WO2022019064A1

WO2022019064A1 - Automated analyzer and automated analysis method

Info

Publication number: WO2022019064A1
Application number: PCT/JP2021/024619
Authority: WO
Inventors: 晃弘井口; 智憲三村; 昌彦飯島; 望寒河江; 尚哉茂手木
Original assignee: 株式会社日立ハイテク
Priority date: 2020-07-20
Filing date: 2021-06-29
Publication date: 2022-01-27
Also published as: JPWO2022019064A1; JP7320137B2

Abstract

Provided is an invention that makes it possible to detect abnormal fluctuation in reaction process data acquired in a preprocessing reaction for removing interfering components. This automated analyzer comprises: a reaction process data acquisition unit configured to acquire reaction process data by measuring absorbance in a preprocessing reaction in a time series; a condition setting unit configured to set a condition relating to the absorbance; an abnormal fluctuation determination unit configured to determine, on the basis of the condition set by the condition setting unit, whether the fluctuation in the reaction process data acquired in the preprocessing reaction will influence measurement of the concentration of a specific component in main reaction; and an output unit for outputting the result of the determination made by the abnormal fluctuation determination unit.

Description

Automatic analyzer and automatic analysis method

The present invention relates to an automated analyzer and an automated analysis method, and is applied to, for example, an automated analyzer and an automated analysis method for measuring the concentration of a specific component contained in a sample based on the absorbance of a sample and a reagent into a reaction solution. Regarding effective technology.

Japanese Patent Application Laid-Open No. 2006-337125 (Patent Document 1) introduces an approximate function to the reaction process data in this reaction to eliminate the influence of disturbance of the reaction process data due to noise of the photometer and the like. Therefore, a technique for calculating a predicted value and warning the measurer when there is an absorbance with a large deviation is described.

In Japanese Patent Application Laid-Open No. 2010-271095 (Patent Document 2), a sample can be appropriately measured by selecting an approximate expression using data of a plurality of measurement points for the item of the rate analysis method in this reaction. A technique that can evaluate whether or not the stirring mechanism constituting the automatic analyzer is functioning normally is described.

Japanese Unexamined Patent Publication No. 2015-197370 (Patent Document 3) describes a technique capable of accurately detecting and classifying an abnormal reaction process curve based on a blood coagulation reaction.

The automatic analyzer is used to measure the concentration of specific components contained in samples such as blood and urine. More specifically, the absorbance measured for the reaction solution obtained by reacting the sample with the reagent corresponding to each component is converted into the concentration of the specific component using a calibration curve prepared in advance.

Here, the calibration curve is created by performing a calibration including measurement of the absorbance of the reaction solution obtained by reacting a standard solution having a known concentration of a specific component with a reagent.

Factors that affect the analysis performance include a sampling mechanism for samples collected from patients, a reagent dispensing mechanism, a stirring mechanism, an optical system, a constant temperature bath, etc., which are the mechanisms constituting the automatic analyzer. Factors other than the automated analyzer that affect the analytical performance include reagents, liquid properties of the control sample, components contained in the patient sample, and the like.

The measurer measures the quality control sample after calibration to check the condition of the automatic analyzer, reagents, etc., and then measures the components contained in the sample. The measurer repeatedly measures the quality-controlled sample during the measurement of the sample to confirm whether the measurement result of the sample is appropriate.

During the reaction between the sample and the reagent, the absorbance is measured multiple times and recorded as time series data. This time series data is also called reaction process data.

There is a method of checking whether there is any abnormality in the reaction process data, and the check method can be classified into two types, the rate method and the endpoint method.

The rate method is mainly used when measuring the activity of enzyme components contained in a sample. Since the reagent of the biochemical item contains sufficient temperament, if the reaction between the sample and the reagent is performed normally, the reaction generally changes linearly by a constant amount with time. ..

There are linearity check and ABS limit as the conventional method of detecting data abnormality at the time of measurement in the rate method. The linearity check checks the linearity of the change in absorbance in the analysis item of the rate method. The difference in the amount of change in absorbance between the first half and the second half of a certain photometric range is obtained, and if the difference exceeds the specified linearity check value, it is judged that it is not a straight line. In addition, if the concentration or enzyme activity value of the sample to be measured is abnormally high and exceeds the measurable range of the reagent, all the substrate or coenzyme in the reagent is consumed before the photometric time, and the absorbance value changes rapidly. Therefore, the correct measured value cannot be obtained. Therefore, the reaction absorption limit value (ABS limit) of the upper limit or the lower limit of the absorbance is set to detect the abnormality of the data.

The endpoint method mainly measures the concentration of components such as proteins and lipids contained in the sample. The substance produced by the reaction between the components in the sample and the reagent gradually approaches a certain amount over time. Therefore, the measured value also asymptotically approaches a constant value with time.

There is a pro zone check as a method of detecting a conventional data abnormality at the time of measurement in the endpoint method. In reagents using an immunoturbidimetric method such as IgA (immunoglobulin A) and CRP (C-reactive protein), the protein may precipitate as a precipitate due to the influence of the salt concentration of the reagent composition. The reaction process data may fluctuate due to this precipitate, and in reality, it often appears in the latter half of the reaction time. If this fluctuation occurs in the photometric point section used for density calculation, it is not possible to obtain an accurate measured value. As a method for checking this, there are an antibody re-addition method and a reaction rate ratio method, and there is a method of issuing an alarm when the limit value specified by the parameter is exceeded.

Japanese Unexamined Patent Publication No. 2006-337125 Japanese Unexamined Patent Publication No. 2010-271095 JP-A-2015-197370

Many items in biochemical analysis often consist of a main reaction to detect the concentration of a specific component and a pretreatment reaction to remove interfering components. Specifically, after carrying out a pretreatment reaction in which the sample is reacted with the first reagent, this reaction in which the sample is reacted with a second reagent other than the first reagent and a third reagent is carried out. Here, for example, the second reagent and the third reagent other than the first reagent used in this reaction are reagents that react with a specific component contained in the sample.

For example, when measuring the concentration of a specific component contained in a sample based on the absorbance of the sample and the reagent with respect to the reaction solution, the absorbance obtained based on the reaction process data in this reaction and the reaction process data in the pretreatment reaction are used. The concentration of the specific component is measured by taking the difference in the absorbances obtained.

Here, the reaction process data that is the basis of the measurement results of each sample may change unintentionally depending on the components contained in the sample. This variation in reaction process data may affect the measurement results of the sample. In addition, the reaction process data may fluctuate due to defects in the dispensing system, optical system, stirring, washing, etc. that make up the automatic analyzer.

In order to check the fluctuation of these reaction process data, it is required for the inspection engineer who is the user of the automatic analyzer to visually check the huge amount of reaction process data in the daily inspection work. It's difficult to do. Among them, if the measurement result is data near the reference range, there is a high possibility that an abnormality in the reaction will be overlooked, and it is difficult to obtain a valid measurement result. Therefore, there is a need for technology to detect fluctuations in reaction process data.

Regarding this point, in the technique using the conventional reaction process approximation method represented by the above-mentioned Patent Document 1 and Patent Document 2, this reaction for detecting the concentration of a specific component is utilized. With these techniques, it is possible to detect anomalies in the reaction process data in this reaction, but it is not possible to detect anomalies in the reaction process data occurring in the pretreatment reaction. That is, in the prior art, it is not considered that the fluctuation of the reaction process data in the pretreatment reaction for the purpose of removing the disturbing component affects the measurement of the concentration of the specific component. On the other hand, the concentration of a specific component is measured by taking the difference between the absorbance obtained based on the reaction process data in this reaction and the absorbance obtained based on the reaction process data in the pretreatment reaction. The inventor has newly found that abnormal fluctuations in reaction process data in a pretreatment reaction may adversely affect the measurement of the concentration of a specific component.

An object of the present invention is to provide a technique capable of detecting anomalous fluctuations in reaction process data in a pretreatment reaction for removing interfering components.
Other issues and novel features will become apparent from the description and accompanying drawings herein.

The automatic analyzer in one embodiment is configured to measure the concentration of a specific component contained in a sample based on the absorbance of the sample and the reagent with respect to the reaction solution. Here, the reaction between the sample and the reagent includes a pretreatment reaction in which the sample and the first reagent are reacted, and a main reaction in which the sample and a reagent other than the first reagent are reacted. The automated analyzer is configured to acquire reaction process data by measuring the absorbance in a time series in the pretreatment reaction, and a condition configured to set conditions related to the absorbance. Based on the conditions set by the setting unit and the condition setting unit, it is determined whether or not the fluctuation of the reaction process data acquired in the pretreatment reaction affects the measurement of the concentration of a specific component in this reaction. It is provided with an abnormal change determination unit configured to output the determination result and an output unit configured to output the determination result determined by the abnormal change determination unit.

Further, the automatic analysis method in one embodiment is a method of measuring the concentration of a specific component contained in a sample based on the absorbance of the sample and the reagent with respect to the reaction solution. Here, the reaction between the sample and the reagent includes a pretreatment reaction in which the sample and the first reagent are reacted, and a main reaction in which the sample and a reagent other than the first reagent are reacted. The automatic analysis method is set in a reaction process data acquisition step of acquiring reaction process data by measuring the absorbance in a pretreatment reaction in time series, a condition setting step of setting conditions related to the absorbance, and a condition setting step. Anomalous fluctuation judgment process for determining whether or not the fluctuation of the reaction process data acquired in the pretreatment reaction affects the measurement of the concentration of a specific component in this reaction, and the abnormality fluctuation judgment based on the above conditions. It includes an output process that outputs the judgment result determined in the process.

