method to obtain a second solidification time;

[0041] Calibrate the second solidification time according to the calibration model to obtain the solidification time, where the calibration model is used to calibrate the solidification time of the derivative detection method and the solidification time of the threshold detection method.

[0042] Optionally, the obtaining the solidification time by processing the solidification curve according to the threshold detection method includes:

[0043] Process the solidification curve according to the threshold detection method to obtain a second solidification time;

[0044] Process the solidification curve according to the derivative detection method to obtain a derivative curve;

[0045] Determine the time corresponding to the first maximum value before the second solidification time in the derivative curve as the solidification time.

[0046] Optionally, the method further includes:

[0047] When the characteristic parameter satisfies the second characteristic condition or the third characteristic condition, output a switching prompt message, where the switching prompt message is used to prompt that the method for processing the solidification curve has switched.

[0048] In a second aspect, an embodiment of the present invention provides a coagulation analyzer, including a sample delivery module for delivering a blood sample, a dispensing module for aspirating and discharging samples or reagents, a sample incubation module for incubating samples, a reagent storage module for storing reagents, a transfer module for transferring reaction cups, a sample detection module for detecting the blood sample to obtain its characteristic parameters, a memory, and a processor; the processor is connected to the memory, where the memory is used to store program code, and the processor is used to call the program code to perform the following steps:

[0049] Obtain the characteristic parameters of the blood sample, where the characteristic parameters are used to evaluate the accuracy of the solidification time obtained by processing the solidification curve of the blood sample according to the derivative detection method, and the solidification curve is a curve of the optical detection value of the blood sample changing with the detection time;

[0050] When the characteristic parameter satisfies the first characteristic condition, process the solidification curve according to the derivative detection method to obtain the solidification time of the blood sample;

[0051] When the characteristic parameter satisfies the second characteristic condition, process the solidification curve according to the derivative detection method and the threshold detection method respectively, and perform a weighted operation on the processing results to obtain the solidification time;

[0052] When the characteristic parameter satisfies the third characteristic condition, process the solidification curve according to the threshold detection method to obtain the solidification time.

[0053] In an embodiment of the present invention, by obtaining a characteristic parameter of a blood sample, the characteristic parameter is used to evaluate the accuracy of the coagulation time obtained by processing the coagulation curve of the blood sample according to the derivative detection method; when the characteristic parameter meets the first characteristic condition, the coagulation time is obtained by processing the coagulation curve according to the derivative detection method; when the characteristic parameter meets the second characteristic condition, the coagulation curve is processed according to the derivative detection method and the threshold detection method respectively, and a weighted operation is performed on the processing results to obtain the coagulation time; and when the characteristic parameter meets the third characteristic condition, the coagulation curve is processed according to the threshold detection method to obtain the coagulation time. It can be seen that since the characteristic parameter can evaluate the accuracy of the coagulation time obtained by processing the coagulation curve of the blood sample according to the derivative detection method, by selecting different methods for processing the coagulation curve of the blood sample according to the magnitude of the characteristic parameter, the accuracy of the processed blood coagulation time can be effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other accompanying drawings can be obtained based on these drawings without creative efforts.

[0055] Figure 1 is a schematic diagram of calculating by the threshold detection method;

[0056] Figure 2 is a schematic diagram of calculating by the derivative detection method;

[0057] Figure 3 is a schematic diagram of the light flux curve and the first derivative curve of a strongly chylous sample;

[0058] Figure 4 is a schematic structural diagram of a coagulation analyzer provided by an embodiment of the present invention;

[0059] Figure 5 is a perspective view of a coagulation analyzer provided by an embodiment of the present invention seen from one direction;

[0060] Figure 6 is Figure 5 a perspective view of the coagulation analyzer shown seen from another direction;

[0061] Figure 7 is Figure 5 a top view of the coagulation analyzer shown;

[0062] Figure 8 is a schematic flow chart of a blood coagulation time calculation method provided by an embodiment of the present invention;

[0063] Figure 9It is a schematic diagram of the interface of a coagulation analyzer provided by an embodiment of the present invention;

[0064] Figure 10 It is a comparison chart of the derivative detection method and the calculation method of the embodiment of the present invention;

[0065] Figure 11 It is a schematic flowchart of a blood coagulation time calculation method provided by an embodiment of the present invention. Specific embodiments

[0066] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention.

[0067] It should be understood that the terms "first", "second", etc. in the specification, claims and drawings of this application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally further includes steps or units not listed, or optionally further includes other steps or units inherent to these processes, methods, products or devices.

[0068] Referring to "embodiment" in the present invention means that the specific features, structures or characteristics described in conjunction with the embodiment can be included in at least one embodiment of the present invention. The appearance of this phrase in various positions in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described in the present invention can be combined with other embodiments.

[0069] Reference Figure 4 , Figure 4 It is a schematic structural diagram of a coagulation analyzer provided by an embodiment of the present invention; the coagulation analyzer 400 includes a sample delivery module 406 for delivering a blood sample, a dispensing module 402 for aspirating and discharging samples or reagents, a sample incubation module 403 for incubating samples, a reagent storage module 409 for storing reagents, a transfer module 407 for transferring reaction cups, a sample detection module 408 for detecting a blood sample to obtain its characteristic parameters, a memory 405, and a processor 401; the above-mentioned various modules communicate with each other through a communication bus 404, wherein the memory 405 is used to store program codes, and the processor 401 is used to call the above program codes to execute the steps of the blood coagulation time calculation method provided in any of the following embodiments.

