Method for selecting blood specimen having possibility of including blood coagulation abnormality

Abstract

Provided is a method for selecting a blood specimen having a possibility of including a coagulation abnormality, the method including: acquiring a parameter Ps(X) based on a coagulation reaction curve Rs(i) or a primary differential curve Vs(i) thereof for a test blood specimen, where the test blood specimen is a blood specimen for which it has not been possible to decisively determine the presence of prolonged APTT, i is a measurement point or time, and X is a variable and is greater than 0; acquiring a parameter Pm(X) for a normal blood specimen; and acquiring an index S for the test blood specimen on the basis of formula (2), (2)', or (2)", where Fs(X) = Ps(X) − Ps(c) and Fm(X) = Pm(X) − Pm(c), or Fs(X) = Ps(X) / Ps(c) and Fm(X) = Pm(X) / Pm(c), a > 0 and a ≤ b, 0 < c ≤ M, and M is a maximum value of X.

Description

Method for selecting blood samples that may have blood coagulation disorders

[0001] The present invention relates to a method for selecting a blood sample that may have a blood coagulation disorder from among blood samples that do not show a clear prolongation of the coagulation time.

[0002] The activated partial thromboplastin time (APTT) is used for screening intrinsic blood coagulation reactions, preoperative testing, and other purposes. Patients with prolonged APTT are considered to have some kind of abnormality in blood coagulation function and are at risk for bleeding if the effects of administered medications or thrombus-related prolongation are ruled out. However, some samples from patients with mild hemophilia or other coagulation disorders do not show a clear prolongation of the APTT, but rather have an APTT within the normal range or slightly prolonged beyond the normal range. Furthermore, the sensitivity of APTT to each coagulation disorder factor, such as coagulation factors, heparin, or coagulation factor inhibitors, can vary depending on the assay reagent. Therefore, APTT screening, such as preoperative testing, may miss patients at risk for bleeding.

[0003] Patent Documents 1 to 4 describe the calculation of parameters such as weighted average time, weighted average height, peak width, and baseline length of the coagulation rate curve of a blood sample, and the use of these parameters to estimate factors that prolong blood coagulation time, evaluate coagulation factor deficiency, etc. Patent Documents 5 and 6 describe the calculation of a function T(X) that represents the measurement point or time at which the coagulation reaction curve reaches X% of the maximum value, and the estimation of factors that prolong the coagulation time of the test blood sample based on T(X). Patent Document 7 describes the calculation of a point p at which the coagulation rate curve reaches S% of the maximum value before and after the point at which the coagulation rate curve reaches the maximum value. k and q k Calculate the p k and q k It is described that parameters for estimating blood coagulation abnormality factors are calculated using the above method.

[0004] International Publication No. 2020 / 101025 International Publication No. 2020 / 158948 International Publication No. 2020 / 218425 International Publication No. 2021 / 177452 International Publication No. 2022 / 186381 International Publication No. 2023 / 032978 International Publication No. 2022 / 054819

[0005] It is desirable to prevent overlooking samples from patients with blood coagulation disorders who do not show a clear prolongation of the clotting time in APTT measurements.

[0006] The inventors have found that even when blood samples from patients with blood coagulation disorders do not show a clear prolongation of the clotting time in APTT measurements, the waveform (shape) of the coagulation reaction curve or its first derivative curve differs from that of samples from normal subjects without coagulation disorders.The inventors have further found that, based on such waveform differences, samples that may have blood coagulation disorders can be detected from blood samples that do not show a clear prolongation of the clotting time.

[0007] The present invention provides the following as representative embodiments: [1] A method for selecting a blood sample that may have a blood coagulation abnormality, comprising: 1) obtaining a parameter Ps(X) based on a coagulation reaction curve Rs(i) or its first derivative curve Vs(i) for a test blood sample, wherein the test blood sample is a blood sample that cannot be determined to have APTT prolongation, i is a measurement point or time, and X is a variable, and X>0; 2) obtaining a parameter Pm(X) for a normal blood sample, wherein PM j (X) is the coagulation reaction curve Rm for each sample in the normal blood sample group. j (i) or its first differential curve Vm j (i) is a parameter based on (i), where i and X are as described above, j represents the sample number of each sample in the normal blood sample group and is an integer from 1 to k, and k represents the total number of samples belonging to the normal blood sample group; 3) obtaining an index S for the test blood sample based on the following formula (2), (2)', or (2)": where Fs(X) = Ps(X) - Ps(c), and Fm(X) = Pm(X) - Pm(c), or Fs(X) = Ps(X) / Ps(c), and Fm(X) = Pm(X) / Pm(c), a>0, and a≦b, 0<c≦M, and M is the maximum value of X; 4) Ps(X) and Ps(c) in the above formula (2), (2)' or (2)" are respectively set to Pm j (X) and Pm j (c) replacing (i) with (ii) to obtain an index S for each sample in the normal blood sample group; 5) comparing the index S for the test blood sample with a statistical value of the index S for each sample in the normal sample group. [2] Ps(X) represents the measurement point or time at which Rs(i) reaches X% of its coagulation reaction end point, and Pm j (X) is Rm j The method according to [1], wherein (i) represents the measurement point or time at which Vs(i) reaches X% of the end point of the coagulation reaction, a = 3 to 97, b = 3 to 97, c = 3 to 97, and 0 < X ​​≦ 100. [3] Ps(X) represents the measurement point or time at which Vs(i) reaches X% of the maximum value, provided that if Ps(X) is greater than Ps(100), Ps(X) is redefined as Ps(200-X), and Pm j (X) is Vm j (i) represents the measurement point or time at which the maximum value is reached by X%, where Pm j (X) is Pm j If it is greater than (100), Pm j (X) is Pm j (200-X), where a = 3 to 98, b = 103 to 198, and c = 3 to 198. [4] Ps(X) represents the minimum value of the measurement point or time at which Vs(i) reaches X% of the maximum value, and Pm j (X) is Vm j The method according to [1], wherein (i) represents the minimum value of the measurement point or time at which Vs(i) reaches X% of the maximum value, a = 3 to 98, b = 3 to 98, c = 3 to 197, and 0 < X ​​≦ 100. [5] Ps(X) represents the maximum value of the measurement point or time at which Vs(i) reaches X% of the maximum value, and Pm j (X) is Vm jThe method according to [1], wherein (i) represents the maximum value of the measurement point or time at which Vs(i) reaches X% of the maximum value, a = 3 to 98, b = 3 to 98, c = 3 to 197, and 0 < X ​​≦ 100. [6] Ps(X) represents the midpoint between the minimum and maximum values ​​of the measurement point or time at which Vs(i) reaches X% of the maximum value, and Pm j (X) is Vm j The method according to [1], wherein (i) represents the midpoint between the minimum and maximum values ​​of the measurement point or time at which Vs(i) reaches X% of the maximum value, and a = 3 to 98, b = 3 to 98, c = 3 to 197, and 0 < X ​​≦ 100. [7] Ps(X) represents the length between the minimum and maximum values ​​of the measurement point or time at which Vs(i) reaches X% of the maximum value, and Pm j (X) is Vm j The method according to [1], wherein (i) represents the length between the minimum and maximum values ​​of the measurement points or times at which X% of the maximum value is reached, and a = 3 to 98, b = 3 to 98, c = 3 to 197, and 0 < X ​​< 100. [8] Ps(X) represents the weighted average time of Vs(i), and Pm j (X) is Vm j (i) represents a weighted average time, which is calculated according to the following formula (3): In the formula, V(i) is Vs(i) or Vm j (i), t1 and t2 respectively represent the minimum and maximum values ​​of the measurement point or time at which V(i) reaches X% of the maximum value, provided that when V(i) is less than X% of the maximum value, V(i) is considered to be 0, a = 3 to 98, b = 3 to 98, c = 3 to 197, and 0 < X ​​≦ 100. [9] The method according to [1], wherein Ps(c) represents the measurement point or time at which Vs(i) reaches c% of the maximum value, PM j (c) is Vm jThe method according to any one of [1] to [8], wherein (i) represents the measurement point or time at which the index S reaches c% of the maximum value.

[10] The method according to any one of [1] to [9], wherein 5) includes calculating SDI_S, which represents the standard deviation index of the index S for the test blood sample, according to the following formula: SDI_S = |([index S for the test blood sample] - [average value of index S for each sample in a normal blood sample group]) / [standard deviation of index S for each sample in a normal blood sample group]|.

[11] The method according to

[10] , which includes selecting the test blood sample as a blood sample that may have a coagulation abnormality when SDI_S is equal to or greater than a predetermined threshold.

[12] The method of

[10] , wherein 5) further comprises: obtaining APTTs for the test blood sample and each sample in the normal blood sample group; calculating SDI_APTT, which represents a standard deviation index of APTTs for the test blood sample, according to the following formula: SDI_APTT=|([APTT for the test blood sample]-[mean APTT for each sample in the normal blood sample group]) / [standard deviation of APTT for each sample in the normal blood sample group]|; and calculating rSDI, which represents a ratio of SDI_S to SDI_APTT, according to the following formula: rSDI=SDI_S / SDI_APTT.

[13] The method of

[12] , further comprising selecting the test blood sample as a blood sample that may have a coagulation abnormality if SDI_S and rSDI are at or above predetermined thresholds.

[14] The method of

[12] , wherein the standard deviation of APTT for each sample in the normal blood sample group is 2 seconds or more.

[15] The method of

[11] or

[13] , comprising outputting information showing the result of the selection for the test blood sample.

[16] The method of any one of [1] to

[15] , wherein the blood sample in which it cannot be determined that the blood coagulation time is prolonged is a sample whose APTT is within a predetermined upper limit of normal + 5 seconds.

[17] The method of any one of [1] to

[16] , wherein the blood sample is plasma.

[18] The method of any one of [1] to

[17] , wherein the coagulation abnormality is coagulation factor deficiency or lupus anticoagulant positivity.

[19] The method according to

[18] , wherein the coagulation factor is factor VIII, factor IX, or von Willebrand factor.

[20] Fs(X) = Ps(X) / Ps(c), and The method described in [1],

[0008] According to the method of the present invention, blood samples that may have a coagulation disorder can be detected from blood samples that do not show a clear prolongation of the APTT. The present invention makes it possible to detect blood samples from subjects who may have a blood coagulation disorder, which could not be detected by conventional screening tests using the APTT.

