Method for quantifying blood coagulation factor activity value, and information processing device

Abstract

The present invention quickly quantifies (estimates) a blood coagulation factor activity value of a test sample using fewer, well-defined parameters than before by analyzing a blood coagulation reaction curve obtained in normal medical care without performing a dedicated additional test for quantifying the blood coagulation factor activity value. Quantification of a blood coagulation factor activity value of a test sample according to the present disclosure includes acquiring a blood coagulation reaction curve showing temporal changes in light intensity due to a coagulation reaction of a reaction solution obtained by mixing a test sample with a reagent. The quantification is performed on the basis of a comparison of a difference between a rise time of the blood coagulation reaction curve and a time corresponding to a point at which the light intensity changes by X% against a calibration curve obtained from blood coagulation reaction curves of a set of samples with known blood coagulation factor activity values (the relationship between the blood coagulation activity value and the difference between the rise time of a known blood coagulation reaction curve and a time at which the light quantity changes by X%).

Description

Method for quantifying blood coagulation factor activity value and information processing device

[0001] The present disclosure relates to a method for quantifying blood coagulation factor activity levels and an information processing device.

[0002] Blood coagulation tests are performed for purposes such as understanding the pathology of the blood coagulation and fibrinolysis system, diagnosing DIC (disseminated intravascular coagulation), confirming the effectiveness of thrombus treatment, diagnosing hemophilia, etc. In particular, blood clotting time measurements involve mixing a sample with a reagent and measuring the time it takes for a fibrin clot to form (hereinafter referred to as blood clotting time). Congenital or acquired abnormalities in blood coagulation ability result in prolonged blood clotting time. A deficiency in blood clotting factors is one cause of prolonged blood clotting time, and the severity (mild, moderate, severe) of hemophilia A is diagnosed based on the level of blood clotting factor VIII activity, while the severity of hemophilia B is diagnosed based on the level of blood clotting factor IX activity.

[0003] A one-stage coagulation assay has traditionally been used to measure blood coagulation factor activity. In this method, for example, normal plasma diluted 5-640 times is first mixed with plasma lacking the blood coagulation factor to be quantified, phospholipids, a coagulation activator (e.g., ellagic acid, silica, kaolin), and calcium chloride, and the blood coagulation time is measured to obtain a calibration curve showing the relationship between blood coagulation factor activity and blood coagulation time. Next, test plasma diluted 5 times is then mixed with plasma lacking the blood coagulation factor to be quantified, phospholipids, a coagulation activator (e.g., ellagic acid, silica, kaolin), and calcium chloride, and the blood coagulation time is measured. This blood coagulation time is then substituted into a previously prepared calibration curve to quantify the blood coagulation factor activity of the test plasma. Thus, in order to obtain blood coagulation factor activity, conventionally, the one-stage coagulation assay must be performed as an additional test separate from routine clinical practice.

[0004] Recently, methods for evaluating blood coagulation factor activity levels by analyzing blood coagulation reaction curves have been proposed as methods that do not require such additional testing. Here, the blood coagulation reaction curve in question is a waveform obtained by optical measurement, recording the change in turbidity over time associated with the formation of fibrin clots. For example, Patent Document 1 discloses a method for outputting information about bleeding tendency using time-related parameters extracted from a blood coagulation reaction curve, a first-derivative coagulation curve, and a second-derivative coagulation curve, which are derived from the blood coagulation reaction curve, as well as the absolute value of the maximum value of the first derivative (|min1|) and the absolute values ​​of the maximum and minimum values ​​of the second derivative (|min2|, |max1|). Patent Document 2 also discloses a method for determining the activity level of blood coagulation factor VIII or blood coagulation factor IX, i.e., the severity of hemophilia A or hemophilia B, using 10 or more parameters obtained from the first-derivative and second-derivative coagulation curves of the blood coagulation reaction curve. Furthermore, Patent Document 3 discloses a method for calculating the concentration (activity value) of blood coagulation factor VIII or blood coagulation factor IX using the time difference between the minimum time and the maximum time at which the coagulation reaction rate becomes S% when the maximum coagulation reaction rate is set to 100% in a coagulation reaction rate curve (first derivative curve) calculated from a blood coagulation reaction curve corrected based on the maximum value of the coagulation reaction amount.

[0005] Japanese Patent Application Laid-Open No. 2022-145224 International Publication No. 2020 / 158948 Patent No. 7235282

[0006] T. Matsumoto et al., Clot waveform analysis using CS-2000i(TM) distinguishes between very low and absent levels of factor VIII activity in patients with severe haemophilia A, Haemophilia, Volume 23(2022) pp. e427-e435

[0007] However, the method of Patent Document 1 uses a combination of parameters obtained from three types of curves, which results in a problem of a complicated evaluation method and procedure. Furthermore, the method of Patent Document 2 also uses a large number of parameters, which results in a complicated evaluation method and procedure. Patent Documents 1, 2, and 3, for example, do not mention quantifying blood coagulation factor activity values ​​using only parameters extracted from the clot waveform. Patent Document 3 does not use a large number of parameters, but the "S%" condition used for evaluation is set to 5 to 20%, and is not uniquely defined, which results in a problem of the user not being able to clearly identify the optimal condition.

[0008] In view of this situation, the present disclosure proposes a technology for rapidly quantifying blood coagulation factor activity values ​​using fewer and clearer parameters than conventional methods by analyzing blood coagulation reaction curves obtained in routine medical practice, without the need for additional dedicated tests for quantifying blood coagulation factor activity values.

[0009] In order to solve the above problems, the present disclosure provides a method for obtaining a blood coagulation reaction curve to be quantified, the method showing the change in light intensity over time due to the coagulation reaction of a reaction solution produced by mixing a test specimen made of plasma obtained by separating blood from a subject with a reagent; and extracting (i-1) a first time width which is the difference between the rise time and the time at which the change in light intensity reaches a predetermined ratio in the blood coagulation reaction curve to be quantified, or (i-2) a second time width which is the difference between the time at which a bimodal peak occurs or the time at which a main peak and a shoulder peak occur in a first derivative curve of the blood coagulation reaction curve to be quantified, or (i-3) a third time width which is the difference between any two times at which multiple extreme values ​​are taken in a second derivative curve of the blood coagulation reaction curve to be quantified; (ii-1) quantifying the blood coagulation factor activity value of the test sample based on the first time width and a known time parameter which is the difference between the rise time and the time at which the change in light intensity reaches the predetermined ratio in a blood coagulation reaction curve of a sample group whose blood coagulation factor activity value is known, or based on the second time width and a known time parameter which is the difference between the time at which a bimodal peak occurs or the time at which a main peak and a shoulder peak occur in a first derivative curve of a blood coagulation reaction curve of a sample group whose blood coagulation factor activity value is known, or based on the third time width and a known time parameter which is the difference between the time at which the extrema appear in the third time width and a second derivative curve of a blood coagulation reaction curve of a sample group whose blood coagulation factor activity value is known.

[0010] The present disclosure also provides an information processing device for quantifying blood coagulation factor activity values ​​of a test specimen made of plasma obtained by separating the blood of a test subject, the information processing device comprising: a storage device for storing a program for quantifying the blood coagulation factor activity values; and a computer for reading and executing the program from the storage device, wherein the computer performs the following processes: a process for acquiring a blood coagulation reaction curve showing a change in light intensity over time due to a coagulation reaction of a reaction solution produced by mixing the test specimen with a reagent; and a process for extracting: (i-1) a first time width which is the difference between the rise time and the time of a point where the change in light intensity reaches a predetermined ratio in the blood coagulation reaction curve of the target to be quantified; (i-2) a second time width which is the difference in the time at which a bimodal peak occurs or the difference in the time at which a main peak and a shoulder peak occur in a first derivative curve of the blood coagulation reaction curve of the target to be quantified; and (i-3) a third time width which is the difference between any two times at which a plurality of extreme values ​​are obtained in a second derivative curve of the blood coagulation reaction curve of the target to be quantified. (ii-1) quantifying the blood coagulation factor activity value of the test sample based on a known time parameter which is the difference between the rise time and the time at which the change in light intensity reaches the predetermined ratio in a blood coagulation reaction curve of a sample group whose blood coagulation factor activity value is known, and the first time width; or (ii-2) quantifying the blood coagulation factor activity value of the test sample based on a known time parameter which is the difference between the time at which a bimodal peak occurs or the time at which a main peak and a shoulder peak occur in a first-order derivative curve of a blood coagulation reaction curve of a sample group whose blood coagulation factor activity value is known, and the second time width; or (ii-3) quantifying the blood coagulation factor activity value of the test sample based on a known time parameter which is the difference between two times corresponding to the order of appearance of the extreme values ​​constituting the third time width in a second-order derivative curve of a blood coagulation reaction curve of a sample group whose blood coagulation factor activity value is known, and the third time width.