[0070] In one embodiment, the coagulation analyzer may further include a display screen for inputting information and outputting information. For example, a doctor can set the working parameters of the analyzer through the display screen, and information such as characteristic parameters can be output using the display screen.

[0071] In one embodiment, reference Figure 5 、 Figure 6 and Figure 7 , Figure 5 FIG. 11 is a perspective view of a coagulation analyzer provided by an embodiment of the present invention as viewed from one direction. Figure 6 FIG. Figure 5 12 is a perspective view of the coagulation analyzer shown in FIG. 11 as viewed from another direction. Figure 7 FIG. Figure 5 13 is a top view of the coagulation analyzer shown in FIG. 11. The coagulation analyzer 1 includes a sample delivery module 11, a cuvette loading module 12, a dispensing module 13, a sample incubation module 14, a reagent storage module 15, a transfer module 16, and a sample detection module 17. The sample delivery module 11 is used to deliver blood samples to achieve the automatic delivery of blood samples, improve the sample injection efficiency, and thus improve the working efficiency of the coagulation analyzer 1. The cuvette loading module 12 is used to deliver reaction cuvettes to achieve the automatic delivery of empty reaction cuvettes and improve the delivery efficiency. The dispensing module 13 is used to aspirate and discharge samples or reagents to add samples or reagents to the corresponding reaction cuvettes. The sample incubation module 14 is used to (heat) incubate samples to enable the samples to reach the optimal reaction conditions, facilitating the detection of sample parameters. The reagent storage module 15 is used to store reagents, which can store various reagents required for sample detection, facilitate the selection of required reagents, and improve the efficiency of aspirating reagents. The transfer module 16 is used to transfer reaction cuvettes so that the reaction cuvettes can move to various positions of the coagulation analyzer 1 to achieve the automatic analysis and detection of samples and improve the operation efficiency. The sample detection module 17 is used to detect samples to obtain the corresponding parameters of the samples. In this embodiment, the sample detection module 17 is used to detect blood samples to obtain their characteristic parameters.

[0072] In one embodiment, reference Figure 5 and Figure 7 FIG. 14 and FIG. 15, the reagent storage module 15 is arranged in a disc-shaped structure and is rotatable. The reagent storage module 15 can store a variety of reagents and can also achieve the refrigeration and automatic barcode recognition of a variety of reagents. It should be noted that the reagent storage module 15 has a refrigeration function for storing low-temperature reagents to achieve the preservation of reagents.

[0073] In one embodiment, reference Figure 5 and Figure 6, the dispensing module 13 includes a puncture needle mechanism 131, a comprehensive needle mechanism 132, and a reagent needle mechanism 133. That is to say, in this embodiment, the coagulation analyzer 1 is a three-needle mechanism, and the transfer of the sample and the reagent is realized jointly by the puncture needle mechanism 131, the comprehensive needle mechanism 132, and the reagent needle mechanism 133, and then the detection of the sample is realized. The puncture needle mechanism 131 is used for aspirating and discharging the sample, the comprehensive needle mechanism 132 is used for aspirating and discharging the sample or the reagent, and the reagent needle mechanism 133 is used for aspirating and discharging the reagent.

[0074] In one embodiment, referring to Figure 5 , Figure 6 and Figure 7 , in order to improve the transfer efficiency of the reaction cups, the transfer module 16 of the coagulation analyzer 1 of the present invention includes a first transfer mechanism 161 and a second transfer mechanism 162. The empty reaction cups are transferred by the first transfer mechanism 161, and the reaction cups added with reagents and samples are transferred by the second transfer mechanism 162, so that the first transfer mechanism 161 and the second transfer mechanism 162 each have their corresponding functions, and the working efficiency of the blood analyzer 1 is improved.

[0075] In one embodiment, referring to Figure 5 and Figure 7 , the sample detection module 17 can complete the data acquisition and result output of various parameter measurements. The sample detection module 17 of this embodiment can support the measurement of the sample by the clotting method, immunoturbidimetry, and substrate release method. Specifically, the sample detection module 17 includes a magnetic bead method detection mechanism 171 and an optical method detection mechanism. The magnetic bead method detection mechanism 171 performs magnetic bead method detection on the sample, and the optical method detection mechanism performs optical method detection on the sample. The magnetic bead method detection mechanism 171 and the optical method detection mechanism are arranged side by side, which can facilitate the transfer of the reaction cups. It should be noted that the magnetic bead method detection mechanism 171 and the optical method detection mechanism can detect the sample by adding different reagents, and the scope of use. In this embodiment, the optical method detection mechanism includes a first optical method detection mechanism 172 and a second optical method detection mechanism 173, and the magnetic bead method detection mechanism 171, the second optical method detection mechanism 173, and the first optical method detection mechanism 172 are arranged in sequence.

[0076] In one embodiment, when the optical method detection mechanism performs optical method detection on the blood sample, its optical detection value can be obtained, and the optical detection value can be the light flux or absorbance.

