Data processing method, analysis system, and automated analyzing device
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2025-09-01
- Publication Date
- 2026-08-13
Smart Images
Figure JP2025030686_13082026_PF_FP_ABST
Abstract
Description
Data processing method, analysis system, and automatic analysis device
[0001] The present invention relates to a data processing method, an analysis system, and an automatic analysis device.
[0002] One of the tests that can be analyzed by an automatic analysis device is a blood coagulation test for examining a patient's blood coagulation ability. In a blood coagulation test, coagulation waveform data indicating changes in the amount of light over time due to a coagulation reaction started by mixing a patient sample and a reagent is acquired, and the coagulation ability is determined based on feature amounts obtained from a waveform obtained by first-differentiating the coagulation waveform and a waveform obtained by second-differentiating the coagulation waveform. For example, Patent Document 1 discloses an automatic analysis device that executes determination of at least one of a disease and a test to be performed based on measurement data and patient information corresponding to the measurement data, and outputs a determination result.
[0003] Japanese Unexamined Patent Application Publication No. 2022-55064
[0004] In Patent Document 1, the blood coagulation time is cited as the measurement data used for determination. Blood coagulation time measurement measures the time until a fibrin clot is formed by mixing a sample and a reagent. When an extension or shortening is observed in the blood coagulation time, an abnormality in the coagulation ability is suspected. However, for example, in mild hemophilia, it is known that the blood coagulation time may fall within the normal range. Thus, there is also a possibility of overlooking a sample with an abnormality in the coagulation ability by simply analyzing only the coagulation waveform and its differential waveforms.
[0005] An object of the present invention is to provide a data processing method, an analysis system, and an automatic analysis system that can estimate the coagulation ability with high accuracy.
[0006] To achieve the above object, a data processing method according to the present invention includes an analysis value acquisition step of acquiring an analysis value related to a coagulation ability based on measurement data that changes over time along with a coagulation reaction of a patient's blood sample, and an analysis value correction step of correcting the analysis value using the characteristic information of the patient.
[0007] Furthermore, in order to achieve the aforementioned objectives, the analysis system according to the present invention comprises an automatic analyzer and a data processing device, wherein the data processing device includes an analysis value acquisition unit that acquires analysis values related to coagulation ability based on measurement data received from the automatic analyzer, and an analysis value correction unit that corrects the analysis values using patient characteristic information.
[0008] Furthermore, in order to achieve the aforementioned objectives, the automated analyzer according to the present invention comprises an analysis unit, an analysis value acquisition unit that acquires analysis values related to coagulation ability based on measurement data from the analysis unit, and an analysis value correction unit that corrects the analysis values using patient characteristic information.
[0009] According to the present invention, it is possible to provide a data processing method, an analysis system, and an automated analysis system that can estimate coagulation ability with high accuracy.
[0010] A diagram showing an example of the overall configuration of the analysis system. A diagram showing an example of the overall configuration of the automated analyzer. A diagram showing an example of the configuration of the photometric port. A flowchart showing the overall flow of processing performed by the control computer. A flowchart showing the details of the inspection item determination in step S404 of Figure 4. A flowchart showing the details of the deviation determination in step S405 of Figure 4. A flowchart showing the details of the analysis value correction in step S406 of Figure 4. An example of a screen displaying the coagulation waveform analysis results and recommended inspection items. An example of a screen notifying the deviation determination results. Another example of a screen notifying the deviation determination results.
[0011] Embodiments of the present invention will be described with reference to the drawings.
[0012] <Analysis System> Figure 1 shows an example of the overall configuration of the analysis system 100. The analysis system 100 includes an automatic analyzer 101, a network 102, a control computer 103 (data processing device), an operation computer 104, and a monitor 105. In the analysis system 100, there may be multiple automatic analyzers connected to the control computer 103, etc. The following describes each part.
[0013] <Configuration of the Automatic Analytical Device> The automatic analytical device 101 will now be described. Figure 2 is a diagram showing an example of the overall configuration of the automatic analytical device 101. As shown in Figure 2, the automatic analytical device 101 comprises an analysis unit 201, an operation unit 202, and a control unit 203.
[0014] (Analysis Unit) The analysis unit 201 has the function of measuring the physical properties of the reaction solution obtained by mixing a sample and a reagent, such as the amount of light emitted, the amount of scattered light, the amount of transmitted light, the current value, and the voltage value. The analysis unit 201 comprises a reaction disk 204, a sample dispensing mechanism 205, a sample disk 206, a reader 206a, a reagent disk 208, a reagent dispensing mechanism 209, and a blood coagulation time measurement unit 210. The analysis unit 201 may also be equipped with measurement units for biochemical items and immunological items. Each part will be described below.
[0015] The reaction disk 204 is a disk-shaped unit that can rotate around a vertical axis and holds a number of reaction cells 211 made of a translucent material. The reaction cells 211 are containers for mixing and reacting the sample and reagents, and a number of them are installed in a ring shape on the reaction disk 204. When the automated analyzer 101 is in operation, the reaction cells 211 are kept at a predetermined temperature (for example, about 37°C) in the constant temperature bath 212 of the reaction disk 204.
