WO2022004730A1 - 体液分析装置、体液検体を判定するための方法、および、コンピュータープログラム - Google Patents

体液分析装置、体液検体を判定するための方法、および、コンピュータープログラム Download PDF

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WO2022004730A1
WO2022004730A1 PCT/JP2021/024579 JP2021024579W WO2022004730A1 WO 2022004730 A1 WO2022004730 A1 WO 2022004730A1 JP 2021024579 W JP2021024579 W JP 2021024579W WO 2022004730 A1 WO2022004730 A1 WO 2022004730A1
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Prior art keywords
body fluid
parameters
value
subject
crp
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English (en)
French (fr)
Japanese (ja)
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憲祐 齊藤
和憲 吉岡
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Horiba Ltd
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Horiba Ltd
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Priority to EP21832401.0A priority patent/EP4152000A4/en
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/569—Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
    • G01N33/56966—Animal cells
    • G01N33/56972—White blood cells
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/569—Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
    • G01N33/56911—Bacteria
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/569—Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
    • G01N33/56983—Viruses
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/63—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/46—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans from vertebrates
    • G01N2333/47—Assays involving proteins of known structure or function as defined in the subgroups
    • G01N2333/4701—Details
    • G01N2333/4737—C-reactive protein
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/26—Infectious diseases, e.g. generalised sepsis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/483—Physical analysis of biological material
    • G01N33/487—Physical analysis of biological material of liquid biological material
    • G01N33/49—Blood

Definitions

  • the present invention assists physicians in differentiating whether a patient has a viral or bacterial infection or the severity of a viral infection (eg, COVID-19) patient.
  • the present invention relates to a body fluid analyzer that provides information that assists a doctor in fully fulfilling the obligation to explain a medical condition to a patient or a guardian of the patient.
  • the body fluid sample collected from the subject is obtained from a subject having a viral infection, is obtained from a subject having a bacterial infection, or is collected from a patient having a viral infection.
  • the present invention relates to a method for determining whether a body fluid sample obtained is obtained from a severely ill patient or a mildly ill patient, and a computer program for the determination.
  • one of the purposes of prescribing a drug in consideration of the result of differentiation is to determine whether or not an antibiotic (including an antibacterial drug) should be administered. This is because the administration of antibiotics is not only ineffective in treating viral infections, but can also cause new problems such as reduction of indigenous bacteria and development of resistant bacteria.
  • WBC blood test values
  • C-reactive protein hereinafter, may be referred to as "CRP”
  • WBC number of leukocytes
  • CRP C-reactive protein
  • Non-Patent Document 1 the relationship between the measured values (test values) of individual blood test items such as white blood cell count and CRP value and viral infections and bacterial infections is individually (for each item). ) Is shown. Therefore, even if a doctor tries to distinguish from the blood test results of a patient based on such findings, for example, (the leukocyte count belongs to the area of viral infection and the CRP value also belongs to the area of viral infection). Since it belongs to, it is differentiated from viral infections), and by logically considering the test values of each test item, it will be linked to the final discrimination.
  • the subject of the present invention solves the above-mentioned problems, and a doctor or the like distinguishes whether a patient has a viral infection or a bacterial infection, or whether a patient with a viral infection is severely ill. It is an object of the present invention to provide a body fluid analyzer capable of giving useful judgment information, a method capable of giving the judgment information, and a computer program capable of giving the judgment information.
  • the body fluid analyzer, the method, and the computer program are used by a doctor to make a definitive diagnosis of whether a patient has a viral infection or a bacterial infection, or by a health center or the like for a patient with a viral infection. It is suitable for assisting in determining the necessity of hospitalization (assistance) and for obtaining more understandable information for the patient (or the patient's guardian) in fulfilling the doctor's accountability.
  • a body fluid analyzer wherein the body fluid analyzer is It has a parameter receiving unit that accepts multiple parameters for use in determining whether a subject has a viral or bacterial infection.
  • the plurality of parameters include the CRP value of the body fluid sample collected from the subject, and include the test value for one or more body fluid test items selected from the body fluid test items other than the CRP value.
  • It has an infectious disease determination unit, and the infectious disease determination unit uses the following relational expression (I) stored in advance, and the subject is either a viral infection or a bacterial infection based on the plurality of parameters. It is configured to calculate the determination information of whether or not you have an infectious disease.
  • the relational expression (I) is expressed from a plurality of data contributors known to have a viral infection and from a plurality of data contributors known to have a bacterial infection, respectively.
  • the explanatory variables are the multiple types of parameters of the same type as the above-mentioned multiple types of parameters
  • the objective variable is the determination information as to whether the plurality of data providers were suffering from a viral infection or a bacterial infection, respectively.
  • the body fluid analyzer [1a] A body fluid analyzer, wherein the body fluid analyzer is It has a parameter receiving unit that accepts multiple types of parameters for use in determining whether a patient with a viral infection is severely ill.
  • the plurality of parameters include the CRP value of the body fluid sample collected from the subject, and include the test value for one or more body fluid test items selected from the body fluid test items other than the CRP value. It has an infectious disease determination unit, and the infectious disease determination unit uses the following relational expression (I) stored in advance and determines whether or not the virus-infected patient is seriously ill based on the plurality of parameters. It is configured to calculate the judgment information of The relational expression (I) is from a plurality of data contributors known to be suffering from a severe viral infection and from a plurality of data providers known to be suffering from the non-severe viral infection.
  • the body fluid analyzer is one or more analyzes selected from discriminant analysis, logistic regression analysis, multiple regression analysis, Cox hazard regression analysis, principal component analysis, factor analysis, dispersion analysis, and cluster analysis.
  • the body fluid analyzer according to the above [1].
  • the multivariate analysis is one or more analyzes selected from discriminant analysis, logistic regression analysis, multiple regression analysis, Cox hazard regression analysis, principal component analysis, factor analysis, dispersion analysis, and cluster analysis.
  • the body fluid analyzer according to the above [1a].
  • the test value of the body fluid sample for one or more body fluid test items selected from the body fluid test items other than the above CRP value includes the white blood cell count.
  • the body fluid analyzer is A white blood cell measurement chamber and a white blood cell count calculation unit for measuring the white blood cell count of a body fluid sample collected from the above subject, and a white blood cell count calculation unit, and It further has a CRP measurement chamber for measuring the CRP value of the body fluid sample and a CRP value calculation unit.
  • the body fluid analyzer according to the above [1] or [2].
  • the test value of the body fluid sample for one or more body fluid test items selected from the body fluid test items other than the above CRP value includes the white blood cell count.
  • the body fluid analyzer is A white blood cell measurement chamber and a white blood cell count calculation unit for measuring the white blood cell count of a body fluid sample collected from the above subject, and a white blood cell count calculation unit, and It further has a CRP measurement chamber for measuring the CRP value of the body fluid sample and a CRP value calculation unit.