[0009] FIG. 1 shows an embodiment of a process for the method for selecting a sample that may have a coagulation disorder according to the present invention. FIG. 2 shows an embodiment of a process for the method for selecting a blood sample that may have a coagulation disorder according to the present invention, including a step of selecting test samples based on APTT. Differences in coagulation reactions between FVIII-deficient samples and other sample types. A-C: coagulation reaction curves; D-F: first derivative curves. U on the vertical axis represents turbidity units (TU). NL, NM, and NH represent samples with APTTs close to the lower, middle, and upper limits of the normal range, respectively, for the NP group. FVIII represents Abn samples (FVIII). Differences in coagulation reactions between FIX-deficient samples and other sample types. The descriptions of A-F and sample types are the same as in FIG. 3. FIX represents Abn samples (FIX). Differences in coagulation reactions between VW samples and other sample types. The descriptions of A-F and sample types are the same as in FIG. 3. VW represents Abn samples (VW). Differences in coagulation reactions between LA-positive samples and other sample types. The descriptions of A to F and sample types are the same as in Figure 3. LA indicates an Abn sample (LA). This figure explains Ps (X) used in Example 1, as well as Fs (X) and index S according to formulas (2a) and (2b). NL and NH indicate samples in which the APTT of the NP group was close to the lower and upper limits of the normal range, respectively. LA indicates an Abn sample (LA). NA indicates the average value of the NP group. NL-NA, NH-NA, and LA-NA indicate the differences between the NL, NM, NH, and LA values ​​and the NA value, respectively. A: S-1 for each sample calculated in Example 1. B and C: SDI_APTT (gray bar), SDI_S (black bar) and rSDI (white bar) for indexes S-1 and S-2 for each sample calculated in Example 1. B: Index S-1. C: Index S-2. The legends for the black bars in Figure A and Figures B and C show a, b, and c used in formulas (2a) and (2b) for calculating the indices S-1 and S-2 in the format [a:b] / [c]. N1 to N12 indicate samples from the NP group, F8, F9, VW, and LA indicate samples from the Abn group, F8 indicates FVIII, and F9 indicates FIX. c1 to c5 indicate samples from the Cont group. * in Figure A indicates samples with S-1 values ​​greater than the maximum value for the NP group. * in Figures B and C indicates that both SDI_S and rSDI exceed the threshold. Figures explaining Ps(X) used in Example 2, and Fs(X) and the index S according to formulas (2a) and (2b).NL, NH, NA, NL-NA, and NH-NA are the same as in Figure 7. FVIII indicates the Abn sample (FVIII), and FVIII-NA indicates the difference between the FVIII value and the NA value. SDI_APTT (gray bar), SDI_S (black bar) and rSDI (white bar) for each sample calculated in Example 2. A: Indicator S-1, B: Indicator S-2. The description of the samples is the same as in Figure 8. A diagram explaining Ps(X) used in Example 3, and Fs(X) and indicator S according to formulas (2a) and (2b). NL, NH, NA, LA, NL-NA, NH-NA, and LA-NA are the same as in Figure 7. SDI_APTT (gray bar), SDI_S (black bar) and rSDI (white bar) for indicators S-1 and S-2 calculated in Example 3. A: Indicator S-1, B: Indicator S-2. The description of the samples is the same as in Figure 8. This figure explains Ps(X) used in Example 4, as well as Fs(X) and indicator S according to formulas (2a) and (2b). NL, NH, NA, NL-NA, and NH-NA are the same as in Figure 7. FVIII and FVIII-NA are the same as in Figure 9. SDI_APTT (gray bar), SDI_S (black bar), and rSDI (white bar) for each sample calculated in Example 4 for indicators S-1 and S-2. A: Indicator S-1, B: Indicator S-2. The description of the samples is the same as in Figure 8. This figure explains Ps(X) used in Example 5, as well as Fs(X) and indicator S according to formulas (2a) and (2b). NL, NH, NA, NL-NA, and NH-NA are the same as in Figure 7. FIX indicates the Abn sample (FIX), and FIX-NA indicates the difference between the FIX value and the NA value. SDI_APTT (gray bar), SDI_S (black bar) and rSDI (white bar) for each sample calculated in Example 5. A: Indicator S-1, B: Indicator S-2. The description of the sample is the same as in Figure 8. A diagram explaining Ps(X) used in Example 6, and Fs(X) and indicator S according to formulas (2a) and (2b). NL, NH, NA, LA, NL-NA, NH-NA, and LA-NA are the same as in Figure 7. SDI_APTT (gray bar), SDI_S (black bar) and rSDI (white bar) for each sample calculated in Example 6. A: Indicator S-1, B: Indicator S-2. The description of the sample is the same as in Figure 8. A diagram explaining Ps(X) used in Example 7, and Fs(X) and indicator S according to formulas (2a) and (2b).NL, NH, NA, NL-NA, and NH-NA are the same as in Figure 7. VW indicates the Abn sample (VW), and VW-NA indicates the difference between the VW value and the NA value. SDI_APTT (gray bar), SDI_S (black bar) and rSDI (white bar) for each sample calculated in Example 7 are shown for each sample. A: Index S-1, B: Index S-2. The description of the samples is the same as in Figure 8. For each SDI_S calculation condition, the maximum SDI_S among the NP group samples (NP#Max; white bar) and the SDI_S of the Abn sample (gray bar) are shown. The horizontal scale in the figure represents the a and b used in the calculation formula for index S as "a:b." A: FVIII sample, B: FIX sample, C: VW sample, D: LA sample. Table 4A shows the average value of SDI_S for each specimen under the condition that rSDI>1. Table 4B shows the average value of SDI_S for each specimen under the condition that rSDI>2.

[0010] All patents, non-patent documents, and other publications cited herein are hereby incorporated by reference in their entirety.

[0011] In the measurement of activated partial thromboplastin time (APTT) in blood coagulation tests, a predetermined reagent is added to a test blood sample, the subsequent blood coagulation reaction is measured, and the coagulation time (APTT) is calculated from the coagulation reaction data. Blood coagulation reactions are measured using common means, such as optical means for measuring scattered light intensity, transmittance, absorbance, etc., or mechanical means for measuring plasma viscosity. Blood coagulation reactions are generally represented by a coagulation reaction curve, which shows the change in the amount of coagulation reaction over time. In this specification, blood samples, blood coagulation reactions, and blood coagulation times may be simply referred to as samples, coagulation reactions, and coagulation times, respectively. Furthermore, in this specification, blood coagulation abnormalities may be simply referred to as coagulation abnormalities, and blood samples with coagulation abnormalities may be referred to as abnormal samples.

[0012] In APTT measurements, samples with APTTs within a predetermined reference range are typically considered normal (no suspicion of coagulation abnormalities), while samples with APTTs exceeding the reference range are suspected of coagulation abnormalities. However, the sensitivity of APTT to each coagulation abnormality factor, such as coagulation factors, heparin, or coagulation factor inhibitors, can vary depending on the reagents and analytical equipment used. Such differences in sensitivity can result in overlooking patients with coagulation abnormalities. It has also been reported that samples with APTTs within the reference range may contain samples from patients with mild hemophilia. Patients with such coagulation abnormalities are at risk of unexpected bleeding during surgery, even if their APTTs are within the reference range. Overlooking patients with mild hemophilia or coagulation abnormalities who do not demonstrate a significant prolongation of the APTT in preoperative testing is a significant clinical issue. Meanwhile, in the field of clinical testing, the reference range for APTT is defined as the range within 95% of the statistical distribution of APTTs in a healthy population without disease, excluding 2.5% on either side. This means that 5% of healthy individuals without coagulation disorders will have an APTT outside the reference range ("pseudo-abnormality"). Until now, no established method has been known for determining whether a specimen with an APTT outside the reference range has a coagulation disorder (pseudo-abnormality).

[0013] The present inventors have discovered that blood samples from patients with coagulation disorders exhibit waveforms of their coagulation reaction curves or their first derivative curves that differ from those of samples from normal subjects (normal sample group), even when the APTT does not show a clear prolongation. In other words, samples whose waveforms of their coagulation reaction curves or their first derivative curves differ from those of normal sample group may have coagulation disorders.

[0014] The present invention provides a method for selecting a blood sample that may have a coagulation abnormality. In the present invention, a blood sample in which it is not certain that APTT prolongation is present is used as a test sample. In the present invention, a parameter reflecting the waveform of the coagulation reaction data of the test sample obtained by APTT measurement and a parameter reflecting the waveform of the coagulation reaction data of a normal sample are determined, and the presence or absence of a coagulation abnormality in the test sample is detected based on the difference between these parameters. The present invention makes it possible to detect abnormal samples that do not show clear APTT prolongation and tend to be overlooked by conventional APTT measurements. Furthermore, the present invention can provide information for evaluating whether a sample suspected of having a coagulation abnormality based on APTT truly has a coagulation abnormality (whether it is a false abnormality).

[0015] The method of the present invention will now be described.

[0016] 1. Test Samples Test samples in the methods of the present invention are samples for which the presence or absence of coagulation abnormalities has not been determined by conventional APTT measurements. Typically, such test samples do not show clear APTT prolongation and cannot be confirmed to have APTT prolongation, such as samples with APTTs within the normal range or slightly prolonged from the normal range. A more specific example of such a test sample is a sample with an APTT within the upper limit of normal + 5 seconds. The lower limit of the APTT of the test sample is not particularly limited, but from the perspective of improving detection efficiency by targeting more suspicious samples, it is desirable to set it at the lower limit of normal. Preferably, samples that show an APTT within the above range (preferably between the lower limit of normal and the upper limit of normal + 5 seconds) in conventional coagulation tests can be considered to have no clear APTT prolongation and can be selected as test samples for the methods of the present invention. On the other hand, samples with clearly prolonged APTTs, such as those with an APTT exceeding the upper limit of normal + 5 seconds, are determined to have coagulation abnormalities and therefore do not necessarily need to be subjected to the methods of the present invention.

[0017] The "normal range" of APTT in this specification is synonymous with the term "reference range" in the field of clinical testing, as described above. The APTT of a sample can be calculated according to the usual APTT measurement procedure described below. Since the APTT is affected by the reagents and analytical equipment used in the measurement, the normal range of APTT used in the method of the present invention can be predetermined by those skilled in the art depending on the reagents and analytical equipment used in the APTT measurement.

[0018] In the method of the present invention, the test sample is preferably plasma from a subject collected for a coagulation test. An anticoagulant commonly used in coagulation tests may be added to the sample. For example, plasma can be obtained by collecting blood using a blood collection tube containing sodium citrate and then centrifuging the blood.