[0077] In one embodiment, the sample detection module 17 may further include a HIL detection mechanism for detecting at least one of the degree of hemolysis, the degree of jaundice, and the degree of chylomicron (lipemia) interference. Here, H represents hemolytic, I represents icterus, and L represents lipemia. By detecting the chylomicron concentration in the sample, the HIL detection mechanism can obtain an indication value of the chylomicron interference degree, such as a chylomicron grade coefficient. For hemolysis and jaundice, similar to chylomicron, an indication value of the hemolysis degree and an indication value of the jaundice degree can be obtained.

[0078] Please refer to Figure 8 , which is a schematic flowchart of a method for calculating blood coagulation time provided by an embodiment of the present invention; the method for calculating blood coagulation time includes:

[0079] Step 800: Obtain characteristic parameters of the blood sample. The characteristic parameters are used to evaluate the accuracy of the coagulation time obtained by processing the coagulation curve of the blood sample according to the derivative detection method. The coagulation curve is a curve of the optical detection value of the blood sample changing with the detection time;

[0080] Specifically, the sample detection module can be used to detect the blood sample to obtain its characteristic parameters. Using these characteristic parameters, the accuracy of the blood coagulation time obtained by processing the coagulation curve of the blood sample according to the derivative detection method can be judged. Here, the coagulation curve refers to a curve of the optical detection value of the blood sample changing with the detection time, such as Figure 2 the coagulation curve in. Actually, during specific detection, a plasma sample is used.

[0081] Step 801: When the characteristic parameters meet the first characteristic condition, process the coagulation curve according to the derivative detection method to obtain the coagulation time of the blood sample;

[0082] Specifically, the first characteristic condition can be set as needed. The first characteristic condition is a range of characteristic parameters indicating that the blood coagulation time calculated by the derivative detection method is accurate and reliable. When the characteristic parameters of the blood sample obtained in step 800 meet the first characteristic condition, the derivative detection method can be used to process the coagulation curve of the blood sample to obtain the corresponding coagulation time.

[0083] Step 802: When the characteristic parameters meet the second characteristic condition, process the coagulation curve according to the derivative detection method and the threshold detection method respectively, and perform a weighted operation on the processing results to obtain the coagulation time;

[0084] Specifically, similarly, the second characteristic condition can be set as needed. The second characteristic condition is a range of characteristic parameters indicating that the accuracy of the blood coagulation time calculated by the derivative detection method cannot be judged. When the characteristic parameters of the blood sample obtained in step 800 satisfy the second characteristic condition, at this time, the derivative detection method and the threshold detection method are respectively used to process the coagulation curve of the blood sample to obtain the corresponding coagulation time, and then the two obtained coagulation times are weighted to obtain the final coagulation time.

[0085] Step 803, when the characteristic parameters satisfy the third characteristic condition, the coagulation time is obtained by processing the coagulation curve according to the threshold detection method.

[0086] Specifically, similarly, the third characteristic condition can be set as needed. The third characteristic condition is a range of characteristic parameters indicating that the blood coagulation time calculated by the derivative detection method is inaccurate and untrustworthy. When the characteristic parameters of the blood sample obtained in step 800 satisfy the third characteristic condition, at this time, the derivative detection method is not used to calculate the coagulation time, but the threshold detection method is used to process the coagulation curve of the blood sample to obtain the corresponding coagulation time.

[0087] In the coagulation time calculation method of the embodiment of the present invention, since the characteristic parameters can evaluate the accuracy of the coagulation time obtained by processing the coagulation curve of the blood sample by the derivative detection method, different methods for processing the coagulation curve of the blood sample are selected according to the size of the characteristic parameters, that is, only the derivative detection method is used for coagulation time calculation, or only the threshold detection method is used for coagulation time calculation, or the derivative detection method and the threshold detection method are combined for coagulation time calculation, which can effectively improve the accuracy of the processed blood coagulation time.

[0088] In one embodiment, the blood coagulation time calculation method further includes:

[0089] Step 804, when the characteristic parameters satisfy the second characteristic condition or the third characteristic condition, a switching prompt message is output, and the switching prompt message is used to prompt that the method for processing the coagulation curve has switched.

[0090] Specifically, during the calculation of the blood coagulation time, a switching prompt message can be output on the display screen of the coagulation analyzer. The switching prompt message includes a first switching prompt message or a second switching prompt message. When the characteristic parameter meets the second characteristic condition, the fusion calculation method of the threshold detection method and the derivative detection method is switched at this time, and the first switching prompt message can be output on the display screen, which is used to prompt the user to switch to the fusion algorithm to process the coagulation curve; for example, the text "Switch to the fusion algorithm" is output on the display screen. Similarly, when the characteristic parameter meets the third characteristic condition, the threshold detection method is switched at this time, and the second switching prompt message can be output on the display screen, which is used to prompt the user to switch to the threshold detection algorithm to process the coagulation curve; for example, the text "Switch to the threshold detection method" is output on the display screen to prompt the user that the characteristic parameter meets the third characteristic condition at this time, and switch to processing the coagulation curve according to the threshold detection method to obtain the blood coagulation time.

[0091] Specifically, the above steps 800, 801, 802, 803, and 804 do not limit the execution order of the steps, but are only used to distinguish different processing steps. In this article, other step numbers are also only for distinguishing different steps and do not limit the execution order of the steps.