  • a plurality of parameters for determining whether the subject has a viral infection or a bacterial infection includes a neutrophil count.
  • the infectious disease determination unit uses the relational expression (I) and is based on at least the white blood cell count and the CRP value contained in the test value, and / or at least based on the neutrophil count and the CRP value. It is configured to calculate determination information indicating that the subject may have either a viral or bacterial infection.
  • the body fluid analyzer according to any one of the above [1] to [3]. [4a] A plurality of parameters for use in determining whether or not the virus-infected patient is severely ill include a platelet count.
  • the infectious disease determination unit uses the relational expression (I), and based on at least the platelet count and CRP value contained in the test value, and / or at least based on the platelet count, white blood cell count, and CRP value.
  • the body fluid analyzer according to any one of the above [1a] to [3a].
  • the body fluid analyzer according to any one of [1a] to [4a] further comprising a chamber for measuring the platelet count of a body fluid sample collected from the virus-infected patient and a platelet count calculation unit.
  • [6a] The body fluid analyzer according to any one of [1a] to [5a] above, wherein the body fluid is blood.
  • the plurality of types of parameters (A) include the CRP value of the body fluid sample, and include the test values for one or more body fluid test items selected from the body fluid test items other than the CRP value.
  • the relational expression (I) is The plurality of species obtained from multiple data contributors known to have a viral infection and from multiple data contributors known to have a bacterial infection, respectively.
  • the explanatory variables are multiple types of parameters of the same type as the parameters of. Using the determination information as to whether the plurality of data providers were suffering from a viral infection or a bacterial infection, respectively, as the objective variable. An equation showing the relationship between the explanatory variables and the objective variables obtained by multivariate analysis. The method.
  • the method is The first step of preparing multiple types of parameters in (A) below, Using the plurality of parameters and the following relational expression (I), the body fluid sample is obtained from a subject suffering from a severe viral infection or suffers from the non-severe viral infection.
  • the plurality of types of parameters (A) include the CRP value of the body fluid sample, and include the test values for one or more body fluid test items selected from the body fluid test items other than the CRP value.
  • the relational expression (I) is Obtained from multiple data contributors known to have a severe viral infection and from multiple data contributors known to have the non-severe viral infection.
  • multiple types of parameters of the same type as the above-mentioned multiple types of parameters are used as explanatory variables.
  • An equation showing the relationship between the explanatory variables and the objective variables obtained by multivariate analysis. The method.
  • the test value of the body fluid sample for one or more body fluid test items selected from the body fluid test items other than the CRP value in the plurality of parameters of the above (A) includes the white blood cell count, the above [7].
  • the method described in. [8a] The test values of the body fluid sample for one or more body fluid test items selected from the body fluid test items other than the CRP value in the plurality of parameters of the above (A) include the white blood cell count and / or the platelet count. , The method according to the above [7a].
  • [10] Computer As a parameter acceptance means for accepting a plurality of the following parameters (A) for use in determining whether a subject has a viral or bacterial infection, and As an infectious disease determination means for calculating determination information as to whether the subject is suffering from a viral infection or a bacterial infection based on the plurality of parameters using the following relational expression (I).
  • the plurality of types of parameters (A) include the CRP value of the body fluid sample derived from the subject, and include the test values for one or more body fluid test items selected from the body fluid test items other than the CRP value.
  • the relational expression (I) is The plurality of species obtained from multiple data contributors known to have a viral infection and from multiple data contributors known to have a bacterial infection, respectively.
  • the explanatory variables are multiple types of parameters of the same type as the parameters of. Using the determination information as to whether the plurality of data providers were suffering from a viral infection or a bacterial infection, respectively, as the objective variable. An equation showing the relationship between the explanatory variables and the objective variables obtained by multivariate analysis. The computer program.
  • [10a] Computer As a parameter acceptance means for accepting the following multiple types of parameters (A) for use in determining whether a patient with a viral infection is seriously ill, and As an infectious disease determination means for calculating determination information as to whether or not the virus infectious disease patient is severe based on the plurality of parameters using the following relational expression (I).
  • the plurality of types of parameters (A) include the CRP value of the body fluid sample derived from the virus-infected patient, and include the test values for one or more body fluid test items selected from the body fluid test items other than the CRP value.
  • the relational expression (I) is Obtained from multiple data contributors known to have a severe viral infection and from multiple data contributors known to have the non-severe viral infection.
  • multiple types of parameters of the same type as the above-mentioned multiple types of parameters are used as explanatory variables.
  • An equation showing the relationship between the explanatory variables and the objective variables obtained by multivariate analysis. The computer program.
  • the test value of the body fluid sample for one or more body fluid test items selected from the body fluid test items other than the CRP value in the plurality of parameters of the above (A) includes the white blood cell count.
  • the computer program described in. [11a] The test values of the body fluid sample for one or more body fluid test items selected from the body fluid test items other than the CRP value in the plurality of parameters of the above (A) include the white blood cell count and / or the platelet count. , The computer program according to the above [8a].
  • [12] The method according to [10] or [11] above, wherein the body fluid is blood.
  • Non-Patent Document 1 the relationship between individual items of blood tests such as white blood cell count and CRP value, and the relationship with viral infections and bacterial infections is individually clarified. That is, in Non-Patent Document 1, the test values of individual items of blood tests, such as the relationship between viral infections and leukocyte counts and the relationship between bacterial infections and leukocyte counts, are considered to be simple regression analysis. Based on the above, it has been linked to a viral or bacterial infection, and the fluctuations in the leukocyte count and CRP value are only shown separately.
  • test values of a plurality of items such as leukocyte count / neutrophil count and CRP value are associated with each other by using them as explanatory variables for multivariate analysis, and are viral infections or bacterial. It is linked to the judgment of infectious disease (objective variable). As a result, it is more likely that a correct discrimination result will be obtained than in the case where each test value is independently linked for discrimination.
  • the area under the ROC curve (hereinafter, may be abbreviated as "AUC") analyzed by the multivariate in the examples described later is a numerical value extremely close to 1, and the plurality of types adopted in the present invention. It is understood that the parameters provide highly accurate discrimination results.
  • the method and calculation formula of the multivariate analysis used in the present invention are virus infection (RSV subtype A & B, Parainfluenza virus 1 & 2, Parainfluenza virus 1 & 2, Parainfluenza virus) using the results of real-time PCR.
  • virus infection RSV subtype A & B, Parainfluenza virus 1 & 2, Parainfluenza virus 1 & 2, Parainfluenza virus
  • bacterial infections S. pneumoniae, H. influenzae, M. pneumoniae, C. pneumoniae, S. pyogenes, and L.