[0019] 2. Acquisition of Coagulation Reaction Data 2.1. Coagulation Reaction Measurement Coagulation reaction data for a sample can be acquired according to the usual coagulation reaction measurement procedure for APTT measurement. Specifically, in coagulation reaction measurement, an APTT measurement reagent is added to a sample to initiate a blood coagulation reaction. The coagulation reaction in a mixture containing the reagent and the sample is measured. APTT measurement reagents are commercially available (e.g., APTT Reagent Coagpia APTT-N and Coagpia APTT-N Calcium Chloride Solution; both manufactured by Sekisui Medical Co., Ltd.). Coagulation reaction measurement can be performed using conventional means, such as optical means for measuring scattered light intensity, transmittance, absorbance, etc., or mechanical means for measuring plasma viscosity. In the following specification, the method of the present invention will be described using coagulation reaction measurement based on scattered light intensity as an example.

[0020] The start of the clotting reaction is typically defined as the time when the sample is mixed with the reagent to initiate the clotting reaction, but other timings may also be defined as the start of the reaction. The duration of the clotting reaction measurement may be, for example, several tens of seconds to approximately seven minutes from the time when the sample and reagent are mixed. This measurement time may be an arbitrarily determined fixed value, or it may be continued until the end of the clotting reaction of each sample is detected. During this measurement time, measurement of the progress of the clotting reaction (measurement of the amount of scattered light) may be repeated at predetermined intervals. For example, measurements may be performed at 0.1-second intervals. The temperature of the mixed solution during the measurement is kept under normal conditions, for example, 30°C or higher and 40°C or lower, preferably 35°C or higher and 39°C or lower. Furthermore, various measurement conditions may be appropriately set depending on the test sample, reagent, measurement means, etc.

[0021] The series of operations in the coagulation reaction measurement described above can be performed using an automatic analyzer. An example of an automatic analyzer is the CP3000 automatic blood coagulation analyzer (manufactured by Sekisui Medical Co., Ltd.). Alternatively, some of the operations may be performed manually. For example, sample preparation may be performed manually, and subsequent operations may be performed by the automatic analyzer.

[0022] 2.2. Obtaining a Coagulation Reaction Curve A coagulation reaction curve R(i) of a sample is obtained from the measured coagulation reaction data. Here, "i" is a variable representing the number of measurement points or the time (also simply referred to as the number of measurement points and time, respectively) from the start of the coagulation reaction. For example, if the measurement (photometric) interval is 0.1 seconds, time is expressed as 0.1 × the number of measurement points. That is, R(i) may be a function of the number of measurement points or a function of time. Generally, the coagulation reaction curve R(i) is obtained by performing noise removal or smoothing processing on the measurement values ​​of the coagulation reaction measurement using conventional means. Alternatively, R(i) may be obtained by zero-point adjusting or relative-value-reducing the measurement data D(i) that has been subjected to the noise removal or smoothing processing. The zero-point adjusted R(i) may be, for example, a curve obtained by shifting D(i) so that its initial value is 0. The relative valued R(i) can be calculated, for example, according to the formula: R(i) = [(D(i) - Dmin) / (Dmax - Dmin)] × A (where D(i) represents R(i) before relative valued, Dmax and Dmin represent the maximum and minimum values ​​of D(i), respectively, and A is an arbitrary constant that corresponds to the maximum value of the relative valued R(i)).

[0023] 2.3. Detection of Clotting Reaction End Point Re If necessary, the clotting reaction end point Re in R(i) can be detected. Re is R(i) at the point where R(i) reaches a plateau; R(i) at the point where the first derivative curve of R(i) reaches a peak and then decreases to 0 or a constant value (see WO2021 / 206107); R(i) at the earliest point where the integrated ratio of R(i) in a short time period is less than a threshold value (e.g., 1.001) (WO2021 / 132552), etc. It can be determined according to any criteria. Detection of Re may be performed after acquiring R(i) up to a predetermined measurement time, or detection of Re may be performed in parallel with acquisition of R(i), and acquisition of R(i) may be terminated once Re is detected. In the latter case, it is possible to shorten the measurement time for one sample to the minimum necessary. For example, the procedures described in WO2021 / 206107 or WO2021 / 132552 allow the detection of Re to be carried out in parallel with the acquisition of R(i) (so-called real-time detection of Re).

[0024] As one embodiment of the method of the present invention, an example of a detection procedure for Re based on the method described in WO 2021 / 132552 will be described in detail. The integrated ratio of R(i) during a short time period is defined as Z(i) and is calculated using the following formula: Integrated ratio Z(i) = Rb(i) / Ra(i) Ra(i) = Sum of R(i-m) to R(i-1) Rb(i) = Sum of R(i+1) to R(i+m) In the above formula, i represents the measurement point number, and m can be set appropriately depending on the measurement conditions and analysis items of the coagulation reaction, for example, m = 10 to 30. R(i) at the earliest measurement point or time point at which Z(i) is less than the threshold Zs is detected as the coagulation reaction end point Re. Zs can be set appropriately depending on the analysis item. For example, in the case of APTT measurement, Zs is preferably 1.050 or less, more preferably in the range of 1.010 to 1.001. In order to prevent erroneous detection of Re due to an abnormal initial reaction, it is preferable to calculate Z(i) after i reaches a predetermined calculation start point and R(i) becomes equal to or greater than a predetermined value. In this procedure, while measuring the coagulation reaction, R(i) is acquired and Z(i) is calculated in parallel, and Re can be detected.

[0025] 2.4. Obtaining a First-Order Derivative Curve If necessary, a first-order derivative curve (clotting reaction rate curve) V(i) may be obtained from the coagulation reaction curve R(i). Differentiation of the coagulation reaction curve can be performed by any method, for example, by calculating the average slope within a section. Alternatively, V(i) may be relativized. The relativized V(i) can be calculated, for example, according to the formula: V(i) = [(D(i) - Dmin) / (Dmax - Dmin)] × A (where D(i) represents V(i) before relativization, Dmax and Dmin represent the maximum and minimum values ​​of D(i), respectively, and A is an arbitrary constant corresponding to the maximum value of the relativized V(i)).

[0026] In this specification, R(i) includes the coagulation reaction curve with or without the relativization, unless otherwise specified. Also, in this specification, V(i) includes the first derivative curve with or without the relativization, unless otherwise specified.

[0027] 3. APTT Calculation The clotting time (APTT) of a sample can be calculated from the clotting reaction data of the sample obtained by the clotting reaction measurement. The method for calculating the APTT is not particularly limited. For example, the APTT can be calculated by any method based on R(i) or V(i). Examples of the APTT calculation method include, but are not limited to, a method in which the point at which R(i) reaches N% of the end point of the clotting reaction (for example, the above-mentioned Re) is calculated as the clotting time (percentage detection method); a method in which the point at which V(i) reaches N% of its maximum value is calculated as the clotting time; and a method in which the point at which the integrated ratio of R(i) in a short time period reaches a predetermined value is set as the calculation starting point Te, and the point at which R(i) reaches N% of R(Te) is calculated as the clotting time (see JP 6-249855 A). Examples include a method of calculating the clotting time based on the time-dependent change in the cumulative ratio of R(i) over a short time period (see WO2021 / 132552); a method of calculating the clotting time based on the weighted average time of V(i) (see WO2021 / 177452); and a method of calculating the clotting time from the point Te when V(i) reaches a predetermined value after reaching its maximum value, when R(i) reaches N% of R(Te) (see WO2021 / 206107).

[0028] Based on the calculated APTT of the sample, a test sample to which the method of the present invention is applied can be selected. In one embodiment, the coagulation reaction of an arbitrary sample is measured, the APTT is calculated, and then a sample in which it cannot be determined that the APTT is prolonged is selected as a test sample of the present invention. In another embodiment, a sample in which it is known from existing coagulation reaction data that the APTT is not clearly prolonged is selected as a test sample of the present invention.

[0029] 4. Acquisition of Parameters In the method of the present invention, parameters are acquired based on the coagulation curve or its first derivative curve of the test sample. In this specification, the coagulation curve and its first derivative curve of the test sample are referred to as Rs(i) and Vs(i), respectively, and the parameter based on these curves is referred to as Ps(X), where X is a variable and X>0.

[0030] Furthermore, in the method of the present invention, corresponding parameters for normal samples are obtained. Specifically, parameters based on the coagulation curve or its first derivative curve of each sample in the normal sample group are obtained, and their average value is calculated. Samples known to have no coagulation abnormality can be used as each normal sample belonging to the normal sample group. The total number of normal samples used is preferably 5 or more, more preferably 10 to 30. In this specification, the coagulation curve and its first derivative curve of each sample in the normal sample group are respectively referred to as Rm j (i) and Vm j Here, j represents the sample number of each sample belonging to the normal sample group and is an integer between 1 and k, and k represents the total number of samples belonging to the normal sample group. Therefore, the coagulation reaction curves Rm1(i), Rm2(i), ... Rm for each of the k normal samples are k (i) is obtained. Alternatively, the first derivative curves Vm1(i), Vm2(i), ... Vm for each of the k normal samples are obtained. k (i) is obtained. j (X) or Vm j Based on (X), the parameter Pm for each sample in the normal sample group is calculated. j (X) is obtained (j = 1 to k). Then, Pm j The average value Pm(X) of (X) is obtained. Pm(X) is expressed by the following formula (1), where X is as above:

[0031] Ps(X), Pm j Specific examples of (X) include those described in (a) to (g) below.

[0032] (a) Ps(X) represents the measurement point or time at which Rs(i) reaches X% of its coagulation reaction end point. Pm j (X) is the coagulation reaction curve Rm for each sample in the normal sample group. j (i) represents the measurement point or time when X% of the coagulation reaction end point is reached. That is, Ps(X) and Pm j (X) satisfies the following formula: Rs(Ps(X)) = Rs_e × X% Rm j (P.M. j (X)) = Rmj _e × X% where Rs_e represents the end point of the coagulation reaction of Rs(i), and Rm j _e is Rm j (i) represents the end point of the coagulation reaction, and 0<X≦100.