[0016] The sample dispensing mechanism 205 has a pipette nozzle and uses the pipette nozzle to aspirate and dispense the sample. The sample dispensing mechanism 205 is located between the sample disk 206 and the reaction disk 204. This sample dispensing mechanism 205 aspirates a predetermined amount of sample from the sample container 213 placed on the sample disk 206 and dispenses it into the reaction cell 211.
[0017] The sample disk 206 is a disk-shaped unit that can rotate around a vertical axis and holds a number of sample containers 213 containing samples. The figure illustrates a configuration in which the sample containers 115 can be arranged in two concentric rows on the sample disk 206.
[0018] The reader 206a is a device that reads the identification data attached to the sample container 213 when the sample is registered. While barcodes and RFID can be used as identification data, in this embodiment, barcodes are used. In other words, the reader 206a is a barcode reader. The barcode contains data such as sample ID, patient ID, and sample type. The identification data read by the reader 206a is transmitted to the control unit 203 along with the position information on the sample disk 206 of the sample container 213 to which the identification data is attached, and is stored in the storage device 216.
[0019] The reagent dispensing mechanism 209 has a pipette nozzle and uses the pipette nozzle to aspirate and dispense reagents. The reagent dispensing mechanism 109 is located between the reagent disk 208 and the reaction disk 204. The reagent dispensing mechanism 209 draws a predetermined amount of reagent from inside the reagent bottle 214, which corresponds to the test item, placed on the reagent disk 208, and dispenses it into the reaction cell 211.
[0020] The reagent disk 208 is a disk-shaped unit that can rotate around a vertical axis and holds a number of reagent bottles 214. Multiple reagent bottles 214 are arranged in a ring shape on the reagent disk 208. The reagents are kept cool on the reagent disk 208, and the reagent dispensing mechanism 209 draws reagents from the reagent bottles 214 according to the measurement item and discharges them into a predetermined empty reaction cell 211 installed on the reaction disk 204, where they are heated to approximately 37°C.
[0021] The blood coagulation time measurement unit 210 has the function of measuring the change in light intensity over time due to the coagulation reaction of a reaction solution produced by mixing a sample consisting of plasma obtained by separating blood acquired from a patient with a reagent. The blood coagulation time measurement unit 210 comprises a reaction vessel housing section 221, a reaction vessel transfer mechanism 222, a sample dispensing station 223, a coagulation reagent probe 224, and a detection unit 225.
[0022] The reaction vessel housing section 221 houses multiple disposable reaction vessels 221a. The reaction vessel transfer mechanism 222 transfers the reaction vessels 221a from the reaction vessel housing section 221 to the sample dispensing station 223. The coagulation reagent probe 224 has a built-in reagent heating function, and the reagent aspirated by the coagulation reagent probe 224 is heated to approximately 40°C. The detection unit 225 is equipped with multiple photometric ports 225a, each having a light source and a photometer.
[0023] (Operation Unit) The operation unit 202 is a device operated by the operator when inputting measurement request data (described later) into the control unit 203 or when displaying various data on the display unit 218. The operation unit 202 may be, for example, a keyboard or mouse, but it may be any other device. In addition, the operation unit 202 and the display unit 218 may be an integrated device such as a touch panel.
[0024] (Control Unit) The control unit 203 includes an analysis control computer 215, a storage device 216, and an interface 217.
[0025] The analysis control computer 215 not only controls the operation of the automatic analyzer 101, but also has the function of calculating measurement data such as coagulation reaction process data based on the light intensity values measured by the analysis unit 201. The calculated measurement data is output to the display unit 218 via the interface 217 and stored in the storage device 216. The measurement data may also be retrieved from the display unit 218 by operation on the operation unit 202.
[0026] The storage device 216 is an HDD or SSD, and although Figure 2 illustrates an external device connected to the analysis control computer 215 via the interface 217, it may also be a device built into the analysis control computer 215. The storage device 216 stores data such as reagent identification data, sample identification data, analysis parameters, measurement request data, calibration results, and measurement data. The measurement request data includes at least the sample ID and measurement items, and other information such as the patient ID may be included as needed.
[0027] Interface 217 is the data input / output unit for the analysis control computer 215 to the analysis unit 201. In Figure 2, the analysis control computer 215 and interface 217 are shown separately, but interface 217 may also be configured as an integrated unit with the analysis control computer 215. Measurement request data from the operation unit 202 to the analysis unit 201 is input to the analysis control computer 215 via interface 217. Measurement data output from the analysis unit 201 via the A / D converter 303 (Figure 3) is also input to the analysis control computer 215 and the storage device 216 via interface 217. Identification data read by the reader 206a is also input to the analysis control computer 215 and the storage device 216 via interface 217.