  • the doctor can refer to the judgment information shown by the body fluid analyzer and distinguish whether it is a viral infection or a bacterial infection with higher credibility, and as a result, an antibiotic. It is possible to reduce the erroneous administration of the virus, reduce the number of indigenous bacteria, and suppress the outbreak of resistant bacteria. Furthermore, as will be understood from the results of AUC in the examples described later, the differential information obtained from the apparatus of the present invention is extremely reliable, and the display format of the information is also a viral infection.
  • the doctor fulfills the above-mentioned obligation to explain to patients and the like to patients (or their guardians) of a wide range of ages more easily and smoothly than before. This can lead to the satisfaction of patients and the like with respect to the medical care provided by doctors.
  • WBC leukocytes
  • test values of a plurality of items such as white blood cell count / lymphocyte count, platelet count, and CRP value are associated with each other by using them as explanatory variables for multivariate analysis, including COVID-19. It is linked to the determination of the severity (objective variable) of patients with viral infections. As a result, it is more likely that a correct discrimination result will be obtained than in the case where each test value is independently linked to discrimination, and it is possible to objectively determine the necessity of treatment intervention.
  • FIG. 1 is a block diagram showing an example of a preferable configuration of the blood analyzer of the present invention.
  • FIG. 2 is a flowchart illustrating an outline of the operation of the blood analyzer illustrated in FIG. The flowchart is also a flowchart for explaining the method of the present invention and the configuration of the computer program of the present invention.
  • FIG. 3 shows the results of discriminating bacterial or viral infections of subjects using two types of multiple logistic regression relational expressions created using a combination of two parameters (age + WBC + CRP and age + neutrophils + CRP) as explanatory variables. It is a figure comparing.
  • the graph on the left shows cases with a definite diagnosis of bacterial infection by PCR, and the graph on the right shows cases with a definite diagnosis of viral infection by PCR.
  • the numerical value of each axis is determined to be 0 or more and less than 0.5: virus infection, more than 0.5 and 1 or less: bacterial infection.
  • the body fluid analyzer of the present invention may be an analyzer (data processing apparatus) having only a parameter receiving unit and an infectious disease determination unit, but one embodiment is shown in FIG. As shown, it is further preferable to have a configuration (mechanism and data processing function) for receiving a container containing a body fluid sample and performing analysis of total blood count and analysis of CRP value.
  • the body fluid sample that can be used in the apparatus is not particularly limited as long as it is a body fluid derived from a subject, and examples thereof include blood, ascites, pleural effusion, and cerebrospinal fluid. Blood is preferred.
  • the body fluid analyzer may be expressed as a blood analyzer, the body fluid measurement mechanism as a blood measurement mechanism, the body fluid test item as a blood test item, the body fluid sample as a blood sample, etc., but the present invention is limited to blood. However, it is clear that it includes an embodiment in which another body fluid is used as a sample.
  • the device will be described in detail with reference to the configuration of the blood analyzer shown in FIG. Further, the description of each configuration included in the apparatus is also a description of each configuration included in the method of the present invention and the computer program of the present invention.
  • the device has at least a parameter receiving unit 600 and an infectious disease determination unit 700.
  • the parameter receiving unit 600 is used to determine whether (a) the subject has a viral or bacterial infection, or (b) the subject suffering from a viral infection is severe. This is the part that accepts multiple types of parameters related to the subject.
  • the plurality of parameters essentially include the CRP value of the body fluid sample collected from the subject, and the test of the body fluid sample for one or more body fluid test items selected from the body fluid test items other than the CRP value. Includes a value.
  • multivariate analysis is used to determine morbidity or severity, and the number of variables (parameters) to be multivariate analyzed is multiple (ie, at least two).
  • Representative examples of the plurality of parameters include, but are not limited to, CRP values and white blood cell counts. Details of the plurality of parameters will be described later.
  • the infectious disease determination unit 700 uses the relational expression (I) described later obtained and stored in advance by multivariate analysis, and based on the plurality of parameters, (a) the subject is a viral or bacterial infectious disease. It is a part configured to calculate the determination information regarding the discrimination of whether or not the subject suffering from any of the above or (b) the subject suffering from a viral infection is severe.
  • the device is based on the patient's blood sample, whether the patient has (a) a viral or bacterial infection, or (b) a severe viral infection. It becomes possible to provide more credible judgment information as to whether or not a person suffers from an infectious disease.
  • the plurality of parameters used in the present invention are a plurality of explanatory variables required for multivariate analysis.
  • the essential parameter is the CRP value
  • the other parameters are the test values for one or more blood test items selected from the blood test items other than the CRP value.
  • the test values for the one or more blood test items include white blood cell count, lymphocyte count, granulocyte count, neutrophil count, (neutrophil / lymphocyte ratio), (granulocyte count / lymphocyte ratio), and the like.
  • the number of platelets and the like can be mentioned.
  • white blood cell count is mentioned as a test value that can be combined with the CRP value to provide more accurate differentiation.
  • Preferred combinations include number, CRP value and white blood cell count and granulocyte count, and CRP value and white blood cell count and neutrophil count and granulocyte count.
  • the number, lymphocyte count, and platelet count are also preferred combinations.
  • additional parameters can be used as explanatory variables in order to further enhance the credibility of the discrimination result.
  • additional parameters include one or more selected from age, gender, elapsed time from onset, and the like.
  • the age of the patient to which the determination according to the present invention is applied is not particularly limited, but is less than 6 years old in a preferred embodiment when distinguishing whether the subject has a viral infection or a bacterial infection.
  • a numerical value of age when inputting a numerical value of age as a parameter, when a numerical value larger than a predetermined age threshold (for example, 5 (years)) is input, (because the age is not less than 6 years old).
  • a predetermined age threshold for example, 5 (years)
  • a mode in which a message or warning such as (calculation impossible) is displayed, or a mode in which an error is displayed may be adopted.
  • Etc. may be displayed.
  • These indications may be verbal indications or may be indications by lamps or the like.
  • the format of the parameters processed in the device was converted into numerical values with predetermined units for general reference by humans (users such as doctors and patients) such as health test results and blood test results. It may be a signal value or data before conversion that can be used for arithmetic processing inside the device.
  • the parameter receiving unit 600 is a part that accepts the above-mentioned plurality of types of parameters and delivers them to the infectious disease determination unit 700.
  • the apparatus has a blood measuring mechanism 100 and a measured value processing unit 500 as a preferred embodiment, and is configured to be able to calculate at least a white blood cell count and a CRP value from a blood sample collected from a subject.
  • the parameter receiving unit 600 is configured to receive the white blood cell count and the CRP value from the measured value processing unit 500.
  • the blood measurement mechanism 100 and the measurement value processing unit 500 are configured so that further blood test values such as neutrophil count, lymphocyte count, and platelet count can be obtained, and the parameter receiving unit 600 receives the further blood test values. It may be configured to be accepted.