[0033] (b) Ps(X) represents the measurement point or time at which Vs(i) reaches X% of its maximum value. j (X) is the Vm for each sample in the normal sample group. j represents the measurement point or time when (i) reaches X% of its maximum value, i.e., Ps(X) and Pm j (X) satisfies the following formula: Vs(Ps(X))=Vs_max×X% Vm j (P.M. j (X)) = Vm j _max × X% In the above formula, Vs_max represents the maximum value of Vs(i), and Vm j _max is Vm j (i), and 0<X≦100. Since the first derivative curve is a mountain-shaped curve, Ps(X) and Pm j There are multiple (X) and they can exist before or after Ps(100) (the point where Vs_max is reached). Therefore, if Ps(X) is greater than Ps(100), Ps(X) is redefined as Ps(200-X). Similarly, Pm j (X) is Pm j If it is greater than (100), Pm j (X) is Pm j Therefore, Ps(X) and Pm j In (X) and Pm(X), the range of X is finally 0<X<200.

[0034] (c) Ps(X) represents the minimum value of the measurement point or time at which Vs(i) reaches X% of its maximum value. j (X) is Vm j (i) represents the minimum value of the measurement point or time at which it reaches X% of its maximum value, where 0<X≦100.

[0035] (d) Ps(X) represents the maximum value of the measurement point or time at which Vs(i) reaches X% of its maximum value.j (X) is Vm j (i) represents the maximum value of the measurement point or time at which it reaches X% of its maximum value, where 0<X≦100.

[0036] (e) Ps(X) represents the midpoint between the minimum and maximum values ​​(calculated in (c) and (d) above) of the measurement point or time when Vs(i) reaches X% of its maximum value. Pm j (X) is Vm j (i) represents the midpoint between the minimum and maximum values ​​of the measurement point or time at which it reaches X% of its maximum value, where 0<X≦100.

[0037] (f) Ps(X) represents the length between the minimum and maximum values ​​(calculated in (c) and (d) above) of the measurement point or time when Vs(i) reaches X% of its maximum value. Pm j (X) is Vm j (i) represents the length between the minimum and maximum values ​​of the measurement point or time at which it reaches X% of its maximum value, where 0<X<100.

[0038] (g) Ps(X) represents the weighted average time of Vs(i). Pm j (X) is Vm j (i) represents the weighted average time. The weighted average time is calculated according to the following formula (3). In the formula, V(i) is Vs(i) or Vm j (i), t1 and t2 respectively represent the minimum and maximum values ​​of the measurement points or times at which V(i) reaches X% of its maximum value, and 0<X≦100, provided that when V(i) is less than X% of the maximum value, V(i) is considered to be 0.

[0039] Ps(X) and Pm according to (a) to (g) above jIn the calculation procedure for (X), X may vary from the initial value by an increment α (α is preferably an integer from 1 to 5). In one example, X is a variable that varies in increments of 1 within the range of 1 < X ≦ 100 (i.e., X = {1, 2, 3, ..., 97, 98, 99, 100}). In another example, X is a variable that varies in increments of 5 within the range of 3 to 98 (i.e., X = {3, 8, 13, ..., 93, 98}). Alternatively, Ps(X) may be expressed as the average value from Ps(X - K) to Ps(X + K). In this case, K is preferably smaller than the increment α of X described above. For example, if K = 2, Ps(X) can be expressed as the average value from Ps(8) to Ps(12) when X = 10, or as the average value from Ps(13) to Ps(17) when X = 15. PM j The same is true for (X). Therefore, a series of Ps(X) and Pm(X) can be obtained according to the varying X as described above.

[0040] 5. Obtaining the index S Next, the index S for the test sample is obtained from the obtained Ps(X) and Pm(X). The index S is calculated according to the following formula (2). where Fs(X) = Ps(X) - Ps(c), and Fm(X) = Pm(X) - Pm(c), or Fs(X) = Ps(X) / Ps(c), and Fm(X) = Pm(X) / Pm(c), where a > 0 and a ≦ b. c is a constant, and 0 < c ≦ M, where M is the maximum value of X. Therefore, in the present invention, in the calculation procedure for Ps(X) and Pm(X) described in 4. above, X is varied so as to fall within the range from a to b and include c, and a series of Ps(X) and Pm(X) is obtained. The index S can be obtained using the obtained series of Ps(X) and Pm(X), and the series of Fs(X) and Fm(X) obtained from Ps(c) and Pm(c).

[0041] Note that Fm(X) is Pm j It can also be expressed by the following formula based on (X), which will be understood to be equivalent to [Pm(X) / Pm(c)].

[0042] The index S is the sum of squares of Fs(X) (however, when a = b in the above formula (2), it is the square of Fs(X)). Furthermore, it can be understood that the index S can be expressed by the following formula (2)' or formula (2)" instead of the above formula (2). For convenience in the following formulas, the index expressed by formula (2)' will be represented as S', and the index expressed by formula (2)" will be represented as S", but in this specification, the indexes expressed by formula (2), formula (2)', and formula (2)" may all be referred to as S.

[0043] Fs(X) represents the difference or ratio of Ps(X) obtained in 4. above to Ps(c). Similarly, Fm(X) represents the difference or ratio of Pm(X) to Pm(c). Ps(c) and Pm(c) may be predetermined values ​​representing the values ​​of Ps(X) and Pm(X), respectively, when X = c.

[0044] Alternatively, for Ps(c) and Pm(c), other predetermined values ​​can be used instead of the predetermined values ​​representing the values ​​of Ps(X) and Pm(X) when X = c described above. For example, if Ps(X) and Pm(X) comply with any of 4.(a), (c) to (g) above, Ps(c) and Pm(c) calculated according to 4.(b) above can be used instead of Ps(c) and Pm(c) calculated according to each of 4.(a), (c) to (g). In this case, Ps(c) is the measurement point or time at which Vs(i) reaches c% of its maximum value, and Pm(c) is as follows: PM j (c) is Vm j (i) represents the measurement point or time at which c% of the maximum value is reached.

[0045] The above-mentioned formula (2) for calculating the index S can be divided into the following formulas (2a) and (2b) depending on the types of Fs(X) and Fm(X). Therefore, in this specification, the value calculated by formula (2a) is referred to as index S-1, and the value calculated by formula (2b) is referred to as index S-2.

[0046] Similar to the index S described above, index S-1 can be expressed by the following formula (2a)' or formula (2a)" instead of the formula (2a), and index S-2 can be expressed by the following formula (2b)' or formula (2b)" instead of the formula (2b). For convenience, in the following formulas, the index represented by formula (2a)' will be represented as S'-1, the index represented by formula (2a)" as S"-1, the index represented by formula (2b)' as S'-2, and the index represented by formula (2b)" as S"-2. However, in this specification, the indexes represented by formula (2a), formula (2a)', and formula (2a)" may all be referred to as S-1, or the indexes represented by formula (2b), formula (2b)', and formula (2b)" may all be referred to as S-2.

[0047] In the formulas (2), (2a) and (2b), the values ​​of a, b and c can be set appropriately depending on the type of Ps(X) (and Pm(X)).

[0048] In one embodiment, when Ps(X) and Pm(X) comply with (a) of 4. above, in formula (2), a is preferably 3 to 97, b is preferably 3 to 97, and c is preferably 3 to 97, provided that when Ps(c) and Pm(c) comply with (b) of 4. above, c is preferably 98 to 102. More specifically, when Ps(c) and Pm(c) comply with (b) of 4. above in formula (2a), a is preferably 3 to 97, more preferably 3 to 77, b is preferably 3 to 97, more preferably 23 to 97, and c is preferably 98 to 102, more preferably 99 to 101. When Ps(c) and Pm(c) comply with (b) of 4. above in formula (2b), a is preferably 3 to 97, more preferably 3 to 77, b is preferably 3 to 97, more preferably 23 to 97, and c is preferably 98 to 102, more preferably 99 to 101. In the case of (b) above, a is preferably 3 to 87, more preferably 3 to 85, b is preferably 4 to 97, more preferably 23 to 97, and c is preferably 98 to 102, more preferably 99 to 101.

[0049] In one embodiment, when Ps(X) and Pm(X) comply with (b) of 4. above, in formula (2), a is preferably 3 to 98, b is preferably 103 to 198, and c is preferably 3 to 198. More specifically, in formula (2a), a is preferably 3 to 98, more preferably 3 to 93, b is preferably 103 to 198, more preferably 123 to 198, and c is preferably 3 to 198, more preferably 98 to 100. In formula (2b), a is preferably 3 to 98, more preferably 3 to 93, b is preferably 103 to 198, more preferably 123 to 198, and c is preferably 3 to 198, more preferably 3 to 117. In formulas (2), (2a), and (2b), c may or may not be within the range of a to b.

[0050] In one embodiment, when Ps(X) and Pm(X) comply with (c) of Section 4. above, in formula (2), a is preferably 3 to 98, b is preferably 3 to 98, and c is preferably 3 to 197. More specifically, in formula (2a), a is preferably 3 to 98, more preferably 23 to 53, b is preferably 3 to 98, more preferably 53 to 98, and c is preferably 3 to 197, more preferably 13 to 68. In formula (2b), a is preferably 3 to 98, more preferably 3 to 93, b is preferably 3 to 98, more preferably 3 to 83, and c is preferably 13 to 192, more preferably 48 to 172. In formulas (2), (2a), and (2b), c may or may not be within the range of a to b.

[0051] In one embodiment, when Ps(X) and Pm(X) comply with (d) of Section 4. above, in formula (2), a is preferably 3 to 98, b is preferably 3 to 98, and c is preferably 3 to 197. More specifically, in formula (2a), a is preferably 3 to 98, more preferably 3 to 53, b is preferably 13 to 98, more preferably 23 to 83, and c is preferably 3 to 197, more preferably 100 to 157. In formula (2b), a is preferably 3 to 98, more preferably 3 to 53, b is preferably 3 to 98, more preferably 23 to 93, and c is preferably 3 to 197, more preferably 3 to 73. In formulas (2), (2a), and (2b), c may or may not be within the range of a to b.

[0052] In one embodiment, when Ps(X) and Pm(X) comply with (e) of Section 4. above, in formula (2), a is preferably 3 to 98, b is preferably 3 to 98, and c is preferably 3 to 197. More specifically, in formula (2a), a is preferably 3 to 98, more preferably 3 to 83, b is preferably 3 to 98, more preferably 13 to 98, and c is preferably 3 to 197, more preferably 100 to 107. In formula (2b), a is preferably 3 to 98, more preferably 13 to 93, b is preferably 3 to 98, more preferably 33 to 98, and c is preferably 3 to 197, more preferably 3 to 127. In formulas (2), (2a), and (2b), c may or may not be within the range of a to b.

