Clinical testing system and method

Abstract

The present application provides a clinical testing system and method, which detects a blood sample to obtain a thromboelastogram; selects a coagulation stage in the thromboelastogram as the selected coagulation stage, and screens multiple trend components from all blood coagulation characteristics based on the temporal dependencies of the various blood coagulation characteristics within the selected coagulation stage; identifies temperature interference through the trend characteristics of external temperature changes and all trend components during the detection process; determines the elastic modulus change of the blood during the coagulation stage through the phase change information of the thromboelastometer probe vibration and the temperature interference during the detection process, and further determines the elastic modulus change of the blood in the remaining coagulation stages; and determines the test index of the subject's coagulation function based on all elastic modulus changes. The scheme of the present application can eliminate external interference in thromboelastogram detection and correct the thromboelastogram, thereby improving the accuracy of coagulation function testing.

Description

Technical Field

[0001] The present application relates to the field of clinical medical testing technology, and more specifically, to a clinical testing system and method. Background Art

[0002] Clinical testing refers to the process of analyzing, testing and evaluating human samples (such as blood, urine, tissue, etc.) through various laboratory techniques to assist doctors in diagnosing diseases, evaluating treatment effects and monitoring health status. It includes: hematological tests, biochemical tests, microbiological tests, urine analysis and imaging examination auxiliary tests and other tests.

[0003] Hematological tests include routine blood tests and coagulation function tests. A commonly used test for coagulation function testing is thromboelastometry (TEG). Existing TEG tests typically first generate a curve describing changes in blood elasticity during coagulation (i.e., a TEG curve), and then extract various coagulation function test indicators from the envelope of this curve. However, due to limitations in testing conditions, the TEG curves obtained in existing technologies often include various abnormal jitters (e.g., temperature interference caused by the effect of temperature on blood coagulation, sensor sampling errors, and other temperature interferences). Ambient temperature changes significantly affect the blood coagulation process, leading to errors in the final test indicators. While other interference factors have less impact on the blood coagulation process, these various interferences can distort the TEG curve, making it difficult to accurately depict the TEG curve when constructing the envelope of the TEG curve. These issues can lead to errors in coagulation function test results. Therefore, eliminating temperature interference in TEG testing and improving the accuracy of coagulation function tests has become a challenge facing the industry. Summary of the Invention

[0004] The present application provides a clinical testing system and method, which can eliminate external interference in thromboelastography testing and improve the accuracy of coagulation function testing.

[0005] In a first aspect, the present application provides a method for extracting test indicators of coagulation function, which is used for extracting test indicators of coagulation function in a clinical testing system, wherein the clinical testing system includes: a thrombelastometer, an intelligent temperature sensor, and an intelligent displacement sensor. The method includes:

[0006] adding an anticoagulant to the blood of the subject to obtain a blood sample, and activating the thromboelastometry instrument to perform a thromboelastometry test on the blood sample to obtain a thromboelastometry map;

[0007] A coagulation stage in the thromboelastogram is selected as a selected coagulation stage, multiple blood coagulation characteristics within the selected coagulation stage are determined, and multiple trend components of blood viscosity change are screened from all blood coagulation characteristics according to the temporal dependencies of the respective blood coagulation characteristics;

[0008] The intelligent temperature sensor collects the external temperature changes in real time during the detection process, and identifies the temperature interference caused by the temperature changes in the selected coagulation stage on the subject's blood coagulation process based on the trend characteristics and all trend components of the temperature changes;

[0009] The intelligent displacement sensor is used to collect phase change information of the thromboelastometry probe vibration in real time during the detection process, and the elastic modulus change of the blood in the selected coagulation stage is determined based on the phase change information and the temperature interference, and the elastic modulus change of the blood in the remaining coagulation stages is further determined;

[0010] The thromboelastogram is corrected based on all elastic modulus changes, and a test index of the subject's coagulation function is extracted from the corrected thromboelastogram.

[0011] In some embodiments, determining a plurality of blood coagulation characteristics within a selected coagulation stage specifically comprises:

[0012] determining blood coagulation characteristics based on the envelope and thromboelastometry curve corresponding to the selected coagulation stage;

[0013] determining a residual curve according to the blood coagulation characteristic;

[0014] If the residual curve is not a monotonic curve, the residual curve is used as a new thromboelastometry curve, and all envelopes of the residual curve are used as envelopes corresponding to the newly selected coagulation stage. The above steps of determining the residual curve based on the envelope corresponding to the selected coagulation stage and the thromboelastometry curve are repeated until the residual curve finally obtained is a monotonic curve, thereby obtaining multiple blood coagulation characteristics.

[0015] In some embodiments, screening multiple trend components of blood viscosity changes from all blood coagulation characteristics based on the temporal dependencies of the various blood coagulation characteristics specifically includes:

[0016] For each blood coagulation characteristic, determining a plurality of cumulative deviation sequences of each blood coagulation characteristic in different local windows;

[0017] Determine the average local deviation of each local window according to all accumulated deviation sequences under each local window;

[0018] determining a temporal dependency of each of the blood coagulation characteristics based on all average local deviations;

[0019] All time series dependencies are compared with a preset dependency threshold, and all blood coagulation characteristics greater than the dependency threshold are regarded as trend components of blood viscosity changes.