[0092] In one embodiment, the characteristic parameter is the curve characteristic of the coagulation curve or the degree of chylomicron interference of the blood sample. Among them, the curve characteristic of the coagulation curve can be the characteristic of the coagulation curve itself, such as the predicted total change value of the optical detection value during the coagulation process of the blood sample. It can also be a characteristic further obtained based on the coagulation curve. For example, the difference between the maximum value and the minimum value of the derivative curve of the coagulation curve of the blood sample during the blood coagulation process, or the number of peaks of the derivative curve of the coagulation curve of the blood sample during the blood coagulation process. The above derivative curve can be a first-order derivative curve, a second-order derivative curve, a third-order derivative curve, etc., without special limitation. The degree of chylomicron interference of the blood sample can be the chylomicron concentration of the blood sample, or the chylomicron grade coefficient (such as grade 1-10, the larger the number, the higher the chylomicron concentration) that can indicate the size of the chylomicron concentration of the blood sample, etc.

[0093] In one embodiment, when the curve characteristic is the predicted total change value of the optical detection value, step 800 includes:

[0094] Step 8001, obtaining a coagulation curve of the optical detection value of the blood sample changing with the detection time;

[0095] Specifically, the sample detection module is used to obtain the optical detection value, such as the light flux or absorbance, and a coagulation curve of the optical detection value changing with the detection time can be obtained.

[0096] Step 8002, determining the minimum optical detection value and the maximum optical detection value in the coagulation curve;

[0097] Step 8003: Determine an estimated total change value of the optical detection value based on the maximum optical detection value and the minimum optical detection value.

[0098] Specifically, the method for obtaining the estimated total change value of the optical detection value can refer to the description of the following embodiments and will not be elaborated herein.

[0099] In one embodiment, when the optical detection value is luminous flux, the minimum optical detection value is the minimum luminous flux, and the maximum optical detection value is the maximum luminous flux. At this time, step 8002 includes:

[0100] Step S11: Determine a first search interval for searching the maximum luminous flux and a second search interval for searching the minimum luminous flux in the solidification curve; the first search interval is the time range from the effective start time of the solidification curve to the first preset search upper limit, and the second search interval is the time range from the time point corresponding to the maximum luminous flux determined in the first search interval to the second preset search upper limit, where the first preset search upper limit is less than the second preset search upper limit.

[0101] Specifically, the above first search interval and second search interval can be set according to the actual situation. Among them, for the solidification curve obtained from the luminous flux of the blood sample, it shows a downward trend. Therefore, the first search interval is used to search and determine the maximum luminous flux of the blood sample during blood coagulation; while the second search interval is used to search and determine the minimum luminous flux of the blood sample during blood coagulation. In addition, during the actual calculation of the coagulation time, after adding the coagulation trigger reagent to the blood sample, the time when the blood sample and the trigger reagent are completely mixed and the optical measurement system is relatively stable is taken as the effective start time. In some embodiments, the effective start time is determined by the specific structure setting of the sample detection module. For example, for the sample detection module of a certain coagulation analyzer, it includes a mechanism that clamps away the blood sample added with the trigger reagent for mixing and then returns it to the original position (after the blood sample is clamped away, the luminous flux detected by the sample detection module will suddenly increase, so the luminous flux data at this time cannot be used). Among them, the time when the mechanism clamps away the blood sample, the mixing time, and the time when the blood sample is returned to the original position can all be set, and the time when the blood sample is returned to the original position is taken as the effective start time, such as 1.2 s or 1.5 s.

[0102] The first preset search upper limit and the second preset search upper limit can be set according to the actual situation, and the first preset search upper limit is less than the sampling cut-off time of the light flux (i.e., the longest sampling time of the light flux of the blood sample). In some embodiments, a preset time duration is reserved before the sampling cut-off time for searching for the termination point of the coagulation reaction, and the time point obtained by subtracting the preset time duration from the sampling cut-off time is the first preset search upper limit. The maximum light flux is searched for and determined between the effective start time and the first preset search upper limit. Refer to Figure 9 , Figure 9 is a schematic diagram of the interface of a coagulation analyzer provided by an embodiment of the present invention; for example, within the detection time of a certain blood sample (such as 0 - 150 s), the sampling cut-off time is 150 s, and 20 s is reserved for searching for the termination point of the coagulation reaction. At this time, the first preset search upper limit is 130 s, that is, Figure 9 the "starting search upper limit" in

[0103] The second preset search upper limit is the longest time at which it is possible to determine the termination point of the coagulation reaction, that is, the last time point that may become the termination point. For example, within 0 - 150 s, the basis for judging the termination point is that the curve is flat for 10 s after this point, then the second preset search upper limit is 140 s, that is, Figure 9 the "effective termination time" in

[0104] Step S21, determine the maximum light flux of the coagulation curve in the first search interval;

[0105] Step S31, determine the minimum light flux of the coagulation curve in the second search interval.

[0106] Further, when the optical detection value is the light flux, the estimated total change value of the optical detection value is the estimated total change value of the light flux dH. The specific estimation process of dH is as follows: After obtaining the coagulation curve of the blood sample regarding the light flux, the effective start time a, the first preset search upper limit b, and the second preset search upper limit d are preset in advance, such as Figure 9 the "effective start time", "starting search upper limit", and "effective termination time" in

[0107] At this time, the first search interval is [a, b], search for the maximum light flux max within the first search interval, and record the position c of the maximum light flux. Then the second search interval is (c, d], search for the minimum light flux min within this interval; then calculate the estimated total change value of the light flux: dH = max - min. The relationship among a, b, c, and d is: a <= c <= b < d.