[0053] In one embodiment, when Ps(X) and Pm(X) comply with (f) of Section 4. above, in formula (2), a is preferably 3 to 98, b is preferably 3 to 98, and c is preferably 3 to 197. More specifically, in formula (2a), a is preferably 3 to 98, more preferably 23 to 98, b is preferably 3 to 98, more preferably 13 to 98, and c is preferably 3 to 98, more preferably 23 to 98. In formula (2b), a is preferably 3 to 83, more preferably 13 to 83, b is preferably 3 to 98, more preferably 33 to 98, and c is preferably 3 to 197, more preferably 13 to 88 and 132 to 197. In formulas (2), (2a), and (2b), c may or may not be within the range of a to b.

[0054] In one embodiment, when Ps(X) and Pm(X) comply with (g) of Section 4. above, in formula (2), a is preferably 3 to 98, b is preferably 3 to 98, and c is preferably 3 to 197. More specifically, in formula (2a), a is preferably 3 to 98, more preferably 3 to 83, b is preferably 3 to 98, more preferably 43 to 73, and c is preferably 3 to 197, more preferably 100 to 107. In formula (2b), a is preferably 3 to 98, more preferably 3 to 93, b is preferably 3 to 98, more preferably 13 to 98, and c is preferably 3 to 197, more preferably 3 to 127. In formulas (2), (2a), and (2b), c may or may not be within the range of a to b.

[0055] In the above procedure of the present invention, Pm(X) and Fm(X) can be calculated in advance according to the types of Ps(X) and Fs(X) obtained from the test sample. In a specific example, prior to measuring coagulation reaction data from the test sample, Pm(X) according to (a) to (g) in 4. above is calculated from the coagulation reaction data of each sample in an existing normal sample group, and Fm(X) according to formulas (2a) and (2b) is calculated using this. Depending on the types of Ps(X) and Fs(X) obtained from the test sample, the index S for the test sample is calculated according to formula (2) above using Fm(X) calculated from the corresponding Pm(X).

[0056] The index S for the test sample reflects the degree of difference in the waveform of the clotting reaction curve or its first derivative curve between the test sample and a normal sample. The larger the index S, the more significantly the waveform of the clotting reaction curve of the test sample differs from that of the normal sample.

[0057] 6. Selection of Blood Samples Possibly Having Coagulation Abnormalities The index S for the test sample is used to evaluate the likelihood that the test sample has a coagulation abnormality. In one embodiment of the present invention, the index S for the test sample is compared with the statistical value of the index S for a group of normal samples to evaluate whether the test sample is likely to have a coagulation abnormality. For example, S-1 or S-2 is calculated for each sample in an arbitrary normal sample group, and the maximum value of these is compared with S-1 or S-2 of the test sample. If S-1 or S-2 of the test sample is greater than the maximum value for the normal sample group, the test sample is likely to have a coagulation abnormality.

[0058] In a preferred embodiment of the present invention, the standard deviation index (SDI) of the index S for the test sample is calculated to compare the index S of the test sample with the statistical value of the index S of the normal sample group. More specifically, the absolute value of the SDI of the index S for the test sample is calculated, which is also referred to herein as SDI_S, and is calculated as follows: SDI_S = |([index S for the test sample] - [average value of index S for each sample in the normal sample group]) / [standard deviation of index S for each sample in the normal blood sample group] | The normal sample group used in the above formula can be samples known to be free of coagulation abnormalities. It may be a sample group different from the normal sample group used to calculate Pm(X) above, but is preferably the same sample group. The total number of normal samples included in the normal sample group is preferably 5 or more, more preferably 10 to 30. Preferably, the standard deviation of the APTT of the normal sample group is 2 seconds or more.

[0059] The index S for each sample in the normal sample group can be calculated using the same procedure as for the index S for the test sample in accordance with Sections 4 and 5 above, except that the test sample is replaced with each sample in the normal sample group. For example, if SDI_S is based on the index S-1 according to Equation (2a) using Ps(X) according to Section 4(a) above, the index S-1 for the normal sample can also be calculated using Section 4(a) and Equation (2a) above. The index S, its mean value, and standard deviation for each sample in the normal sample group can be calculated in advance. For example, prior to measuring coagulation reaction data from the test sample, the indexes S-1 and S-2 can be calculated from the existing coagulation reaction data for each sample in the normal sample group using each of Sections 4(a) to (g) above. When calculating the SDI described above, an appropriate index corresponding to the index S for the test sample is used.

[0060] Furthermore, in the present invention, the SDI of the APTT for the test sample is used, if necessary, to select samples that may have a coagulation abnormality. More specifically, the absolute value of the SDI of the APTT for the test sample is calculated, which is also referred to as SDI_APTT in this specification, and is calculated as follows: SDI_APTT = |([APTT for the test sample] - [mean APTT value for each sample in the normal sample group]) / [standard deviation of APTT for each sample in the normal blood sample group] | The normal sample group used in the above formula is the same sample group as used to calculate SDI_S. The APTT, its mean value, and standard deviation for each sample in the normal sample group can be calculated in advance, for example, prior to measuring coagulation reaction data from the test sample. Next, the ratio of SDI_S to SDI_APTT (hereinafter also referred to as SDI ratio or rSDI) is calculated as follows: rSDI = SDI_S / SDI_APTT

[0061] Based on the SDI_S or the SDI_S and rSDI, it can be evaluated whether the test specimen is likely to have a coagulation disorder, such as a deficiency of a coagulation factor or a positive lupus anticoagulant (LA) test result. Examples of the coagulation factor include factor VIII (FVIII), factor IX (FIX), and von Willebrand factor (VW).

[0062] More specifically, a test sample with an SDI_S at or above a threshold, or a test sample with both an SDI_S and an rSDI at or above a threshold, may have a coagulation disorder. The threshold can be set as appropriate; for example, the SDI_S can be calculated for each sample in an arbitrary normal sample population, and a value greater than the maximum of these values ​​can be set as the threshold. In a preferred embodiment, the threshold for SDI_S is preferably 3 or greater, more preferably 4 or greater, and for rSDI is preferably 1 or greater, more preferably 2 or greater. Given the lack of a clear prolongation of APTT, test samples assessed as possibly having a coagulation disorder using the method of the present invention are likely to be samples from patients with some type of coagulation disorder, such as mild hemophilia, even though they do not exhibit clear symptoms. Therefore, the method of the present invention makes it possible to select samples from patients with coagulation disorders that have previously been difficult to detect. Furthermore, test samples determined to have a possible coagulation disorder can be subjected to additional testing, if necessary, to determine the presence or type of coagulation disorder. Furthermore, in the case of test samples in which the APTT was prolonged but which were determined to be unlikely to have coagulation abnormalities, it can be inferred that the APTT prolongation may have been due to a false abnormality in the APTT.

[0063] Alternatively, the SDI_S for each of the indicators S-1 and S-2, or the SDI_S and rSDI, can be determined and used to evaluate the test specimen. For example, a test specimen in which the SDI_S for S-1 and the SDI_S for S-2 are both at or above a threshold value is evaluated as possibly having a coagulation abnormality. Also, for example, a test specimen in which the SDI_S and rSDI for S-1 and the SDI_S and rSDI for S-2 are both at or above a threshold value is evaluated as possibly having a coagulation abnormality.

[0064] The selection results obtained above can be output in any format. For example, information regarding whether the test sample is likely to have a coagulation abnormality (in other words, whether the waveform of the test sample's coagulation reaction curve or its first derivative curve differs from that of a normal sample) can be output in any format. More detailed output examples for waveforms that differ from those of a normal sample include flags indicating information such as "waveform different from normal sample," "additional testing necessary," or "possible coagulation abnormality." Along with the selection result information, the APTT of the test sample and information regarding whether APTT prolongation is present can also be output. For example, if the APTT of the test sample is prolonged beyond the upper limit of the normal range, the APTT and a flag indicating APTT prolongation can be output. On the other hand, if the APTT of the test sample is within the upper limit of the normal range, the APTT can also be output. Alternatively, information regarding the APTT can be output even if the test sample is not selected as having a possible coagulation abnormality and therefore information regarding the selection result is not output.

[0065] 7. Application to Other Clotting Reaction Measurement Methods The method of the present invention has been described above using an example of clotting reaction measurement based on the amount of scattered light. However, a person skilled in the art would be able to apply other clotting reaction measurement methods (e.g., clotting reaction measurement based on transmittance, absorbance, viscosity, etc.) to the clotting reaction measurement of the present invention, and such applications are therefore within the scope of the present invention.

[0066] 8. Program and Apparatus The series of processes of the method of the present invention described above can be performed automatically by an automatic analysis device. For example, an automatic analysis device controlled by a computer program can be used. Therefore, one aspect of the present invention is a program for performing the method of the present invention described above. Another aspect of the present invention is an apparatus for performing the method of the present invention described above. The execution of the method of the present invention by the apparatus can be controlled by the program of the present invention. A further aspect of the present invention is a system for performing the method of the present invention, which system includes the apparatus or program for performing the method of the present invention described above.

[0067] An embodiment of the apparatus of the present invention will be described below. In this embodiment of the apparatus of the present invention, an automatic analyzer 1 includes a control unit 10, an operation unit 20, a measurement unit 30, and an output unit 40. The configuration of the automatic analyzer 1 will be described below.

[0068] The control unit 10 controls the overall operation of the automated analyzer 1. The control unit 10 may be configured by a computer (e.g., a personal computer). The control unit 10 includes a CPU, memory, storage, a communication interface (I / F), and can process commands from the operation unit 20, control the operation of the measurement unit 30, store and analyze measurement data received from the measurement unit 30, store analysis results, and control the output of analysis results by the output unit 40. The control unit 10 may also be connected to other devices such as external media or a host computer. In the control unit 10, the computer that controls the operation of the measurement unit 30 and the computer that analyzes the data measured by the measurement unit 30 may be the same or different.

[0069] The operation unit 20 acquires input from an operator and transmits the acquired input information to the control unit 10. For example, the operation unit 20 includes a user interface (UI) such as a keyboard or a touch panel. Under the control of the control unit 10, the output unit 40 outputs the detection results of samples that may have coagulation abnormalities, and, as necessary, the coagulation reaction data of the samples measured by the measurement unit 30, and the results of R(i), V(i), APTT, etc. based on the data. For example, the output unit 40 includes a display device such as a display.