[0020] In some embodiments, identifying the temperature interference on the subject's blood coagulation process caused by the temperature change in the selected coagulation stage based on the trend characteristics of the temperature change and all trend components specifically includes:

[0021] determining a trend characteristic corresponding to the temperature change in a selected solidification stage;

[0022] Determine the similarity between the temporal dependence of each trend component and the trend characteristics;

[0023] The temperature interference on the blood coagulation process of the subject caused by the temperature change in the selected coagulation stage is screened out from all trend components according to all similarities.

[0024] In some embodiments, determining the change in elastic modulus of blood in a selected coagulation stage according to the phase change information and the temperature interference specifically includes:

[0025] determining an elastic component in the blood coagulation process based on the temperature disturbance and all trend components;

[0026] The change in elastic modulus of blood in a selected coagulation stage is determined based on the elastic component and the phase change information.

[0027] In some embodiments, modifying the thromboelastogram based on all elastic modulus changes specifically includes:

[0028] Determine a correction curve diagram based on all elastic modulus changes;

[0029] An upper envelope and a lower envelope of the correction curve are determined, and a curve consisting of the upper envelope and the lower envelope is used as a corrected thromboelastogram.

[0030] In some embodiments, the test indicators of coagulation function in the present application include: coagulation reaction time, coagulation clotting time, coagulation formation rate and final coagulation strength.

[0031] In a second aspect, the present application provides a clinical testing system, which includes: a thromboelastometry instrument, an intelligent temperature sensor, an intelligent displacement sensor, and a test index extraction unit, wherein the test index extraction unit includes:

[0032] a collection module, configured to add an anticoagulant to the blood of the subject to obtain a blood sample, and then instruct the thromboelastometry instrument to perform a thromboelastometry test on the blood sample to obtain a thromboelastometry map;

[0033] a processing module, configured to select a coagulation stage in the thromboelastogram as a selected coagulation stage, determine a plurality of blood coagulation characteristics within the selected coagulation stage, and screen a plurality of trend components of blood viscosity change from all the blood coagulation characteristics based on temporal dependencies of the respective blood coagulation characteristics;

[0034] The processing module is further configured to instruct the intelligent temperature sensor to collect real-time temperature changes of the outside world during the detection process, and to identify temperature interference caused by the temperature changes in the selected coagulation stage on the subject's blood coagulation process based on the trend characteristics and all trend components of the temperature changes;

[0035] The processing module is further configured to instruct the intelligent displacement sensor to collect phase change information of the thromboelastometry probe vibration in real time during the detection process, determine the change in elastic modulus of the blood in the selected coagulation stage based on the phase change information and the temperature interference, and continue to determine the change in elastic modulus of the blood in the remaining coagulation stages;

[0036] The execution module is used to correct the thromboelastogram based on all elastic modulus changes and extract a test index of the subject's coagulation function from the corrected thromboelastogram.

[0037] In a third aspect, the present application provides a computer device, comprising a memory and a processor, wherein the memory stores a code, and the processor is configured to obtain the code and execute the above-mentioned method for extracting test indicators of coagulation function.

[0038] In a fourth aspect, the present application provides a computer-readable storage medium storing a computer program, which implements the above-mentioned method for extracting test indicators of coagulation function when executed by a processor.

[0039] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0040] In the clinical testing system and method provided herein, an anticoagulant is first added to a subject's blood to obtain a blood sample. The thrombelastometer is activated to perform a thrombelastogram test on the blood sample to obtain a thrombelastogram. A coagulation stage in the thrombelastogram is selected as a selected coagulation stage, multiple blood coagulation characteristics within the selected coagulation stage are determined, and multiple trend components of blood viscosity change are screened from all blood coagulation characteristics based on the temporal dependencies of the individual blood coagulation characteristics. The intelligent temperature sensor is used to collect real-time ambient temperature changes during the testing process. Based on the trend characteristics of the temperature changes and all trend components, the temperature interference caused by the temperature changes in the selected coagulation stage on the subject's blood coagulation process is identified. The intelligent displacement sensor is used to collect real-time phase change information of the thrombelastometer probe vibration during the testing process. Based on the phase change information and the temperature interference, the elastic modulus change of the blood in the selected coagulation stage is determined. The elastic modulus change of the blood in the remaining coagulation stages is then determined. The thrombelastogram is corrected based on all elastic modulus changes, and a test index of the subject's coagulation function is extracted from the corrected thrombelastogram.

[0041] It can be seen that the present application pre-segments the thromboelastogram and decomposes each coagulation stage obtained by the segmentation, decomposing the thromboelastogram containing multiple vibration modes into multiple blood coagulation characteristics of single vibration modes. Subsequently, the noise and error therein are removed by the time series dependency of the blood coagulation characteristics (i.e., the blood coagulation characteristics with small time series dependency). The remaining blood coagulation characteristics are the components that can reflect a certain trend change (i.e., trend components). Furthermore, all trend components are compared with the trend characteristics of the external temperature change, and the error due to the temperature change is removed. The trend component caused by blood coagulation (i.e., temperature interference) is screened out, and finally, the remaining components are combined with the phase change information of the thrombelastometer probe vibration to re-fit the thromboelastometry curve for each coagulation stage. The re-fitted thromboelastometry curve eliminates the effects of temperature interference and sensor error, and finally, the test indicators of the subject's coagulation function are extracted from the re-fitted thromboelastometry curve. In summary, the present application can eliminate external interference in thromboelastometry detection and correct the thromboelastometry, thereby improving the accuracy of coagulation function detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 is an exemplary flow chart of a method for extracting test indicators of coagulation function according to some embodiments of the present application;