  • the configuration example shown in FIG. 1 is merely a preferable example, and the plurality of types of parameters received by the parameter receiving unit 600 may be a CRP value and the above-mentioned test value, and further, age, gender, and course from onset. One or more parameters selected from time and the like may be added.
  • the test value of the blood sample collected from the subject may be a value analyzed by an external blood analyzer, in which case the parameter receiving unit 600 uses the test value for the Internet, LAN, and various data communications. It may be accepted from the interface (not shown).
  • the arrow line connected to the parameter receiving unit 600 represents a signal line for receiving a parameter from the outside.
  • Parameters other than the test values such as the age and sex of the subject are posted on the label attached to the sample container containing the blood sample using a barcode or the like (not shown), and the blood measurement mechanism 100 is attached to the label.
  • the listed parameters may be read, and the read parameters may be configured to be accepted by the parameter receiving unit 600. Further, these parameters may be received from the outside via the above-mentioned communication port.
  • the device may be provided with various input devices (not shown) such as a keyboard and a touch panel, and the parameter receiving unit 600 is useful for distinguishing the subject's age, gender, elapsed time from onset, and the like. Additional parameters may be received from the input device.
  • infectious disease determination unit 700 uses the following relational expression (I) obtained and stored in advance to use the above-mentioned plurality of parameters (for example, CRP value and other test values (red blood cell count (WBC), neutrophil count).
  • CRP value red blood cell count (WBC), neutrophil count.
  • lymphocyte count (NEU #), lymphocyte count (LYM #), platelet count (PLT), total red blood cell count (TNC), red blood cell count (RBC), hemoglobin concentration (HGB), hematocrit value (HCT), average red blood cell volume ( MCV), average erythrocyte hemoglobin amount (MCH), average erythrocyte hemoglobin concentration (MCHC), erythrocyte distribution width (RDW-CV, RDW-SD), platelet distribution width (PDW), platelet clit value (PCT), average platelet volume (MCV) MPV), small erythrocyte ratio (MIC%), macrocytic erythrocyte ratio (MAC%), lymphocyte ratio (LYM%), monosphere count (MON #), monosphere ratio (MON%), neutrophils Ratio (NEU%), Erythrocyte count (EOS #), Erythrocyte ratio (EOS%), Erythrocyte count (BAS #), Erythrocyte ratio (BAS%), Atypical lymphocyte count (ALY #)
  • determining whether a subject has a viral infection or a bacterial infection means that in a preferred embodiment of the present invention, (the subject has either a viral infection or a bacterial infection). Determining that you are affected).
  • determination information as to whether a plurality of data providers have suffered from a viral infection or a bacterial infection, respectively means that, in a preferred embodiment of the present invention, each data provider has a viral infection. And information when suffering from one of the bacterial infections. Therefore, it is preferable to exclude the determination that both are affected and the information that both are affected.
  • the verdicts are (subject is likely to have a bacterial infection), (subject is likely to have a viral infection), (subject is likely to have a bacterial infection and virus). It is highly possible that you have both infectious diseases).
  • the "determination information as to whether the plurality of data providers each suffered from a viral infection or a bacterial infection” each data provider suffers from both a viral infection and a bacterial infection. It may include information that it was done.
  • a virus-infected patient is severe (whether or not a subject is suffering from a severe virus infection)
  • a virus-infected patient It is meant to determine whether the subject is suffering from the severe viral infection or is suffering from the non-severe (mild or moderate) viral infection.
  • determination information as to whether a plurality of data providers were suffering from a severe virus infection or a non-severe virus infection, respectively is, in a preferred embodiment of the present invention, each data provision. Information when a person is suffering from either a severe viral infection or a non-severe (mild or moderate) viral infection.
  • “Severe” and “non-severe” are classified according to the viral infection of interest according to the criteria for clinical severity.
  • the viral infection whose severity can be differentiated by the present invention is not particularly limited, but in one preferred embodiment, it is SARS-CoV-2 infection (COVID-19).
  • SARS-CoV-2 infection COVID-19
  • “severe” means that the patient is in a state of respiratory failure to the extent that artificial respiration management or intensive care by ECMO is required.
  • the degree of respiratory failure is usually assessed by oxygen saturation (SPO2). In the examples described later, SPO2 of less than 94 is defined as severe, and SPO2 of 94 or more is defined as mild (not severe).
  • the relational expression (I) is obtained in advance by multivariate analysis according to the following procedures (a1) and (a2).
  • (A1) From a plurality of data providers known to have a viral infection and from a plurality of data providers known to have a bacterial infection, the above-mentioned plurality, respectively. Get the same multiple parameters as the species parameters. For example, when the CRP value and the white blood cell count are acquired in advance from the above-mentioned data provider as a plurality of parameters, and the relational expression (I) is constructed and stored, the infectious disease determination unit 700 also performs the blood of the patient.
  • Judgment information regarding discrimination is calculated from the CRP value and white blood cell count of the sample.
  • the above-mentioned plurality of types of parameters are referred to as "explanatory variables".
  • the determination information regarding the discrimination of whether the data provider was suffering from a viral infection or a bacterial infection is used as the "objective variable”.
  • a relational expression for example, a multiple regression equation, a multiple discriminant, etc. showing the relationship between the "explanatory variable” and the "objective variable” is obtained.
  • the relational expression (I) is obtained in advance by multivariate analysis according to the following procedures (b1) to (b2).
  • (B1) From multiple data contributors known to have a severe viral infection and from multiple data contributors known to have the non-severe viral infection, respectively.
  • the same multiple types of parameters as the above-mentioned multiple types of parameters are obtained. For example, when the CRP value, the white blood cell count, and the platelet count are acquired in advance from the above-mentioned data provider as a plurality of parameters, and the relational expression (I) is constructed and stored, the infectious disease determination unit 700 also performs.
  • Judgment information regarding discrimination is calculated from the CRP value, white blood cell count, and platelet count of the patient's blood sample.
  • explanatory variables The above-mentioned plurality of types of parameters are referred to as "explanatory variables".
  • determination information regarding the discrimination between the severe viral infection and the non-severe viral infection, respectively is used as the "objective variable”.
  • a relational expression for example, a multiple regression equation, a multiple discriminant, etc.
  • the relational expression (I) is stored in a storage device in the device or an external communicable storage device so that the infectious disease determination unit 700 can refer to it.
  • the relational expression (I) is stored in the relational expression holding unit 710 provided in one area of the storage device in the apparatus.