[0070] The measuring unit 30 executes a series of processes for a blood coagulation test and acquires measurement data of the coagulation reaction of a sample including a blood sample. The measuring unit 30 includes various equipment and analysis modules necessary for a blood coagulation test, such as a sample container for storing the blood sample, a reagent container for storing the test reagent, a reaction container for the reaction between the sample and the reagent, a probe for dispensing the blood sample and the reagent into the reaction container, a light source, a detector for detecting scattered light or transmitted light from the sample in the reaction container, a data processing circuit for sending data from the detector to the control unit 10, and a control circuit for controlling the processing of the measuring unit 30 in response to commands from the control unit 10. Alternatively, the measuring unit 30 is not necessary when calculating R(i), V(i), APTT, etc. using already acquired coagulation reaction data.

[0071] The control unit 10 analyzes the coagulation reaction of the sample based on the coagulation reaction data. This analysis may include calculation of R(i) and V(i), calculation of APTT, calculation of Ps(X), Fs(X) and index S, and detection of a sample that may have a coagulation abnormality using index S. The R(i) and V(i) data may be generated by the control unit 10 based on measurement data from the measurement unit 30, or may be generated by another device, for example, the measurement unit 30, and sent to the control unit 10. The control unit 10 also includes a memory for storing the APTT, Ps(X), Fs(X) and index S for normal samples. j (X), Pm(X), Fm(X), the index S, thresholds used for detecting samples that may have coagulation abnormalities, etc. may be stored, or the control unit 10 may retrieve these values ​​stored in an external device or on a network for the detection.

[0072] The above analysis can be performed by a program for carrying out the method of the present invention. Thus, the control unit 10 can be provided with a program for the method of the present invention for selecting a blood sample that may have a blood coagulation disorder.

[0073] The analysis results from the control unit 10 are sent to the output unit 40 and output. The output may take any form, such as display on a screen, transmission to a host computer, or printing. The output information from the output unit may include the APTT of the test sample, information on the possibility of the test sample having a coagulation abnormality, etc. The type of information output from the output unit may be controlled by the program of the present invention.

[0074] 9. Analysis Flow One embodiment of the process of the method for selecting a blood sample that may have a coagulation abnormality according to the present invention, which is carried out under the control of the program of the present invention, is described below and in Figure 1. S1: Acquire coagulation reaction data (Rs(i) or Vs(i)) of the test sample. S2: Calculate APTT based on Rs(i) or Vs(i). S3: Calculate Ps(X) based on Rs(i) or Vs(i). S4: Calculate index S using Ps(X). S5: Calculate SDI and SDI ratio of index S. S6: If both SDI and SDI ratio exceed the threshold, determine that there is a "possible coagulation abnormality." S7: Output APTT and the determination result.

[0075] Another embodiment of the process of the method for selecting a blood sample possibly having a coagulation disorder according to the present invention, which is carried out under the control of the program of the present invention, is described below and in FIG. 2 . This process includes a step of selecting a test sample based on APTT. The threshold conditions used in this process are an example that uses SDI (SDI_S) and SDI ratio (rSDI). S01: Acquire coagulation reaction data (Rs(i) or Vs(i)) of the test sample. S02: Calculate APTT based on Rs(i) or Vs(i). S03: Determine whether the APTT of the test sample exceeds a predetermined value (UL+5 (seconds); UL = upper limit of normal range). APTT≦UL+5 →Go to S04 APTT>UL+5 →Go to S10 S04: Calculate Ps(X) from Rs(i) that satisfies the following: Rs(Ps(X))=Rs_e×X% S05: Calculate index S from Ps(X). S06: Calculate the SDI and SDI ratio of index S. S07: Compare the SDI and SDI ratio with a threshold value. If both the SDI and SDI ratio exceed the threshold value → go to S08. If neither the SDI nor the SDI ratio exceeds the threshold value → go to S09. S08: Determine whether the APTT of the test sample exceeds the UL. APTT>UL → go to S40 APTT≦UL → go to S50 S09: Determine whether the APTT of the test sample exceeds the UL. APTT>UL → go to S20 APTT≦UL → go to S30 S10: Output the APTT together with a flag indicating "APTT>UL+5". S20: Output the APTT together with a flag indicating "APTT>UL". S30: Output the APTT. S40: Output APTT, a flag indicating "APTT>UL", and a flag indicating "possible coagulation abnormality". S50: Output APTT and a flag indicating "possible coagulation abnormality".

[0076] The present invention will be described in more detail below with reference to examples, but the present invention is not limited to these examples. The coagulation reaction measurements in the following examples were carried out according to the procedure for APTT measurement.

[0077] 1. Methods 1.1) Samples Normal sample (NP): Plasma from healthy individuals without coagulation disorders (N1-N12, total n = 12). Abnormal sample (Abn): Plasma from patients with coagulation disorders (total n = 4). FVIII deficiency (FVIII) (n = 1). FIX deficiency (FIX) (n = 1). von Willebrand disease (VW) (n = 1). LA positive (LA) (n = 1). Control sample (Cont) (total n = 5). APTT series samples (c1-c5) were prepared as follows using Control P-N I, which has a normal APTT, and Control P-N II, which has a prolonged APTT, included with the Coagpia Control P-N (manufactured by Sekisui Medical Co., Ltd.). Control P-N I was used as is for c1. Samples c2-c5 were prepared by mixing Control P-N I and Control P-N II at different ratios to achieve different APTTs.

[0078] 1.2) Coagulation Reaction Measurement Coagulation reaction measurements of specimens containing specimens were performed using a CP3000 automated blood coagulation analyzer (manufactured by Sekisui Medical Co., Ltd.). 50 μL of specimen was heated in a cuvette at 37°C for 45 seconds, after which 50 μL of APTT measurement reagent at approximately 37°C was added. After a further 171 seconds, 50 μL of calcium chloride solution was added to initiate the coagulation reaction. The reaction was carried out at 37°C. To measure the coagulation reaction, the cuvette was irradiated with light having a wavelength of 660 nm from an LED light source, and the amount of scattered light at a 90-degree side angle was measured at 0.1-second intervals. The measurement time was 200 seconds.

[0079] 1.3) Acquisition of a Coagulation Reaction Curve The measurement data of the coagulation reaction from each sample was subjected to smoothing processing including noise removal, and then zero-point adjustment processing was performed so that the amount of scattered light at the start of measurement was 0. The obtained data was converted into relative values ​​so that the maximum value was 100(%), and a coagulation reaction curve R(i) was created. R(i) was first differentiated and converted into relative values ​​so that the maximum value was 100(%), to calculate V(i). The maximum value V_max of V(i) for each sample was calculated.

[0080] 1.4) Detection of coagulation reaction end point Re The R(i) at the earliest time point at which the integrated ratio Z(i) of the coagulation reaction curve R(i) (see WO2021 / 132552) becomes less than the integrated ratio threshold Zs was detected as the coagulation reaction end point Re. The integrated ratio threshold Zs was set to 1.001. The integrated ratio Z(i) at time point i was calculated as follows: Integrated ratio Z(i) = Rb(i) / Ra(i) Ra(i) = Sum of R(i-20) to R(i-1) Rb(i) = Sum of R(i+1) to R(i+20)

[0081] 1.5) Calculation of APTT The time point when R(i) reached 50% of Re was determined as the APTT. The APTT for each sample was as follows: NP: 26.1 to 39.4 seconds. Abn: 34.3 to 41.2 seconds (FVIII: 41.2 seconds, FIX: 35.7 seconds, VW: 38.7 seconds, LA: 34.3 seconds). Cont: 26.4 to 28.6 seconds. Since the upper limit of the normal range for APTT under the measurement conditions of this example was 39 seconds, the APTTs for the Abn and Cont groups were within the upper limit of the normal range + 5 seconds (44 seconds).

[0082] 1.6) Calculation of parameters Ps(X) and Pm(X) For each specimen in the NP, Abn, and Cont groups, Ps(X) was calculated according to (a) to (g) in the above section 4. ("Parameter Acquisition"). Furthermore, the parameters for each specimen in the NP group were calculated as Pm(X). j (X) (j = 1 to 12), and then averaged to obtain Pm(X).

[0083] 1.7) Calculation of index S Indicators S-1 and S-2 for each sample were calculated according to the following formulas (2a) and (2b).

[0084] Regarding the index S used in the example of abnormal specimen detection described later, the parameters Ps(X) and Pm(X) used to calculate S-1 and S-2, as well as the calculation formula and a, b, and c in the formula, are as shown in Table 1 below. However, the following correction was made to Ps(X) and Pm(X) according to 4.(b) of Example 2: if Ps(X) is greater than Ps(100), Ps(X) is redefined as Ps(200-X); and Pm j (X) is Pm jIf it is greater than (100), Pm j (X) to Pm j Redefined as (200-X).

[0085]

[0086] 1.8) Calculation of SDI For the index S (S-1 and S-2, respectively) for each sample in the Abn group, the SDI (SDI_S) was calculated as follows: SDI_S = |([Index S for each sample in the Abn group] - [Mean value of index S for each sample in the NP group]) / [Standard deviation of index S for each sample in the NP group]| Next, for the APTT of each sample in the Abn group, the SDI (SDI_APTT) was calculated as follows: SDI_APTT = |([APTT for each sample in the Abn group] - [Mean value of APTT for each sample in the NP group]) / [Standard deviation of APTT for each sample in the NP group]| The SDI ratio (rSDI) was calculated as follows: rSDI = SDI_S / SDI_APTT

[0087] 1.9) Thresholds for detecting coagulation abnormalities The thresholds for detecting the presence or absence of coagulation abnormalities in a sample were set to 4 for SDI_S and 2 for rSDI. Samples with both SDI_S and rSDI greater than the thresholds were determined to have coagulation abnormalities.

[0088] 2. Coagulation Reaction 2.1) FVIII Deficiency Figure 3 shows the coagulation reaction of FVIII-deficient samples (FVIII) in the Abn group. Figures 3A-C show the coagulation reaction curves, and Figures 3D-F show the first-derivative curves. In the figures, NL, NM, and NH indicate samples in the NP group with APTTs near the lower, middle, and upper limits of the normal range, respectively, while FVIII indicates Abn samples (FVIII). Figures 3A and 3D show the measured coagulation reaction U (turbidity unit of scattered light, TU) and its first-derivative. In Figures 3B and 3E, the reaction is relativized so that the maximum value of U in Figures 3A and 3D is 100%. In Figure 3C, the reaction time is relativized so that the time when the reaction U is 50% in Figure 3B corresponds to 100% (time) on the horizontal axis. In Figure 3F, the reaction time is relativized so that the time when the reaction U is 100% in Figure 3E corresponds to 100% (time) on the horizontal axis. As shown in Figure 3D and E, the first derivative curves for FVIII showed an asymmetric peak, with a shoulder appearing after the peak top. When comparing FVIII with NM, differences were observed after the peak top of the first derivative curves, as shown in Figure 3F.