[0028] <Analysis Operation of the Automated Analyzer> The analysis operation of the blood coagulation time item using the automated analyzer 101 will be described. In this embodiment, a sample consisting of plasma obtained by separating blood acquired from a patient is used. The operation parameters for the measurement items that can be requested to be measured by the automated analyzer 101 are pre-inputted into the operation unit 202 by the operator and stored in the storage device 216. When the operator inputs the measurement request data for each sample, the analysis starts. When it is time for the measurement of a sample ID for which measurement request data has been input, the operation parameters corresponding to the measurement item of the corresponding measurement request data are read from the storage device 216 and input into the analysis control computer 215. The analysis control computer 215 then controls the analysis unit 201 according to the operation parameters.
[0029] In the blood coagulation time measurement unit 210, the reaction vessel 221a is transferred to the sample dispensing station 223 by the reaction vessel transfer mechanism 222. The sample dispensing mechanism 205, positioned between the sample dispensing station 223 and the sample disk, aspirates the sample from the sample container 213 and dispenses it into the reaction vessel 221a at the sample dispensing station 223.
[0030] Furthermore, the reagent dispensing mechanism 209 draws reagents according to the test item from the reagent bottle 214, which is kept cool on the reagent disk 208, and dispenses them into a predetermined empty reaction cell 211 installed on the reaction disk 204.
[0031] Subsequently, the reagent, which has been kept warm at approximately 37°C inside the reaction cell 211, is aspirated by the coagulation reagent probe 224 with a reagent heating function after a certain period of time, and is further heated to approximately 40°C by the coagulation reagent probe 224. During this time, the reaction vessel 221a, in which the sample has been dispensed, is transferred to an arbitrary photometric port 225a of the detection unit 225 by the reaction vessel transfer mechanism 222. Then, the warmed reagent is discharged (dispensed) into the reaction vessel 221a at the photometric port 225a by the coagulation reagent probe 224, and the blood coagulation reaction between the sample and the reagent begins inside the reaction vessel 221a.
[0032] At the photometric port 225a, measurement data is output from the photometer 302 (Figure 3) at predetermined time intervals (for example, a 0.1-second cycle) after the reagent is dispensed into the reaction vessel 221a.
[0033] <Method for acquiring coagulation reaction process data> The method for acquiring coagulation reaction process data using the automatic analyzer 101 will be explained. Figure 3 shows an example of the configuration of the photometric port 225a. Light irradiated from the light source 301 is scattered by the reaction liquid in the reaction vessel 221a. The photometer 302 (light sensor) receives the scattered light scattered by the reaction liquid in the reaction vessel 221a. For example, a halogen lamp or LED can be used as the light source 301. The photometer 302 (light sensor) is composed of a photodiode or the like. The signal received by the photometer 302 (light sensor) is converted into a light intensity value as a digital signal by the A / D converter 303, and is input to the analysis control computer 215 as coagulation reaction process data (coagulation waveform data representing the time change of light intensity) and stored in the storage device 216. The operation of the photometric port 225a is controlled by the analysis control computer 215. Here, light scattering is used, but transmitted light or the like may also be used.
[0034] <Network> The network 102 shown in Figure 1 is a LAN or similar network connecting the automated analyzer 101, the control computer 103, and the operation computer 104. Information used by the analysis system 100 and measurement request data from the operation computer 104 are exchanged via the network 102. The network 102 is connected to, for example, a hospital network, HIS (Hospital Information System) or LIS (Laboratory Information System). The network 102 may be wireless or wired. Within the range of the network 102, the automated analyzer 101, the control computer 103, and the operation computer 104 can be installed in any location, and the analysis system 100 can be operated even if each installation location is far apart.
[0035] <Operating Computer> The operating computer 104 shown in Figure 1 is a device operated by the operator when inputting measurement request data and other information into the control computer 103, or when displaying various data on the monitor 105. Input to the operating computer 104 may be done by touching the monitor 105, or by using a keyboard, mouse, or other means. The operating computer 104 and the monitor 105 may also be integrated into one unit.
[0036] <Control Computer> The control computer 103 shown in Figure 1 includes a processor 110, a memory 120, and a storage 130. In this embodiment, the control computer 103 includes the memory 120 and storage 130, but the memory 120 and storage 130 may be provided by the operation computer 104. The control computer 103 also has an interface 106 that inputs and outputs data transmitted from the automatic analyzer 101 via the network 102 and data transmitted from the operation computer 104 to the memory 120 and storage 130. The interface 106 receives, for example, measurement data (coagulation reaction process data) that changes over time in accordance with the coagulation reaction of a patient's blood sample from the automatic analyzer 101. In Figure 1, an example is shown in which the control computer 103 and the interface 106 are configured as a single unit, but they may be separate.