[0107] In another embodiment, when the optical detection value is the absorbance, the minimum optical detection value is the minimum absorbance, and the maximum optical detection value is the maximum absorbance; at this time, step 8002 includes:

[0108] Step S12: Determine a first search range for searching for the minimum absorbance in the solidification curve and a second search range for searching for the maximum absorbance. The first search range is the time range from the effective start time of the solidification curve to the first preset search upper limit, and the second search range is the time range from the time point corresponding to the minimum absorbance determined in the first search range to the second preset search upper limit. The first preset search upper limit is less than the second preset search upper limit.

[0109] Specifically, for the solidification curve obtained based on the absorbance of the blood sample, which shows an upward trend. Therefore, the first search range is used to search for and determine the minimum absorbance of the blood sample during blood coagulation; while the second search range is used to search for and determine the maximum absorbance of the blood sample during blood coagulation. Similar to when the optical detection value is the light flux, the first search range and the second search range can be set as needed, and the above descriptions regarding the first search range and the second search range can be referred to.

[0110] Step S22: Determine the minimum absorbance of the solidification curve in the first search range.

[0111] Step S32: Determine the maximum absorbance of the solidification curve in the second search range.

[0112] In one embodiment, a threshold detection method for determining the start point and end point of the solidification process can also be used to determine the maximum optical detection value and the minimum optical detection value during the solidification process, and the change amount between the two is used as an estimated value of the total change amount of the optical detection value. The method of using the threshold detection method to determine the start point and end point of the solidification process can be the determination method in the prior art and will not be elaborated here.

[0113] In one embodiment, when the curve feature is the estimated total change in optical detection value or the difference between the maximum and minimum values of the derivative curve of the blood sample's coagulation curve during blood coagulation, the corresponding first characteristic condition is the first characteristic parameter range, the second characteristic condition is the second characteristic parameter range, and the third characteristic condition is the third characteristic parameter range; the value of the third characteristic parameter range is less than the value of the second characteristic parameter range, and the value of the second characteristic parameter range is less than the value of the first characteristic parameter range. Taking the estimated total change in light flux as an example, the estimated total change in light flux is dH. In this embodiment, the first characteristic parameter range, the second characteristic parameter range, and the third characteristic parameter range are adjacent and continuous on the number axis. That is, the above-mentioned first characteristic parameter range is that dH is greater than Y1. At this time, it is considered that a relatively obvious main peak can be obtained after differentiating the coagulation curve, and the coagulation time can be accurately calculated using the derivative detection method. Therefore, the derivative detection method is completely used to calculate the coagulation time; the second characteristic parameter range is [X1, Y1]. At this time, there are concerns about the accuracy of calculating the coagulation time using the derivative detection method, and a method of fusing the derivative detection method and the threshold detection method needs to be used; the third characteristic parameter range is that dH is less than X1. At this time, it is considered that there are interference factors in the blood sample or it is a low-fibrin sample, and it is completely unreliable to use the derivative detection method to calculate the coagulation time.

[0114] In another embodiment, when the characteristic parameter is the number of peaks or the degree of chyle interference of the derivative curve of the blood sample's coagulation curve during blood coagulation, the corresponding first characteristic condition is the first characteristic parameter range, the second characteristic condition is the second characteristic parameter range, and the third characteristic condition is the third characteristic parameter range; the value of the first characteristic parameter range is less than the value of the second characteristic parameter range, and the value of the second characteristic parameter range is less than the value of the third characteristic parameter range. Assuming the number of peaks is f, in this embodiment, the first characteristic parameter range, the second characteristic parameter range, and the third characteristic parameter range are adjacent and continuous on the number axis. That is, the above-mentioned first characteristic parameter range is that f is less than X2, the second characteristic parameter range is [X2, Y2], and the third characteristic parameter range is that f is greater than Y2.

[0115] Furthermore, when the characteristic parameter is the degree of chyle interference of the blood sample, when the degree of chyle interference is the chyle concentration, the first characteristic parameter range is the first chyle concentration range, and the second characteristic parameter range and the third characteristic parameter range are the second chyle concentration range and the third chyle concentration range respectively. When the degree of chyle interference is the chyle grade coefficient, the first characteristic parameter range is the first chyle grade coefficient range, and the second characteristic parameter range and the third characteristic parameter range are the second chyle grade coefficient range and the third chyle grade coefficient range respectively.

[0116] It should be specifically noted that for the two endpoints X and Y of the above second characteristic parameter range, such as X1, X2, Y1, and Y2, the determination method of the endpoint values can be obtained through a large number of clinical trials or derived by simulating with a curve model. Refer to Figure 9 , before calculating the coagulation time, after determining X and Y in advance, X and Y can be input on the display interface of the coagulation analyzer to facilitate determining the specific method for calculating the coagulation time. X is the Figure 9 "lower limit" in Figure 9 , and Y is the

[0117] "upper limit" in

[0118] Specifically, if a single value X is used as the judgment index for switching between the derivative detection method and the threshold detection method, when the characteristic parameter changes within a very small range before and after X (assuming X is 10), at this time, the coagulation time calculation methods used for the two characteristic parameters (assuming 9.999 and 10.01) before and after X are completely different, resulting in a large difference in the calculated coagulation time, there is a risk of value jump, and it affects the value repeatability near X. In the embodiment of the present invention, a transition interval [X, Y] (i.e., the second characteristic condition, and all characteristic parameters are divided into three intervals by using the second characteristic condition) is used instead, which can make the calculation result of the coagulation time change continuously within an interval. Therefore, it can reduce the influence brought by the method switching on aspects such as value repeatability to a certain extent.