According to one embodiment, it is possible to detect anomalous fluctuations in reaction process data in a pretreatment reaction that removes interfering components.

It is a figure explaining the configuration example of the automatic analyzer which analyzes a sample. It is a graph which shows an example of the reaction process data of CRP. It is a graph which shows an example of the reaction process data of LDL-C. It is a figure which shows the functional block composition of an automatic analyzer. It is a table which shows an example of the initial condition set in a condition setting part. It is a table which shows an example of the exception condition set in the condition setting part. It is a graph which expands and shows the reaction process data in the pretreatment reaction among the reaction process data shown in FIG. It is a graph which expands and shows the reaction process data in the pretreatment reaction among the reaction process data shown in FIG. It is a figure which shows an example of the display which is output from an output part. It is a flowchart which shows the flow of the whole operation which detects the abnormal fluctuation of the reaction process data of h by an automatic analyzer. It is a flowchart explaining the flow of the analysis operation for detecting the abnormal fluctuation of reaction process data. It is a flowchart explaining the flow of the analysis operation for detecting the abnormal fluctuation of reaction process data. It is a flowchart explaining the modification of operation. It is a table which shows an example of a specific condition. It is a flowchart explaining the operation of estimating the fluctuation cause of the reaction process data. It is a figure which shows an example of a warning display. It is a graph which shows the example of the reaction process data of UA (uric acid). It is a graph which shows the example of the reaction process data of CRE (creatinine). It is a table which shows an example of the initial condition set in a condition setting part. It is a table which shows an example of an exception condition. It is a graph which calculated the difference between the absorbance and the absorbance immediately before it in the section of the pretreatment reaction from the 1st photometric point to the 2nd photometric point of the reaction process data shown in FIG. 17, and plotted them in chronological order. It is a graph which calculated the difference between the absorbance and the absorbance immediately before it in the section of the pretreatment reaction from the 1st photometric point to the 2nd photometric point of the reaction process data shown in FIG. 17, and plotted them in chronological order. It is a flowchart explaining the flow for detecting the abnormal change of reaction process data by the analysis method of an application example.

In all the drawings for explaining the embodiment, the same members are designated by the same reference numerals in principle, and the repeated description thereof will be omitted. In addition, in order to make the drawing easier to understand, hatching may be added even if it is a plan view.

<New findings found by the present inventor>
First, the novel first finding found by the present inventor is that (a) changes in absorbance in the pretreatment reaction (changes in the reaction process data) affect the reaction of the reaction process data. There are two types of fluctuations: one that affects the measurement of the concentration of a specific component and (b) the fluctuation of the absorbance in the pretreatment reaction but does not affect the measurement of the concentration of the specific component in this reaction. That is. Based on this first finding, in order to detect abnormal fluctuations in the reaction process data in the pretreatment reaction, "changes in the reaction process data due to (a)" and "changes in the reaction process data due to (b)" are used. It can be seen that it is necessary to distinguish and detect only "variation of reaction process data due to (a)" as anomalous variation of reaction process data.

In the following description, "(a) a change in absorbance in the pretreatment reaction affects the reaction of this reaction and affects the measurement of the concentration of a specific component" is simply referred to as "effect change". "(B) Absorbance in the pretreatment reaction fluctuates but does not affect the measurement of the concentration of a specific component in this reaction" is simply referred to as "non-influenced fluctuation".

Subsequently, the novel second finding found by the present inventor is the finding shown below. The variation in absorbance varies randomly if it is caused by an optical system caused by an automated analyzer. For example, air bubbles in the reaction solution and dripping of the washing solution also cause a large fluctuation in the absorbance. This variation in absorbance can generally be classified as a "sudden error". On the other hand, the contaminants contained in the sample are an abnormal reaction because they react with the reagent components, but they undergo characteristic changes such as an increase / decrease in absorbance in a certain direction. This can generally be categorized as "systematic error". As for the coping method when noise occurs at the stage of pretreatment reaction after adding the first reagent (variation of reaction process data), there are items and the degree of the error in "sudden error" and "systematic error". Is very different. It is important to quantitatively affect the effects of each item at the stage of the pretreatment reaction, and to extract the characteristics and deal with them. Based on this second finding, if the fluctuation of the reaction process data in the pretreatment reaction can be distinguished into "sudden error" and "systematic error", the fluctuation of the reaction process data is caused by the sample itself. It will be possible to distinguish whether it is a fluctuation caused by an automatic analyzer or a fluctuation caused by an automatic analyzer.

Based on the above-mentioned first finding, even if this reaction is normal, the pretreatment reaction of the interfering component after the addition of the first reagent may affect the calculation of the measurement result of this reaction. In such a case, in the fluctuation check of the reaction process data in the main reaction as in the prior art, there is a possibility that the abnormal fluctuation (noise) of the reaction process data in the pretreatment reaction may be overlooked. For this reason, it is important to detect abnormal fluctuations in reaction process data at the stage of pretreatment reaction.

Furthermore, based on the above-mentioned second finding, it is also important to identify whether the fluctuation of the reaction process data is due to the sample itself or the fluctuation due to the automated analyzer. In this regard, since the absorbance of this reaction increases in a concentration-dependent manner, when the change in absorbance of this reaction is large, the effect of sudden noise is relatively small, and the noise is buried and difficult to detect. This means that at the stage of this reaction, it becomes difficult to identify whether the fluctuation of the reaction process data is due to the sample itself or the fluctuation due to the automated analyzer. .. On the other hand, since the reaction process data in the pretreatment reaction has a feature that the fluctuation of the absorbance is small, sudden noise is likely to become apparent. This is because the technical idea of detecting abnormal fluctuations in the reaction process data at the stage of the pretreatment reaction is that the abnormal fluctuations in the reaction process data are due to the sample itself, or due to the mechanism of the automatic analyzer. It means that it is suitable for sensitively determining whether or not the fluctuation is to occur. Therefore, it can be said that the technical idea of detecting abnormal fluctuations in the reaction process data at the stage of the pretreatment reaction has important technical significance in investigating the cause of the abnormal fluctuations in the reaction process data.

Furthermore, the interfering components contained in the sample differ for each sample. Since the effect of the pretreatment reaction of the interfering component also differs from sample to sample, the effect on this reaction also differs. Therefore, when this reaction is approximated by an approximate formula, it is not possible to determine whether the event is caused by a deviation in the sample component or a malfunction of the automatic analyzer, and it is difficult to systematically classify the event. In particular, in the case of hemolytic samples and hyperlipidemia, the reaction after the addition of the first reagent is significantly different from other normal samples. The reaction process data in the pretreatment reaction of a normal sample remains flat, but when a certain amount of contaminants are contained, the absorbance is asymptotic during the pretreatment reaction due to the reaction to remove the contaminants. In some cases, it may decrease. On the other hand, even for the same item, if air bubbles adhere to the reaction vessel during reagent dispensing or the light source lamp is unstable, random absorbance fluctuations occur. In many cases, the deviation in absorbance due to these automated analyzers and the fluctuation in absorbance due to the sample are mixed. For items that change suddenly, it is desirable to perform re-examination or maintenance by stopping the automatic analyzer, but if it is affected by contaminants on the sample, it is not a malfunction of the automatic analyzer, so re-inspection It is desirable to carry out automatically. However, even when measuring a sample that is greatly affected by impurities contained in the sample, it is difficult for the measurer of the automatic analyzer to make a remeasurement without being aware of it until the measurement is completed. Is the reality.

Also, the coping method when an abnormality occurs is different. When sudden noise is measured due to dripping of cleaning liquid, it is important to stop the analysis of the automatic analyzer without continuing the analysis. Occurrence of such a serious event is extremely rare. Although the content of impurities in the sample varies depending on the content, it is contained in most of the samples, and in many items, the reagents are adjusted so as not to affect this reaction by devising the reagents. However, when the content of impurities contained in the sample is large, there are some items that affect the concentration component of this reaction. In that case, it is important to reduce the sample volume and remeasure it in order to ensure the reliability of the data.

From this, if the abnormal fluctuation of the reaction process data can be detected at an early stage of the concentration measurement of the specific component, the subsequent measures can be promptly implemented. That is, to detect abnormal fluctuations in the reaction process data at the stage of the pretreatment reaction prior to this reaction, it is necessary to immediately interrupt the measurement and remeasure it, or stop the automatic analyzer. It means that it can be judged at an early stage of measurement. Therefore, it can be seen that the technical idea of detecting abnormal fluctuations in the reaction process data at the stage of the pretreatment reaction is very useful from the viewpoint of shortening the inspection result reporting time and enabling the state management of the automatic analyzer.
Two specific examples of the pretreatment reaction are given.

For lipid components such as LDL-C (LDL cholesterol), a pretreatment reaction is carried out in order to remove interfering components other than the target component. If the lipid component in the sample is excessive, the excess lipid component cannot be completely removed in the pretreatment reaction, so unlike a normal sample, the absorbance of the pretreatment reaction increases, and this effect is removed. If it does not work, it may not be possible to obtain reasonable measurement results. In addition, if the serum contains an excessive amount of globulin component, it becomes cloudy due to being mixed with a reagent for biochemical measurement, and the absorbance increases during the reaction time, which should not increase in the pretreatment reaction. There is. As a result, the measured concentration may become abnormal. In addition to the above two cases, there are cases where the reaction process data becomes abnormal during the pretreatment reaction due to the components contained in the sample.