[0037] The storage device 130 includes a patient information database 131 and a test item determination table 132. The patient information database 131 stores, for each patient, characteristic information including past measurement data from the automated analyzer 101 connected to the control computer 103, medical history, medication history, and at least one of family history. The patient's characteristic information may also include whether or not the patient is elderly, whether or not they have a tendency towards thrombosis, etc. The test item determination table 132 stores tables (for example, Tables 1-3 described later) that are referenced when determining test items.
[0038] In Figure 1, the functions conceptually performed by the processor 110 are shown as a coagulation waveform analysis unit 121, an analysis value correction unit 122, a deviation determination unit 123, and an inspection item determination unit 124. The programs for realizing these functions are stored in the memory 120. The programs may be read according to requests entered into the operating computer 104, or they may be read when coagulation reaction process data is input from the automatic analyzer 101 via the network 102. The programs may be provided pre-installed in ROM or the like, or they may be provided or distributed as files in an installable or executable format recorded on a computer-readable recording medium. Furthermore, the programs may be stored on other computers connected to the network 102 and provided or distributed by allowing downloads via the network.
[0039] The coagulation waveform analysis unit 121 (analysis value acquisition unit) estimates the coagulation ability of a patient sample based on features extracted from the first derivative waveform and second derivative waveform of the coagulation reaction process data. Specifically, first, the coagulation waveform analysis unit 121 acquires normalized waveforms by normalizing the light intensity axis and time axis of the coagulation reaction process data, its first derivative waveform, and its second derivative waveform, and extracts features from each normalized waveform. Next, the coagulation waveform analysis unit 121 estimates the cause of the prolonged blood coagulation time using a neural network based on the extracted features and features extracted from a group of samples for which the cause of prolonged blood coagulation time is known. In this specification, the estimation results by the coagulation waveform analysis unit 121, including each disease state that is a candidate for coagulation ability and the probability of belonging to each disease state (belonging probability), are referred to as "analysis values." However, sometimes only the names of disease states for which the belonging probability is 50% or higher are referred to as "analysis values." Examples of pathological conditions include "hemophilia A," "lupus anticoagulant (LA) positive," and "coagulation factor inhibitor positive."
[0040] The analysis value correction unit 122 acquires the characteristic information of the patient sample corresponding to the identification data read by the reading device 206a from the patient information database 131, and corrects the analysis value using the acquired characteristic information. Since the characteristic information of each patient stored in the patient information database 131 is updated reflecting the results of actual definitive diagnoses, measurement data of the automatic analyzer, etc., the reliability of the analysis value correction improves as the amount of its accumulation increases. The analysis value corrected by the analysis value correction unit 122 is notified to the screen of the monitor 105 via the operation computer 104 (see FIG. 8).
[0041] The deviation determination unit 123 compares the characteristic information used for correcting the past analysis values of the patient with the current characteristic information of the patient, and determines whether there is a deviation. Also, the deviation determination unit 123 compares the past measurement data of the patient with the current measurement data of the patient, and determines whether there is a deviation. The determination result by the deviation determination unit 123 is notified to the screen of the monitor 105 via the operation computer 104 (see FIGS. 9 and 10).
[0042] The test item determination unit 124 determines the next recommended test item based on either one or both of the corrected analysis value and the characteristic information. The determination result by the test item determination unit 124 is notified to the screen of the monitor 105 via the operation computer 104 (see FIG. 8).
[0043] <Specific Example of Data Processing> FIG. 4 is a flowchart showing the overall flow of the process executed by the control computer 103. Here, as an example, a process of estimating the coagulation ability, that is, the prolongation factor when the blood coagulation time is prolonged will be described.
[0044] The process by the control computer 103 starts when the identification data of the patient sample and the coagulation reaction process data output from the automatic analyzer 101 are input to the control computer 103 (step S401).
[0045] Then, the coagulation waveform analysis unit 121 acquires an analysis value related to the coagulation ability based on the coagulation reaction process data, and stores the analysis value in the patient information database 131 (step S402).
[0046] Next, the analysis value correction unit 122 searches the patient information database 131 to determine whether there is characteristic information of the patient sample corresponding to the identification data (step S403).
[0047] Here, in step S403, if the characteristic information of the patient sample does not exist in the patient information database 131, no correction of the analysis value is performed, and the test item determination unit 124 determines the recommended test items based on the uncorrected analysis value (step S404). Details of the determination of the test items will be described later with reference to FIG. 5.
[0048] On the other hand, in step S403, if the characteristic information of the patient sample exists in the patient information database 131, the deviation determination unit 123 determines whether there is a deviation between the coagulation reaction process data and the characteristic information for the patient sample (step S405). Details of the determination of the deviation will be described later with reference to FIG. 6.
[0049] Here, in step S405, if it is determined that there is a deviation, the analysis value correction unit 122 corrects the analysis value using the characteristic information of the patient sample (step S406). Details of the correction of the analysis value will be described later with reference to FIG. 7.