[0118] In one embodiment, in 801, when the characteristic parameter satisfies the first characteristic condition, the coagulation time of the blood sample is obtained by processing the coagulation curve according to the derivative detection method. The existing derivative detection method in the prior art can be used for processing to obtain the coagulation time, and no special limitation is made.

[0119] In one embodiment, in step 802, when the characteristic parameter satisfies the second characteristic condition, the coagulation curve is processed according to the derivative detection method and the threshold detection method respectively, and a weighted operation is performed on the processing results to obtain the coagulation time, including:

[0120] Step 8021, processing the coagulation curve according to the derivative detection method to obtain the first coagulation time;

[0121] Specifically, assume that the first coagulation time is t1.

[0122] Step 8022, processing the coagulation curve according to the threshold detection method to obtain the second coagulation time;

[0123] Specifically, assume that the second coagulation time is t2.

[0124] Step 8023, calibrating the second coagulation time according to the calibration model, where the calibration model is used to calibrate the coagulation time of the derivative detection method and the coagulation time of the threshold detection method;

[0125] Specifically, the calibration model can be a linear calibration model, a double logarithmic linear calibration model, a double reciprocal linear calibration model, a high-order calibration model, etc., without special limitation. Taking the linear calibration model as an example, it is necessary to pre-determine the calibration parameters K and B of the linear calibration model. Among them, the coagulation time of a certain blood sample can be calculated by using the threshold detection method and the derivative detection method respectively in advance, that is, K and B are determined according to a large number of clinical experiments. It can also be obtained by simulating and deriving K and B using a curve model. Suppose the calibrated second coagulation time is t3, that is, t3 = t2 * K + B.

[0126] Step 8024: Perform a weighted operation on the first coagulation time and the calibrated second coagulation time to obtain the coagulation time.

[0127] Specifically, the final coagulation time can be obtained by performing a weighted calculation on t1 and t3. Among them, the weights of the weighted operation can be determined by different methods for determining weights, without special limitation.

[0128] In one embodiment, step 8024 includes:

[0129] Determine the first weight of the first coagulation time and the second weight of the second coagulation time according to the characteristic parameter and the second characteristic condition.

[0130] Specifically, according to the characteristic parameter and the second characteristic condition, the first weight of the first coagulation time and the second weight of the second coagulation time can be determined. In this embodiment, taking the total estimated value of the light flux change dH as the characteristic parameter as an example, assuming that the second characteristic condition is the second characteristic parameter range [X, Y], then the first weight is M = (dH - X) / (Y - X), and the second weight is N = (Y - dH) / (Y - X). Then the coagulation time calculated by fusing the derivative detection method and the threshold detection method is t = t1 * M + t3 * N.

[0131] In one embodiment, in order to improve the accuracy of the coagulation time obtained by the threshold detection method, in the embodiment of the present invention, in step 803, processing the coagulation curve according to the threshold detection method to obtain the coagulation time includes:

[0132] Step 8031: Process the coagulation curve according to the threshold detection method to obtain the second coagulation time;

[0133] Specifically, assume that the second coagulation time is t2.

[0134] Step 8032: Calibrate the second coagulation time according to the calibration model to obtain the coagulation time, where the calibration model is used to calibrate the coagulation time of the derivative detection method and the coagulation time of the threshold detection method.

[0135] Specifically, similarly, the calibration model can be a linear calibration model, a double logarithmic linear calibration model, a double reciprocal linear calibration model, a high-order calibration model, etc., without special limitation. Taking the linear calibration model as an example, it is necessary to pre-determine the calibration parameters K and B of the linear calibration model. The calibrated second coagulation time is t3, that is, t3 = t2 * K + B. Refer to Figure 9 During actual calculation, K and B can be input on the display interface of the coagulation analyzer to calculate the second coagulation time.

[0136] In another embodiment, in step 803, processing the coagulation curve according to the threshold detection method to obtain the coagulation time includes:

[0137] Step 8033, processing the coagulation curve according to the threshold detection method to obtain the second coagulation time;

[0138] Specifically, assume that the second coagulation time is t2.

[0139] Step 8034, processing the coagulation curve according to the derivative detection method to obtain the derivative curve;

[0140] Step 8035, determining the time corresponding to the first maximum value before the second coagulation time in the derivative curve as the coagulation time.

[0141] Specifically, in the derivative curve, search forward from the position corresponding to t2, and determine the time corresponding to the first maximum value (i.e., peak value) found as the coagulation time. This embodiment provides another method for determining the coagulation time based on the threshold detection method. Other methods for determining the coagulation time based on the threshold detection method are also feasible, without special limitation.