Therefore, in the present embodiment, based on the first finding described above, "impact fluctuation" and "non-impact variation" are distinguished, and only "impact variation" is detected as an abnormal variation in the reaction process data. There is. Further, in the present embodiment, based on the above-mentioned second finding, a device for distinguishing whether the fluctuation of the reaction process data is due to the sample itself or the fluctuation due to the automated analyzer. Is also given. Hereinafter, the technical idea in the present embodiment to which this device has been devised will be described.

<Configuration of automated analyzer>
FIG. 1 is a diagram illustrating a configuration example of an automatic analyzer that analyzes a sample.
In FIG. 1, the automatic analyzer 100 includes an analysis unit 1, a storage unit 14, a display unit 15, an operation unit 16, and a control unit 17. The analysis unit 1 includes a transfer line 4, a sample probe 5, a reagent probe 6, a reagent disk 8, a reaction disk 10, a stirring unit 11, a photometer 12, and a cleaning unit 13.

The transport line 4 transports the sample rack 3 on which a plurality of sample containers 2 containing samples such as blood and urine are stored to a position where the sample probe 5 accesses. The sample rack 3 and the transport line 4 may be replaced with a sample disk that rotates in one direction in order to move the sample container 2 mounted in a ring shape.

The reagent disk 8 stores a plurality of reagent containers 7 containing reagents to be reacted with the sample, and rotates in one direction in order to move the reagent container 7 to a position where the reagent probe 6 can access. The reaction disc 10 holds a plurality of reaction vessels 9 to which the sample and the reagent are dispensed in a ring shape, and rotates in one direction in order to move the reaction vessel 9 to a predetermined position.

The sample probe 5 dispenses a sample from the sample container 2 mounted on the sample rack 3 conveyed by the transfer line 4 to the reaction container 9. The reagent probe 6 dispenses the reagent from the reagent container 7 into the reaction vessel 9 into which the sample is dispensed. The number of reagents dispensed into the reaction vessel 9 is not limited to one, and may be plural.

The stirring unit 11 is arranged around the reaction disk 10 and stirs in the reaction vessel 9 in which the sample and the reagent are dispensed. The photometer 12 is arranged around the reaction disk 10 and measures the absorbance of the solution in the reaction vessel 9 stirred by the stirring unit 11 each time the reaction vessel 9 crosses the front. Since the reaction disk 10 rotates intermittently at a constant timing, the absorbance of the solution in the reaction vessel 9 is measured at regular time intervals. The measured absorbance is converted into the concentration of a specific component contained in the sample using a calibration curve prepared in advance. The calibration curve is created by performing a calibration including measurement of the absorbance of the reaction solution obtained by reacting a standard solution having a known concentration of a specific component with a reagent. The cleaning unit 13 is arranged around the reaction disk 10 and cleans the reaction vessel 9 for which analysis has been completed.

The standard solution used for calibration is an aqueous solution containing a specific component, and has at least a concentration near the upper limit value and a concentration near the lower limit value in the measurement range of the automatic analyzer 100. That is, at least two standard solutions are used. The standard solution in which the concentration of the specific component is substantially zero and does not react with the reagent is called the first standard solution, and in many cases, it is physiological saline, purified water, or the like.

The storage unit 14 is, for example, an HDD (Hard Disk Drive) or SSD (Solid State Drive), and stores the absorbance measured by the photometer 12 and the concentration converted from the absorbance.

The display unit 15 is, for example, a liquid crystal display or a touch panel, and displays information such as absorbance and concentration. The operation unit 16 is, for example, a keyboard or a mouse, and operations such as inputting conditions and parameters necessary for analysis are performed. When the display unit 15 is a touch panel, the GUI (Graphical User Interface) displayed on the touch panel functions as the operation unit 16. The control unit 17 is, for example, an arithmetic unit such as a CPU (Central Processing Unit), which controls each unit and executes various operations.
As described above, the automatic analyzer 100 is configured.

<Example of reaction process data>
Next, an example of reaction process data will be described.
FIG. 2 is a graph showing an example of CRP reaction process data.
In FIG. 2, the horizontal axis indicates the photometric point (photometric time), and the vertical axis indicates the absorbance. The time range from "Measuring point 1" to "Measuring point 17" corresponds to the pretreatment reaction, and the time range from "Measuring point 18" to "Measuring point 34" corresponds to this reaction.

In the graph for the sample 200A shown in FIG. 2, the reaction process data in the pretreatment reaction is almost flat, which indicates that the reaction process data in the pretreatment reaction has little fluctuation and is normal. Further, in the graph for the sample 200A, it can be seen that the reaction process data in this reaction tends to increase. The reaction process data of the sample 200A is an example of normal data. On the other hand, in the graph for the sample 200B, the reaction process data in the pretreatment reaction is not flat and tends to increase. Since the reaction process data in the pretreatment reaction is usually flat, the reaction process data of the sample 200B showing the fluctuation of the increasing tendency is abnormal. That is, the reaction process data of the sample 200B is an example of abnormal data.

Here, the concentration of the specific component is measured, for example, based on the difference between the absorbance of this reaction and the absorbance of the pretreatment reaction. For example, in FIG. 2, the absorbance of this reaction is the absorbance of the final photometric point “photometric point 34”, while the absorbance of the pretreatment reaction is the final photometric point of the pretreatment reaction “photometry”. The absorbance at point 17 ”is used. Therefore, in the abnormal data of the sample 200B, since the absorbance of the “photometric point 17”, which is the final photometric point of the pretreatment reaction, is large, the measurement is performed based on the difference between the absorbance of this reaction and the absorbance of the pretreatment reaction. It will affect the concentration of the specific component. That is, the fluctuation of the reaction process data of the sample 200B shown in FIG. 2 corresponds to the “effect fluctuation”.
Subsequently, FIG. 3 is a graph showing an example of reaction process data of LDL-C.

In the graph for the sample 300A shown in FIG. 3, the reaction process data in the pretreatment reaction is almost flat, which indicates that the reaction process data in the pretreatment reaction has little fluctuation and is normal. On the other hand, in the graph for the sample 300B shown in FIG. 3, the reaction process data in the pretreatment reaction shows a decreasing tendency. Therefore, at first glance, the graph for the sample 300B is considered to be abnormal. However, in reality, it is considered that the sample 300B contains a large amount of interfering components, and as a result of the progress of removal of the interfering components in the pretreatment reaction, the absorbance due to the interfering components is reduced. Then, in the final stage of the pretreatment reaction (“photometric point 17”), it is considered that most of the disturbing components are removed and the absorbance becomes normal. That is, the absorbance of the final photometric point 34 is used as the absorbance of this reaction, while the absorbance of the pretreatment reaction is that of the final photometric point 17 of the pretreatment reaction. Assuming that the absorbance is used, in the reaction process data of the sample 300B, the fluctuation in the pretreatment reaction does not affect the measurement of the concentration of the specific component. That is, the fluctuation of the reaction process data in the sample 300B is the normal data corresponding to the “non-influenced fluctuation”.

Therefore, when detecting the abnormal variation in the pretreatment reaction, for example, the variation of the reaction process data in the sample 200B shown in FIG. 2 can be detected as an abnormal variation, while the variation of the reaction process data in the sample 300B shown in FIG. 3 can be detected. Fluctuations need not be detected as anomalous fluctuations.

In the following, an automated analyzer that detects "impact fluctuation" as anomalous fluctuation but does not detect "non-impact fluctuation" as anomalous fluctuation will be described.

Since the expression related to the absorbance is displayed as an integer on the automatic analyzer, the absorbance described in the present specification is expressed as an integer value, for example, multiplied by 10,000.

<Functional block configuration of automatic analyzer>
FIG. 4 is a diagram showing a functional block configuration of the automatic analyzer.
In FIG. 4, the automatic analyzer 100 includes a reaction process data acquisition unit 500, a condition setting unit 501, an abnormality fluctuation determination unit 502, an output unit 504, a measurement interruption unit 505, and a data storage unit 506. ing.

The reaction process data acquisition unit 500 is configured to acquire reaction process data obtained by measuring the absorbance in a time series in the pretreatment reaction. As an example of the reaction process data, the reaction process data shown in FIGS. 2 and 3 can be mentioned. The reaction process data acquired by the reaction process data acquisition unit 500 is stored in the data storage unit 506.

Next, the condition setting unit 501 is configured to be able to set initial conditions including conditions related to absorbance. For example, FIG. 5 is a table showing an example of initial conditions set by the condition setting unit 501. In FIG. 5, the component to be measured for the concentration is set in the “item”. For example, when "LDL" is set in "Item", the condition used for the analysis of the reaction process data of "LDL" is set in the row corresponding to "LDL".

The conditions set for each "item" include "photometric point", "variation tolerance", "point number", "Err tolerance", "absorbance width of pretreatment reaction", "judgment method" and "measurement". There is "continuation".

The "measurement point" defines the measurement section used for analysis of reaction process data. For example, when "5-17" is described in "Measuring point", the reaction process data is analyzed using the reaction process data from "Measuring point 5" to "Measuring point 17".

The "variation tolerance" defines the range of allowable deviation from the approximate function to which the reaction process data is fitted. For example, when "100" is described in "variation tolerance", it means that the range of allowable deviation from the approximation function is "100".

The "number of points" defines the permissible number of reaction process data that is outside the permissible deviation range from the approximation function. For example, when "5" is described in "the number of points", it means that the allowable number of reaction process data outside the allowable range of deviation is "5".

The "Err tolerance" defines the tolerance of the squared error based on the approximate function and the measured reaction process data. For example, when "200" is described in "Err tolerance", it means that the tolerance of the square error is "200".