[0043] Figure 2 is a thromboelastogram according to some embodiments of the present application;

[0044] Figure 3 is an exemplary flow chart of determining trend components according to some embodiments of the present application;

[0045] Figure 4 is a structural diagram of a test indicator extraction unit according to some embodiments of the present application;

[0046] Figure 5 It is a structural diagram of a computer device for implementing a method for extracting test indicators of coagulation function according to some embodiments of the present application. DETAILED DESCRIPTION

[0047] In order to better understand the technical solution of the present application, the technical solution of the present application will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0048] refer to Figure 1 , which is an exemplary flow chart of a method for extracting test indicators of coagulation function according to some embodiments of the present application. The method 100 for extracting test indicators of coagulation function mainly includes the following steps:

[0049] In step 101, an anticoagulant is added to the blood of a subject to obtain a blood sample, and the thromboelastometry instrument is started to perform a thromboelastometry test on the blood sample to obtain a thromboelastometry.

[0050] It should be noted that the anticoagulant in this application is a 38 g / L sodium citrate solution. In other embodiments, other anticoagulants may also be selected, which is not limited here.

[0051] In specific implementation, adding an anticoagulant to the subject's blood to obtain a blood sample can be achieved in the following manner, namely: first, adding the anticoagulant to the subject's blood to obtain anticoagulated plasma, then centrifuging the anticoagulated plasma at a speed of 1000 r / min for 5 minutes, and taking the upper 0.4 ml of anticoagulated plasma from the centrifuged anticoagulated plasma and mixing it with 0.4 ml of calcium chloride solution, and finally, using the mixed anticoagulated plasma as a blood sample. Other methods can also be used in other embodiments, which are not limited here.

[0052] In a specific implementation, the thromboelastometry instrument is activated to perform a thromboelastometry test on the blood sample. The thromboelastometry test can be obtained in the following manner: 0.36 ml of the blood sample is placed in a blood cup, the blood cup is placed on a reaction pool that can rotate back and forth at an angle of 4°45', and the thromboelastometry instrument is activated to measure the coagulation process of the blood sample to obtain the thromboelastometry. The starting time of the thromboelastometry test is the time when the blood sample is prepared, that is, the timing of the thromboelastometry test begins at the time when the blood sample is prepared.

[0053] In step 102, for each coagulation stage in the thromboelastogram, multiple blood coagulation characteristics within the selected coagulation stage are determined, and multiple trend components of blood viscosity change are screened from all blood coagulation characteristics based on the temporal dependencies of the individual blood coagulation characteristics.

[0054] In some embodiments, reference Figure 2 This figure is a thromboelastogram shown in some embodiments of the present application, wherein the thromboelastogram includes: a thromboelastogram curve and an envelope line, and the coagulation stage includes: a pre-coagulation stage, a thrombus formation stage, a thrombus maximum strength stage, and a thrombus dissolution stage. In other embodiments, the thromboelastogram can also be divided into other different stages according to actual needs, which is not limited here.

[0055] It should be noted that the division of coagulation stages in the present application can be achieved in the following manner, namely: first, by inputting the corrected thromboelastogram into the TEG5000 thromboelastogram, the TEG5000 thromboelastogram can automatically calculate and calculate various coagulation function test indicators (including coagulation reaction time, coagulation clotting time, coagulation formation rate and coagulation final strength) from the thromboelastogram, and then, the data segment corresponding to the coagulation reaction time in the thromboelastogram is used as the pre-coagulation stage, the data segment corresponding to the coagulation clotting time is used as the thrombus formation stage, the data segment after the thrombus formation stage until the final coagulation strength appears is used as the thrombus maximum strength stage, and the data segment after the thrombus maximum strength stage is used as the thrombus dissolution stage. In other embodiments, the coagulation stages can also be divided by other existing technologies, which are not limited here.

[0056] In some embodiments, determining multiple blood coagulation characteristics within a selected coagulation stage can be accomplished using the following steps:

[0057] determining blood coagulation characteristics based on an envelope corresponding to a selected coagulation stage and a thromboelastomeric curve corresponding to the selected coagulation stage;

[0058] determining a residual curve according to the blood coagulation characteristic;

[0059] If the residual curve is not a monotonic curve, the residual curve is used as a new thromboelastometry curve, and all envelopes of the residual curve are used as envelopes corresponding to the newly selected coagulation stage. The above steps of determining the residual curve based on the envelope corresponding to the selected coagulation stage and the thromboelastometry curve are repeated until the residual curve finally obtained is a monotonic curve, thereby obtaining multiple blood coagulation characteristics.

[0060] It should be noted that the step of determining the residual curve based on the envelope line and thrombus elasticity curve corresponding to the selected coagulation stage in this application includes: determining the blood coagulation characteristics based on the envelope line corresponding to the selected coagulation stage and the thrombus elasticity curve corresponding to the selected coagulation stage; and determining the residual curve based on the blood coagulation characteristics.

[0061] In some embodiments, determining the blood coagulation characteristics based on the envelope corresponding to the selected coagulation stage and the thromboelastomeric curve corresponding to the selected coagulation stage can be achieved by the following steps:

[0062] Determine the coagulation trend of blood based on the envelope corresponding to the selected coagulation stage;

[0063] determining a candidate characteristic curve based on the coagulation trend and the thromboelastometry curve corresponding to the selected coagulation stage;

[0064] determining a stationary characteristic of the candidate characteristic curve;

[0065] The smooth feature is compared with a preset feature threshold. If the smooth feature is greater than or equal to the feature threshold, the candidate characteristic curve is used as a new thromboelastometry curve, and the envelope of the residual curve is used as the envelope corresponding to the newly selected coagulation stage. The above steps of determining the smooth feature based on the envelope corresponding to the selected coagulation stage are repeated until the final smooth feature is less than the feature threshold. The candidate characteristic curve corresponding to the smooth feature less than the feature threshold is used as the blood coagulation feature.