  • the specific analysis method itself for multivariate analysis is not particularly limited, but for example, discriminant analysis, logistic regression analysis, multiple regression analysis, Cox hazard regression analysis (also called Cox proportional hazard analysis), principal component analysis. , Factor analysis, dispersion analysis, and one or more analytical methods selected from cluster analysis are preferred. In the present invention, it is preferable to carry out one of these analysis methods, but by selecting and carrying out two or more analysis methods, the determination may be confirmed and the accuracy of the determination may be higher. ..
  • discriminant analysis In a discriminant analysis of whether a subject has a viral or bacterial infection, for example, multiple data contributors (Dw) who have been proven to have a viral infection, and a bacterial infection.
  • Dw multiple data contributors
  • the leukocyte count X1 and CRP value X2 are used as explanatory variables to determine whether the disease is a viral or bacterial infection.
  • the two values be the objective variable (Y1). For example, a viral infection is 0 and a bacterial infection is 1.
  • the regression coefficients (a 1 , a 2 , a 0 ) are calculated by using the following equation (i) as the relational expression (I).
  • Y1 a 1 X1 + a 2 X2 +. .. .. + A 0 formula (i) a 1 X 1 represents the product of a 1 and X 1. a 0 is also referred to as a constant term.
  • the additional parameters X3, X4 ,. .. .. Is added as an explanatory variable, (a 3 ⁇ X3 + a 4 ⁇ X4 + ...) is added to the right side of the above equation (i).
  • the regression coefficient of the relational expression is, for example, the value of the actual discrimination of the data provider (whether it is a viral infection or a bacterial infection) and the value obtained by applying each parameter (explanatory variable) of the data provider to the relational expression. It is calculated so that the correlation ratio is maximized.
  • the test value (white blood cell count, CRP value) is input to the above formula (i), and if Y1 ⁇ 0, the subject is highly likely to have a viral infection. If Y1> 0, the determination information that the subject has a high possibility of bacterial infection is output. Further, when the result of the calculation by the relational expression (I) is obtained as the probability of bacterial infection (%) and the probability of viral infection (%), the calculation result (judgment result) exceeds 50%. It may be determined that one is affected. For example, if it is calculated that the probability of bacterial infection is 55% and the probability of viral infection is 45%, the determination information that the subject has a high probability of bacterial infection is output. It may be configured as follows.
  • the discrimination information for dividing into two groups of viral infection and bacterial infection was calculated, and the discrimination information is, for example, four groups (1. Only affected by viral infection). 2. Affected only with bacterial infections 3. Affected with both viral and bacterial infections 4. Not affected with either viral or bacterial infections), etc.
  • the information may be divided into three or more groups. Further, in that case, parameters from data providers proved to belong to each group may be collected and the above relational expression (I) may be calculated, and if necessary, a plurality of the relational expressions may be used. There may be.
  • logistic regression analysis In logistic regression analysis (also referred to as multiple logistic regression analysis), whether the subject has a viral or bacterial infection using a pre-calculated relational expression based on the parameters from the above data provider. The probability is calculated. The parameters from the data provider used in the logistic regression analysis are the same as those in the above-mentioned discriminant analysis.
  • the number of each of the data providers (Dw, Db) of the past data in the multivariate analysis exemplified above is not particularly limited, but for example, k-fold cross-validation (eg, 2-split, 3-split, 5-split, etc.) ) Is preferably the number of people who can execute.
  • the data provider Dw is 260 cases
  • the data provider Db is 229 cases
  • the age is from less than 1 year to 16 years
  • 258 cases are male
  • 231 cases are female
  • the relationship has high credibility. Enough to get the formula.
  • the same procedure as above can be used to distinguish whether or not a virus-infected patient is severely ill. For example, from multiple data contributors (Dw) who have been proven to have a severe viral infection and from multiple data contributors (Db) who have been proven to have the non-severe viral infection, respectively.
  • Dw data contributors
  • Db data contributors
  • the white blood cell count X1, the CRP value X2, and the platelet count X3 are used as explanatory variables, and whether the disease is severe or not is used as the objective variable (Y1, Y2).
  • the regression coefficients (a 1 , a 2 , a 3 , a 0 ) are calculated by using the above equation (i) or (ii) as the relational expression (I).
  • the regression coefficient of the relational expression is, for example, the correlation ratio between the actual discrimination value of the data provider (severe or not) and the value obtained by applying each parameter (explanatory variable) of the data provider to the relational expression. It is required to be the maximum.
  • the test values (white blood cell count, platelet count, CRP value) are input to the above formula (i) or (ii) to obtain the Y1 or Y2 value, and the same as above is performed.
  • the subject can obtain determination information that is likely to be severe or not likely to be severe. Further, as in the case of discriminating the type of infectious disease, the information for discriminating the severity of the viral infection is, for example, four groups (1. severe, 2. moderate, 3. mild, 4. asymptomatic) and the like. The information may be divided into three or more groups. In that case, parameters from data providers proved to belong to each group may be collected and the above relational expression (I) may be calculated, and if necessary, the relational expression may be plural. May be good.
  • the device further comprises a blood measuring mechanism 100.
  • the blood measurement mechanism 100 receives the sample container 80 containing the blood sample M1 at a predetermined position, measures the blood sample M1 in the sample container 80, and sends the obtained measurement signal to the measurement value processing unit 500. It is configured. Since the CRP value is indispensable for differentiation and the white blood cell count is suitable as another blood test item, the white blood cell measurement mechanism 100 is a white blood cell measurement chamber for measuring the white blood cell count of the blood sample M1 (hereinafter referred to as “white blood cell measurement chamber”).
  • the red blood cell measuring chamber (hereinafter, also referred to as RBC chamber) 20 is provided as well as the blood analyzer of Patent Document 1.
  • the RBC chamber 20 is a chamber configured to count red blood cells and platelets, but in order to distinguish the severity of a virus-infected patient, the platelet count is used as an explanatory variable in addition to the CRP value and the white blood cell count. Therefore, it is desirable that the blood measuring mechanism 100 includes an RBC chamber.
  • the counting in the following description includes not only simply counting the number of blood cells such as white blood cells, but also measuring the volume of each blood cell. This makes it possible to analyze how many volumes of blood cells are present (that is, the volume frequency distribution of blood cells).
  • the "frequency" in the volume frequency distribution is the number of particles for each volume (or channel).
  • the volume measurement value indicating the volume of blood cells is not a specific numerical value, and the total width from the minimum value (which may be zero) to the maximum value of the volume measurement value is 256 steps (0 to 255) or 1024 steps (0 to 255 steps). It is preferable to classify into 0 to 1023) and the like. This facilitates the handling of data when performing the process of obtaining the frequency distribution by the analysis unit described later.
  • Each section divided as described above is also called a channel.
  • the WBC chamber 30 In the WBC chamber 30, hemolysis treatment is applied to the blood sample M1 and a diluted solution is added to form a sample solution, leukocytes in the sample solution are counted, and a signal at the time of counting is transmitted. The signal may be processed by the analysis unit 220.