The "absorbance width of the pretreatment reaction" defines the permissible value for the difference between the minimum value and the maximum value of the reaction process data in the pretreatment reaction. For example, when "150" is described in "absorbance width of pretreatment reaction", it means that the allowable value for the absorbance width is "150".

The "judgment method" defines whether a plurality of conditions related to absorbance are used as AND conditions or OR conditions. Specifically, the AND condition or the OR condition of the condition based on the "variation tolerance" and the "number of points", the condition based on the "Err tolerance", and the condition based on the "absorbance width of the pretreatment reaction". It is stipulated whether to judge abnormal fluctuations in reaction process data. For example, when "AND" is described in the "determination method", it means that the presence or absence of abnormal fluctuations in the reaction process data is determined by using a plurality of conditions related to the above-mentioned absorbance as AND conditions.

"Continued measurement" defines whether to continue the measurement or interrupt the measurement when there is an abnormal change in the reaction process data. For example, when "stop" is described in "continuation of measurement", it means that the measurement is interrupted when there is an abnormal change in the reaction process data.

Although not shown in FIG. 5, the condition setting unit 501 is configured so that the approximation function used when fitting the reaction process data can be selected and set. For example, the types of approximation functions include a linear function, an inverse proportional function, an exponential function, a logarithmic function, and the like, and an approximation function used for fitting can be set from these functions. However, in the present embodiment, for the sake of simplicity, a linear function will be selected as the approximate function used for fitting.

In the automatic analyzer 100, "impact variation" is detected as anomalous variation, while "non-impact variation" is not detected as anomalous variation. Therefore, in the condition setting unit 501, not only the conditions shown in FIG. 5 but also the following are shown. Exception conditions are also configured to be set.

For example, FIG. 6 is a table showing an example of an exception condition set by the condition setting unit 501. In FIG. 6, the component to be measured for the concentration is set in the “item”. For example, when "LDL" is set in "Item", the line corresponding to "LDL" defines an exception condition for not determining the reaction process data of "LDL" as an abnormal change. This exception condition includes "light measurement point", "change direction", and "change rate".

The measurement section of the reaction process data is defined in the "measurement section (measurement point)". For example, when "5-17" is described in "Measuring point", it means that the reaction process data from "Measuring point 5" to "Measuring point 17" is within the scope of the exception condition.

The "change direction" defines the change direction of the reaction process data, which is an exception condition. For example, when the "change direction" is described as "continuous decrease", it means that the exception condition is applied when the change of the reaction process data is continuous decrease. In other words, when the "change direction" is described as "continuous decrease", it means that the exception condition is not applied when the change of the reaction process data is other than "continuous decrease".

The "rate of change" defines the rate of change of reaction process data, which is an exception condition. For example, when the "rate of change" is described as "100", it means that the exception condition is applied when the slope of the approximate function to which the reaction process data is fitted is "100" or less.

In the "Comment" column, the factors that cause fluctuations in the reaction process data can be simply described. For example, when "weak chyle effect" is described in the "comment" column, it can be understood that "weak chyle" causes fluctuations in the reaction process data corresponding to the exception condition.

As described above, the condition setting unit 501 is configured to set, for example, the exception condition shown in FIG. 6 in addition to the condition shown in FIG. Then, the conditions related to the absorbance (FIGS. 5 and 6) set by the condition setting unit 501 are stored in the data storage unit 506.

Subsequently, in the abnormal fluctuation determination unit 502, the fluctuation of the reaction process data acquired in the pretreatment reaction affects the measurement of the concentration of the specific component in this reaction based on the conditions related to the absorbance set in the condition setting unit 501. It is configured to determine if it is a variable that it exerts.
The abnormal change determination unit 502 is configured to perform the determination process shown below.

<< First judgment processing configuration >>
The anomalous fluctuation determination unit 502 determines whether or not the difference between the minimum value and the maximum value of the reaction process data is within the allowable range of the "absorbance width of the pretreatment reaction" set by the condition setting unit 501. It is configured in. Thereby, the abnormal fluctuation determination unit 502 can determine whether or not the fluctuation of the reaction process data exceeds a certain slope.

<< Second judgment processing configuration >>
The anomalous fluctuation determination unit 502 includes a parameter determination unit 503 configured to determine parameters included in the approximation function by fitting reaction process data with an approximation function (regression line). The parameter determination unit 503 is configured to determine the parameters of the slope “a” and the Y-intercept “b” of the regression line “Y = aX + b” through fitting to the reaction process data. Then, the abnormal variation determination unit 502 is configured to evaluate the deviation of the reaction process data from the regression line based on the "variation allowable value" and the "point number" set by the condition setting unit 501.

Specifically, if the "variation tolerance" set by the condition setting unit 501 is "A", the abnormality fluctuation determination unit 502 determines whether the reaction process data is within the tolerance range of "Y = aX + b ± A". It is configured to determine. Then, when there is reaction process data that does not fall within this permissible range, the abnormal fluctuation determination unit 502 exceeds the number of permissible data specified by the "point number" for the number of reaction process data that does not fall within the permissible range. It is configured to determine whether or not it is. As a result, the abnormal fluctuation determination unit 502 can determine whether the fluctuation of the reaction process data is a fluctuation with a large deviation from the regression line.

For example, FIG. 7 is an enlarged graph showing the reaction process data in the pretreatment reaction among the reaction process data shown in FIG. 2. In FIG. 7, the reaction process data of the sample 200A is evaluated within the allowable range of the regression line shown by the broken line, and the reaction process data of the sample 200B is evaluated within the allowable range of the regression line shown by the broken line. It is shown to be in a state of being.

In FIG. 7, the number of reaction process data in the reaction process data of the sample 200A that exceeds the allowable range of the regression line is the reaction process data that exceeds the allowable range of the regression line in the reaction process data of the sample 200B. Less than the number of data. Therefore, for example, the abnormality fluctuation determination unit 502 can determine that the number of reaction process data in the reaction process data of the sample 200A that exceeds the allowable range of the regression line is smaller than the allowable number of data. On the other hand, the abnormality fluctuation determination unit 502 can determine that the number of reaction process data in the reaction process data of the sample 200B that exceeds the allowable range of the regression line is larger than the allowable number of data.

Similarly, FIG. 8 is a graph showing an enlarged reaction process data in the pretreatment reaction among the reaction process data shown in FIG. In FIG. 8, the reaction process data of the sample 300A is evaluated within the allowable range of the regression line shown by the broken line, and the reaction process data of the sample 300B is evaluated within the allowable range of the regression line shown by the broken line. It is shown to be in a state of being.

In FIG. 8, the number of reaction process data in the reaction process data of the sample 300A that exceeds the allowable range of the regression line is the reaction process data that exceeds the allowable range of the regression line in the reaction process data of the sample 300B. Less than the number of data. Therefore, for example, the abnormality fluctuation determination unit 502 can determine that the number of reaction process data in the reaction process data of the sample 300A that exceeds the allowable range of the regression line is smaller than the allowable number of data. On the other hand, the abnormality fluctuation determination unit 502 can determine that the number of reaction process data in the reaction process data of the sample 300B that exceeds the allowable range of the regression line is larger than the allowable number of data.

<< Third judgment processing configuration >>
The anomalous fluctuation determination unit 502 allows fluctuations in the reaction process data acquired in the pretreatment reaction based on the allowable range of the square error between the approximation function (regression line) set in the condition setting unit 501 and the reaction process data. It is configured to determine if it is within range. As a result, the abnormal fluctuation determination unit 502 can determine whether or not the reaction process data has a large variation.

<< Fourth judgment processing configuration >>
When the fluctuation of the reaction process data acquired in the preprocessing reaction corresponds to the exception condition (see FIG. 6) set by the condition setting unit 501, the abnormal fluctuation determination unit 502 performs the first determination process and the second determination process described above. Regardless of the result of the judgment process and the third judgment process, it is configured to judge that the fluctuation of the reaction process data is not an abnormal fluctuation.

As a result, the abnormal fluctuation determination unit 502 detects "impact fluctuation" as abnormal fluctuation, but does not detect "non-impact fluctuation" as abnormal fluctuation.

<< Abnormality judgment processing configuration >>
The abnormal change judgment unit 502 comprehensively considers the judgment results of the first judgment process, the second judgment process, the third judgment process, and the fourth judgment process, and the change of the reaction process data in the pretreatment reaction is an abnormal change. It is configured to determine if it exists.

Specifically, based on the "determination method" set by the condition setting unit 501, the abnormality change determination unit 502 determines whether or not the change in the reaction process data in the pretreatment reaction is an abnormality change. For example, when the "judgment method" set by the condition setting unit 501 is an AND condition, the difference between the minimum value and the maximum value of the reaction process data in the first judgment process is the allowable range of the "absorbance width of the pretreatment reaction". It is judged that the fluctuation is not within the range, and the fluctuation of the reaction process data is judged to be a fluctuation with a large deviation from the regression line in the second judgment processing, and the fluctuation of the reaction process data is squared in the third judgment processing. If it is determined that the error is not within the permissible range and the exception condition is not satisfied in the fourth determination process, the abnormality change determination unit 502 determines that the change in the reaction process data in the pretreatment reaction is abnormal. It is judged to be fluctuating. On the other hand, even if the judgment results of the first judgment processing, the second judgment processing, and the third judgment processing are the same as above, if it is determined in the fourth judgment processing that the exception condition is satisfied, the abnormal change judgment unit 502 determines. It is judged that the fluctuation of the reaction process data in the pretreatment reaction is not an abnormal fluctuation.