[0066] It should be noted that the coagulation trend in this application is a curve that describes the elastic change trend of the blood coagulation process. In this application, the coagulation trend of blood can be determined based on the envelope corresponding to the selected coagulation stage. This can be achieved in the following way, namely: averaging all the envelopes corresponding to the selected coagulation stage and using the resulting curve as the coagulation trend.

[0067] It should be noted that the step of determining the smooth characteristics based on the envelope corresponding to the selected coagulation stage in this application includes: determining the coagulation trend of blood based on the envelope corresponding to the selected coagulation stage; determining the candidate characteristic curve based on the coagulation trend and the thrombus elastic curve corresponding to the selected coagulation stage; and determining the smooth characteristics of the candidate characteristic curve.

[0068] It should be noted that the candidate characteristic curve in the present application is a candidate curve in the process of determining the blood coagulation characteristics. As a preferred embodiment, the candidate characteristic curve is determined in the present application based on the coagulation trend and the thrombus elasticity curve corresponding to the selected coagulation stage. It can be achieved in the following way, namely: subtract the coagulation trend curve from the thrombus elasticity curve corresponding to the selected coagulation stage, and use the curve obtained after subtraction as the candidate characteristic curve.

[0069] In specific implementation, the stationary feature of the candidate characteristic curve can be determined in the following manner, namely: first, the number of zero-crossing points in the candidate characteristic curve is counted, then the number of extreme points in the candidate characteristic curve is counted, and then the difference between the number of zero-crossing points and the number of extreme points is taken, and finally, the difference is used as the stationary feature.

[0070] It should be noted that the smoothness characteristic in this application is a parameter value that reflects the smoothness of the curve fluctuation. The larger the smoothness characteristic, the more unstable the curve fluctuation. The smaller the smoothness characteristic, the smoother the curve fluctuation. In theory, the blood coagulation characteristic is a curve with smooth fluctuation. If the smoothness characteristic of the curve is large, it means that the curve is not a simple blood coagulation characteristic, but is mixed with other characteristics, such as the influence of temperature or the sampling error of the sensor.

[0071] In addition, it should be noted that the feature threshold in this application is usually preset to a smaller value. For example, in this application, the feature threshold is preset to 1. In other embodiments, the feature threshold can also be preset to other values, all of which fall within the scope of protection of this application and are not limited here.

[0072] It should be noted that the residual curve in the present application is the thrombus elasticity curve in the thrombus elastogram after removing the blood coagulation characteristics. As a preferred embodiment, the residual curve determined according to the blood coagulation characteristics in the present application can be implemented in the following manner, namely: the thrombus elasticity curve corresponding to the selected coagulation stage is subtracted from the curve corresponding to the blood coagulation characteristics, and the obtained curve is used as the residual curve.

[0073] In addition, it should be noted that, in the present application, a monotonic curve refers to a curve that is monotonically increasing or monotonically decreasing.

[0074] In some embodiments, reference Figure 3 This figure is an exemplary flow chart of determining trend components according to some embodiments of the present application. In the present application, screening multiple trend components of blood viscosity changes from all blood coagulation characteristics based on the temporal dependencies of the various blood coagulation characteristics can be achieved by the following steps, namely:

[0075] In step 1021, for each blood coagulation characteristic, a plurality of cumulative deviation sequences of each blood coagulation characteristic in different local windows are determined;

[0076] In step 1022, the average local deviation of each local window is determined based on all accumulated deviation sequences under each local window;

[0077] In step 1023, the temporal dependency of each blood coagulation characteristic is determined based on all the average local deviations;

[0078] In step 1024, all the time series dependencies are compared with a preset dependency threshold, and all the blood coagulation characteristics that are greater than the dependency threshold are regarded as trend components of blood viscosity change.

[0079] In a specific implementation, the following method can be used to sequentially determine the multiple cumulative deviation sequences of each blood coagulation characteristic in different local windows: first, a blood coagulation characteristic is selected as the selected blood coagulation characteristic, and multiple local windows of different sizes are preset. For each local window, the selected blood coagulation characteristic is divided into multiple local data segments according to the size of the local window (i.e., the selected blood coagulation characteristic is evenly divided into multiple local data segments of length N, where N is the size of the local window). Then, for each local data segment, the sum of the first n data in the local data segment is subtracted by n times the mean of the local data segment, and the resulting value is used as the nth cumulative deviation. All cumulative deviations are arranged in order of magnitude of n, and the resulting sequence is used as the cumulative deviation sequence of the local data segment. Then, a cumulative deviation sequence for each local data segment is obtained, thereby obtaining multiple cumulative deviation sequences of the blood coagulation characteristic in each local window.

[0080] It should be noted that the cumulative deviation sequence in the present application is a sequence composed of multiple cumulative deviations, wherein the cumulative deviation represents the cumulative degree of fluctuation of the blood coagulation characteristics at the corresponding moment. The larger the cumulative deviation, the greater the cumulative degree of fluctuation of the blood coagulation characteristics before the corresponding moment, and the smaller the cumulative deviation, the smaller the cumulative degree of fluctuation of the blood coagulation characteristics before the corresponding moment.