[0050] The analysis value correction unit 122 outputs the condition as an analysis value and stores it in the patient information database 131 if, after correcting the analysis value, there is a condition whose probability of belonging is 50% or more. The threshold for the probability of belonging to be output or stored as an analysis value is not limited to 50% and can be arbitrarily determined. Subsequently, in step S404, the test item determination unit 124 determines the recommended test item based on the analysis value. In the example in Figure 4, first, the analysis value correction unit 122 determines whether the probability of belonging to hemophilia A is 50% or more (step S407), and if it is 50% or more, it outputs hemophilia A as an analysis value. In step S407, if the probability of belonging to hemophilia A is less than 50%, the analysis value correction unit 122 determines whether the probability of belonging to coagulation factor inhibitor is 50% or more (step S408), and if it is 50% or more, it outputs coagulation factor inhibitor as an analysis value. In step S408, if the probability of belonging to a coagulation factor inhibitor is less than 50%, the analysis value correction unit 122 determines whether the probability of belonging to LA positivity is 50% or higher (step S409). If it is 50% or higher, it outputs LA positivity as the analysis value. In step S409, if the probability of belonging to LA positivity is less than 50%, the analysis value correction unit 122 outputs Unknown because there is no disease state with a 50% or higher probability of belonging. If Unknown is output, in step S404, the test item determination unit 124 determines the recommended test item based only on the characteristic information of the patient sample. In the example in Figure 4, the determination is made in the order of hemophilia A, coagulation factor inhibitor, and LA positivity, but other orders are acceptable, and the determination of other disease states may also be included.
[0051] (Determination of inspection items) Figure 5 is a flowchart showing the details of the determination of inspection items in step S404 of Figure 4.
[0052] First, before determining the test items, the analysis value correction unit 122 searches the patient information database 131 to see if there is characteristic information of the patient sample corresponding to the identification data (step S403).
[0053] In step S403, if there is no characteristic information, the test item determination unit 124 determines whether the analysis value acquired by the coagulation waveform analysis unit 121 and stored in the patient information database 131 is unknown (step S501).
[0054] If the result in step S501 is "Unknown", the test item determination unit 124 outputs "Cross Mixing Test" as the recommended test item (step S502).
[0055] On the other hand, if it is determined in step S501 that the result is not "Unknown", the test item determination unit 124 refers to the following (Table 1) stored in the test item determination table 132 and determines the recommended test item based on the analysis value obtained by the coagulation waveform analysis unit 121 (step S503). For example, if the analysis value is hemophilia A, "measurement of intrinsic coagulation factor activity" is output as the recommended test item.
[0056]
[0057] Next, in step S403, if characteristic information is available, the test item determination unit 124 determines whether the analysis value, corrected by the analysis value correction unit 122 and stored in the patient information database 131, is unknown (step S504). Note that in the flowchart of Figure 4, if there is no characteristic information for the patient sample, a discrepancy is determined in step S405. However, in the flowchart of Figure 5, we assume that there is no discrepancy and explain the process as performed in steps S406-S410 in Figure 4.
[0058] In step S504, if it is determined to be "Unknown," the test item determination unit 124 determines the recommended test item based on the characteristic information of the patient sample, while referring to the following (Table 2) stored in the test item determination table 132 (step S505). For example, if the characteristic information is abnormal AST / ALT values and decreased platelet count, "abdominal ultrasound examination" is output as the recommended test item.
[0059]
[0060] On the other hand, if it is determined in step S504 that the result is not unknown, the test item determination unit 124 determines the recommended test item based on the corrected analysis value and the patient sample characteristics information, while referring to the following (Table 3) stored in the test item determination table 132 (step S506). For example, if the corrected analysis value is hemophilia A and the patient information is PT prolongation, "Differential diagnosis of DIC" is output as the recommended test item.
[0061]
[0062] (Determination of deviation) Figure 6 is a flowchart showing the details of the deviation determination in step S405 of Figure 4.
[0063] First, the deviation determination unit 123 reads characteristic information and measurement data of the patient sample corresponding to the identification data from the patient information database 131 (step S601). The characteristic information read includes not only the current (current) characteristic information of the patient sample, but also the characteristic information used to correct the past (previous) analysis values of the patient sample. The measurement data read includes not only the current measurement data of the patient sample, but also the previous measurement data of the patient sample.
[0064] Next, the discrepancy determination unit 123 compares the characteristic information of the current and previous patient samples to determine whether or not there is a discrepancy in the characteristic information (step S602).
[0065] If it is determined in step S602 that there is no discrepancy in the characteristic information, the process proceeds to step S406 in Figure 4, which is called the analysis value correction.
[0066] On the other hand, if it is determined in step S602 that there is a discrepancy in characteristic information, the discrepancy determination unit 123 determines whether or not there is a discrepancy in the measurement data by comparing the current and previous measurement data of the patient sample (step S603).
[0067] In step S603, if it is determined that there is no discrepancy in the measurement data, the discrepancy determination unit 123 adds the details of the discrepancy in the characteristic information to the patient information database 131 (step S604), and terminates the discrepancy determination process.