[0142] The coagulation time calculation method of the embodiments of the present invention can, while retaining the advantages of the derivative detection method, improve the anti-interference calculation ability of the derivative detection method by means of the fusion of the threshold detection method and the derivative detection method. Refer to Figure 10 , Figure 10 is a comparison chart of the derivative detection method and the calculation method of the embodiments of the present invention. Figure 10 For the APTT repeatability experiment value comparison when completely using the second derivative method and using the fusion algorithm of the embodiments of the present invention under strong chyle interference, it can be seen that the value repeatability is significantly improved under strong interference when using the fusion calculation algorithm of the embodiments of the present invention.

[0143] In one embodiment, taking the pre-estimated total change in light flux dH as an example, the process of the entire blood coagulation time calculation method will be described below:

[0144] Refer to Figure 11 , Figure 11It is a schematic flowchart of a blood coagulation time calculation method provided by an embodiment of the present invention. According to experimental empirical values in advance, the judgment interval [X, Y] of dH, the method school calibration coefficients K and B are determined, and the search interval [a, b] and d are determined. The determined parameters are input into the coagulation analyzer to calculate the coagulation time of the blood sample. Then, the maximum value max of the coagulation curve of the blood sample is searched within the interval [a, b], and the position corresponding to max is c. Next, the minimum value min of the coagulation curve is searched within the interval (c, d]. The estimated value of dH is calculated based on max and min, dH≈max - min. Finally, the specific calculation method is determined according to the relationship between dH and X, Y. When dH>Y, the derivative detection method is completely used to calculate the coagulation time t1; when dH<X, the threshold detection method is used to calculate the coagulation time t2, and K and B are used for linear calibration; when dH is within the interval [X, Y], the threshold detection method and the derivative detection method are respectively used to calculate the coagulation time to obtain t1 and t2, and the final result t is obtained by weighted calculation according to their respective weights: t = t1*(dH - X) / (Y - X)+(t2*K + B)*(Y - dH) / (Y - X). The calculation result of the coagulation time is output on the display interface of the coagulation analyzer.

[0145] In addition, it should be pointed out here that: The embodiment of the present invention also provides a computer storage medium, and the computer program includes program instructions. When the processor executes the program instructions, it can execute the description of the blood coagulation time calculation method mentioned above. Therefore, it will not be repeated here. In addition, the description of the beneficial effects of using the same method will not be repeated either. For the technical details not disclosed in the embodiment of the computer storage medium involved in the present invention, please refer to the description of the method embodiment of the present invention.

[0146] Those of ordinary skill in the art can understand that all or part of the processes in the above method embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above method embodiments. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc.

[0147] The above-disclosed are only the preferred embodiments of the present invention. Of course, the scope of the rights of the present invention cannot be limited thereby. Therefore, equivalent changes made according to the claims of the present invention still fall within the scope covered by the present invention.

Claims

1. A method for calculating blood coagulation time, characterized in that, it includes: Obtaining characteristic parameters of a blood sample, where the characteristic parameters are used to evaluate the accuracy of the coagulation time obtained by processing the coagulation curve of the blood sample according to the derivative detection method, and the coagulation curve is a curve of the optical detection value of the blood sample changing with the detection time; the characteristic parameter is the curve characteristic of the coagulation curve or the degree of chyle interference of the blood sample; When the characteristic parameter satisfies the first characteristic condition, the coagulation time of the blood sample is obtained by processing the coagulation curve according to the derivative detection method; the first characteristic condition is a range of characteristic parameters indicating that the blood coagulation time calculated by the derivative detection method is accurate and credible; When the characteristic parameter satisfies the second characteristic condition, the coagulation curve is processed according to the derivative detection method and the threshold detection method respectively, and a weighted operation is performed on the processing results to obtain the coagulation time; the second characteristic condition is a range of characteristic parameters indicating that the accuracy of the blood coagulation time calculated by the derivative detection method cannot be judged; When the characteristic parameter satisfies the third characteristic condition, the coagulation curve is processed according to the threshold detection method to obtain the coagulation time; the third characteristic condition is a range of characteristic parameters indicating that the blood coagulation time calculated by the derivative detection method is inaccurate and unreliable.

2. The method according to claim 1, characterized in that, The curve characteristic includes any one of the estimated total change value of the optical detection value of the blood sample, the difference between the maximum value and the minimum value of the derivative curve of the coagulation curve of the blood sample during blood coagulation, and the number of peaks of the derivative curve of the coagulation curve of the blood sample during blood coagulation.

3. The method according to claim 1, characterized in that, When the curve characteristic is the estimated total change value of the optical detection value, the obtaining of the characteristic parameters of the blood sample includes: Obtaining the coagulation curve of the optical detection value of the blood sample changing with the detection time; Determining the minimum optical detection value and the maximum optical detection value in the coagulation curve; Determining the estimated total change value of the optical detection value according to the maximum optical detection value and the minimum optical detection value.

4. The method according to claim 3, characterized in that, The optical detection value is the light flux, the minimum optical detection value is the minimum light flux, and the maximum optical detection value is the maximum light flux; The determining of the minimum optical detection value and the maximum optical detection value in the coagulation curve includes: Determining a first search interval for searching for the maximum light flux and a second search interval for searching for the minimum light flux in the coagulation curve; the first search interval is the time range from the effective start time of the coagulation curve to the first preset search upper limit, and the second search interval is the time range from the time point corresponding to the maximum light flux determined in the first search interval to the second preset search upper limit, and the first preset search upper limit is less than the second preset search upper limit; Determining the maximum light flux of the coagulation curve in the first search interval; Determining the minimum light flux of the coagulation curve in the second search interval.