  • the WBC chamber 30 may be configured to count at least leukocytes by, for example, an impedance method.
  • leukocytes are treated so that they can be classified into lymphocytes, monocytes, and granulocytes by adding additional reagents to the sample solution.
  • the frequency distribution of lymphocytes, monocytes, and granulocytes can be obtained.
  • the diluted solution also has an action of protecting the cell membrane of leukocytes.
  • the hemolytic agent destroys red blood cells and platelets and exerts a contractile effect on three types of white blood cells (lymphocytes, monocytes, and granulocytes).
  • lymphocytes hemolytic agents cause dehydration from within the cytoplasm, causing the nuclear envelope to contract (naked nucleation).
  • monocytes and granulocytes the degree of naked nucleation is different from each other, and granulocytes are smaller than monocytes.
  • the WBC chamber 30 may also be configured to be capable of measuring hemoglobin concentration (Hgb).
  • the RBC chamber 20 is a chamber configured to count red blood cells and platelets based on an impedance method or the like, and by analyzing the counting results, the volume frequency distribution of red blood cells and platelets can also be obtained.
  • the hematocrit value (Hct) is calculated by dividing the total volume of red blood cells in a sample obtained by an impedance method or the like by the total volume of blood.
  • a chamber for measuring the number of neutrophils As a chamber for measuring the number of neutrophils, leukocytes are treated with a reagent into particles that can be counted into lymphocytes, monocytes, neutrophils, and eosinophils, and the particles are counted.
  • a measuring chamber can be mentioned. Examples of such a measurement chamber include the LMNE cell (LMNE chamber) described in Patent Document 2.
  • LMNE chamber examples of such a measurement chamber include the LMNE cell (LMNE chamber) described in Patent Document 2.
  • LMNE chamber particles are counted using a reagent and a particle counting mechanism (particularly a mechanism for performing a condensing flow impedance method).
  • the frequency distribution of lymphocytes, monocytes, neutrophils, and eosinophils can be obtained, and thus the number of neutrophils can also be obtained.
  • the CRP value and the neutrophil count are used.
  • a relational expression showing the relationship between the objective variable (viral infection and bacterial infectious disease) is obtained, and the discrimination results of the subjects are compared between the two, so that erroneous judgment can be further reduced.
  • the blood measuring mechanism 100 further includes a chamber for measuring the number of neutrophils.
  • a measurement chamber for counting basophils may be provided. This enables 5 classifications of leukocytes and enables more detailed blood analysis.
  • particle components other than basophils are hemolyzed and contracted by a hemolytic agent, and basophils are counted by a particle counting mechanism.
  • the CRP chamber is configured to measure a CRP parameter value, which is an indicated value corresponding to the CRP value of the blood sample M1, and transmit the measured value.
  • Examples of the method for obtaining the CRP parameter value in the measurement chamber include the CRP latex immunonephelometer RATE method.
  • Examples of the configuration of the CRP chamber include a configuration in which a light irradiation unit and a light detection unit are provided on the lower wall surface to acquire the intensity of the detected transmitted light or scattered light.
  • a blood sample is mixed with an anti-human C reactive protein (CRP) antibody-sensitized latex in the presence of a buffer, and the CRP and the latex particles in the sample are mixed.
  • CRP C reactive protein
  • the rate of agglutination caused by the antigen-antibody reaction with and is measured, and the CRP concentration is obtained using a polymorphic calibration line prepared in advance based on standard serum with the rate of agglutination as a variable.
  • CRP C reactive protein
  • the hematocrit value which is the ratio of red blood cells contained in a certain amount of blood, exceeds a certain value (example: 55%)
  • the amount of plasma derived from the subject is small, so that citrate is used.
  • the sodium citrate concentration increases. Therefore, when obtaining the value, hematocrit correction may be performed by adjusting the amount of sodium citrate solution by a predetermined method in consideration of the CLSI guideline.
  • the process of agglutinating latex particles by causing an antibody reaction (Ii) The step of measuring the turbidity change rate due to the agglutination reaction with red light and determining the CRP concentration in the hemolytic sample using a polymorphic calibration curve prepared in advance based on standard serum, and (iii) hematocrit measured at the same time.
  • the correction may be performed by a method including a step of converting the value into the plasma CRP concentration of the subject and then displaying the value.
  • a mechanism for executing the impedance method (electric resistance method) (a mechanism for measuring the volume of a particle by using a change in the electrical characteristics (impedance) in the aperture when the particle passes through the aperture).
  • Mechanism for performing flow cytometry (The volume of the particles is determined from the optical characteristics such as light scattering and light absorption obtained by irradiating the particles in the sample liquid traveling through the flow cell with a predetermined irradiation light. Measuring mechanism), Condensing flow impedance method (a mechanism in which an impedance method and a mechanism for performing flow cytometry are mixed in one flow path so that each particle can be measured by the impedance method and flow cytometry). And so on.
  • Conventionly known techniques such as Patent Documents 1 and 2 can be referred to.
  • the blood measuring mechanism 100 has a dispensing mechanism 70 in addition to the CRP chamber 10, the RBC chamber 20, and the WBC chamber 30.
  • the dispensing mechanism 70 has a sampling nozzle 50 and a moving mechanism 60.
  • the moving mechanism 60 includes a horizontal moving mechanism 61 and a vertical moving mechanism 62 so that the sampling nozzle 50 can be moved in the horizontal direction and the vertical direction.
  • the sampling nozzle 50 moves to the sample container 80, various reagent containers (not shown), the CRP chamber 10, the RBC chamber 20, and the WBC chamber 30 under the control of the mechanism control unit 300 included in the control unit 200, and blood.
  • It is an elongated tube that sucks and discharges samples, reagent solutions, diluents, sample solutions created in the chamber, and so on.
  • the blood measuring mechanism 100 is appropriately provided with a dilution mechanism, a cleaning mechanism, a suction / discharge pump, a syringe, an electromagnetic valve, and the like (these are not shown).
  • a dilution mechanism a cleaning mechanism, a suction / discharge pump, a syringe, an electromagnetic valve, and the like.
  • conventionally known particle analyzers, blood analyzers, and blood cell counters can be referred to.
  • control unit 200 In the example of FIG. 1, the control unit 200 has a mechanism control unit 300 and an analysis unit 220 which is a main part of the calculation.
  • the mechanism control unit 300 is a part that controls and operates the blood measurement mechanism 100.
  • An external drive circuit or the like for controlling the blood measuring mechanism may be appropriately connected to the control unit 200.
  • the analysis unit 220 receives the identification information of the subject read from the sample container 80 by the blood measurement mechanism 100, receives the signal of the measurement result from the blood measurement mechanism 100, calculates the blood test value of the sample, and receives the blood test value of the sample. Judgment information for discrimination is calculated, and these blood test values and judgment information are output. In the example of FIG.