[0011] Further features related to the present disclosure will become apparent from the description of this specification and the accompanying drawings. Also, aspects of the present disclosure are achieved and realized by the elements and combinations of various elements and the aspects of the following detailed description and the appended claims. The description of this specification is merely exemplary and does not limit the scope or application of the claims of the present disclosure in any way.

[0012] According to the present disclosure, it is possible to quantify the blood coagulation factor activity value of a test sample more quickly than by the conventional one-stage coagulation method, by using a small number of time-related parameters extracted from a blood coagulation reaction curve or its derivative curve, which shows the change in light intensity over time due to the blood coagulation reaction of a reaction solution produced by mixing a test sample with a reagent.

[0013] 1 is a diagram showing an example of a blood coagulation reaction curve. FIG. 1 is a diagram showing an example in which only the slope of a blood coagulation reaction curve changes while the rising point remains fixed when blood coagulation factor activity decreases. FIG. 2 is a diagram showing an example of a group of blood coagulation reaction curves obtained from samples with different blood coagulation factor VIII activity levels. FIG. 3 is a diagram showing the relationship between the time of the rising point extracted from the blood coagulation reaction curve and the blood coagulation factor VIII activity level, the relationship between the blood coagulation time when the change in light intensity becomes 50% extracted from the blood coagulation reaction curve and the blood coagulation factor VIII activity level, and the relationship between the time obtained by subtracting the time of the rising point from the blood coagulation time when the change in light intensity becomes 50% and the blood coagulation factor VIII activity level. FIG. 4 is a diagram showing the relationship between a first time width and the blood coagulation factor VIII activity level. FIG. 5 is a diagram showing an example of the overall configuration of the automatic analyzer of Example 1. FIG. 6 is a diagram showing a flowchart of a quantification program for blood coagulation factor activity levels of Example 1. FIG. 7 is a diagram showing the relationship between the analysis unit, PC, and communication interface of Example 1, and an example of displaying the quantification results of the blood coagulation factor activity levels of test samples on the display unit. FIG. 8 is a diagram showing the relationship between a first time width and the blood coagulation factor IX activity level. 1 is a diagram showing an example of a first derivative curve for a blood coagulation reaction curve of a blood coagulation factor VIII-deficient sample. 2 is a diagram showing an example in which a shoulder peak occurs at a measurement time earlier than the occurrence time of the main peak. 3 is a diagram showing an example in which a shoulder peak occurs at a measurement time later than the occurrence time of the main peak. 4 is a diagram showing examples of first derivative curves obtained using samples with different blood coagulation factor VIII activity levels. 5 is a diagram showing the relationship between a second time width and blood coagulation factor VIII activity levels. 6 is a diagram showing a flowchart of a quantification program for blood coagulation factor activity levels in Example 2. 7 is a diagram showing examples of a blood coagulation curve, a first derivative curve, and a second derivative curve, where the first derivative curve is clearly bimodal and the level of the earlier peak on the vertical axis is higher. 8 is a diagram showing examples of a blood coagulation curve, a first derivative curve, and a second derivative curve, where the first derivative curve is clearly bimodal and the level of the later peak on the vertical axis is higher. 9 is a diagram showing examples of a blood coagulation curve, a first derivative curve, and a second derivative curve, where the first derivative curve exhibits a shoulder peak and the time at which the shoulder peak occurs is later than the time at which the main peak occurs.1 is a diagram showing examples of a blood coagulation curve, a first derivative curve, and a second derivative curve, in which the first derivative curve exhibits a shoulder peak and the time at which the shoulder peak appears is earlier than the time at which the main peak appears. FIG. 2 is a diagram showing examples of a blood coagulation curve, a first derivative curve, and a second derivative curve obtained from a sample in which the first derivative curve is unimodal. FIG. 3 is a diagram showing examples of a group of second derivative curves obtained from samples with different blood coagulation factor VIII activity levels. FIG. 4 is a diagram showing an example of a time width at which the third time width is a maximum, and a diagram showing the relationship between the third time width and the blood coagulation factor VIII activity level. FIG. 5 is a diagram showing an example of a time width at which the third time width is a minimum, and a diagram showing the relationship between the third time width and the blood coagulation factor VIII activity level. FIG. 6 is a diagram showing a flowchart of a program for quantifying blood coagulation factor activity levels in Example 3. FIG. 7 is a diagram showing an example in which the conceptual diagrams of the first time width described in Example 1, the second time width described in Example 2, and the third time width described in Example 3 are organized.

[0014] Hereinafter, embodiments and examples of the present disclosure will be described with reference to the accompanying drawings. In the accompanying drawings, functionally identical elements may be denoted by the same numerals. Note that the accompanying drawings show embodiments and implementation examples according to the principles of the present disclosure, but these are intended to aid in understanding the present disclosure and are not to be used to interpret the present disclosure in a limiting manner. The descriptions in this specification are merely typical examples and are not intended to limit the scope or application of the present disclosure in any way.

[0015] Although the present embodiment has been described in sufficient detail to enable those skilled in the art to practice the present disclosure, it should be understood that other implementations and forms are possible, and that changes in configuration and structure and substitutions of various elements are possible without departing from the scope and spirit of the technical ideas of the present disclosure. Therefore, the following description should not be interpreted as being limited thereto.

[0016] Example 1 In Example 1, blood coagulation factor activity values ​​are quantified using time-related parameters extracted from a blood coagulation reaction curve.

[0017] The specimens subject to the present disclosure are not particularly limited as long as they are specimens derived from a subject that undergo a blood coagulation reaction. A specimen consisting of plasma obtained by separating blood collected from a subject is preferred. Furthermore, the reagents used to obtain a blood coagulation reaction curve are not particularly limited as long as they are reagents for measuring the activated partial thromboplastin time (APTT). Furthermore, the apparatus for obtaining a blood coagulation reaction curve is not particularly limited as long as it is capable of measuring the change in light intensity (light intensity is an index including turbidity) of the reaction solution over time due to the blood coagulation reaction. The reagent used to measure the blood coagulation reaction curve shown in this example may be, for example, the Coagpia APTT-N (manufactured by Sekisui Medical Co., Ltd.). Furthermore, the apparatus may be, for example, the Hitachi Automated Analyzer 3500 (manufactured by Hitachi High-Tech Corporation).

[0018] <Considerations on Blood Coagulation Reaction Curves> Figure 1 is a diagram showing an example of a blood coagulation reaction curve. In Figure 1, the horizontal axis represents measurement time, and the vertical axis represents light intensity. The light intensity here represents scattered light intensity. Furthermore, T1 in Figure 1 represents the time at which the blood coagulation reaction curve rises, and T2 represents the time at which the light intensity changes by X% of the total change in light intensity. T2 can also be expressed as the blood coagulation time. In the present disclosure, the value of the change in light intensity (X%) can range from 10% to 90%, but Figure 1 shows an example in which a suitable change in light intensity is 50%.

[0019] It is known that the blood clotting time (T2) changes depending on the activity value of a blood coagulation factor, as shown in the CT graph in FIGURE 2 of Non-Patent Document 1. However, Non-Patent Document 1 does not describe how the time to the rising point (T1) changes, and it was unclear whether, when blood coagulation factor activity decreases, the rising point (T1) remains fixed and only the slope of the blood coagulation reaction curve changes, causing the blood clotting time to extend (a conceptual diagram is shown in FIG. 2), or whether the rising point (T1) also changes depending on the activity value of a blood coagulation factor.

[0020] Therefore, the inventors confirmed that not only the slope of the blood coagulation reaction curve but also the time to the rising point (T1) varies depending on the blood coagulation factor activity value. Figure 3 shows a group of blood coagulation reaction curves obtained from samples with different blood coagulation factor VIII activity values. Here, the samples with different blood coagulation factor VIII activity values ​​were prepared by mixing commercially available Factor VIII Deficient Plasma (manufactured by Precision BioLogic, Inc.) and Normal Reference Plasma (manufactured by Precision BioLogic, Inc.) at different ratios. Figure 3 shows that as the blood coagulation factor VIII activity value decreases, the time to the rising point (T1) becomes slower, and the time to the point where the change in light intensity reaches X% (T2) also becomes slower.