[0081] In a specific implementation, the average local deviation of each local window can be determined based on all cumulative deviation sequences under each local window in the following manner: first, a local window is selected as a selected window; for each cumulative deviation sequence under the selected window, first, the minimum value in the cumulative deviation sequence is subtracted from the maximum value in the cumulative deviation sequence, and the obtained value is used as the deviation range of the cumulative deviation sequence; then, the deviation range is divided by the standard deviation of the cumulative deviation sequence; then, the obtained quotient is used as the local deviation of the cumulative deviation sequence, and then the local deviation of each cumulative deviation sequence is obtained; the average value of all local deviations is used as the average local deviation of the selected window; and the average local deviation of the remaining local windows is continuously determined.

[0082] It should be noted that the average local deviation in this application is the average value of all local deviations of the blood coagulation characteristics in different local time periods, wherein the local deviation is a parameter indicating the degree of data deviation in a local time period of the blood coagulation characteristics. The larger the local deviation, the greater the degree of data deviation in a local time period of the blood coagulation characteristics, and the smaller the local deviation, the smaller the degree of data deviation in a local time period of the blood coagulation characteristics.

[0083] In specific implementation, the temporal dependence of each blood coagulation characteristic can be determined based on all the average local deviations in the following manner, namely: first, the size of the local window corresponding to each average local deviation is obtained, then the natural logarithm of the average local deviation is used as the dependent variable, and the size of the local window is used as the independent variable, and all the average local deviations and the size of the local window are fitted by linear regression in the prior art, and finally, the slope of the curve in the fitting result is used as the temporal dependence of the blood coagulation characteristic, thereby obtaining the temporal dependence of each blood coagulation characteristic.

[0084] It should be noted that the timing dependence in this application is a parameter value that represents the degree of temporal correlation between various data in the blood coagulation characteristics. The greater the timing dependence, the greater the degree of temporal correlation between various data in the blood coagulation characteristics. The smaller the timing dependence, the smaller the degree of temporal correlation between various data in the blood coagulation characteristics. Among them, the timing dependence is a value between zero and one. Generally speaking, the smaller the timing dependence, the more likely the corresponding blood coagulation characteristics are to be interfered by disordered noise or sensor errors.

[0085] It should be noted that the dependency threshold in this application is a value preset according to actual needs. The dependency threshold is usually preset to any value between zero and one. For example, the dependency threshold can be preset to 0.5 in this application.

[0086] It should be noted that the trend component in the present application is the component data with strong trend change characteristics in the thromboelastometry curve.

[0087] In step 103, the intelligent temperature sensor collects the external temperature changes in real time during the detection process, and identifies the temperature interference caused by the temperature changes in the selected coagulation stage on the subject's blood coagulation process based on the trend characteristics and all trend components of the temperature changes.

[0088] In specific implementation, the real-time collection of external temperature changes during the detection process by the intelligent temperature sensor can be achieved in the following manner, namely: the external temperature value during the detection process is collected by the intelligent temperature sensor at every preset sampling interval, all temperature values ​​are arranged in the order of collection, and the obtained sequence is used as the external temperature change during the detection process, wherein the starting time of the temperature change sampling is the same as the starting time of the thromboelastogram, and the sampling interval can be preset according to actual needs. For example, the sampling interval is preset to 0.1s in this application.

[0089] In some embodiments, identifying the temperature interference caused by the temperature change in the selected coagulation stage on the subject's blood coagulation process based on the trend characteristics of the temperature change and all trend components can be achieved by using the following steps:

[0090] determining a trend characteristic corresponding to the temperature change in a selected solidification stage;

[0091] Determine the similarity between the temporal dependence of each trend component and the trend characteristics;

[0092] The temperature interference on the blood coagulation process of the subject caused by the temperature change in the selected coagulation stage is screened out from all trend components according to all similarities.

[0093] In specific implementation, determining the trend characteristics corresponding to the temperature change in the selected solidification stage can be achieved by adopting the following steps, namely: first, obtaining the data segment corresponding to the temperature change in the selected solidification stage, then calculating the Hurst index of the data segment, and then using the Hurst index as the trend characteristics corresponding to the temperature change in the selected solidification stage.

[0094] It should be noted that the trend feature in this application is a parameter value that represents the long-term memory of the temperature change trend. The larger the trend feature, the stronger the long-term memory of the temperature change trend. The smaller the trend feature, the weaker the long-term memory of the temperature change trend.

[0095] In specific implementation, the following steps can be used to determine the similarity between the temporal dependency of each trend component and the trend feature, namely: for each trend component, the inverse of the difference between the temporal dependency of the trend component and the trend feature can be used as the similarity between the temporal dependency of the trend component and the trend feature, thereby obtaining the similarity between the temporal dependency of each trend component and the trend feature.

[0096] It should be noted that the similarity in this application is a parameter value that represents the degree of similarity between the changing trend of the trend component and the trend of temperature change. The greater the similarity, the greater the similarity between the changing trend of the trend component and the trend of temperature change. The smaller the similarity, the smaller the similarity between the changing trend of the trend component and the trend of temperature change.

[0097] In a specific implementation, the temperature interference on the subject's blood coagulation process caused by the temperature change in the selected coagulation stage is screened out from all trend components based on all similarities, which can be achieved by the following steps, namely: the trend component with the largest similarity is used as the temperature interference on the subject's blood coagulation process caused by the temperature change in the selected coagulation stage.