In this way, the abnormal fluctuation determination unit 502 is configured so that "impact fluctuation" can be detected as an abnormal fluctuation, but "non-impact fluctuation" is not detected as an abnormal fluctuation.

For example, the reaction process data for the sample 200B in FIG. 7 is “influence variation”, while the reaction process data for the sample 300B in FIG. 8 is “non-influence variation”.

Regarding this point, assuming that the abnormality change determination unit 502 does not have the fourth judgment processing configuration, the change of the reaction process data with respect to the sample 200B of FIG. 7 and the change of the reaction process data with respect to the sample 300B of FIG. 8 are determined as abnormal changes. It is thought that it will be done.

However, in the present embodiment, the abnormal change determination unit 502 has not only the first determination processing configuration to the third determination processing configuration but also the fourth determination processing configuration related to the exception condition. As a result, according to the present embodiment, the fluctuation of the reaction process data shown in FIG. 8 is not judged to be an abnormal fluctuation because it corresponds to the exception condition. From the above, according to the automatic analyzer 100 in the present embodiment, a configuration is realized in which "impact variation" is detected as anomalous variation, but "non-impact variation" is not detected as anomalous variation. ..

Next, the output unit 504 is configured to output the determination result determined by the abnormal fluctuation determination unit 502. For example, the output unit 504 can issue a warning by voice or display a warning text or an image on the display device when the determination result determined by the abnormality fluctuation determination unit 502 is an abnormality fluctuation. It is configured in. The output method from the output unit 504 can be set in advance by the condition setting unit 501.

FIG. 9 shows an example of the display output from the output unit 504. As a result, the measurer can grasp that the reaction process data has abnormal fluctuations in the pretreatment reaction. Further, the automatic analyzer 100 in the present embodiment interrupts the measurement of the concentration of the specific component contained in the sample when the abnormality change determination unit 502 determines that the change in the reaction process data is an “effect change”. It has a measurement interruption unit 505 configured as described above. Whether or not the measurement is interrupted by the measurement interruption unit 505 can be set in advance by the condition setting unit 501.

From the above, according to the automatic analyzer 100 in the present embodiment, it is possible to detect abnormal fluctuations in the reaction process data at an early stage (pretreatment reaction stage) of the concentration measurement of the specific component. Response can be carried out promptly. That is, since the automatic analyzer 100 in the present embodiment can detect abnormal fluctuations in the reaction process data at the stage of the pretreatment reaction prior to the main reaction, is it necessary to immediately interrupt the measurement and remeasure? Alternatively, it can be determined early in the measurement whether the automated analyzer needs to be shut down. Therefore, the technical idea of detecting the "impact fluctuation" of the reaction process data at the stage of the pretreatment reaction is very useful from the viewpoint of shortening the inspection result reporting time and enabling the state management of the automatic analyzer. Recognize.

<Operation of automatic analyzer>
Subsequently, the operation of the automatic analyzer 100 will be described.
FIG. 10 is a flowchart showing a flow of an overall operation for detecting an abnormal change in reaction process data in the automatic analyzer 100. In FIG. 10, first, a condition is set (S101). Specifically, in the condition setting unit 501, the initial conditions including the conditions related to the absorbance shown in FIG. 5 are set, and the exception conditions shown in FIG. 6 are set. After that, the condition setting unit 501 sets the output method of the determination result (S102). For example, as a method of outputting the judgment result, it is conceivable to display a warning or a warning message by a buzzer. Then, the analysis of the reaction process data is started (S103). In the following, the analysis operation of the reaction process data will be described.

11 and 12 are flowcharts illustrating the flow of analysis operation for detecting abnormal fluctuations in reaction process data. In the present embodiment, as a method for detecting abnormal fluctuations in the reaction process data, a method for analyzing the reaction process data by approximating the relationship between the measured absorbance and time with a linear function (regression line). Is shown.

First, the absorbance of the reaction solution, which is a mixture of the sample and the first reagent, is measured with a photometer (S201). As a result, reaction process data in the pretreatment reaction is acquired (S202). The acquired reaction process data is stored in the data storage unit 506 of the automatic analyzer 100 (S203). Here, for example, the data storage unit 506 is premised on the configuration included in the automatic analyzer 100, but the data storage unit 506 is not limited to this, and the data storage unit 506 may be used in a server or the like connected to the automatic analyzer 100 via a network. It may be installed.

Next, it is determined whether the reaction process data of the measurement point (photometric section) necessary for the analysis of the reaction process data in the pretreatment reaction could be acquired (S204). If the required reaction process data has been obtained, proceed to the next process. On the other hand, if the required reaction process data cannot be obtained, the absorbance measurement of the reaction solution is continued until the reaction process data are available.

Subsequently, the absorbance width is calculated based on the acquired reaction process data (S205). For example, the absorbance width can be calculated from the difference between the maximum value and the minimum value of the absorbance. After that, for example, from the reaction process data (absorbance) and measurement time of the photometric section specified by the photometric point shown in FIG. 5, the regression line “Y = aX + b” when “Y” is the absorbance and “X” is the measurement time. The slope "a" and the Y-intercept "b" of "" are calculated (S206).

Then, the allowable width is calculated from the slope of the calculated regression line and the Y-intercept (S207). As the permissible width, for example, since the “variation permissible value” (referred to as A) shown in FIG. 5 is set on both sides of the regression line, the permissible width is “Y = aX + b ± A”. In the present embodiment, an arbitrary value can be set in the "variation tolerance", but the "variation tolerance" is set based on the standard deviation in the reaction process data of the past sample and the quality control sample. You may.

After that, the number of data outside the allowable range specified by the calculated allowable width is calculated, and the calculated number of data is stored in the data storage unit 506 (S208).

Further, the square error (Err) between the reaction process data and the regression line is calculated and stored in the data storage unit 506 (S209). The square error is calculated by comparing the measured absorbance (reaction process data) with the calculated regression line. The square error is calculated to distinguish whether the fluctuation of the reaction process data is due to the sample itself or the fluctuation due to the malfunction of the automatic analyzer 100. For example, when the fluctuation of the reaction process data is caused by the turbidity component of the sample, the reaction process data tends to gradually increase or decrease at regular time intervals. On the other hand, when the fluctuation of the reaction process data is caused by a defect in the optical system of the automatic analyzer 100, the tendency of the fluctuation is not uniform and the variation is often large.

Next, it is determined whether or not the fluctuation of the reaction process data is an abnormal fluctuation (S210). For example, the calculated number of data “B” outside the permissible range, the calculated absorbance width “C”, and the calculated square error “Err” are set as, for example, the number of points “D” as shown in the table shown in FIG. And the Err tolerance value "E" is compared with the absorbance width "F" of the pretreatment reaction. For example, when "B> D", "Err> E", and "C> F", it is determined that the fluctuation of the reaction process data is an abnormal fluctuation. Here, the determination method can be set, for example, in the determination method column of FIG. For example, when "OR" is set, the fluctuation of the reaction process data is an abnormal fluctuation when the condition of "B> D", "Err> E", or "C> F" is satisfied. Is judged. On the other hand, for example, when "AND" is set, the fluctuation of the reaction process data is abnormal when the conditions of "B> D", "Err> E" and "C> F" are satisfied. Is judged to be.

If it is determined that the fluctuation of the reaction process data is not an abnormal fluctuation, the process is terminated. On the other hand, if it is determined that the fluctuation of the reaction process data is an abnormal fluctuation, the process proceeds to the next step.

Subsequently, it is determined whether or not the fluctuation of the reaction process data corresponds to the exception item (S211). This is in consideration of not determining that the fluctuation of the reaction process data is an abnormal fluctuation when the fluctuation of the reaction process data is "non-influenced fluctuation". That is, by registering in advance the case where the fluctuation of the reaction process data is "non-influenced fluctuation" in the exception item, it is possible to prevent the "non-influenced fluctuation" from being judged as an abnormal fluctuation.

For example, exception items are set as shown in the table shown in FIG. The exception item indicates, for example, a measurement item for removing impurities contained in a sample by a pretreatment reaction, and refers to an item in which a change in absorbance occurs during the pretreatment reaction. Fluctuations in reaction process data in the pretreatment reaction of each item are basically determined based on the parameters shown in FIG. However, in items such as "LDL-C", a change in absorbance occurs in order to remove a component other than the specific component of interest in the pretreatment reaction (see, for example, sample 300B in FIG. 3). In addition to this, items that cause a change in absorbance (“non-influenced fluctuation”) in the pretreatment reaction can be registered in advance as an exception condition. Such fluctuations in the reaction process data are fluctuations in the reaction process data peculiar to the item and are "non-impact fluctuations". Therefore, they can be added as exception items and distinguished from "impact fluctuations". ..

First, if the exception item is applicable, for example, the metering section set as shown in FIG. 6 is set (S212). Then, in the set photometric section, it is determined whether or not the change direction (change tendency) of the reaction process data coincides with the "change direction" set as shown in FIG. 6 (S213). If they match, it is determined whether or not the value is equal to or less than the set value by comparing the rate of change in absorbance set as shown in FIG. 6 with the slope “a” of the regression line (S214). If it is less than the set value, the fluctuation of the reaction process data is regarded as "non-influenced fluctuation" and excluded from the warning target. In this embodiment, only the direction of change is mentioned, but for example, the absorbance at the start of measurement in the pretreatment reaction or the absorbance corresponding to the concentration calculation point in the reaction process data in the pretreatment reaction can be used as a judgment material. can.