[0021] 4 shows graph A, which represents the relationship between the rising point time extracted from the blood coagulation reaction curve of FIG. 3 and the blood coagulation factor VIII activity value, and graph B, which represents the relationship between the blood coagulation time extracted from the blood coagulation reaction curve when the change in light intensity reaches 50% and the blood coagulation factor VIII activity value (the vertical and horizontal axes are logarithmic). In FIG. 4, graph A and graph B have different slopes. If both graphs have the same slope, or if one graph has no slope, such as y = a (a is a constant), extracting the difference between the two graphs is meaningless. However, in this case, since graph A and graph B have different slopes, if the difference between the rising point time and the time when the change in light intensity reaches X% is extracted and used as the first time width, it is believed that the first time width will be a feature that more accurately reflects the influence of the blood coagulation factor activity value in the sample than either the rising point time or the time when the change in light intensity reaches X% alone. For example, the difference data between graphs A and B is graph C in Figure 4, and the slope of graph C is greater than the slopes of graphs A and B. Therefore, when quantifying the blood coagulation factor activity value in a sample using the values ​​on the vertical axis, using graph C, which has a greater slope, as the calibration curve allows changes in the values ​​on the vertical axis to be more sensitively reflected in the blood coagulation factor activity value than when graphs A or B are used, thereby enabling more accurate quantification.

[0022] FIG. 5 is a graph showing the relationship between a first time interval extracted from the blood coagulation reaction curves of multiple samples with known blood coagulation factor VIII activity levels and blood coagulation factor VIII activity levels (the vertical and horizontal axes are expressed in logarithmic notation). The graph in FIG. 5 shows an example in which the first time interval is the difference between the time at the rising point of the blood coagulation reaction curve and the time at which the light intensity reaches 50%. Using the graph in FIG. 5 as a calibration curve makes it possible to quantify the blood coagulation factor VIII activity level of a test sample with an unknown blood coagulation factor VIII activity level. The calibration curve may be, for example, a curve approximated to the data in the graph in FIG. 5 . In the example of FIG. 5 , the data is linear in a double logarithmic graph, so a curve approximated by a power function (y = a x b) can be used, where a and b are calibration factors.

[0023] The following provides a specific explanation of an automatic analyzer for obtaining a blood coagulation reaction curve, a method for obtaining a blood coagulation reaction curve, a program for quantifying blood coagulation factor activity values, and the like.

[0024] <Configuration and Operation Examples of Automated Analyzer 100> The following describes the automated analyzer 100 used to acquire a blood coagulation reaction curve. Fig. 6 is a diagram showing an example of the overall configuration of the automated analyzer 100 that can be used in common in each embodiment. Here, basic device operations will be described using Fig. 6, but are not limited to the following example.

[0025] 6, the automatic analyzer 100 includes an analysis unit 130, an operation computer 118, a storage unit 119, and a control computer 120. The analysis unit 130 is generally composed of a specimen dispensing mechanism 101, a specimen disk 102, a reagent dispensing mechanism 106, a reagent disk 107, a reaction vessel stock unit 111, a reaction vessel transport mechanism 112, a detection unit 113, and a reaction vessel disposal unit 117. In order to improve processing capacity, the automatic analyzer 100 may be provided with an incubator 122 without a detector for warming specimens before adding a measurement start reagent.

[0026] The specimen dispensing mechanism 101 aspirates specimens 103a contained in specimen containers 103 arranged on a specimen disk 102 that rotates clockwise and counterclockwise, and dispenses the specimens into reaction containers 104. The specimen dispensing mechanism 101 performs the aspirating and dispensing operations of the specimen by the operation of a specimen syringe pump 105 controlled by a control computer 120.

[0027] The reagent dispensing mechanism 106 aspirates a reagent 108a contained in a reagent container 108 arranged on a reagent disk 107 and dispenses the reagent into a reaction container 104. The reagent dispensing mechanism 106 performs the aspirating and dispensing operations of the reagent by the operation of a reagent syringe pump 110 controlled by a control computer 120.

[0028] A reagent heating mechanism 109 is built into the reagent dispensing mechanism 106. The temperature of the reagent 108a aspirated by the reagent dispensing mechanism 106 is raised to an appropriate temperature (predetermined temperature) by the reagent heating mechanism 109, which is controlled by a control computer 120.

[0029] The reaction vessel transport mechanism 112 transports and sets the reaction vessel 104. The reaction vessel transport mechanism 112 holds the reaction vessel 104 and rotates it horizontally, thereby transporting and setting the reaction vessel 104 from the reaction vessel stock section 111 to the reaction vessel setting section 114 of the detection unit 113.

[0030] The detection unit 113 has one or more reaction vessel mounting sections 114 (one is shown as an example in this embodiment) for mounting the reaction vessel 104, and measures the light intensity of the reaction solution (a mixture of the sample 103a and the reagent 108a) in the reaction vessel 104 inserted in the reaction vessel mounting section 114. The detection unit 113 controls the temperature of the reaction solution in the reaction vessel 104 inserted in the reaction vessel mounting section 114 to, for example, 37°C. Note that while this embodiment shows a case where one detection unit 113 is provided, a configuration having multiple detection units 113 may also be used. An example of the detection principle of the detection unit 113 is described below. Light irradiated from the light source 115 is scattered by the reaction solution in the reaction vessel 104. The detection section (optical sensor) 116 receives the scattered light scattered by the reaction solution in the reaction vessel 104. For example, a halogen lamp or an LED is used as the light source 115. The detection section (optical sensor) 116 is composed of a photodiode or the like. The signal received by the detection section (optical sensor) 116 is converted into a digital light quantity value by an A / D converter 121, and is input to the control computer 120 as blood coagulation reaction curve data (coagulation reaction data showing the change in the detected light quantity over time), and is then stored in the memory section 119. The operation of the detection unit 113 is controlled by the control computer 120. Here, a detector using scattered light is used, but there are also other detectors, such as those using transmitted light.

[0031] The reaction vessel transport mechanism 112 holds the reaction vessel 104 after measurement has been completed, and discards it into a reaction vessel discarding unit 117 .

[0032] The control computer 120 is an information processing device having a computer system including a processor, memory, etc. The control computer 120 not only controls the operations of the automated analyzer 100, such as dispensing the sample 103a and the reagent 108a, transferring the reaction vessel 104, and discarding the reaction vessel 104, but also calculates the blood clotting time and rise time from the measured values ​​of light intensity that change over time in response to the clotting reaction of the reaction solution (blood clotting reaction curve data), creates calibration curves and calculates calibration factors for use in quantifying blood clotting factor activity values, and quantifies blood clotting factor activity values. The calculated blood clotting time and rise time, and the quantified blood clotting factor activity values ​​are output to the display unit 118c and stored in the memory unit 119. These results may also be printed out by a printer 123 via the operation computer 118.

[0033] The memory unit 119 is connected to the control computer 120 and stores programs such as a control program, a measurement program, a calibration curve generation program, and a blood coagulation factor activity quantification program, as well as measured blood coagulation reaction curve data, calibration curve information, and blood coagulation factor activity quantification results. The various programs are read and executed in response to requests input to the operation computer 118 or requests transmitted from the communication interface 124. Input to the operation computer 118 may be made by touching the display unit 118c or via the connected keyboard 118b. Alternatively, input may be made by selecting items displayed on the display unit 118c with the mouse 118a. The blood coagulation reaction curve data, calibration curve information, and blood coagulation factor activity quantification results stored in the memory unit 119 are output to the display unit 118c. Alternatively, they may be sent to the communication interface 124 and transmitted to the outside, or printed by the printer 123 as needed. The communication interface 124 is connected to, for example, a network within a hospital, and communicates with a hospital information system (HIS) and a laboratory information system (LIS).

[0034] As described above, the blood coagulation factor activity value of the test sample is quantified by calling up the blood coagulation factor activity value quantification program and the blood coagulation reaction curve data of the test sample stored in the memory unit 119 into the control computer 120. Alternatively, the blood coagulation reaction curve data of the test sample may be transferred to the analysis computer 125 that executes the blood coagulation factor activity value quantification program, and the analysis computer 125 may quantify the blood coagulation factor activity value of the test sample and display the results on the screen of the analysis computer 125. Alternatively, the waveform data stored in the memory unit 119 may be written to another external storage medium or the like via the control computer 120 and the operation computer 118, and an independent analysis computer having the blood coagulation factor activity value quantification program may read the written blood coagulation reaction curve data and quantify the blood coagulation factor activity value of the test sample.