[0098] It should be noted that the temperature interference in this application is the component data that describes the interference caused by external temperature changes on the blood coagulation process.

[0099] In step 104, the phase change information of the vibration of the thromboelastometry probe during the detection process is collected in real time by the intelligent displacement sensor, and the elastic modulus change of the blood in the selected coagulation stage is determined based on the phase change information and the temperature interference, and the elastic modulus change of the blood in the remaining coagulation stages is further determined.

[0100] In a specific implementation, real-time acquisition of phase change information of the thromboelastometry probe vibration during the detection process by the intelligent displacement sensor can be achieved in the following manner: the intelligent displacement sensor acquires the horizontal displacement value of the thromboelastometry probe during the detection process at preset sampling intervals, arranges all displacement values ​​in the order of acquisition, and uses the obtained sequence as a displacement sequence; then, the phase value of each displacement value in the displacement sequence is calculated by the Hilbert transform in the prior art, and all the obtained phase values ​​are arranged in the order of acquisition of the corresponding displacement values, and the obtained sequence is used as the external phase change information during the detection process, wherein the start time of displacement value acquisition is the same as the start time of the thromboelastometry graph, and the sampling interval can be preset according to actual needs. For example, in this application, the sampling interval is preset to 0.1s.

[0101] In some embodiments, determining the change in elastic modulus of blood in a selected coagulation stage based on the phase change information and the temperature disturbance can be achieved by using the following steps:

[0102] determining an elastic component in the blood coagulation process based on the temperature disturbance and all trend components;

[0103] The change in elastic modulus of blood in a selected coagulation stage is determined based on the elastic component and the phase change information.

[0104] In specific implementation, determining the elastic component in the blood coagulation process based on the temperature interference and all trend components can be achieved in the following manner, namely: removing the temperature interference from all trend components, summing the remaining trend components, and using the obtained curve as the elastic component in the blood coagulation process.

[0105] It should be noted that the elastic component in the present application refers to the component in the thromboelastogram that only describes the elastic changes during the blood coagulation process.

[0106] In a specific implementation, determining the change in the elastic modulus of blood in a selected coagulation stage based on the elastic component and the phase change information can be achieved in the following manner: first, discretely sampling the elastic component to obtain a discrete sequence; then, obtaining a data segment corresponding to a selected coagulation stage of the phase change information; multiplying the discrete sequence by the data segment; and using the obtained sequence as the change in the elastic modulus of blood in the coagulation stage, wherein the interval of discrete sampling is the same as the sampling interval when collecting the phase change information.

[0107] It should be noted that the elastic modulus change in this application is a sequence describing the change in the elastic modulus of a blood sample during the blood coagulation process.

[0108] In step 105, the thromboelastogram is corrected based on all elastic modulus changes, and a test index of the subject's coagulation function is extracted from the corrected thromboelastogram.

[0109] In some embodiments, the correction of the thromboelastogram based on all elastic modulus changes can be achieved by the following steps:

[0110] Determine a correction curve diagram based on all elastic modulus changes;

[0111] An upper envelope and a lower envelope of the correction curve are determined, and a curve consisting of the upper envelope and the lower envelope is used as a corrected thromboelastogram.

[0112] In specific implementation, the correction curve diagram can be determined based on all elastic modulus changes in the following manner: all elastic modulus changes are rearranged into a sequence according to the order of the solidification stages, and then the rearranged sequence is fitted using the Lagrange interpolation method in the prior art, and finally, the fitted curve is used as the correction curve diagram.

[0113] It should be noted that the correction curve diagram in this application refers to the corrected thrombus elasticity curve in the thromboelastogram.

[0114] In specific implementation, the upper envelope and lower envelope of the correction curve graph can be determined in the following manner, namely: first, all the maximum points in the correction curve graph are extracted, and then all the maximum points are fitted into a curve by the cubic spline interpolation method in the prior art, and the fitted curve is used as the upper envelope of the correction curve graph; then, all the minimum points in the correction curve graph are extracted, and then all the minimum points are fitted into a curve by the cubic spline interpolation method in the prior art, and the fitted curve is used as the lower envelope of the correction curve graph.

[0115] In specific implementation, the test indicators of the coagulation function of the subject can be extracted from the corrected thromboelastogram in the following manner, namely: the corrected thromboelastogram can be input into the TEG5000 thromboelastogram, and the TEG5000 thromboelastogram can automatically calculate and extract various coagulation function test indicators (including coagulation reaction time, coagulation clotting time, coagulation formation rate and final coagulation strength) from the thromboelastogram. In other embodiments, the test indicators of the coagulation function of the subject can also be extracted from the corrected thromboelastogram by other existing technologies, which is not limited here.