In other cases, it is displayed (S215) that the fluctuation of the reaction process data in the pretreatment reaction is an abnormal fluctuation (“effect fluctuation”), and the measurer is notified. This notification method is not limited to the display example as shown in FIG. 9, and can be warned by, for example, a method of adding an alarm indicating an abnormality to the reaction process data, a method of sounding a warning sound from the automatic analyzer 100, or the like. ..

Subsequently, for example, referring to the column of "measurement continuation" in FIG. 5, it is determined whether or not the measurement interruption setting is set (S216). If "stop" is set, the measurement is stopped (S217). On the other hand, when "continue" is set, the measurement is continued and the concentration of the specific component is calculated (S218). As described above, the analysis operation of the reaction process data is completed.

<Modification example of operation>
In the above-mentioned operation, an example was described in which the "non-influenced fluctuation" of the reaction process data is not judged to be an abnormal fluctuation of the reaction process data by setting the exception condition, but the reaction process is not set as the exception condition. Exception conditions can also be incorporated into the conditions for determining abnormal data fluctuations.
FIG. 13 is a flowchart illustrating a modified example of the operation.

In this modification, after performing the operation shown in the flowchart shown in FIG. 11, the change direction of the fluctuation of the reaction process data is specified (S301). For example, it is specified whether the fluctuation of the reaction process data is "monotonically decreasing", "monotonically increasing", "repeating increase or decrease", or the like. After that, in this modification, it is determined whether or not the reaction process data is abnormally changed (S302). In the judgment here, not only the judgment conditions used in the embodiment but also the conditions corresponding to the exception conditions regarding the change direction and the rate of change of the fluctuations of the reaction process data are taken into consideration, and the fluctuations of the reaction process data are abnormal fluctuations. It is judged whether or not there is. For example, the judgment regarding the change direction in S302 is made based on the change direction specified in S301, and the judgment regarding the change rate in S302 is whether the slope of the regression line calculated in S206 is equal to or less than the set value. It is done based on whether or not. As a result, even in this modification, the "non-influenced fluctuation" of the reaction process data can be prevented from being judged as an abnormal fluctuation of the reaction process data. Subsequent operations are the same as those of the embodiment shown in FIG. 12, and thus the description thereof will be omitted. As described above, the operation of this modification is performed.

<Estimation of the cause of fluctuations in reaction process data>
For example, fluctuations in reaction process data often fluctuate randomly when the cause is an optical system caused by an automated analyzer. On the other hand, the contaminants contained in the sample are abnormal reactions because they react with the reagent components, but they often undergo characteristic changes such as an increase / decrease in absorbance in a certain direction. Furthermore, when the fluctuation of the reaction process data is caused by the turbidity component of the sample, the reaction process data tends to gradually increase or decrease at regular time intervals. On the other hand, when the fluctuation of the reaction process data is caused by a defect in the optical system of the automatic analyzer, the tendency of the fluctuation is not uniform and the variation is often large.

As described above, the fluctuation of the reaction process data includes the fluctuation caused by the contaminants contained in the sample and the fluctuation caused by the mechanism of the automatic analyzer and the measurement conditions. Therefore, if it is possible to identify whether the fluctuation of the reaction process data is caused by the sample itself or the mechanism or measurement conditions of the automatic analyzer, the cause of the fluctuation of the reaction process data should be determined. Because it can be done, the subsequent response becomes easy.

Regarding this point, it is difficult to identify whether it is caused by the sample itself or by the mechanism and measurement conditions of the automatic analyzer in the analysis of one test unit.

Therefore, in the present embodiment, in addition to the analysis of one test unit (reaction process data unit for one sample), the reaction process data for a plurality of samples is accumulated, and the reaction process data for the accumulated plurality of samples is analyzed. By doing so, the cause of fluctuations in the reaction process data is estimated.
In the following, an automated analyzer that embodies this technical idea will be described.

In FIG. 4, the automatic analyzer 100 has a specific condition setting unit 600 and a fluctuation cause estimation unit 601. The specific condition setting unit 600 is configured to set specific conditions for identifying the cause of fluctuation of the reaction process data. For example, in the specific condition setting unit 600, the specific condition shown in FIG. 14 is set. In FIG. 14, for example, in "HDL", the square error (Err) is set to "50" as the "check value", and the "check rule" is set to "5 times in a row". This is because the reaction process data having a square error of "50" or more is detected 5 times or more in succession in the accumulated reaction process data for "HDL" (when the "check rule" is violated). It is judged that the fluctuation of the process data is caused by the mechanism of the automatic analyzer and the measurement conditions. This is because it is unlikely that the sample itself is the cause of the fluctuation, and it is highly probable that the mechanism of the automated analyzer and the measurement conditions are the cause of the fluctuation, because the reaction process data with large variations is measured five or more times in a row. Because it is possible. Further, in "LDL", the width (absorbance width) is set to "100", the "aggregation unit" is set to "1000 test", and the "check rule" is "aggregation" as the "check value". Unit: 1% is set. This is when the reaction process data having an absorbance width of "100" or more is measured at a high frequency of 1% or more of 1000 tests in the accumulated reaction process data for "LDL" (in the "check rule"). (In case of violation), it is judged that the fluctuation of the reaction process data is caused by the mechanism of the automatic analyzer and the measurement conditions. This is because it is unlikely that the sample itself is the cause of the fluctuation, and the mechanism of the automated analyzer and the measurement conditions are considered to be the cause of the fluctuation, because the reaction process data having a large absorbance range is measured frequently.

Then, the fluctuation cause estimation unit 601 is caused by the sample itself based on the specific condition (see FIG. 14) set by the specific condition setting unit 600, or is caused by the mechanism or the measurement condition of the automatic analyzer. It is configured to identify if it is.

The fluctuation cause estimation unit 601 estimates the fluctuation cause of the reaction process data according to, for example, the flowchart shown in FIG. FIG. 15 is a flowchart illustrating an operation of estimating the cause of fluctuation of the reaction process data. In FIG. 15, for example, by analyzing the reaction process data, the data of the item set in the “check value” shown in FIG. 14 is acquired and stored in the data storage unit 506 (S401).

Next, it is determined whether or not a predetermined number of data has been accumulated (S402). For example, in the case of "HDL" shown in FIG. 14, it is determined whether or not five or more "square errors" are accumulated. Further, in the case of "LDL" shown in FIG. 14, it is determined whether or not 1000 or more "widths (absorbance widths)" are accumulated.

Subsequently, when the accumulated data reaches a predetermined number or more, it is determined whether or not the "check rule" shown in FIG. 14 is violated (S403). If the "check rule" is violated, a warning is displayed by presuming that the fluctuation of the reaction process data is caused by the mechanism of the automatic analyzer and the measurement conditions (S404). FIG. 16 is a diagram showing an example of a warning display.

In this way, when fluctuations in the reaction process data in the pretreatment reaction occur continuously or frequently, the contamination of the sample is not the cause of the fluctuations, but the mechanism and measurement conditions of the automatic analyzer Since there is a high probability that it is the cause of the fluctuation, a warning can be displayed to encourage the inspection of the mechanism of the automatic analyzer and the review of the measurement conditions.

<Application example>
As one of the analysis methods of the reaction process data for embodying the technical idea in the present embodiment, the linear approximation method has been described as an example, but the analysis method of the reaction process data is not limited to this. For example, the analysis method shown below can also be mentioned.

This analysis method calculates the difference between the absorbance at the target photometric point and the absorbance at the photometric point immediately before it in the analysis target section of the reaction process data in the pretreatment reaction, and the reaction process in the pretreatment reaction. This is a method for analyzing data.

FIG. 17 is a graph showing an example of reaction process data of UA (uric acid). In this reaction process data, the time from "Measuring point 1" to "Measuring point 19" corresponds to the preprocessing reaction, and the range from "Measuring point 20" to "Measuring point 38" corresponds to this reaction. ..

In the graph for sample 700A, the reaction process data in the pretreatment reaction is almost flat. This indicates that the reaction process data in the pretreatment reaction has little fluctuation and is normal. On the other hand, in the graph for the sample 700B, the reaction process data in the pretreatment reaction is not flat and tends to increase. Since the reaction process data in the pretreatment reaction is usually flat, the reaction process data of the sample 700B showing an increasing tendency is abnormal. As mentioned above, this corresponds to "impact fluctuation".

FIG. 18 is a graph showing an example of reaction process data of CRE (creatinine). In the graph for the sample 800A, the reaction process data in the pretreatment reaction is almost flat. This indicates that the reaction process data in the pretreatment reaction has little fluctuation and is normal. On the other hand, in the sample 800B, there is a sudden increase in absorbance at the photometric points near 5 points. This variation in absorbance corresponds to "non-influenced variation" that does not affect the calculation of the concentration of CRE. However, such fluctuations may be caused by the optical system of the automatic analyzer itself, depending on whether or not the frequency is high.

Conditions for analyzing such reaction process data are set in the condition setting unit 501. For example, FIG. 19 is a table showing an example of initial conditions set by the condition setting unit 501. In FIG. 19, the conditions set for each “item” include “photometric point”, “variation allowable value”, “variation allowable absorbance difference”, “point number”, “determination method”, and “measurement continuation”. ..

The "measurement point" defines the measurement section used for analysis of reaction process data. For example, when "5-19" is described in "Measuring point". The reaction process data is analyzed using the reaction process data from the “measurement point 5” to the “measurement point 19”.

"Allowable fluctuation value" defines the allowable value of the amount of fluctuation in the section specified by "Measuring point". For example, when "± 200" is described, it means that the range of fluctuation allowed within the specified section is "± 200". When "15%" is described as "15%" in "Variation tolerance", it means that the range of variation allowed within the specified interval is "15%" of the absorbance width of the reaction process data to be analyzed. means.