[0035] <Method of Obtaining a Blood Coagulation Reaction Curve> Next, the analysis operation of the blood coagulation time item and the acquisition of the blood coagulation reaction curve will be described. The blood coagulation time item in this embodiment is the activated partial thromboplastin time (APTT) item.

[0036] First, the operator (user) sets the parameters required for the analysis. To set the parameters, the desired analysis item, sample volume, reagent volume, output unit (seconds: unit of APTT clotting time), etc. are input into the automated analyzer. After setting the parameters, the operator places the sample container 103 and reagent container 108 containing the sample 103a and reagent 108a, respectively, on the sample disk 102 and reagent disk 107, and then performs the analysis. The reagent 108a can be, for example, a commercially available APTT measurement reagent.

[0037] <Analysis Operation for APTT Item> Next, the analysis operation for the APTT item will be described. In the automated analyzer 100, the sample dispensing mechanism 101 dispenses a sample 103a into an empty reaction vessel 104 housed in the reaction vessel stock section 111. The reaction vessel 104 containing the sample 103a is moved (transported) by the reaction vessel transport mechanism 112 to the reaction vessel installation section 114 of the detection unit 113. The first reagent contains an activator such as ellagic acid or kaolin. The first reagent is aspirated from the reagent vessel 108 by the reagent dispensing mechanism 106 and heated to an appropriate temperature by the reagent heating mechanism 109. The temperature at this time is preferably 37°C. The heated first reagent is then dispensed into the reaction vessel 104 containing the sample 103a that has already been placed in the reaction vessel installation section 114. The mixture of the sample 103a and the first reagent is temperature-controlled within the reaction vessel 104. The temperature at this time is also preferably 37°C. At this time, the mixture of the specimen 103a and the first reagent may be stirred by a stirring mechanism (not shown). The second reagent is a calcium chloride solution, aspirated from the reagent container 108 by the reagent dispensing mechanism 106 and heated to an appropriate temperature by the reagent heating mechanism 109. The temperature at this time is preferably 37°C. The heated second reagent is then dispensed into the reaction container 104 containing the mixture of the specimen 103a and the first reagent already installed in the reaction container installation unit 114. Before the second reagent is dispensed, the mixture of the specimen 103a and the first reagent is temperature-controlled for a certain period of time, preferably 180 seconds. Simultaneously with the start of dispensing the second reagent, the change in turbidity over time of the reaction solution, which is the mixture of the specimen 103a and the first and second reagents, is optically measured, resulting in a blood coagulation reaction curve. The measurement ends when the coagulation reaction is completed (when no change in turbidity is observed). Alternatively, the measurement ends after a certain period of time has elapsed. The certain period of time is, for example, 5 minutes. The optically measured change in turbidity over time is input into the storage unit 119 via the control computer 120 as a blood coagulation reaction curve.

[0038] An example of a blood coagulation reaction curve for the APTT item is shown in Figure 1, where the horizontal axis represents measurement time and the vertical axis represents light intensity. Figure 1 shows an example of a clot waveform in the APTT item for Factor VIII Deficient Plasma (Precision BioLogic, Inc.), a commercially available sample with a blood coagulation factor VIII activity level of less than 1%, with the vertical axis representing scattered light intensity.

[0039] <Quantification Program for Blood Coagulation Factor Activity Values> Figure 7 is a flowchart for explaining the quantification process for blood coagulation factor activity values, which is executed by executing a quantification program for blood coagulation factor activity values. The computer system of the control computer 120 executes the quantification program for the blood coagulation factor activity values ​​of the sample, thereby quantifying the blood coagulation factor activity values ​​of Example 1. A specific description will be given with reference to Figure 7. Each step in the flowchart of Figure 7 may be executed by the control computer 120, the operation computer 118, the analysis computer 125, or another computer on the network. Here, an example in which the computer system of the control computer 120 executes each step will be described.

[0040] (i) Step S701: The control computer 120 reads the blood coagulation curve data obtained by measuring the blood coagulation reaction of the test sample. Specific analytical operations for obtaining the blood coagulation curve are as described above in <Method for obtaining a blood coagulation curve>.

[0041] (ii) Step S702: The control computer 120 performs noise processing on the blood coagulation reaction curve data. Here, noise processing may be, for example, smoothing processing using a moving average process, an approximation curve generated using an approximation formula that can maintain the shape of the blood coagulation reaction curve, or a combination of these. Note that the processing of step S702 may be omitted and may be performed as needed. If the processing of step S702 is omitted, the curve data used in step S703 may be the blood coagulation reaction curve data read in step S701. If the processing of step S702 is performed, the curve data used in step S703 may be data that has been subjected to noise processing, such as an approximation curve generated using an approximation formula.

[0042] (iii) Step S703: The control computer 120 extracts the time of the rising point of the blood coagulation reaction curve and the time of the point where the change in light intensity is X% of the total change in light intensity, where X% is set to, for example, 50%.

[0043] (iv) Step S704 The control computer 120 calculates the difference between the time (T1) at the rising point and the time (T2) at which the light amount changes by X% as a first time width.

[0044] (v) Step S705: The control computer 120 compares the first time width calculated in step S704 with a previously generated calibration curve showing the relationship between the first time width and the activity value of the blood coagulation factor to be quantified, thereby quantifying the activity value of the blood coagulation factor in the test sample. The quantification results may be displayed, for example, on the screen of the analytical computer 125. The first time width used to generate the calibration curve is calculated by processing blood coagulation reaction curve data of a group of samples whose activity values ​​of the blood coagulation factor to be quantified are known. It is desirable that the method of calculating the first time width used to generate the calibration curve be the same as the method of calculating the first time width in the test sample.

[0045] <GUI Configuration Example> FIG. 8 shows the relationship (GUI: Graphical User Interface) between the analysis unit 130, control computer 120, and communication interface 124, and an example of the display of the blood coagulation factor activity value results of the test sample on the display unit 118c.

[0046] Display section 118c displays the specimen number (S_No.) of the test specimen for which the results are to be displayed, a field for selecting the type of curve, and a field for selecting the type of blood coagulation factor to be quantified. Display section 118c also displays the blood coagulation time of the selected specimen number, a calibration factor (Cal. Factor) corresponding to the calibration curve information of the selected curve type, and the quantification result of the activity value of the selected blood coagulation factor (factor activity value in the figure).

[0047] 8 shows an example of a screen display when selecting the type of curve and the type of blood coagulation factor to be quantified, but the screen may be one that can display first-order derivative curves and second-order derivative curves in advance in parallel with the blood coagulation reaction curves as described later in Examples 2 and 3, or the operator (user) may select and determine the curve to be displayed by default. Furthermore, it is preferable that the display field for Calb. Factor be changed so as to correspond to the number of curves to be displayed, depending on the content of the curves to be displayed.

[0048] 8 shows an example of a screen display when the type of blood coagulation factor is also selected, but the screen may be one that can display multiple blood coagulation factors, may be a selection format, or may allow the user to select and determine the type of blood coagulation factor to be displayed by default. The display field for factor activity values ​​should preferably be changed so as to correspond to the number of types of blood coagulation factors.

[0049] Furthermore, the GUI of Fig. 8 shows a calibration curve in the lower left of the screen. This calibration curve represents the relationship between the time interval extracted from the selected curve and the activity value of the selected blood coagulation factor. Alternatively, as shown in the lower right of the screen of Fig. 8, a graph of the selected curve for the sample with the selected sample number may be displayed.

[0050] <Type of blood coagulation factor to be quantified> The type of blood coagulation factor is not limited to factor VIII, and may also be blood coagulation factor IX, blood coagulation factor XI, or blood coagulation factor XII. In this case, samples prepared to measure various activity values ​​of the blood coagulation factor may be used as the sample used to obtain the calibration curve. Figure 9 shows, as an example, a graph representing the relationship between the first time interval and blood coagulation factor IX activity value obtained from the blood coagulation reaction curves of samples with nine different blood coagulation factor IX activity values ​​(the vertical and horizontal axes are expressed in logarithmic scales). This graph serves as the calibration curve used to quantify blood coagulation factor IX activity value. Note that the calibration curve may be, for example, a curve approximating the data of the graph in Figure 9. In this example, samples with different blood coagulation factor IX activity levels were prepared by mixing commercially available Factor IX Deficient Plasma (manufactured by Precision BioLogic, Inc.) and Normal Reference Plasma (manufactured by Precision BioLogic, Inc.) at different ratios.