  • the analysis unit 220 is a unit that receives, processes, and outputs data for analyzing blood and calculating determination information for discrimination, and is a measurement value receiving unit 400 and a measured value processing unit. It includes 500, a parameter receiving unit 600, an infectious disease determination unit 700, a calculation result output unit 800, and the like.
  • the control unit 200 may be constructed by a logic circuit or the like, but it is appropriate that the control unit 200 is composed of a computer and a computer program.
  • the computer executes a computer program configured to control the operation of each part of the blood measuring mechanism 100, and to calculate blood test values and determination information for discrimination.
  • the measured value receiving unit 400 receives the measured value transmitted from each measuring unit (10, 20, 30) in the blood measuring mechanism 100 as data that can be calculated.
  • the measured value receiving unit 400 may be configured to have an interface as hardware and software (computer program) for receiving the received measured value signal as a measured value data set.
  • the measured value receiving unit 400 may store each received measured value in a storage device (not shown).
  • the measured value processing unit 500 has a CRP value calculation unit 510, a red blood cell count calculation unit 520, and a white blood cell count calculation unit 530.
  • the red blood cell count calculation unit 520 receives the measured value (data as measured) in the RBC chamber from the measured value receiving unit 400, and calculates the red blood cell count, the platelet count, and their volume frequency distribution in the blood sample M1.
  • the white blood cell count calculation unit 530 receives the measured value in the WBC chamber from the measured value receiving unit 400, and calculates the white blood cell count and the volume frequency distribution in the blood sample M1.
  • the leukocyte count calculation unit 530 receives the measured values in the WBC chamber from the measured value receiving unit 400 and lymphocytes in the blood sample M1. The number, monocyte count, granulocyte count and their volume frequency distribution are further calculated. Further, the CRP value calculation unit 510 receives the measured value (signal value transmitted from the light receiving sensor) in the CRP chamber from the measured value receiving unit 400, and determines the CRP value of the blood sample M1.
  • the measurement value processing unit 500 may further include a neutrophil number calculation unit or the like. The neutrophil number calculation unit receives the measured value in the chamber for measuring the neutrophil from the measured value receiving unit 400, and calculates the neutrophil number and the volume frequency distribution in the blood sample M1.
  • the calculation result output unit 800 displays the calculation result (blood analysis result of the conventional blood analyzer) in the measurement value processing unit 500 and the determination information related to the above discrimination calculated by the infectious disease determination unit 700 in the display device 900 or the printer. It is a part that outputs to peripheral devices such as, communication lines, external computers, etc.
  • FIG. 2 is a flowchart illustrating an outline of the operation of the apparatus illustrated in FIG.
  • the CRP value analysis steps s1 to s4 and the white blood cell count analysis steps s5 to s8 are shown in parallel, but the operations of these two series may be in series.
  • the numbers assigned to each step are for identification purposes.
  • RBC chambers are added, blood samples are distributed to each chamber in a predetermined order, in which sample solution is formed (a part of the blood sample diluted in the WBC chamber is transferred to the RBC chamber).
  • the movement of the sample solution between the chambers is also included, such as being further diluted there), and then the measurement proceeds independently in each chamber, and the time required for the measurement is also independent for each chamber.
  • the operation of each part is based on the command of the control part.
  • the case where the CRP value and the white blood cell count are used as a plurality of types of parameters will be taken as an example, and the flow of measuring these parameters and calculating the judgment information using them will be described.
  • Step s1 CRP value measurement steps s1 to s4
  • nozzle sampling nozzle
  • the dispensing mechanism 70 is activated, and the sampling nozzle (hereinafter referred to as “nozzle”) 50 moves to measure the CRP value, and the reagent required for the measurement (the reagent container is not shown) and the blood sample in the sample container 80.
  • a predetermined amount of M1 is supplied to the CRP chamber 10, and a sample liquid for measuring the CRP value is formed there. Nozzles are cleaned as appropriate.
  • Step s2 A measured value (absorbance) corresponding to the CRP value is obtained in the CRP chamber, and the measured value is transmitted to the analysis unit 220.
  • the measured value receiving unit 400 of the analysis unit 220 receives the measured value of CRP from the CRP chamber.
  • the CRP value calculation unit 510 of the measurement value processing unit 500 receives the CRP measurement value from the measurement value acceptance unit 400 and determines the CRP value.
  • the CRP value calculation unit 510 may have a reference table for converting the measured value of CRP into the CRP value.
  • the CRP value is sent to the parameter receiving unit 600.
  • Step s5 The dispensing mechanism 70 is activated, and the nozzle 50 supplies a predetermined amount of the blood sample M1 in the sample container 80 to the WBC chamber 30, and a predetermined amount of a diluted solution (water, physiological saline, phosphate buffer diluted) is supplied thereto. (Liquid, etc.) is supplied to dilute the blood sample M1.
  • a diluted solution water, physiological saline, phosphate buffer diluted
  • Liquid, etc. is supplied to dilute the blood sample M1.
  • a hemolytic agent that dissolves (hemolyzes) red blood cells is further added to the diluted blood sample to form a sample solution in which red blood cells are dissolved.
  • Step s6 White blood cells are counted in the WBC chamber 30, the volume of each white blood cell is measured, and the measured value (a signal having a size corresponding to the volume) is transmitted to the analysis unit 220.
  • the hemoglobin concentration may be measured by an optical device for performing a colorimetric method (non-cyan method), and the measured value may be transmitted.
  • a process for further classifying leukocytes into lymphocytes, monocytes, and granulocytes may be performed.
  • particle counting is also performed in the RBC chamber 20, the volume of particles containing red blood cells and platelets is measured, and the measured value is sent to the analysis unit 220.
  • the measured value receiving unit 400 receives the measured value related to the white blood cell count from the WBC chamber.
  • the white blood cell count calculation unit 530 of the measurement value processing unit 500 receives the measured value of white blood cells from the measurement value receiving unit 400 and calculates the white blood cell count per blood unit volume.
  • the white blood cell count is sent to the parameter receiving unit 600.
  • the red blood cell count calculation unit 520 receives the measured values of red blood cells and platelets from the measured value receiving unit 400, and calculates the red blood cell count and the platelet count per blood unit volume.
  • the calculation result in the measured value processing unit 500 may be output through the calculation result output unit 800, or may be displayed on the display device 900 or the like as a histogram or scattergram.