[0068] In step S603, if it is determined that there is a discrepancy in the measurement data, the discrepancy determination unit 123 refers to the patient information database 131 and determines whether or not there is a new medication that was not taken last time (step S605).
[0069] In step S605, if it is determined that there are no new medications being taken, the discrepancy determination unit 123 adds the discrepancy between the characteristic information and the measurement data to the patient information database 131 and outputs a notification prompting the patient to remeasure after checking the status of the measuring device (step S606), and terminates the discrepancy determination process. An example of the screen displayed on the monitor 105 at this time is shown in Figure 9, which will be described later. If the patient's current measurement data shows a large discrepancy compared to the previous measurement, even though there are no new medications being taken, it is possible that there is a malfunction in the measuring device.
[0070] On the other hand, if it is determined in step S605 that new medication has been taken, the discrepancy determination unit 123 adds the discrepancy between the characteristic information and the measurement data to the patient information database 131 and outputs a notification prompting remeasurement after discontinuing medication (step S607), and terminates the discrepancy determination process. An example of the screen displayed on the monitor 105 at this time is shown in Figure 10, which will be described later. This is because medication may be influencing the discrepancy in the measurement data.
[0071] In step S605 of Figure 6, the presence or absence of new medication is determined, but it is not limited to medication; changes in other characteristic information, such as changes in medical history (e.g., the addition of a condition that has been definitively diagnosed since the last measurement), may also be determined. Furthermore, even if the same medication was taken both times, if the amount taken this time has increased by a certain amount compared to the previous time, it may be considered that new medication has been taken.
[0072] (Correction of Analytical Values) Figure 7 is a flowchart detailing the correction of analytical values in step S406 of Figure 4. The method of correcting analytical values described below is merely one example, and other methods (for example, a method of normalizing and correcting the results of each sample) may also be used to correct analytical values.
[0073] First, the analysis value correction unit 122 extracts the analysis values obtained by the coagulation waveform analysis unit 121 and the current characteristic information from the patient information database 131 for the patient sample corresponding to the identification data (step S701). At this time, the analysis values read out are as follows (Table 4): the probability of belonging to the disease state "hemophilia A" is 10%, the probability of belonging to the disease state "LA positive" is 60%, and the probability of belonging to the disease state "coagulation factor inhibitor positive" is 30%.
[0074]
[0075] Next, the analysis value correction unit 122 extracts other patients from the patient information database 131 who have a common pathological condition as an analysis value with the pathological condition included in the extracted analysis value (step S702). Specifically, other patients who have a certain or higher probability of belonging to any of the following conditions are extracted: hemophilia A, LA positive, or coagulation factor inhibitor positive.
[0076] Next, the analysis value correction unit 122 calculates the number of other patients extracted in step S702 that have characteristic information in common with the characteristic information of the patient corresponding to the identification data (step S703). For example, if "elderly" is included as characteristic information of the patient corresponding to the identification data, the number of patients who have the characteristic information of "elderly" and have an analysis value of "hemophilia A", the number of patients who have the characteristic information of "elderly" and have an analysis value of "LA positive", and the number of patients who have the characteristic information of "elderly" and have an analysis value of "coagulation factor inhibitor positive" are calculated, respectively.
[0077] Furthermore, the analysis value correction unit 122 calculates the prevalence rate based on the number of patients calculated in step S703 and the number of patients who have actually received a confirmed diagnosis (step S704). For example, if there are 100 patients who have the identification information "elderly" and an analysis value of "LA positive," and of those, 50 patients have received a confirmed diagnosis of "LA positive," the prevalence rate will be 50%. The prevalence rates for each disease state for each characteristic information calculated through the above steps are stored in the patient information database 131 linked to the identification data in the format shown below (Table 5).
[0078]
[0079] Next, the analysis value correction unit 122 calculates a weighted average for each analysis value (pathological condition) (step S705). If there are 1 to n types of patient characteristic information corresponding to the identification data, the weighted average is calculated by the following (Equation 1).
[0080]
[0081] Since the prevalence of each disease can vary significantly depending on the characteristic information, it is effective to weight the prevalence of each characteristic information as a weight. Based on the data in (Table 5) and (Equation 1), the weighted average values for each disease are 49.8 for hemophilia A, 87.4 for LA-positive, and 210.5 for coagulation factor inhibitor-positive. The calculated weighted average values are stored in the patient information database 131, linked to the identification data.
[0082] Subsequently, the analysis value correction unit 122 converts the weighted average value for each analysis value (pathological condition) into a ratio value (step S706). In the example above, the ratio value is converted to hemophilia A:LA positive:coagulation factor inhibitor positive = 14:25:61. The converted ratio value is stored in the patient information database 131, linked to the identification data.
[0083] Finally, the analysis value correction unit 122 calculates the ratio value converted in step S706 and the average value of the belonging probability included in the analysis value acquired by the coagulation waveform analysis unit 121 using the following formula (Equation 2) (step S707).