[0089] 2.2) FIX Deficiency Figure 4 shows the clotting response of FIX-deficient samples (FIX) from the Abn group. The data shown in Figures 4A-F are the same as those in Figures 3A-F, except that the Abn samples were FIX. As shown in Figure 4F, the clotting response of FIX differed from that of NM after the peak of the first derivative curve, but the difference was smaller than that of FVIII.

[0090] 2.3) von Willebrand Disease (VW) Figure 5 shows the clotting response of the Abn group VW specimen (VW). The data shown in Figures 5A-F are the same as those in Figures 3A-F, except that the Abn specimen was VW. As shown in Figures 5D and 5E, the first-order derivative curve for VW was slightly asymmetric above the peak; that is, the curve descended gradually after the peak top, followed by a rapid decline. Comparing VW with NM, as shown in Figure 5F, a difference was observed in the curve after the peak top, and the difference was slightly larger than that for FVIII.

[0091] 2.4) LA Positive Figure 6 shows the clotting reactions of LA-positive specimens (LA) in the Abn group. The data shown in Figures 6A-F are the same as those in Figures 3A-F, except that the Abn specimens were LA. As shown in Figures 6D and 6E, the first derivative curves for LA were slightly asymmetrical above the peak, i.e., the curves showed a gentler rise just before the peak top. Comparing LA with NM, as shown in Figure 6F, differences were observed before the peak top of the first derivative curve, and some differences were also observed after the peak top.

[0092] 3. Examples of Coagulation Abnormality Detection Example 1 The parameter Ps(X) was determined according to 4.(a) above, and used to calculate the indices S-1 and S-2. Figure 7 illustrates Ps(X) for each sample, as well as Fs(X) and the indices S according to equations (2a) and (2b). In Figure 7A, the vertical axis is X (1 to 100) and the horizontal axis is Ps(X). Figures 7B to 7D show Fs(X) = Ps(X) - Ps(V100), and the absolute values ​​of Fs(X) - Fm(X) and Fs(X) - Fm(X), respectively. Figures 7E to 7G show Fs(X) = Ps(X) / Ps(V100), and the absolute values ​​of Fs(X) - Fm(X) and Fs(X) - Fm(X), respectively. Ps(V100) was calculated according to 4. (b) represents Ps(100). In the figure, NL and NH indicate samples in the NP group whose APTT was close to the lower and upper limits of the normal range, respectively; LA indicates Abn samples (LA); and NA indicates the average value for the NP group. LA was greater than NL and NH for both S-1 and S-2 at X = 1 to 99. Figure 8A shows the index S-1 for each sample. Figures 8B and 8C show the SDI_APTT, SDI_S, and rSDI for the indexes S-1 and S-2 for each sample. The calculation formulas for S-1 and S-2 are shown in Table 1. N1 to N12 indicate samples in the NP group; FVIII, FIX, VW, and LA indicate samples in the Abn group; and c1 to c5 indicate samples in the Cont group. The legend for the black bars in the figures indicates the a, b, and c used in formulas (2a) and (2b) used to calculate the indices S-1 and S-2, expressed in the format [a:b] / [c], where [V100] means that Ps(c) was the aforementioned Ps(V100). S-1 in Figures 8A and 8B represents the sum of squares from Fs(15) to Fs(55) according to formula (2a). S-2 in Figure 8C represents the sum of squares from Fs(15) to Fs(35) according to formula (2b). As shown in Figure 8A, the S-1 values ​​for the Abn group (FVIII, FIX, VW, and LA) were all greater than the maximum value (NP12) for the NP group. Furthermore, as shown in Figures 8B and 8C, SDI_S and rSDI were greater than the set thresholds (4 for SDI_S and 2 for rSDI) in the Abn group (FVIII, FIX, VW, and LA) for S-1 and in FVIII, FIX, and LA for S-2.It was shown that either abnormal specimens could be detected based on indicators S-1 or S-2.

[0093] Example 2: Parameter Ps(X) was determined according to Section 4.(b) above, and used to calculate the indicators S-1 and S-2. The formulas for calculating S-1 and S-2 are shown in Table 1. Figures 9A-G, like Figures 7A-G, illustrate Ps(X) for each sample, as well as Fs(X) and indicator S according to equations (2a) and (2b). FVIII was greater than NL and NH for S-1 at X = 117-197 and for S-2 at X = 102-197. Figures 10A and 10B show the SDI_APTT, SDI_S, and rSDI for indicators S-1 and S-2 for each sample. S-1 in Figure 10A is based on equation (2a), and S-2 in Figure 10B is based on equation (2b). As shown in Figure 10A and B, SDI_S and rSDI were greater than the set threshold for FVIII, VW, and LA for S-1, and for FVIII and LA for S-2, demonstrating that FVIII, VW, and LA samples can be detected based on the indicators S-1 and S-2.

[0094] Example 3: Parameter Ps(X) was calculated according to Section 4.(c) above, and used to calculate indicators S-1 and S-2. The formulas for calculating S-1 and S-2 are shown in Table 1. Figures 11A-G, like Figures 7A-G, explain Ps(X) for each sample, as well as Fs(X) and indicator S according to equations (2a) and (2b). LA was greater than NL and NH for X = 3 to 83 for S-1 and X = 3 to 98 for S-2. Figures 11B-A and 11B-B show the SDI_APTT, SDI_S, and rSDI for indicators S-1 and S-2 for each sample. The SDI_S and rSDI for indicators S-1 and S-2 were greater than the thresholds set for LA. It was demonstrated that LA samples could be detected based on indicators S-1 and S-2.

[0095] Example 4: Ps(X) was calculated according to Section 4.(d) above, and the indicators S-1 and S-2 were calculated using this. The formulas for calculating S-1 and S-2 are shown in Table 1. Figures 12A-G, like Figures 7A-G, explain Ps(X) for each sample, as well as Fs(X) and indicator S according to equations (2a) and (2b). FVIII was greater than NL and NH at X values ​​of 3 to 83 for S-1 and 3 to 98 for S-2. Figures 12B-A and 12B show the SDI_APTT, SDI_S, and rSDI of indicator S-1 for each sample. SDI_S and rSDI were greater than the set thresholds for FVIII and VW for S-1 and for FVIII and LA for S-2. It was demonstrated that FVIII, VW, and LA samples could be detected based on indicator S-1 or S-2.

[0096] Example 5: Ps(X) was determined according to Section 4.(e) above, and used to calculate the indicators S-1 and S-2. The formulas for calculating S-1 and S-2 are shown in Table 1. Figures 13A-G, like Figures 7A-G, illustrate Ps(X) for each sample, as well as Fs(X) and indicator S according to equations (2a) and (2b). FIX was greater than NL and NH for both S-1 and S-2 at X values ​​between 3 and 98. Figures 14A and 14B show the SDI_APTT, SDI_S, and rSDI of indicators S-1 and S-2 for each sample. S-1 in Figure 14A is based on equation (2a), and S-2 in Figure 14B is based on equation (2b). As shown in Figures 14A and 14B, the SDI_S and rSDI of indicators S-1 and S-2 were greater than the thresholds set for the Abn groups (FVIII, FIX, VW, and LA), demonstrating that all abnormal samples could be detected based on indicators S-1 and S-2.

[0097] Example 6: Ps(X) was calculated according to Section 4.(f) above, and used to calculate the indicators S-1 and S-2. The formulas for calculating S-1 and S-2 are shown in Table 1. Figures 15A-G, like Figures 7A-G, illustrate Ps(X) for each sample, as well as Fs(X) and indicator S according to equations (2a) and (2b). LA was greater than NL and NH for X = 3 to 83 for S-1 and X = 3 to 93 for S-2. Figures 16A and 16B show the SDI_APTT, SDI_S, and rSDI for indicators S-1 and S-2 for each sample. S-1 in Figure 16A is based on equation (2a), and S-2 in Figure 16B is based on equation (2b). The SDI_S and rSDI were greater than the set thresholds for FVIII, VW, and LA for S-1, and for FVIII and LA for S-2, demonstrating that FVIII, VW, and LA samples can be detected based on the indicators S-1 or S-2.

[0098] Example 7: Ps(X) was calculated according to Section 4.(g) above, and the indices S-1 and S-2 were calculated using this. The formulas for calculating S-1 and S-2 are shown in Table 1. Figures 17A-G, like Figures 7A-G, illustrate Ps(X) for each sample, as well as Fs(X) and the indices S according to formulas (2a) and (2b). VW was greater than NL and NH for X = 3 to 98 for S-1 and X = 48 to 98 for S-2. Figures 18A and 18B show the SDI_APTT, SDI_S, and rSDI for the indices S-1 and S-2 for each sample. S-1 in Figure 18A is based on formula (2a), and S-2 in Figure 18B is based on formula (2b). In the Abn group (FVIII, FIX, VW, and LA), the SDI_S and rSDI of S-1 and S-2 were greater than the set thresholds, demonstrating that all abnormal samples can be detected based on the indicators S-1 and S-2.

[0099] Example 8 (8-1) The index S (S-1 and S-2, respectively) of normal samples (NP group; N1 to N12) was calculated, and SDI_S was calculated as follows. The parameters Ps(X), Pm(X), and calculation formula used in the calculation, as well as a, b, and c in the formula, and the number of calculated SDI_S are as shown in Table 2 below. SDI_S = |([index S for each sample in the NP group] - [average value of index S for each sample in the NP group]) / [standard deviation of index S for each sample in the NP group] |

[0100]

[0101] The distribution of maximum SDI_S values ​​within the NP group under each calculation condition is shown in Table 3. While there were samples with an SDI_S greater than 3, there were no indices with an SDI greater than 4. For S-1 in (c), S-2 in (d), S-1 and S-2 in (e), S-2 in (f), and S-1 and S-2 in (g) of Section 4., no samples had an SDI_S greater than 3. Therefore, it was shown that the threshold for these SDI_S values ​​was set at 3, and test samples with an SDI_S greater than the threshold could be selected as samples with a possibility of having a coagulation abnormality. Furthermore, for S-1 and S-2 in (a), S-1 and S-2 in (b), S-2 in (c), S-1 in (d), and S-1 in (f) of Section 4., no samples had an SDI_S greater than 4. Therefore, it was shown that the threshold value of SDI_S was set to 4, and test samples with SDI_S greater than the threshold value could be selected as samples that may have a coagulation abnormality.