[0116] In addition, in another aspect of the present application, in some embodiments, the present application provides a clinical testing system, which includes: a thromboelastometry instrument, an intelligent temperature sensor, and an intelligent displacement sensor. In addition, the clinical testing system in the present application also includes a test index extraction unit, reference Figure 4 , which is a schematic diagram of the structure of a test indicator extraction unit according to some embodiments of the present application. The test indicator extraction unit 400 includes: a collection module 401, a processing module 402 and an execution module 403, which are described as follows:

[0117] The collection module 401 in this application is mainly used to add an anticoagulant to the blood of the subject, obtain a blood sample, and instruct the thromboelastometry instrument to perform a thromboelastometry test on the blood sample to obtain a thromboelastometry map;

[0118] Processing module 402, in the present application, is primarily configured to select a coagulation stage in the thromboelastogram as a selected coagulation stage, determine multiple blood coagulation characteristics within the selected coagulation stage, and screen multiple trend components of blood viscosity change from all blood coagulation characteristics based on temporal dependencies of the individual blood coagulation characteristics;

[0119] It should be noted that the processing module 402 in the present application is also used to instruct the intelligent temperature sensor to collect the external temperature changes during the detection process in real time, and identify the temperature interference caused by the temperature changes in the selected coagulation stage on the subject's blood coagulation process based on the trend characteristics and all trend components of the temperature changes;

[0120] It should be noted that the processing module 402 in the present application is further configured to instruct the intelligent displacement sensor to collect phase change information of the thromboelastometry probe vibration in real time during the detection process, determine the change in the elastic modulus of the blood in the selected coagulation stage based on the phase change information and the temperature interference, and continue to determine the change in the elastic modulus of the blood in the remaining coagulation stages;

[0121] The execution module 403 in the present application is mainly used to correct the thromboelastogram based on all elastic modulus changes, and extract the test index of the subject's coagulation function from the corrected thromboelastogram.

[0122] In addition, the present application also provides a computer device, which includes a memory and a processor, wherein the memory stores code, and the processor is configured to obtain the code and execute the above-mentioned method for extracting test indicators of coagulation function.

[0123] In some embodiments, reference Figure 5, which is a schematic diagram of the structure of a computer device for implementing the method for extracting test indicators of coagulation function according to some embodiments of the present application. The method for extracting test indicators of coagulation function in the above embodiment can be Figure 5 The computer device 500 shown in FIG. 5 is implemented as shown in FIG. 5 . The computer device 500 includes at least one processor 501 , a communication bus 502 , a memory 503 , and at least one communication interface 504 .

[0124] The processor 501 may be a general-purpose central processing unit (CPU) or an application-specific integrated circuit (ASIC).

[0125] The communication bus 502 may be used to transmit information between the aforementioned components.

[0126] The memory 503 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, a random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, an optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk or other magnetic storage device, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto. The memory 503 may be independent and connected to the processor 501 via the communication bus 502. The memory 503 may also be integrated with the processor 501.

[0127] Memory 503 is used to store program code for executing the present invention, and is controlled by processor 501. Processor 501 is used to execute the program code stored in memory 503. The program code may include one or more software modules. The method for extracting test indicators for coagulation function in the above embodiment can be implemented by processor 501 and one or more software modules in the program code in memory 503.

[0128] The communication interface 504 uses any device such as a transceiver to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), etc.

[0129] In a specific implementation, as an example, a computer device may include multiple processors, each of which may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. A processor herein may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0130] The aforementioned computer device can be a general-purpose computer device or a dedicated computer device. In a specific implementation, the computer device can be a desktop computer, a portable computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. The embodiments of this application do not limit the type of computer device.

[0131] In addition, the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned method for extracting test indicators of coagulation function.

[0132] In summary, in the clinical testing system and method disclosed in the embodiment of the present application, first, an anticoagulant is added to the blood of the subject to obtain a blood sample, the thromboelastometry instrument is started to perform thromboelastometry on the blood sample to obtain a thromboelastometry; a coagulation stage in the thromboelastometry is selected as the selected coagulation stage, multiple blood coagulation characteristics within the selected coagulation stage are determined, and multiple trend components of blood viscosity changes are screened from all blood coagulation characteristics according to the time series dependence of each blood coagulation characteristic; the external temperature changes during the detection process are collected in real time by the intelligent temperature sensor, and based on the time series dependence of each blood coagulation characteristic, the temperature of the blood sample is detected. According to the trend characteristics of the temperature change and all trend components, the temperature interference caused by the temperature change in the selected coagulation stage to the blood coagulation process of the subject is identified; the phase change information of the vibration of the thrombelastometer probe during the detection process is collected in real time by the intelligent displacement sensor, and the elastic modulus change of the blood in the selected coagulation stage is determined according to the phase change information and the temperature interference, and the elastic modulus change of the blood in the remaining coagulation stages is further determined; the thromboelastogram is corrected based on all elastic modulus changes, and the test index of the subject's coagulation function is extracted from the corrected thromboelastogram.

[0133] Thus, the present application pre-segments the thrombelastogram and decomposes each coagulation stage obtained by the segmentation, thereby decomposing the thrombelastogram curve containing multiple vibration modes into multiple blood coagulation characteristics of a single vibration mode. Subsequently, the noise and error (i.e., blood coagulation characteristics with low temporal dependence) are removed by using the temporal dependence of the blood coagulation characteristics. The remaining blood coagulation characteristics are components that can reflect certain trend changes. Furthermore, all trend changes are compared with the trend characteristics of external temperature changes, and the trend components caused by temperature changes on blood coagulation (i.e., temperature interference) are filtered out. Finally, the remaining components are combined with the phase change information of the thrombelastometer probe vibration to refit the thrombelastogram curve for each coagulation stage. The refitted thrombelastogram removes the effects of temperature interference and sensor error, and ultimately, the test indicators of the subject's coagulation function are extracted from the refitted thrombelastogram curve. In summary, the present application can eliminate external interference in thrombelastogram detection, correct the thrombelastogram, and thereby improve the accuracy of coagulation function detection.