[0051] <Effects of Example 1> To quantify the blood coagulation factor activity value of a test sample, time-related parameters extracted only from the blood coagulation reaction curve are used. Since the analysis target is only the blood coagulation reaction curve, the number of analytical steps is extremely small (no effort is required to generate a differential curve), and this method is advantageous in terms of speed. Furthermore, the first time width calculated as the difference between the time when a certain light intensity is reached and the time when the rising point occurs in the blood coagulation reaction curve is advantageous in that it is a feature that more accurately reflects the influence of the blood coagulation factor activity value in the sample compared to when each time is used alone.

[0052] Example 2 relates to quantifying blood coagulation factor activity values ​​using time-related parameters extracted from a first-order derivative curve obtained by first-order differentiation of a blood coagulation reaction curve. In Example 2, the configuration of the automated analyzer 100, the method for obtaining a blood coagulation reaction curve (e.g., FIG. 1 ), and the types of blood coagulation factors to be quantified are the same as in Example 1. Therefore, in Example 2, to avoid duplication, the description of these will be omitted and only the components different from Example 1 will be described.

[0053] <Considerations on First-Order Derivative Curves of Blood Coagulation Reaction Curves> Depending on the combination of reagents and devices used to obtain a blood coagulation reaction curve, a first-order derivative curve of a blood coagulation reaction curve obtained from a sample deficient in blood coagulation factors may exhibit a bimodal curve with two peaks, or a main peak and a shoulder peak. FIG. 10 shows an example of a first-order derivative curve of a blood coagulation reaction curve of a sample deficient in blood coagulation factor VIII. The graph in FIG. 10 shows a clear bimodal curve. FIG. 10 also shows an example of a first-order derivative curve of a blood coagulation reaction curve obtained by measuring Factor VIII Deficient Plasma (manufactured by Precision BioLogic, Inc.), a commercially available sample with a blood coagulation factor VIII activity value of less than 1%, using the APTT parameter. The example shown in FIG. 10 is a first-order derivative curve obtained by subjecting the blood coagulation reaction curve data to differential processing according to Equation (1), followed by a moving average process as a smoothing process to remove noise.

[0054] y1(n) = (y0(n+1) - y0(n-1)) ÷ 2Δt Equation (1)

[0055] Here, y1(n) represents the nth first differential curve data, y0(n+1) and y0(n-1) represent the (n+1)th and (n-1)th blood coagulation reaction curve data, respectively, and Δt represents the measurement interval of the blood coagulation reaction curve data (for example, 0.1 seconds), where n is an integer and n≧2.

[0056] 11A and 11B are diagrams showing examples of curves exhibiting a main peak and a shoulder peak. Fig. 11A shows an example in which the shoulder peak occurs at a measurement time earlier than the occurrence time of the main peak. Fig. 11B shows an example in which the shoulder peak occurs at a measurement time later than the occurrence time of the main peak.

[0057] The inventors measured samples with different blood coagulation factor VIII activity levels and thoroughly examined the measurement results. As a result, they confirmed that the lower the blood coagulation factor VIII activity level, the longer the width of the time period during which the bimodal peak appears in the first-order derivative curve, or the width of the time period during which the main peak and shoulder peak appear. The healthier the subject (completely healthy), the more likely the first-order derivative curve is to be unimodal, while the more severe the condition, the more likely the first-order derivative curve is to be bimodal. Furthermore, a first-order derivative curve including a main peak and a shoulder peak tends to be obtained when the patient is not completely healthy but is not classified as severely ill.

[0058] Figure 12 shows a group of first-order derivative curves obtained using samples with different blood coagulation factor VIII activity levels. The example shown in Figure 12 also shows waveforms that have been subjected to noise removal processing. The samples with different blood coagulation factor VIII activity levels were prepared by mixing commercially available Factor VIII Deficient Plasma (manufactured by Precision BioLogic, Inc.) and Normal Reference Plasma (manufactured by Precision BioLogic, Inc.) at different ratios. Figure 12 shows that as the blood coagulation factor VIII activity level decreases, the width of the bimodal peak or the width of the main peak and shoulder peak increases.

[0059] Therefore, the inventors conceived that the time span of the bimodal appearance or the time span of the main peak and the shoulder peak could be extracted as a second time span and used to quantify blood coagulation factor activity. Figure 13 is a graph showing the relationship between the second time span and blood coagulation factor VIII activity obtained using multiple samples with known blood coagulation factor VIII activity (the vertical and horizontal axes are logarithmic). The inventors confirmed that the time span between the appearance of a single, clearly convex main peak and the appearance of a shoulder peak can be treated equivalently to the time span of the bimodal appearance. Therefore, it is possible to use a mixture of the second time span, which is the difference between the time span of the bimodal appearance and the second time span, which is the difference between the time span of the single, clearly convex main peak and the time span of the shoulder peak (i.e., they can be treated equally without distinguishing between them as time spans). Therefore, by using the graph shown in Figure 13 as a calibration curve (which may be a table of the graph values ​​or an approximate formula for the graph), blood coagulation factor VIII activity can be quantified from test samples with unknown blood coagulation factor VIII activity. The calibration curve may be, for example, a curve that approximates the data of the graph in Fig. 13. An example of a method for identifying the occurrence time of the shoulder peak in the first derivative curve will be specifically described below in (Program for quantification of blood coagulation factor activity values).

[0060] <Quantification Program for Blood Coagulation Factor Activity Values> Figure 14 is a flowchart for explaining the quantification process for blood coagulation factor activity values, which is executed by executing a quantification program for blood coagulation factor activity values. The computer system of the control computer 120 executes the quantification program for the blood coagulation factor activity values ​​of the sample, thereby quantifying the blood coagulation factor activity values ​​of Example 2. A specific description will be given with reference to Figure 14. Note that each step of the flowchart in Figure 14 may be executed by the control computer 120, the operation computer 118, the analysis computer 125, or another computer on the network. Here, an example in which the computer system of the control computer 120 executes each step will be described.

[0061] (i) Step S1401: The control computer 120 reads the blood coagulation curve data acquired by measuring the blood coagulation reaction of the test sample. Specific analytical operations for acquiring the blood coagulation curve are as described in the "Method for Acquiring a Blood Coagulation Curve" section of Example 1.

[0062] (ii) Step S1402: The control computer 120 derives a first-order differential curve for the blood coagulation reaction curve. When obtaining the first-order differential curve by performing pre- and post-differential processing on the blood coagulation reaction curve data as in Equation (1), noise processing such as smoothing may be performed before or after, or only after, performing step S1402 to suppress the influence of noise. The first-order differential curve may be the first-order differential curve derived in this manner, or an approximate curve generated using an approximate equation that can maintain the waveform shape may be used. Furthermore, when deriving the first-order differential curve by first-order differentiation of an approximate equation that can maintain the shape of the blood coagulation reaction curve, noise processing such as smoothing may or may not be performed on the blood coagulation reaction curve data before performing step S1402.

[0063] (iii) Step S1403: The control computer 120 derives a second-order derivative of the blood coagulation curve. The second-order derivative may be derived directly from the coagulation curve data, or may be derived by differentiating the first-order derivative data. However, it is desirable to perform appropriate noise processing as needed to clarify the waveform shape of the second-order derivative. For example, when deriving second-order derivative data from first-order derivative data, if the original first-order derivative data was obtained by performing pre- and post-differential processing on the blood coagulation curve data, the first-order derivative data is likely to be affected by noise. Therefore, it is desirable to perform noise processing using a smoothing process before deriving the second-order derivative. Furthermore, it is desirable to derive the second-order derivative by differentiating an approximation formula that can maintain the shape of the first-order derivative. Alternatively, the second-order derivative may be an approximation curve generated using an approximation formula that can maintain the waveform shape of the coagulation curve data or the second-order derivative data derived from the first-order derivative data. In this case, it is also desirable to perform appropriate noise processing as needed before approximation.