Here, for example, when the "variation tolerance" is described as an absolute numerical value, the reaction process data in the pretreatment reaction is measured at the stage (early stage of measurement) without measuring the reaction process data in the main reaction. It is possible to determine the presence or absence of an abnormality.

On the other hand, when the "variation tolerance" is described as a percentage of the absorbance width of the reaction process data to be analyzed, the "variation tolerance" must be measured at the stage where the entire reaction process data including the pretreatment reaction and the main reaction is measured. It is effective when it is not possible to judge the presence or absence of an abnormality based on the "value", but it is difficult to express the "variable allowable value" as an absolute numerical value.

The "variable allowable absorbance difference" defines the allowable range of the difference in adjacent absorbances in the section specified by the "photometric point". For example, when "100" is described in "variation allowable absorbance difference", it means that the allowable value of the difference between adjacent absorbances in the section specified by the "photometric point" is "100". When "15%" is described in "Variation allowable absorbance difference", the allowable value of the difference in adjacent absorbances in the section specified by "Metering point" is the total absorbance change amount of the reaction process data to be analyzed. It means "15%". In this case as well, when the conditions are expressed in absolute numerical values, as in the case of the "variable tolerance", the stage (measurement) in which the reaction process data in the pretreatment reaction is measured without measuring the reaction process data in this reaction. It is possible to judge the presence or absence of abnormalities at an early stage). On the other hand, expressing the condition as a percentage is effective when it is difficult to express the "variation allowable absorbance difference" as an absolute numerical value.

The "number of points" defines the number of data that are outside the range of the "variability allowable absorbance difference" in the difference in the absorbances adjacent to each other in the section specified by the "photometric point". For example, when the "number of points" is described as "2", the number of data in which the difference between adjacent absorbances in the section specified by the "photometric point" is outside the range of the "variability allowable absorbance difference" is "2". If it is as follows, it means that it is within the allowable range. In other words, if the difference between adjacent absorbances in the section defined by the "photometric point" is greater than the number of data outside the range of the "variation allowable absorbance difference", it means that the difference is out of the allowable range.

The "judgment method" defines whether to judge multiple conditions related to analysis by "AND condition" or to use them as "OR condition".

"Continue measurement" defines whether to continue the measurement or interrupt the measurement when there is an abnormal change in the reaction process data.

Next, in this analysis method as well as the reaction process data analysis method using the approximation function, the automatic analyzer 100 detects "impact variation" as anomalous variation, while "non-influence variation" is anomalous variation. In order not to detect it, the condition setting unit 501 uses not only the condition shown in FIG. 19 but also the exception condition as shown in FIG. 20.

FIG. 20 is a table showing an example of exception conditions. In FIG. 20, a component to be measured for concentration is set in the “item”. For example, when "AST" is set in the "item", an exception condition is defined so that the reaction process data of "AST" is not regarded as an abnormal fluctuation. This exception condition includes "light measurement point", "change direction", and "variation tolerance".

The "measurement point" defines the measurement section of the reaction process data. For example, when "5-19" is described in "Measuring point", it means that the reaction process data from "Measuring point 5" to "Measuring point 19" is within the scope of the exception condition.

The "direction of change" defines the direction of change in the reaction process data, which is an exception condition. For example, it means that the exception condition is applied when the "change direction" is "continuous decrease".

The "variation tolerance" defines the tolerance of reaction process data, which is an exception condition. For example, when the "variable allowable value" is described as "-400", it means that the exception condition is applied if it is "-400" or more.

In the "Comment" column, the factors that cause fluctuations in the reaction process data can be simply described. When "weak chyle effect" is described in the "comment" column, it can be understood that "weak chyle" causes fluctuations in the reaction process data corresponding to the exception conditions.

The conditions related to the absorbance analysis (FIGS. 19 and 20) set in the condition setting unit 501 are stored in the data storage unit 506. Then, the abnormal fluctuation determination unit 502 performs the determination process shown below based on the conditions related to the absorbance analysis set by the condition setting unit 501.

The abnormal fluctuation determination unit 502 performs arithmetic processing at the "light measurement point" set by the condition setting unit 501. Specifically, when "mn" is specified, the absorbance "A (x)" at the photometric point "x" and the absorbance "A (x-1)" at the photometric point "x-1" immediately before it. The difference {A (x) -A (x-1)} is repeated from the photometric point "x = m" to the photometric point "x = n". The anomalous fluctuation determination unit 502 calculates {A (x) -A (x-1)} from the metering point "x = m" to the metering point "x = n", and then totals the calculated results. Judge whether or not it is within the range of "variable tolerance".

A specific example is shown below.
FIG. 21 shows the absorbance “A (x)” and the absorbance “A (x—” immediately before the photometry point “A (x)” in the section from the photometric point “1” to the photometric point “19”, which is the preprocessing reaction of the reaction process data shown in FIG. It is a graph which calculated the difference {A (x)-A (x-1)} from "1)" and plotted it in chronological order.

As shown in FIG. 17, in the case of the sample 700A, since there is almost no change in the absorbance in the pretreatment reaction, the absorbance "A (x)" in the sample 700A shown in FIG. 21 and the absorbance "A (x-1) immediately before that" are shown in FIG. ) ”And the difference {(A (x) -A (x-1)) changes with data close to“ 0 ”. On the other hand, in the case of the sample 700B, since it is the reaction process data in which the absorbance gradually increases with the passage of time in the pretreatment reaction, the graph of the sample 700B shown in FIG. 21 is always a value of “0” or more. Is taken. From this, in the case of reaction process data such as sample 700B, the total value of {A (x) -A (x-1)} from the photometric point "x = m" to the photometric point "x = n" is growing. When the direction of fluctuation was the decreasing direction, the calculated values of {A (x) -A (x-1)} from the metering point "x = m" to the metering point "x = n" were totaled. The value becomes smaller. The abnormality determination unit 502 includes the "variation tolerance" set by the condition setting unit 501 and {A (x) -A (x-1)} from the photometric point "x = m" to the photometric point "x = n". Is compared with the total value of, and it is evaluated whether or not the fluctuation of the reaction process data in the pretreatment reaction is large.

Next, the abnormality determination unit 502 determines that the absolute value of each value obtained by calculating {A (x) -A (x-1)} from the measurement point "x = m" to the measurement point "x = n" is a condition. It is determined whether or not it is equal to or less than the "variation allowable absorbance difference" set by the setting unit 501. At this time, the absolute value of each value calculated from the photometric point “x = m” to the photometric point “x = n” {(A (x) −A (x-1)) is the “variation allowable absorbance difference”. It is confirmed whether or not the number of exceeded data exceeds the "number of points" set by the condition setting unit 501.

FIG. 22 shows the absorbance “A (x)” and the absorbance A (x-1) immediately before the photometric point “A (x)” in the section from the photometric point “1” to the photometric point “19”, which is the preprocessing reaction of the reaction process data shown in FIG. It is a graph which calculated the difference {A (x)-A (x-1)} of, and plotted it in chronological order.

In the case of the sample 800A shown in FIG. 18, since there is almost no change in the absorbance in the pretreatment reaction, the difference between the absorbance A (x) in the sample 800A shown in FIG. 22 and the absorbance A (x-1) immediately before it {A ( x) -A (x-1)} changes with data close to "0". On the other hand, in the case of the sample 800B shown in FIG. 18, since there is a variation of several points in the pretreatment reaction section, the difference between the absorbance A (x) and the absorbance A (x-1) immediately before it {A (x)-. A (x-1)) is not stable near "0" and varies widely.

However, in the sample 800B, the difference between the absorbance A (x) and the absorbance A (x-1) immediately before it {A (x) -A (x-1)) fluctuates between the plus side and the minus side. The sum of the difference {A (x) -A (x-1)} between the absorbance A (x) from the photometric point "x = m" to the photometric point "x = n" and the absorbance A (x-1) immediately before it. The value is smaller than that of the sample 700B. Therefore, even in this analysis method, it is possible to distinguish between continuous increase and decrease of absorbance and variation in absorbance.

The broken line shown in FIG. 22 is drawn by "± 30" set in the "variation allowable absorbance difference" of the CRE set in the condition setting unit 501. Since all the data of the sample 800A is inside the broken line, it is judged that there is no abnormality. On the other hand, in the sample 800B, the data of four points exceeds the broken line at the "light measurement point" designated by the condition setting unit 501. Therefore, the sample 800B is determined to be abnormal because it is larger than "2", which is the "number of points" of the CRE set by the condition setting unit 501.

Here, when the fluctuation of the reaction process data corresponds to the exception condition (see FIG. 20) set by the condition setting unit 501, the abnormality fluctuation determination unit 502 indicates that the fluctuation of the reaction process data is abnormal regardless of the above-mentioned result. Judge that it is not fluctuating.

For example, as shown in FIG. 19, it is determined whether or not the reaction process data in the pretreatment reaction is abnormal according to the "determination method" set by the condition setting unit 501. When the "judgment method" is set by the "AND condition", the abnormality fluctuation determination unit 502 performs {A (x) -A (x-1) from the photometric point "x = m" to the photometric point "x = n". )} After the calculation, the total value of the results of this calculation exceeds the "variable allowable value", and the number of data exceeding the "variable allowable absorbance difference" exceeds the "point number". Judge as abnormal.

On the other hand, when the "OR condition" is set, the abnormality fluctuation determination unit 502 determines that an abnormality occurs when any of the above two conditions exceeds the value set by the condition setting unit 501.