[0084]
[0085] In the example above, the average values for each analysis value (pathology) are calculated as follows: hemophilia A at 12.0%, LA-positive at 42.5%, and coagulation factor inhibitor-positive at 45.5%. These average values are stored in the patient information database 131 as corrected analysis values, linked to the identification data. However, since there are no pathologies with a membership probability of 50% or higher, the corrected analysis values are "Unknown".
[0086] <Specific Examples of Screen Display> The screens shown in Figures 8-10 below are all output from the operating computer 104 to the monitor 105 in response to the operator's actions.
[0087] Figure 8 shows an example of a screen displaying coagulation waveform analysis results and recommended test items. The screen in Figure 8 is output when the operator selects (clicks) the tab 801 labeled "Analysis Results" on a predetermined screen displayed on the monitor 105. The screen in Figure 8 consists of an analysis value area 802 that displays the final adopted analysis values, a belonging probability area 803 that displays the belonging probability for each disease state, a patient ID area 804 that displays information necessary for patient identification, a test item area 805 that displays recommended test items for the patient sample, and a comment area 806 that displays comments.
[0088] At the top of the affiliation probability area 803, there is a display switching button 803a for selecting whether to highlight the analysis results before or after correction. When the display switching button 803a is operated (clicked), the analysis results to be highlighted can be switched. Figure 8 shows an example where the corrected analysis results are highlighted. Analysis results that are not highlighted are shown with a dashed line around the graph representing the affiliation probability.
[0089] In the inspection item area 805, the recommended inspection item name 805a, the checkbox 805b, and the measurement request button 805c are displayed. The checkbox 805b is displayed before the recommended inspection item name 805a, and you can select (click) whether or not to check each recommended inspection item. The measurement request button 805c can send the information of the recommended inspection item name 805a that is checked by the checkbox 805b as measurement request data to the automatic analyzer 101 connected to the control computer 103 via the interface 106.
[0090] The comment area 806 allows the operator to enter any comment. Comments may be entered by touching the monitor 105 connected to the operating computer 104, or by using a keyboard, mouse, or other means.
[0091] Figure 9 shows an example of a screen that notifies the results of a deviation judgment. The screen in Figure 9 is displayed when the operator selects (clicks) the tab 901 labeled "Deviation Notification" on a predetermined screen displayed on the monitor 105. The screen in Figure 9 consists of a data area 902 that displays the deviated measurement data, a patient ID area 903 that displays information necessary for patient identification, a recommended work area 904 that displays the next recommended work according to the deviation judgment result, and a comment area 905 that displays comments.
[0092] The data area 902 displays the date 902a, sample ID 902b, measurement item 902c, measurement data 902d, unit 902e, and deviation range 902f. The date 902a is the date on which the PT etc. was measured, and the sample ID 902b is the ID of the sample on which the PT etc. was measured. The measurement data 902d is the measurement result for each item of the PT etc., and the unit 902e is the unit of the measurement data. The deviation range 902f is a value that represents the degree of deviation from the previous measurement data of the same sample ID.
[0093] The comment area 905 allows the operator to enter any comment. Comments may be entered by touching the monitor 105 connected to the operating computer 104, or by using a keyboard, mouse, or other means.
[0094] In the example shown in Figure 9, the message "Please check the device status. If there is no problem with the device, please remeasure." is displayed in the recommended work area 904. This corresponds to the notification in step S606 of Figure 6, because if the patient's current measurement data differs significantly from the previous measurement, even though the patient has not taken any medication, there is a possibility that there is a malfunction in the measuring device. Such notifications can help prevent misdiagnosis due to abnormal measurement data.
[0095] Figure 10 shows another example of a screen that notifies the deviation judgment result. The screen in Figure 10 is composed of the same areas as in Figure 9.
[0096] In the example shown in Figure 10, the message "If necessary, discontinue medication and remeasure" is displayed in the recommended work area 904. This corresponds to the notification in step S607 of Figure 6, because medication may be influencing the discrepancy in the measurement data. Such notifications can help prevent misdiagnosis due to the effects of medication.
[0097] <Effects of this Embodiment> Because blood coagulation function is governed by a complex mechanism, seemingly unrelated patient characteristics may be involved in coagulation ability, and temporary abnormalities may occur due to the effects of medication or malnutrition. Furthermore, collecting necessary information from a vast amount of data, such as past measurement data, medical history, and family history, for diagnosis is a burdensome task for busy healthcare professionals. However, in this embodiment, coagulation ability is determined not only by the analytical values obtained through coagulation waveform analysis, but also by taking into account the patient's characteristics and information from other patients. In other words, in this embodiment, coagulation ability is determined using values corrected from the analytical values, so coagulation abnormalities that would have been overlooked by simply using analytical values can be extracted, and necessary tests for a definitive diagnosis can be suggested to healthcare professionals. As a result, it can contribute to reducing the burden on healthcare professionals, improving the reliability of blood coagulation tests, and accelerating diagnosis.