[0134] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0135] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A method for extracting test indicators of coagulation function, for use in a clinical testing system for extracting test indicators of coagulation function, the clinical testing system comprising: Thromboelastometer, intelligent temperature sensor and intelligent displacement sensor, characterized in that the method includes: adding an anticoagulant to the blood of the subject to obtain a blood sample, and activating the thromboelastometry instrument to perform a thromboelastometry test on the blood sample to obtain a thromboelastometry map; A coagulation stage in the thromboelastogram is selected as a selected coagulation stage, multiple blood coagulation characteristics within the selected coagulation stage are determined, and multiple trend components of blood viscosity change are screened from all blood coagulation characteristics according to the temporal dependencies of the respective blood coagulation characteristics; The intelligent temperature sensor collects the external temperature changes in real time during the detection process, and identifies the temperature interference caused by the temperature changes in the selected coagulation stage on the subject's blood coagulation process based on the trend characteristics and all trend components of the temperature changes; The intelligent displacement sensor is used to collect phase change information of the thromboelastometry probe vibration in real time during the detection process, and the elastic modulus change of the blood in the selected coagulation stage is determined based on the phase change information and the temperature interference, and the elastic modulus change of the blood in the remaining coagulation stages is further determined; The thromboelastogram is corrected based on all elastic modulus changes, and a test index of the subject's coagulation function is extracted from the corrected thromboelastogram.

2. The method according to claim 1, wherein Determining multiple blood coagulation characteristics within a selected coagulation stage specifically includes: determining blood coagulation characteristics based on the envelope and thromboelastometry curve corresponding to the selected coagulation stage; determining a residual curve according to the blood coagulation characteristic; If the residual curve is not a monotonic curve, the residual curve is used as a new thromboelastometry curve, and all envelopes of the residual curve are used as envelopes corresponding to the newly selected coagulation stage. The above steps of determining the residual curve based on the envelope corresponding to the selected coagulation stage and the thromboelastometry curve are repeated until the residual curve finally obtained is a monotonic curve, thereby obtaining multiple blood coagulation characteristics.

3. The method according to claim 1, wherein According to the temporal dependence of each blood coagulation characteristic, multiple trend components of blood viscosity change are screened out from all blood coagulation characteristics, including: For each blood coagulation characteristic, determining a plurality of cumulative deviation sequences of each blood coagulation characteristic in different local windows; Determine the average local deviation of each local window according to all accumulated deviation sequences under each local window; determining a temporal dependency of each of the blood coagulation characteristics based on all average local deviations; All time series dependencies are compared with a preset dependency threshold, and all blood coagulation characteristics greater than the dependency threshold are regarded as trend components of blood viscosity changes.

4. The method according to claim 1, wherein Identifying the temperature interference on the blood coagulation process of the subject caused by the temperature change in the selected coagulation stage according to the trend characteristics of the temperature change and all trend components specifically includes: determining a trend characteristic corresponding to the temperature change in a selected solidification stage; Determine the similarity between the temporal dependence of each trend component and the trend characteristics; The temperature interference on the blood coagulation process of the subject caused by the temperature change in the selected coagulation stage is screened out from all trend components according to all similarities.

5. The method according to claim 1, wherein Determining the change in elastic modulus of blood in a selected coagulation stage according to the phase change information and the temperature interference specifically includes: determining an elastic component in the blood coagulation process based on the temperature disturbance and all trend components; The change in elastic modulus of blood in a selected coagulation stage is determined based on the elastic component and the phase change information.

6. The method according to claim 1, wherein Correcting the thromboelastogram based on all elastic modulus changes specifically includes: Determine a correction curve diagram based on all elastic modulus changes; An upper envelope and a lower envelope of the correction curve are determined, and a curve consisting of the upper envelope and the lower envelope is used as a corrected thromboelastogram.

7. The method according to claim 1, wherein The test indicators of coagulation function include: coagulation reaction time, coagulation clotting time, coagulation formation rate and final coagulation strength.

8. A clinical testing system comprising a thrombelastometer, an intelligent temperature sensor, an intelligent displacement sensor, and a test index extraction unit, characterized in that: The test indicator extraction unit includes: a collection module, configured to add an anticoagulant to the blood of the subject to obtain a blood sample, and then instruct the thromboelastometry instrument to perform a thromboelastometry test on the blood sample to obtain a thromboelastometry map; a processing module, configured to select a coagulation stage in the thromboelastogram as a selected coagulation stage, determine a plurality of blood coagulation characteristics within the selected coagulation stage, and screen a plurality of trend components of blood viscosity change from all the blood coagulation characteristics based on temporal dependencies of the respective blood coagulation characteristics; The processing module is further configured to instruct the intelligent temperature sensor to collect real-time temperature changes of the outside world during the detection process, and to identify temperature interference caused by the temperature changes in the selected coagulation stage on the subject's blood coagulation process based on the trend characteristics and all trend components of the temperature changes; The processing module is further configured to instruct the intelligent displacement sensor to collect phase change information of the thromboelastometry probe vibration in real time during the detection process, determine the change in elastic modulus of the blood in the selected coagulation stage based on the phase change information and the temperature interference, and continue to determine the change in elastic modulus of the blood in the remaining coagulation stages; The execution module is used to correct the thromboelastogram based on all elastic modulus changes and extract a test index of the subject's coagulation function from the corrected thromboelastogram.

9. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores codes, and the processor is configured to obtain the codes and execute the method for extracting test indicators of coagulation function according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for extracting test indicators of coagulation function according to any one of claims 1 to 7 is implemented.

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