[0064] (iv) Step S1404: The control computer 120 determines whether the second derivative curve of the blood coagulation reaction curve exhibits a clear bimodal distribution. This determination may be made using an image or other methods. Here, a determination method using second derivative curve data is shown as an example.

[0065] Figures 15A to 15D show examples of blood coagulation reaction curves, first derivative curves, and second derivative curves. Figure 15A shows an example of a clear bimodal curve in which the vertical axis level of the earlier peak is higher. Figure 15B shows an example of a clear bimodal curve in which the vertical axis level of the earlier peak is lower. Figure 15C shows an example of a shoulder peak in which the shoulder peak occurs later than the main peak. Figure 15D shows an example of a shoulder peak in which the shoulder peak occurs earlier than the main peak.

[0066] When the first-order derivative curve has a clear bimodal profile, there are three points (open circles shown on the second-order derivative curves in FIGS. 15A and 15B ) at which the value of the second-order derivative curve is zero at measurement times later than the time (T1) of the rising point of the blood coagulation reaction curve, whereas in the case of a shoulder peak, there is only one point (open circle shown on the second-order derivative curves in FIGS. 15C and 15D ) at which the value of the second-order derivative curve is zero. In other words, the number of times the value of the second-order derivative curve becomes zero between T1 and Tend (the end time of measurement) is used as an index, and if this number occurs three times, it can be determined that there is a clear bimodal profile.

[0067] If it is determined that the first-order differential curve does not have a clear bimodal characteristic (No in step S1404), the process proceeds to step S1406. If it is determined that the first-order differential curve has a clear bimodal characteristic (Yes in step S1404), the process proceeds to step S1405.

[0068] (v) Step S1405 The control computer 120 calculates the time at which each bimodal peak occurs. When calculating the time at which each bimodal peak occurs, the time at which the quadratic derivative curve becomes zero may be used, for example.

[0069] (vi) Step S1406: The control computer 120 determines whether the first-order differential curve is a shoulder peak type. This determination may be performed using an image or other methods. Here, a determination method using second-order differential curve data is shown as an example. A shoulder peak type can be determined by using the following indicators: the second-order differential curve has one zero point between T1 and Tend, and four extreme values ​​between T1 and Tend. If the first-order differential curve were unimodal, the second-order differential curve would have one zero point between T1 and Tend, but two extreme values ​​between T1 and Tend (see FIG. 16). Therefore, the presence of a main peak and a shoulder peak can be determined by using the number of zero points and the number of extreme values ​​between T1 and Tend as indicators.

[0070] If it is determined that the first-order differential curve has a main peak and a shoulder peak (Yes in step S1406), the process proceeds to step S1407. On the other hand, if it is determined that the first-order differential curve does not have a main peak and a shoulder peak (No in step S1406), the control computer 120 determines that quantification is impossible. Note that "quantification is impossible" means that the first-order differential curve is close to a unimodal curve, and in this case, it can be determined that the patient is likely to be healthy.

[0071] In addition, in order to determine whether a first-order differential curve is of the bimodal type or shoulder peak type, a method based on image determination using machine learning can also be used in addition to a method based on a second-order differential curve.

[0072] (vii) Step S1407: The control computer 120 calculates the times at which the main peak and shoulder peak occur. The time at which the main peak occurs may be, for example, the time at which the value of the first-order derivative curve reaches its maximum, or may be determined from the point at which the value of the second-order derivative curve reaches zero. The time at which the shoulder peak occurs may be, for example, in a region where three extrema of the second-order derivative curve occur within the range from T1 to T3 or within the range from T3 to Tend, where the time at which the main peak of the first-order derivative curve occurs is taken as the reference (time: T3). When three extrema of the second-order derivative curve occur within the range from T3 to Tend (as in FIG. 15C ), the time at which the second-order derivative curve reaches its maximum within that range can be determined as the time at which the shoulder peak of the first-order derivative curve occurs. When three extrema of the second-order derivative curve occur within the range from T1 to T3 (as in FIG. 15D ), the time at which the second-order derivative curve reaches its minimum within that range can be determined as the time at which the shoulder peak of the first-order derivative curve occurs.

[0073] (viii) Step S1408 The control computer 120 calculates the time width during which bimodality occurs or the time width during which a main peak and a shoulder peak occur as a second time width.

[0074] (ix) Step 1409: The control computer 120 compares a previously generated calibration curve showing the relationship between the second time width and the activity value of the blood coagulation factor to be quantified with the second time width calculated in step S1408, thereby quantifying the activity value of the blood coagulation factor in the test sample. The quantification results may be displayed, for example, on the screen of the analytical computer 125. The second time width used to create the calibration curve is calculated by processing blood coagulation reaction curve data of a group of samples whose activity values ​​of the blood coagulation factor to be quantified are known. It is desirable that the method of calculating the second time width used to create the calibration curve be the same as the method of calculating the second time width in the test sample.

[0075] Effect of Example 2 In Example 2, when quantifying the blood coagulation factor activity of a test sample, a time-related parameter extracted from a first-order derivative curve of a blood coagulation reaction curve is used. Specifically, the time-related parameter extracted from the first-order derivative curve is a second time width, which is the difference in time between the occurrence of a clear bimodal peak and the occurrence of a shoulder peak, and has the advantage that the time position to be used is uniquely determined. Furthermore, compared to the conventional one-stage coagulation method, it is possible to quantify the blood coagulation factor activity of a test sample more quickly.

[0076] Example 3 relates to quantifying blood coagulation factor activity values ​​using time-related parameters extracted from a second-order derivative curve obtained by second-order differentiation of a blood coagulation reaction curve. Since the configuration of the automated analyzer 100, the method for obtaining the blood coagulation reaction curve ( FIG. 1 , etc.), and the types of blood coagulation factors to be quantified are the same as those in Example 1, the description thereof will be omitted to avoid duplication, and only the configuration parts different from Example 1 will be described.

[0077] <Considerations on the second derivative curve of a blood coagulation reaction curve> Depending on the combination of reagents and equipment used to obtain a blood coagulation reaction curve, the first derivative curve of a blood coagulation reaction curve obtained from a sample deficient in blood coagulation factors may exhibit a bimodal shape with two peaks, or a main peak and a shoulder peak. In the case of such a sample, as shown in Figure 15, the second derivative curve of the blood coagulation reaction curve has four extreme values ​​in the range from T1 to Tend.

[0078] The inventors confirmed that the difference in time between any two of these four extreme values ​​correlates with the blood coagulation factor activity value. Figure 17 shows a group of second-order derivative curves obtained using samples with different blood coagulation factor VIII activity values. The samples with different blood coagulation factor VIII activity values ​​were prepared by mixing commercially available Factor VIII Deficient Plasma (manufactured by Precision BioLogic, Inc.) and Normal Reference Plasma (manufactured by Precision BioLogic, Inc.) at different ratios. The example in Figure 17 shows a waveform that has been subjected to noise removal processing. It can be seen from Figure 17 that, for example, the width of the time period for the maximum or minimum becomes longer as the blood coagulation factor VIII activity value decreases.

[0079] Therefore, the inventors considered that by extracting the time width during which the extreme values ​​occur as a third time width, it could be used to quantify the activity of blood coagulation factors.

[0080] 18A and 18B are graphs showing the relationship between the third time width extracted from the second derivative curves of multiple samples with known blood coagulation factor VIII activity values ​​and the blood coagulation factor VIII activity value (the vertical and horizontal axes are logarithmic). FIG. 18A shows an example of a graph in which the third time width is the time width at which the maximum occurs. FIG. 18B shows an example of a graph in which the third time width is the time width at which the minimum occurs. Using the graphs shown in FIGS. 18A and 18B as calibration curves makes it possible to quantify the blood coagulation factor VIII activity value of test samples with unknown blood coagulation factor VIII activity values. The calibration curve may be, for example, a curve approximated to the data in the graph of FIG. 18. Here, the third time width may be, for example, the time width at which the first maximum and minimum occur, counted from the shortest measurement time. The combination of the times (order) at which the four extreme values ​​occur is arbitrary and not particularly limited. The quantification program and other related information will be described in detail below.

[0081] <Quantification Program for Blood Coagulation Factor Activity Values> Figure 19 is a flowchart for explaining a method for quantifying blood coagulation factor activity values, which is executed by executing a quantification program for blood coagulation factor activity values. The computer system of the control computer 120 executes the quantification program for the blood coagulation factor activity values ​​of the sample, thereby quantifying the blood coagulation factor activity values ​​of Example 3. The quantification method of Example 3 will be specifically described with reference to Figure 19. Each step in the flowchart of Figure 19 may be executed by the control computer 120, the operation computer 118, the analysis computer 125, or another computer on the network. Here, an example in which the computer system of the control computer 120 executes each step will be described.