[0098] Furthermore, abnormalities in measurement data caused by the condition of the automated analyzer, or changes in the patient's medication adherence, could lead to misdiagnosis. However, in this embodiment, if there is a discrepancy between the measurement data or characteristic information (such as medication history), the operator is notified, allowing them to quickly take action as needed, such as maintaining the measuring device or re-measuring after discontinuing medication.
[0099] In the above-described embodiment, the measurement data acquired by the analysis unit 201 of the automatic analyzer 101 is output to the control computer 103, and the control computer 103 acquires analysis values related to coagulation ability and corrects the analysis values. However, some of the above-described processes performed by the control computer 103 may be performed within the automatic analyzer 101. In that case, some of the coagulation waveform analysis unit 121, the analysis value correction unit 122, the deviation determination unit 123, and the inspection item determination unit 124 are stored in the control unit 203 of the automatic analyzer 101, etc.
[0100] 100...Analysis system, 101...Automatic analyzer, 102...Network, 103...Control computer, 104...Operation computer, 105...Monitor, 201...Analysis unit, 202...Operation unit, 203...Control unit, 204...Reaction disk, 205...Sample dispensing mechanism, 206...Sample disk, 206a...Reader, 208...Reagent disk, 209...Reagent dispensing mechanism, 210...Blood coagulation time measurement unit, 211...Reaction cell, 212...Constant temperature bath, 213...Sample container, 214...Reagent bottle, 215...Analysis control computer, 216...Storage device, 217...Interface, 218...Display unit, 221...Reaction vessel housing unit, 221a...Reaction vessel, 222...Reaction vessel transfer mechanism, 223...Sample dispensing station, 224...Coagulation reagent probe, 225...Detection unit, 225a...Photometric port, 301...Light source, 302...Photometer, 303...A / D converter, 801...Tab, 802...Analysis value area, 803...Probability of belonging area, 803a...Display switching button, 804...Patient ID area, 805...Test item area, 805a...Recommended test item name, 805b...Check box, 805c...Measurement request button, 806...Comment area, 901...Tab, 902...Data area, 903...Patient ID area, 904...Recommended work area, 905...Comment area
Claims
1. A data processing method comprising: an analytical value acquisition step of obtaining analytical values related to coagulation ability based on measurement data that changes over time in accordance with the coagulation reaction of a patient's blood sample; and an analytical value correction step of correcting the analytical values using the patient's characteristic information.
2. A data processing method according to claim 1, further comprising a test item determination step of determining recommended test items based on the corrected analysis values and / or characteristic information.
3. A data processing method according to claim 2, wherein the analysis value is the probability of each pathological condition, and if there is no pathological condition with a probability of 50% or more as the analysis value, the recommended test item is determined in the test item determination step based on the characteristic information.
4. A data processing method according to claim 2, wherein if the characteristic information is not available, the recommended inspection item is determined in the inspection item determination step based on the uncorrected analysis value.
5. A data processing method according to claim 1, further comprising: a measurement data discrepancy determination step of comparing the patient's past measurement data with the patient's current measurement data; and a notification step of notifying the patient if there is a discrepancy in the measurement data.
6. A data processing method according to claim 5, further comprising a characteristic information deviation determination step of comparing the characteristic information used to correct the patient's past analysis values with the patient's current characteristic information, wherein if there is no deviation in each of the characteristic information, the notification step provides a notification prompting the user to remeasure after checking the status of the measuring device.
7. A data processing method according to claim 5, further comprising a characteristic information deviation determination step of comparing the characteristic information used to correct the patient's past analysis values with the patient's current characteristic information, wherein if a deviation in each of the characteristic information indicates a new medication has been taken, the notification step provides a notification prompting remeasurement after discontinuing the medication.
8. A data processing method according to claim 5, wherein the notification step also includes notification of the degree of deviation of the measurement data.
9. A data processing method according to claim 1, wherein the analysis value is the probability of each pathological condition, and in the analysis value correction step, the probability is corrected using the prevalence rate of each pathological condition of other patients whose characteristic information is common to the patient.
10. A data processing method according to claim 2, further comprising a display step of displaying the corrected analysis value and the recommended inspection item on a screen, wherein a button for requesting measurement of the recommended inspection item is also displayed on the screen.
11. An analytical system comprising: an automated analyzer for measuring changes in light intensity over time associated with the coagulation reaction of a patient's blood sample; and a data processing device connected to the automated analyzer for processing related to the coagulation ability of the blood sample, wherein the data processing device includes: an analysis value acquisition unit for acquiring analysis values related to coagulation ability based on measurement data received from the automated analyzer; and an analysis value correction unit for correcting the analysis values using the patient's characteristic information.
12. An automated analyzer comprising: an analysis unit that measures changes in light intensity over time associated with the coagulation reaction of a patient's blood sample; an analysis value acquisition unit that acquires analytical values related to coagulation ability based on the measurement data from the analysis unit; and an analysis value correction unit that corrects the analytical values using the patient's characteristic information.