After making such a determination, the abnormality determination unit 502 determines whether or not the exception condition set by the condition setting unit 501 is satisfied, and if the exception condition is applicable, the abnormality determination unit 502 preprocesses. It is judged that the fluctuation of the reaction process data in the reaction is not an abnormal fluctuation.
Other features and operations are the same as the analysis method using the approximation function.

FIG. 23 is a flowchart illustrating a flow for detecting abnormal fluctuations in reaction process data by the above-mentioned analysis method. In this application example, a method of analysis is shown by using the difference in absorbance continuously measured by the reaction process data.

First, the absorbance of the reaction solution, which is a mixture of the sample and the first reagent, is measured with a photometer (S501). As a result, reaction process data in the pretreatment reaction is acquired (S502). The acquired reaction process data is stored in the data storage unit 506 of the automatic analyzer 100 (S503). Here, for example, the data storage unit 506 is premised on the configuration included in the automatic analyzer 100, but the data storage unit 506 is not limited to this, and the data storage unit 506 may be a server or the like connected to the automatic analyzer 100 via a network. It may be installed.

Next, the automatic analyzer 100 determines whether the reaction process data of the measurement point (photometric section) necessary for the analysis of the reaction process data in the pretreatment reaction could be acquired (S504). Subsequently, the automated analyzer 100 has the absorbance from the photometric point “x = m” to the photometric point “x = n” in the section (“mn”) of the “photometric point” designated by the condition setting unit 501. Calculate the absorbance difference {A (x) -A (x-1)} with (S505). Then, the automatic analyzer 100 calculates the total of the calculated absorbance differences {A (x) −A (x-1)} (S506).

Next, the automatic analyzer 100 calculates an allowable value. For example, as shown in FIG. 19, when the “variation allowable value” and the “variation allowable absorbance difference” are set as percentages in the condition setting unit 501, the allowable value is set based on the absorbance width of the reaction process data to be analyzed. Calculate (S507). Then, the allowable value and the calculated absolute value of the absorbance difference {A (x) −A (x-1)} are compared to calculate the number of data out of the allowable range (S508). In this application example, any numerical value can be input, but the "variation tolerance" and "variation tolerance difference" are based on the statistical analysis of the reaction process data of past samples and quality control samples. May be set.

Judgment as to whether or not the reaction process data is abnormal fluctuation is performed, for example, in "S210" in FIG. 12 and "S302" in FIG. In this application example, the abnormality determination unit 502 is performed according to the "variation allowable value", "point number", and "determination condition" set in the condition setting unit 501. For example, the total “G” of the calculated absorbance difference {A (x) −A (x-1)} and the number of data “H” outside the permissible range are set as the fluctuation permissible value “I” set by the condition setting unit 501. , Compare with the number of points "K". When "G> I" and "H> K", the reaction process data is determined to be anomalous variation. Here, when "OR" is set in the "determination method", it is determined that the reaction process data is an abnormal fluctuation when "G> I" or "H> K".

For the subsequent determination processing, it is possible to estimate the cause of fluctuation of the reaction process data by performing the same processing as the analysis method (FIGS. 12 to 16) using the approximate straight line.

Although the invention made by the present inventor has been specifically described above based on the embodiment thereof, the present invention is not limited to the embodiment and can be variously modified without departing from the gist thereof. Needless to say.

1 Analytical unit 2 Specimen container 3 Specimen rack 4 Conveyance line 5 Specimen probe 6 Reagent probe 7 Reagent container 8 Reagent disk 9 Reaction container 10 Reaction disk 11 Stirring unit 12 Luminometer 13 Cleaning unit 14 Storage unit 15 Display unit 16 Operation unit 17 Control Unit 100 Automatic analyzer 200A Specimen 200B Specimen 300A Specimen 300B Specimen 500 Reaction process data acquisition unit 501 Condition setting unit 502 Abnormal change judgment unit 503 Parameter determination unit 504 Output unit 505 Measurement interruption unit 506 Data storage unit 600 Specific condition setting unit 601 Fluctuation Cause estimation unit 700A sample 700B sample 800A sample 800B sample

Claims

An automatic analyzer configured to measure the concentration of a specific component contained in the sample based on the absorbance of the sample and the reagent with respect to the reaction solution.
The reaction between the sample and the reagent is
A pretreatment reaction in which the sample and the first reagent are reacted, and
This reaction in which the sample is reacted with a reagent other than the first reagent,
Including
The automatic analyzer is
A reaction process data acquisition unit configured to acquire reaction process data by measuring the absorbance in time series in the pretreatment reaction, and a reaction process data acquisition unit.
A condition setting unit configured to set conditions related to absorbance,
Whether or not the fluctuation of the reaction process data acquired in the pretreatment reaction affects the measurement of the concentration of the specific component in the main reaction based on the condition set by the condition setting unit. Anomalous fluctuation judgment unit configured to judge
An output unit configured to output the determination result determined by the abnormal fluctuation determination unit, and an output unit.
An automated analyzer equipped with.
In the automatic analyzer according to claim 1,
The above-mentioned condition regarding the absorbance is an automatic analyzer including an absorbance width indicating a range of absorbance.
In the automatic analyzer according to claim 1,
The abnormal fluctuation determination unit is an automatic analyzer having a parameter determination unit configured to determine parameters included in the approximation function by fitting the reaction process data with an approximation function.
In the automatic analyzer according to claim 3,
The condition setting unit is configured to set an allowable range indicating an allowable deviation range from the approximate function.
The abnormal fluctuation determination unit is an automatic analyzer configured to determine whether or not the fluctuation of the reaction process data acquired in the pretreatment reaction is an abnormal fluctuation based on the permissible range.
In the automatic analyzer according to claim 3,
The condition setting unit is configured to set an allowable range of the square error between the approximation function and the reaction process data.
The abnormal fluctuation determination unit is an automatic analyzer configured to determine whether or not the fluctuation of the reaction process data acquired in the pretreatment reaction is an abnormal fluctuation based on the permissible range.
In the automatic analyzer according to claim 1,
The condition regarding the absorbance set by the condition setting unit is that the fluctuation of the reaction process data acquired in the pretreatment reaction does not affect the measurement of the concentration of the specific component in the main reaction. Exceptional conditions are also included,
The abnormality fluctuation determination unit is configured to determine that the fluctuation of the reaction process data is not an abnormal fluctuation when the fluctuation of the reaction process data acquired in the pretreatment reaction corresponds to the exception condition. Automatic analyzer.
In the automatic analyzer according to claim 1,
When the abnormal fluctuation determination unit determines that the fluctuation of the reaction process data is a fluctuation that affects the measurement of the concentration of the specific component in the main reaction, the automatic analyzer contains the specific component contained in the sample. An automated analyzer with a measurement interruption that is configured to interrupt the measurement of the concentration of.
In the automatic analyzer according to claim 1,
The pretreatment reaction is a reaction for removing a component other than the specific component and an interfering component that affects the measurement of the absorbance in the main reaction.
The main reaction is an automatic analyzer, which is a reaction for measuring the concentration of the specific component.
In the automatic analyzer according to claim 1,
The automatic analyzer is an automatic analyzer configured to measure the concentration of the specific component based on the difference between the absorbance in the main reaction and the absorbance in the pretreatment reaction.
In the automatic analyzer according to claim 1,
The automatic analyzer is
A data storage unit that stores the reaction process data for each of the plurality of samples,
A specific condition setting unit configured to set a specific condition for identifying a plurality of fluctuation causes of the reaction process data stored in the data storage unit, and a specific condition setting unit.
A fluctuation cause estimation unit configured to estimate a fluctuation cause of the reaction process data based on the specific condition set by the specific condition setting unit, and a fluctuation cause estimation unit.
Have,
The output unit is an automatic analyzer configured to output the fluctuation cause estimated by the fluctuation cause estimation unit.
In the automatic analyzer according to claim 10,
The specific condition is a condition for specifying whether the fluctuation of the reaction process data is a fluctuation caused by the sample or a fluctuation caused by the automatic analyzer.
In the automatic analyzer according to claim 1,
The abnormal fluctuation determination unit is the above-mentioned acquired by the pretreatment reaction based on the absorbance difference between the absorbance of the first measurement point and the absorbance of the second measurement point adjacent to each other included in the absorbance measured in time series. An automatic analyzer configured to determine whether or not fluctuations in reaction process data affect the measurement of the concentration of the specific component in the reaction.
In the automatic analyzer according to claim 12,
The abnormal fluctuation determination unit is an automatic analyzer capable of determining a continuous decrease or increase of the reaction process data.
In the automatic analyzer according to claim 12,
The abnormal fluctuation determination unit is an automatic analyzer capable of determining whether or not the fluctuation of the reaction process data is within the permissible range based on the absolute value of the absorbance difference.
It is an automatic analysis method that measures the concentration of a specific component contained in the sample based on the absorbance of the sample and the reagent with respect to the reaction solution.
The reaction between the sample and the reagent is
A pretreatment reaction in which the sample and the first reagent are reacted, and
This reaction in which the sample is reacted with a reagent other than the first reagent,
Including
The automatic analysis method is
A reaction process data acquisition step of acquiring reaction process data by measuring the absorbance in time series in the pretreatment reaction, and a reaction process data acquisition step.
Condition setting process for setting conditions related to absorbance, and
Whether or not the fluctuation of the reaction process data acquired in the pretreatment reaction affects the measurement of the concentration of the specific component in the main reaction based on the conditions set in the condition setting step. Abnormal fluctuation judgment process to judge
An output process that outputs the judgment result determined in the abnormal fluctuation determination process, and
An automated analysis method.