[0082] (i) Step S1901: The control computer 120 reads the blood coagulation curve data acquired by measuring the blood coagulation reaction of the test sample. Specific analytical operations for acquiring the blood coagulation curve are as described in the "Method for Acquiring a Blood Coagulation Curve" section of Example 1.

[0083] (ii) Step S1902: The control computer 120 derives a second-order differential curve for the blood coagulation curve. The second-order differential curve data may be derived directly from the coagulation curve data, or may be derived by differentiating the first-order differential curve data obtained by differentiating the coagulation curve data. In this case, noise processing may be performed appropriately while maintaining the original shape characteristics so that the shape of the resulting second-order differential curve becomes clear. Alternatively, the second-order differential curve may be an approximation curve generated using an approximation formula that maintains the waveform shape of the second-order differential curve data derived from the coagulation curve data or the first-order differential curve data. In this case, noise processing may also be performed appropriately as needed before approximation.

[0084] (iii) Step S1903 The control computer 120 calculates the occurrence times of a plurality of extrema on the quadratic differential curve.

[0085] (iv) Step S1904 The control computer 120 calculates the difference between any two occurrence times of the plurality of extreme values ​​as a third time width.

[0086] (v) Step S1905: The control computer 120 compares a previously generated calibration curve showing the relationship between the third time width and the activity value of the blood coagulation factor to be quantified with the third time width calculated in step S1904, thereby quantifying the blood coagulation factor activity value of the test sample. The quantification results may be displayed, for example, on the screen of the analytical computer 125. The third time width used to create the calibration curve is calculated by processing blood coagulation reaction curve data of a group of samples whose activity values ​​of the blood coagulation factor to be quantified are known. It is desirable that the method of calculating the third time width used to create the calibration curve be the same as the method of calculating the third time width for the test sample.

[0087] Effect of Example 3 In Example 3, when quantifying the blood coagulation factor activity value of a test sample, a time-related parameter extracted from a second-order derivative curve of a blood coagulation reaction curve is used. Specifically, the time-related parameter extracted from the second-order derivative curve is a third time width, which is the time width between at least two of the multiple extreme values ​​of the second-order derivative curve. By quantifying the blood coagulation factor activity value using this third time width, it becomes possible to quantify the blood coagulation factor activity value of a test sample more quickly than the conventional one-stage coagulation method.

[0088] [Modifications] The present disclosure is not limited to the above-described embodiments and includes various modifications. The above-described embodiments have been described in detail to clearly explain the present disclosure, and are not necessarily limited to those including all of the described configurations. It is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace part of the configuration of each embodiment with the same configuration or another configuration.

[0089] Here, to facilitate a fundamental understanding of the technology of the present disclosure, the time widths of Examples 1 to 3 will be summarized. FIG. 20 is a diagram showing an example in which the concepts of the first time width described in Example 1, the second time width described in Example 2, and the third time width described in Example 3 are organized. Example 1 proposes a program for quantifying blood coagulation factor activity values ​​using a first time width extracted from a blood coagulation reaction curve, Example 2 proposes a program for quantifying blood coagulation factor activity values ​​using a first time width extracted from a first derivative curve of the blood coagulation reaction curve, and Example 3 proposes a program for quantifying blood coagulation factor activity values ​​using a third time width extracted from a second derivative curve of the blood coagulation reaction curve. The quantification programs of Examples 1 to 3 are proposed as examples for use independently of each other. However, a computer system equipped with all of the quantification programs may be constructed, allowing an operator (user) to arbitrarily select one or more programs to use.

[0090] [Summary] The functions of this embodiment and each example can also be realized by software program code. In this case, a storage medium on which the program code is recorded is provided to a system or device, and the computer (or CPU or MPU) of that system or device reads the program code stored in the storage medium. In this case, the program code read from the storage medium itself realizes the functions of the above-mentioned embodiments, and the program code itself and the storage medium on which it is stored constitute the present disclosure. Examples of storage media for providing such program code include flexible disks, CD-ROMs, DVD-ROMs, hard disks, optical disks, magneto-optical disks, CD-Rs, magnetic tape, non-volatile memory cards, and ROMs.

[0091] Furthermore, an operating system (OS) running on a computer may perform some or all of the actual processing based on instructions in the program code, and the functions of the above-described embodiments may be realized by this processing.Furthermore, after the program code is read from a storage medium and written to memory on the computer, a CPU of the computer may perform some or all of the actual processing based on instructions in the program code, and the functions of the above-described embodiments may be realized by this processing.

[0092] Furthermore, the program code of the software that realizes the functions of the embodiments and each example may be distributed via a network and stored in a storage means such as a hard disk or memory of the system or device, or in a storage medium such as a CD-RW or CD-R, so that when used, the computer (or CPU or MPU) of the system or device reads and executes the program code stored in the storage means or storage medium.

[0093] The processes and techniques described herein are not inherently related to any specific device and can be implemented by a combination of components. Various types of general-purpose devices can also be added. A dedicated device may be constructed to perform the functions of this embodiment and each example. Various functions can also be formed by appropriately combining multiple components disclosed in this embodiment and each example. For example, some components may be omitted from all the components shown in the embodiment and each example, or components from different examples may be appropriately combined.

[0094] Although specific examples are described in this disclosure, they are in all respects for the purpose of explanation (understanding the technology of the present disclosure) and not for the purpose of limitation. Those skilled in the art will recognize that there are many combinations of hardware, software, and firmware suitable for implementing the technology of the present disclosure. For example, the software described can be implemented in a wide variety of programming or scripting languages, such as assembler, C / C++, Perl, Shell, PHP, Java (registered trademark), etc.

[0095] Furthermore, in the above-described embodiment, the control lines and information lines are those that are considered necessary for the explanation, and not all control lines and information lines in the product are necessarily shown. All components may be interconnected.

[0096] In addition, other implementations of the present disclosure will be apparent to those skilled in the art from consideration of the present embodiments and examples. The specification and examples are exemplary only, with the scope and spirit of the present disclosure being indicated by the following claims.

[0097] 100 Automatic analyzer 101 Sample dispensing mechanism 102 Sample disk 103 Sample container 103a Sample 104 Reaction container 105 Sample syringe pump 106 Reagent dispensing mechanism 107 Reagent disk 108 Reagent container 108a Reagent 109 Reagent heating mechanism 110 Reagent syringe pump 111 Reaction container stock section 112 Reaction container transport mechanism 113 Detection unit 114 Reaction container installation section 115 Light source 116 Detection section (optical sensor) 117 Reaction container disposal section 118 Operation computer 118a Mouse 118b Keyboard 118c Display section 119 Memory section 120 Control computer 121 A / D converter 122 Incubator 123 Printer 124 Communication interface 125 Analysis computer 130 Analysis section

Claims

1. A method for quantifying blood coagulation factor activity values, comprising: acquiring a blood coagulation reaction curve to be quantified, the blood coagulation reaction curve showing the change in light intensity over time due to the coagulation reaction of a reaction solution produced by mixing a test sample, which is made of plasma obtained by separating blood from a subject, with a reagent; extracting a first time width, which is the difference between the rise time and the time at which the change in light intensity reaches a predetermined rate, in the blood coagulation reaction curve to be quantified; and quantifying the blood coagulation factor activity value of the test sample based on a known time parameter, which is the difference between the rise time and the time at which the change in light intensity reaches the predetermined rate, in the blood coagulation reaction curve of a group of samples whose blood coagulation factor activity values ​​are known, and the first time width.

2. A method for quantifying blood coagulation factor activity values ​​according to claim 1, further comprising: performing noise processing on the blood coagulation reaction curve to be quantified to generate a noise-removed curve; and the first time width is extracted from the noise-removed curve.

3. A method for quantifying blood coagulation factor activity levels according to claim 1, further comprising displaying the results of the quantification of the blood coagulation factor activity levels of the test specimen on a display unit.

4. A method for quantifying blood coagulation factor activity values ​​according to claim 3, further comprising: creating a calibration curve showing the relationship between the known time parameter and the known blood coagulation factor activity value; and displaying on the display unit the calibration curve and information in which the first time width of the test sample is plotted on the calibration curve.