5. The method according to claim 3, characterized in that, The optical detection value is the absorbance, the minimum optical detection value is the minimum absorbance, and the maximum optical detection value is the maximum absorbance; Determining the minimum optical detection value and the maximum optical detection value in the solidification curve includes: Determining a first search interval for searching for the minimum absorbance and a second search interval for searching for the maximum absorbance in the solidification curve. The first search interval is the time range from the effective start time of the solidification curve to the first preset search upper limit, and the second search interval is the time range from the time point corresponding to the minimum absorbance determined in the first search interval to the second preset search upper limit. The first preset search upper limit is less than the second preset search upper limit; Determining the minimum absorbance of the solidification curve in the first search interval; Determining the maximum absorbance of the solidification curve in the second search interval.

6. The method according to claim 2, wherein, when the curve feature is the estimated total change value of the optical detection value or the difference between the maximum value and the minimum value, the first feature condition is the first feature parameter range, the second feature condition is the second feature parameter range, and the third feature condition is the third feature parameter range; The value of the third feature parameter range is less than the value of the second feature parameter range, and the value of the second feature parameter range is less than the value of the first feature parameter range.

7. The method according to claim 2, wherein, when the feature parameter is the number of peaks or the degree of chyle interference, the first feature condition is the first feature parameter range, the second feature condition is the second feature parameter range, and the third feature condition is the third feature parameter range; The value of the first feature parameter range is less than the value of the second feature parameter range, and the value of the second feature parameter range is less than the value of the third feature parameter range.

8. The method according to any one of claims 1-7, wherein, processing the solidification curve according to the derivative detection method and the threshold detection method respectively, and performing a weighted operation on the processing results to obtain the solidification time, includes: Processing the solidification curve according to the derivative detection method to obtain a first solidification time; Processing the solidification curve according to the threshold detection method to obtain a second solidification time; Calibrating the second solidification time according to a calibration model, wherein the calibration model is used to calibrate the solidification time of the derivative detection method and the solidification time of the threshold detection method; Performing a weighted operation on the first solidification time and the calibrated second solidification time to obtain the solidification time.

9. The method according to claim 8, wherein, performing a weighted operation on the first solidification time and the calibrated second solidification time to obtain the solidification time, includes: Determining a first weight of the first solidification time and a second weight of the second solidification time according to the feature parameter and the second feature condition.

10. The method according to any one of claims 1-7, wherein, processing the solidification curve according to the threshold detection method to obtain the solidification time, includes: Processing the solidification curve according to the threshold detection method to obtain a second solidification time; Calibrating the second solidification time according to a calibration model to obtain the solidification time, wherein the calibration model is used to calibrate the solidification time obtained by the derivative detection method and the solidification time obtained by the threshold detection method.

11. The method according to any one of claims 1-7, characterized in that, The processing the solidification curve according to the threshold detection method to obtain the solidification time includes: Processing the solidification curve according to the threshold detection method to obtain a second solidification time; Processing the solidification curve according to the derivative detection method to obtain a derivative curve; Determining the time corresponding to the first maximum value before the second solidification time in the derivative curve as the solidification time.

12. The method according to any one of claims 1-7, characterized in that, The method further includes: When the characteristic parameter satisfies the second characteristic condition or the third characteristic condition, outputting a switching prompt message, where the switching prompt message is used to prompt that the method for processing the solidification curve has switched.

13. A coagulation analyzer, characterized in that, including a sample delivery module for delivering a blood sample, a dispensing module for aspirating and discharging samples or reagents, a sample incubation module for incubating samples, a reagent storage module for storing reagents, a transfer module for transferring reaction cups, a sample detection module for detecting the blood sample to obtain its characteristic parameters, a memory, and a processor; the processor is connected to the memory, wherein the memory is used to store program code, and the processor is used to call the program code to perform the following steps: Obtaining characteristic parameters of a blood sample, where the characteristic parameters are used to evaluate the accuracy of the solidification time obtained by processing the solidification curve of the blood sample according to the derivative detection method, and the solidification curve is a curve of the optical detection value of the blood sample changing with the detection time; the characteristic parameter is a curve characteristic of the solidification curve or the degree of chyle interference of the blood sample; When the characteristic parameter satisfies the first characteristic condition, processing the solidification curve according to the derivative detection method to obtain the solidification time of the blood sample; the first characteristic condition is a range of characteristic parameters indicating that the blood coagulation time calculated by the derivative detection method is accurate and credible; When the characteristic parameter satisfies the second characteristic condition, processing the solidification curve according to the derivative detection method and the threshold detection method respectively, and performing a weighted operation on the processing results to obtain the solidification time; the second characteristic condition is a range of characteristic parameters indicating that the accuracy of the blood coagulation time calculated by the derivative detection method cannot be judged; when the characteristic parameter satisfies the third characteristic condition, processing the solidification curve according to the threshold detection method to obtain the solidification time; the third characteristic condition is a range of characteristic parameters indicating that the blood coagulation time calculated by the derivative detection method is inaccurate and unreliable.

Images