[0102]

[0103] (8-2) For the Abn samples (FVIII, FIX, VW, and LA) used in Examples 1 to 7, 66 SDI_S values ​​were calculated based on S-1 values ​​in accordance with Section 4.(a) in Table 2. Figures 19A to 19D show the maximum SDI_S values ​​(white bars) among the samples in the NP group and the SDI_S values ​​(gray bars) for the Abn samples for each SDI_S calculation condition. The horizontal scale in the figure represents a and b in Equation (2a) used to calculate the index S(S-1) as "a:b." The SDI_S values ​​for FVIII exceeded the maximum values ​​for the NP group when a was in the range of 5 to 95 and b was in the range of 25 to 95. The SDI_S values ​​for FIX exceeded the maximum values ​​for the NP group when a was in the range of 5 to 45 and b was in the range of 25 to 75. The SDI_S of VW exceeded the maximum value of the NP group when a was in the range of 5 to 75 and b was in the range of 35 to 85. The SDI_S of LA exceeded the maximum value of the NP group when a was in the range of 5 to 75 and b was in the range of 5 to 95.

[0104] (8-3) S-1 and S-2 were calculated for the NP group (N1-N12) and the Abn group (FVIII, FIX, VW, and LA) under the conditions in Table 2, and their SDI_S and rSDI were determined. Table 4A in Figure 20 shows the average SDI_S values ​​under conditions where rSDI > 1 for each sample. Since the maximum value for the NP group was 3.1, values ​​exceeding 3.1 are indicated in bold and hatched in the table. Table 4B in Figure 20 shows the average SDI_S values ​​under conditions where rSDI > 2 for each sample. Values ​​exceeding 3.1 are indicated in bold and hatched in the table. As shown in Tables 4A and 4B, for all Abn samples, the average SDI_S value when rSDI > 1 was greater than the maximum value for the NP group for at least one of the SDI_S values ​​based on (a) to (g) in Section 4 above. Furthermore, the mean value of SDI_S when rSDI > 2 was higher than when rSDI > 1, indicating that abnormal samples could be detected more accurately by setting rSDI > 2 as an additional threshold. On the other hand, the deviation from the mean of the APTT distribution (SDI_APTT) alone could not distinguish the Abn group from the NP group. It was shown that the Abn group can be distinguished from the NP group by using a new perspective, the deviation from the mean of the index S distribution (SDI_S).

[0105] The results of this example indicated that for indicators S-1 and S-2 according to (a) to (g) of Section 4, the appropriate threshold value for SDI_S for distinguishing between abnormal and normal samples is 3 or greater, or 4 or greater. Furthermore, the results of this example demonstrate that the calculation conditions for indicator S used to detect abnormal samples, such as the calculation procedure for Ps(X) ((a) to (g) of Section 4), the conditions a, b, and c, or the type of indicator S (S-1 based on Formula (2a) or S-2 based on Formula (2b)), can be optimized depending on the type of abnormal sample to be detected, the desired detection accuracy, and the like. Those skilled in the art will understand that the calculation conditions and number of calculations for indicator S can be optimized based on the results of determinations for a large number of normal samples and a large number of abnormal samples with various coagulation abnormality factors.

[0106] In the method of the present invention, one index S is calculated for one test sample under the optimized conditions, and if the SDI_S exceeds a threshold, the test sample can be evaluated as possibly having a coagulation abnormality. Alternatively, in the method of the present invention, two or more indexes S using different calculation conditions can be calculated for one test sample, and if at least one of the SDI_S exceeds a threshold, the test sample can be evaluated as possibly having a coagulation abnormality.

[0107] 19, the pattern of index S (fluctuation of index S due to calculation conditions) may differ depending on the cause of the coagulation abnormality. By creating a database of patterns of index S of abnormal specimens for each cause of coagulation abnormality, it may be possible to detect specimens that may have various causes of coagulation abnormalities based on the database, for example, by using a machine learning model based on the database.

Claims

1. A method for selecting a blood sample that may have a blood coagulation abnormality, comprising: 1) obtaining a parameter Ps(X) based on the coagulation reaction curve Rs(i) or its first derivative curve Vs(i) for a test blood sample, wherein the test blood sample is a blood sample that cannot be determined to have APTT prolongation, i is a measurement point or time, X is a variable, and X>0; 2) obtaining a parameter Pm(X) for a normal blood sample, wherein PM j (X) is the coagulation reaction curve Rm for each sample in the normal blood sample group. j (i) or its first differential curve Vm j (i) is a parameter based on (i), where i and X are as described above, j represents the sample number of each sample in the normal blood sample group and is an integer from 1 to k, and k represents the total number of samples belonging to the normal blood sample group; 3) obtaining an index S for the test blood sample based on the following formula (2), (2)', or (2)": where Fs(X) = Ps(X) - Ps(c), and Fm(X) = Pm(X) - Pm(c), or Fs(X) = Ps(X) / Ps(c), and Fm(X) = Pm(X) / Pm(c), a>0, and a≦b, 0<c≦M, and M is the maximum value of X; 4) Ps(X) and Ps(c) in the above formula (2), (2)' or (2)" are respectively set to Pm j (X) and Pm j (c) replacing the index S with (d) and obtaining an index S for each sample in the normal blood sample group; 5) comparing the index S for the test blood sample with a statistical value of the index S for each sample in the normal sample group.

2. Ps(X) represents the measurement point or time when Rs(i) reaches X% of its coagulation reaction end point, and Pm j (X) is Rm j The method according to claim 1, wherein (i) represents the measurement point or time at which the coagulation reaction reaches X% of the end point, and a=3 to 97, b=3 to 97, c=3 to 97, and 0<X≦100.

3. Ps(X) represents the measurement point or time when Vs(i) reaches X% of its maximum value. However, if Ps(X) is greater than Ps(100), Ps(X) is redefined as Ps(200-X), and Pm j (X) is Vm j (i) represents the measurement point or time at which the maximum value is reached by X%, where Pm j (X) is Pm j If it is greater than (100), Pm j (X) is Pm j 2. The method of claim 1, wherein a is redefined as (200-X), a=3 to 98, b=103 to 198, and c=3 to 198.

4. Ps(X) represents the minimum value of the measurement point or time at which Vs(i) reaches X% of the maximum value, and Pm j (X) is Vm j The method according to claim 1, wherein (i) represents the minimum value of the measurement point or time at which X% of the maximum value is reached, a=3 to 98, b=3 to 98, c=3 to 197, and 0<X≦100.

5. Ps(X) represents the maximum value of the measurement point or time when Vs(i) reaches X% of the maximum value, and Pm j (X) is Vm j The method according to claim 1, wherein (i) represents the maximum value of the measurement point or time at which X% of the maximum value is reached, a = 3 to 98, b = 3 to 98, c = 3 to 197, and 0 < X ​​≦ 100.

6. Ps(X) represents the midpoint between the minimum and maximum values ​​of the measurement point or time when Vs(i) reaches X% of the maximum value, and Pm j (X) is Vm j The method according to claim 1, wherein (i) represents the midpoint between the minimum and maximum values ​​of the measurement point or time at which X% of the maximum value is reached, and a = 3 to 98, b = 3 to 98, c = 3 to 197, and 0 < X ​​≦ 100.

7. Ps(X) represents the length between the minimum and maximum values ​​of the measurement point or time when Vs(i) reaches X% of the maximum value, and Pm j (X) is Vm j The method according to claim 1, wherein (i) represents the length between the minimum and maximum values ​​of the measurement points or times at which X% of the maximum value is reached, and a = 3 to 98, b = 3 to 98, c = 3 to 197, and 0 < X ​​< 100.

8. Ps(X) represents the weighted average time of Vs(i), and Pm j (X) is Vm j (i) represents a weighted average time, which is calculated according to the following formula (3): In the formula, V(i) is Vs(i) or Vm j (i), t1 and t2 respectively represent the minimum and maximum values ​​of the measurement points or times at which V(i) reaches X% of the maximum value, provided that when V(i) is less than X% of the maximum value, V(i) is considered to be 0, a = 3 to 98, b = 3 to 98, c = 3 to 197, and 0 < X ​​≦ 100.

9. Ps(c) represents the measurement point or time at which Vs(i) reaches c% of its maximum value; PM j (c) is Vm j The method of claim 1 , wherein (i) represents the measurement point or time at which c % of the maximum value is reached.

10. The method of claim 1, wherein step 5) includes calculating SDI_S, which represents the standard deviation index of the index S for the test blood sample, according to the following formula: SDI_S = |([index S for the test blood sample] - [average value of index S for each sample in the normal blood sample group]) / [standard deviation of index S for each sample in the normal blood sample group]|.

11. The method of claim 10, further comprising selecting the test blood sample as a blood sample likely to have a coagulation disorder if SDI_S is at or above a predetermined threshold.

12. The method of claim 10, wherein step 5) further comprises: obtaining APTTs for the test blood sample and each sample in the normal blood sample group; calculating SDI_APTT, which represents a standard deviation index of APTTs for the test blood samples, according to the following formula: SDI_APTT = | ([APTT for the test blood sample] - [mean APTT for each sample in the normal blood sample group]) / [standard deviation of APTT for each sample in the normal blood sample group] |; and calculating rSDI, which represents a ratio of SDI_S to SDI_APTT, according to the following formula: rSDI = SDI_S / SDI_APTT.

13. The method of claim 12, further comprising selecting the test blood sample as a blood sample likely to have a coagulation disorder if SDI_S and rSDI are at or above a predetermined threshold.

14. The method according to claim 12, wherein the standard deviation of APTT for each sample in said normal blood sample group is 2 seconds or more.

15. The method according to claim 11 or 13, further comprising outputting information indicating the results of said selection for said test blood specimen.

16. The method according to claim 1, wherein the blood sample in which it cannot be determined that the blood clotting time is prolonged is a sample in which the APTT is within +5 seconds of a predetermined upper limit of the normal range.

17. The method of claim 1, wherein the blood sample is plasma.

18. The method of claim 1, wherein the coagulation abnormality is a coagulation factor deficiency or lupus anticoagulant positivity.

19. The method of claim 18, wherein the coagulation factor is factor VIII, factor IX, or von Willebrand factor.

20. Fs(X) = Ps(X) / Ps(c), and 2. The method of claim 1, wherein

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