5. A method for quantifying blood coagulation factor activity values, comprising: acquiring a blood coagulation reaction curve of a target to be quantified, the curve showing the change in light intensity over time due to the coagulation reaction of a reaction solution produced by mixing a test specimen, which is made of plasma obtained by separating blood from a subject, with a reagent; extracting a second time width, which is the difference in the time at which a bimodal peak appears or the difference in the time at which a main peak and a shoulder peak appear, in a first-order differential curve of the blood coagulation reaction curve of the target to be quantified; and quantifying the blood coagulation factor activity values ​​of the test specimen based on a known time parameter, which is the difference in the time at which a bimodal peak appears or the difference in the time at which a main peak and a shoulder peak appear, in a first-order differential curve of the blood coagulation reaction curve of a group of specimens whose blood coagulation factor activity values ​​are known, and the second time width.

6. A method for quantifying blood coagulation factor activity values ​​according to claim 5, further comprising: performing noise processing on at least one of the blood coagulation reaction curve to be quantified or a first derivative curve of the blood coagulation reaction curve to generate a noise-removed curve; and the second time width is extracted from the noise-removed first derivative curve.

7. A method for quantifying blood coagulation factor activity levels according to claim 5, further comprising displaying the results of the quantification of the blood coagulation factor activity levels of the test specimen on a display unit.

8. A method for quantifying a blood coagulation factor activity value according to claim 7, further comprising: creating a calibration curve showing the relationship between the known time parameter and the known blood coagulation factor activity value; and displaying the calibration curve and information in which the second time width of the test sample is plotted on the calibration curve on the display unit.

9. A method for quantifying blood coagulation factor activity values, comprising: acquiring a blood coagulation reaction curve of a target to be quantified, the curve showing the change in light intensity over time due to the coagulation reaction of a reaction solution produced by mixing a test sample, which is made of plasma obtained by separating blood from a test subject, with a reagent; extracting a third time width, which is the difference between any two of the times at which a plurality of extreme values ​​are obtained in a second-order derivative curve of the blood coagulation reaction curve of the target to be quantified; and quantifying the blood coagulation factor activity values ​​of the test sample based on the third time width and a known time parameter, which is the difference between two times corresponding to the order in which the extreme values ​​constituting the third time width appear in a second-order derivative curve of the blood coagulation reaction curve of a group of samples whose blood coagulation factor activity values ​​are known.

10. A method for quantifying blood coagulation factor activity values ​​according to claim 9, further comprising performing noise processing on at least one of the blood coagulation reaction curve to be quantified or a second derivative curve of the blood coagulation reaction curve to generate a noise-removed curve, and the third time width is extracted from the noise-removed second derivative curve.

11. A method for quantifying blood coagulation factor activity levels according to claim 9, further comprising displaying the results of the quantification of the blood coagulation factor activity levels of the test specimen on a display unit.

12. A method for quantifying blood coagulation factor activity values ​​according to claim 11, further comprising: creating a calibration curve showing the relationship between the known time parameter and the known blood coagulation factor activity value; and displaying on the display unit the calibration curve and information in which the third time width of the test sample is plotted on the calibration curve.

13. A method for quantifying blood coagulation factor activity according to claim 1, 5, or 9, wherein the blood coagulation factor to be quantified in the test sample is blood coagulation factor VIII, blood coagulation factor IX, blood coagulation factor XI, or blood coagulation factor XII.

14. An information processing device for quantifying the blood coagulation factor activity value of a test sample consisting of plasma obtained by separating the blood of a test subject, comprising: a storage device for storing a program for quantifying the blood coagulation factor activity value; and a computer for reading and executing the program from the storage device, wherein the computer performs the following processes: acquiring a blood coagulation reaction curve to be quantified, which shows the change in light intensity over time due to the coagulation reaction of a reaction solution produced by mixing the test sample with a reagent; extracting a first time width, which is the difference between the rise time and the time at which the change in light intensity reaches a predetermined rate, in the blood coagulation reaction curve to be quantified; and quantifying the blood coagulation factor activity value of the test sample based on a known time parameter, which is the difference between the rise time and the time at which the change in light intensity reaches the predetermined rate, in the blood coagulation reaction curve of a group of samples whose blood coagulation factor activity values ​​are known, and the first time width.

15. An information processing device according to claim 14, wherein the computer further performs a process of performing noise processing on the blood coagulation reaction curve to be quantified to generate a noise-removed curve, and the computer quantifies the blood coagulation factor activity value based on the first time width extracted from the noise-removed curve.

16. An information processing device according to claim 14, wherein the computer further executes a process for displaying the quantitative results of the blood coagulation factor activity value of the test sample on a display unit.

17. An information processing device according to claim 16, wherein the computer further executes the following processes: creating a calibration curve showing the relationship between the known time parameter and the known blood coagulation factor activity value; and displaying the calibration curve and information in which the first time width of the test sample is plotted on the calibration curve on the display unit.

18. An information processing device for quantifying the activity of blood coagulation factors in a test sample consisting of plasma obtained by separating the blood of a test subject, comprising: a storage device for storing a program for quantifying the activity of blood coagulation factors; and a computer for reading and executing the program from the storage device, wherein the computer performs the following processes: acquiring a blood coagulation reaction curve to be quantified, which shows the change in light intensity over time due to the coagulation reaction of a reaction solution produced by mixing the test sample with a reagent; extracting a second time width, which is the difference in the time at which bimodalities occur or the difference in the time at which a main peak and a shoulder peak occur, in a first-order differential curve of the blood coagulation reaction curve to be quantified; and quantifying the activity of blood coagulation factors in the test sample based on the second time width and a known time parameter, which is the difference in the time at which bimodalities occur or the difference in the time at which a main peak and a shoulder peak occur, in a first-order differential curve of the blood coagulation reaction curve of a group of samples whose blood coagulation factor activity values ​​are known.

19. An information processing device according to claim 18, wherein the computer further performs a process of performing noise processing on at least one of the blood coagulation reaction curve to be quantified or the first derivative curve of the blood coagulation reaction curve to generate a noise-removed curve, and the computer quantifies the blood coagulation factor activity value based on the second time width extracted from the noise-removed first derivative curve.

20. An information processing device according to claim 18, further comprising the step of displaying the quantitative results of the blood coagulation factor activity value of the test sample on a display unit.

21. An information processing device according to claim 20, further executing the steps of: creating a calibration curve showing the relationship between the known time parameter and the known blood coagulation factor activity value; and displaying the calibration curve and information in which the second time width of the test sample is plotted on the calibration curve on the display unit.

22. An information processing device for quantifying the activity of blood coagulation factors in a test sample consisting of plasma obtained by separating the blood of a test subject, comprising: a storage device for storing a program for quantifying the activity of blood coagulation factors; and a computer for reading and executing the program from the storage device, wherein the computer performs the following processes: acquiring a blood coagulation reaction curve to be quantified, which shows the change in light intensity over time due to the coagulation reaction of a reaction solution produced by mixing the test sample with a reagent; extracting a third time width, which is the difference between any two of the times at which multiple extreme values ​​are taken in the second derivative curve of the blood coagulation reaction curve to be quantified; and quantifying the activity of blood coagulation factors in the test sample based on the third time width and a known time parameter, which is the difference between two times corresponding to the order in which the extreme values ​​constituting the third time width appear in the second derivative curve of the blood coagulation reaction curve of a group of samples whose blood coagulation factor activity values ​​are known.

23. An information processing device according to claim 22, wherein the computer further executes a process of performing noise processing on at least one of the blood coagulation reaction curve to be quantified or the second derivative curve of the blood coagulation reaction curve to generate a noise-removed curve, and the computer quantifies the blood coagulation factor activity value based on the third time width extracted from the noise-removed second derivative curve.

24. An information processing device according to claim 22, wherein the computer further executes a process for displaying the quantitative results of the blood coagulation factor activity value of the test sample on a display unit.

25. An information processing device according to claim 24, wherein the computer further executes the following processes: creating a calibration curve showing the relationship between the known time parameter and the known blood coagulation factor activity value; and displaying the calibration curve and information in which the third time width of the test sample is plotted on the calibration curve on the display unit.

26. An information processing device according to claim 14, 18 or 22, wherein the blood coagulation factor to be quantified in the test sample is blood coagulation factor VIII, blood coagulation factor IX, blood coagulation factor XI or blood coagulation factor XII.

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