  • the infectious disease determination unit 700 receives the leukocyte count and CRP value from the parameter receiving unit 600, and substitutes these leukocyte count and CRP value into the above relational expression (I) stored in the relational expression holding unit 710 as explanatory variables for the subject. Then, the objective variable Y is calculated. Judgment information on whether the subject has a viral infection or a bacterial infection (if the objective variable is the severity of the viral infection patient, whether the subject is severe or not) according to the calculation result. Is selected (when the objective variable Y is an established value, it may be used as it is as determination information).
  • Judgment information is preferably calculated by the above steps.
  • the calculated determination information is transmitted to the calculation result output unit 800 and output to a display device or the like.
  • the display of the result of the determination information obtained by the infectious disease determination unit 700 may be, for example, "there is a high possibility of a viral infection (or a bacterial infection)” or "the possibility of a viral infection (or a bacterial infection)”. ⁇ % "Or” likely to be a severe (or non-severe) viral infection", “possible to be a severe (or non-severe) viral infection” It may be a sentence, a numerical value, a symbol, or the like that can be understood by the operator of the blood analyzer or the person who sees the analysis result as a reference for the above discrimination, such as "the sex is ⁇ %".
  • the blood sample derived from the subject is (a) obtained from a subject with a viral infection, obtained from a subject with a bacterial infection, or (b) a severe viral infection. It is a method of determining whether it is obtained from a subject with a disease or a subject with a non-severe viral infection.
  • the blood sample derived from the subject is, for example, a blood sample collected from the subject.
  • whether the subject who is the donor of the blood sample has (a) a viral infection (affected by a viral infection) or a bacterial infection (bacterial infection).
  • the method has a first step of preparing the plurality of parameters described above.
  • the method for acquiring the plurality of parameters is not particularly limited, but it is preferable to use the blood analyzer according to the present invention described above.
  • the method uses the plurality of parameters and the above-mentioned relational expression (I), and whether the blood sample is obtained from a subject having (a) a viral infection or a subject having a bacterial infection.
  • the determination method using the above-mentioned relational expression (I) is as described in detail above.
  • the multivariate analysis used in the method according to the invention is selected from discriminant analysis, logistic regression analysis, multiple regression analysis, Cox hazard regression analysis, principal component analysis, factor analysis, dispersion analysis, and cluster analysis, as described above. It may be one or more analyzes.
  • test values of the blood sample for one or more blood test items selected from the blood test items other than the above CRP values are as described above.
  • Computer program according to the present invention may be provided as recorded on a computer-readable medium, or may be provided from another computer or an external storage device via a network.
  • the program is a computer program that causes a computer to function as the above-mentioned parameter receiving unit (that is, parameter receiving means) and as the above-mentioned infectious disease determination unit (that is, infectious disease determination means).
  • the parameter receiving unit and the infectious disease determination unit are as described in detail above.
  • the program further includes a computer program that causes the computer to function as each part (white blood cell count calculation unit, CRP value calculation unit, neutrophil count calculation unit, control unit, etc.) of the blood analyzer according to the present invention described above. You may go out.
  • Example 1 Outline of clinical trial The clinical trial was conducted according to a predetermined protocol approved by the review committee of the National Hospital Organization Tokyo Medical Center (J Infect Chemother (2012) 18: 832-840).
  • Example 2 Setting of relational expression (I) by multivariate analysis
  • samples derived from infants under 7 years old were infected with virus, infected with bacteria, and mixed (virus) by PCR test. It was classified into (both bacterial) infection and mycoplasma infection (virus infection 260 cases, bacterial infection 229 cases, mixed infection 208 cases, mycoplasma infection 86 cases (783 cases in total).
  • the samples classified above were statistically analyzed using StatFlex (Artec Co., Ltd.).
  • Example 3 Evaluation of Relational Expression (I) by K-Divided Cross Validation
  • the method of validation 1 is based on the raw data obtained from the above clinical trial (J Infect Chemother (2012) 18: 832-840).
  • (I) Divide into 5 parts, create a calculation formula (that is, corresponding to the formula (ii) of the present invention) by one of the divisions, and evaluate all 5 divisions.
  • (Ii) Divide into three, create a calculation formula (that is, corresponding to the formula (ii) of the present invention) by one of the divisions, and evaluate all three divisions (see Table 3 for the results).
  • Validation 2 From the results of the above validation 1, the validity of the formula (ii) of the present invention set in Example 2 (validity of the analysis method) was sufficiently verified and confirmed, but from the viewpoint of further improving the reliability, the following Validation 2 was performed.
  • the method of validation 2 is to first divide the raw data obtained from the above clinical trial (J Infect Chemother (2012) 18: 832-840) into two and use one of the two divisions to calculate (the present invention). (Equivalent to equation (ii)) was created and the remaining 1 division was evaluated. Next, all the raw data is shuffled and divided into two again, a calculation formula (corresponding to the formula (ii) of the present invention) is created by one of the two divisions, and the remaining one division is evaluated. The work was repeated 5 times. The five evaluations were given as processing A, B, C, D, and E, respectively.
  • Example 4 Comparison of differentiation results by two relational expressions with different parameters StatFlex (stat) of blood samples collected from 286 cases of viral infections and 409 cases of bacterial infections (695 cases in total) confirmed by PCR.
  • StatFlex stat
  • PCR multivariate analysis (multiple logistics regression) of Flex Co., Ltd.
  • the neutrophil, and the case where CRP was selected the regression coefficients (a 0 to a 3 ) of the above equation (ii) were obtained so that the area under the ROC curve (AUC) was maximized, respectively.
  • the results are shown in Tables 6-1 and 6-2 below.
  • Example 5 Differentiation of severity of SARS-CoV-2 infection (COVID-19) 42 cases confirmed to be SARS-CoV-2 positive by PCR were severely affected by oxygen saturation (SPO2). It was classified into 31 cases (SPO2: less than 94) and 11 mild cases (SPO2: 94 or more). For blood samples collected from these cases, severe COVID-19 and mild COVID-19 were selected as objective variables and explanatory variables using multivariate analysis (multiple logistic regression) of StatFlex (Artec Co., Ltd.). After selecting WBC, CRP, platelets (PLT), lymphocytes (LYM), etc., we evaluated and examined what combination had the largest area under the ROC curve (AUC). The results are shown in Tables 7-1 and 7-2 below.
  • Tables 8-1 and 8-2 are examples in which the severity is differentiated by substituting the actual test values using the relational expression (ii) having the regression coefficients shown in Tables 7-1 or 7-2 above. Shown in.
  • INDUSTRIAL APPLICABILITY it becomes possible to provide useful determination information for a doctor to distinguish whether a patient has a viral infection or a bacterial infection, whereby a viral cold can be obtained. Nevertheless, erroneous prescriptions such as prescribing antibiotics have been suppressed, and problems caused by erroneous prescriptions such as the development of resistant bacteria have been suppressed. Further, according to the present invention, it becomes possible to objectively determine whether or not a patient with a viral infection (eg, COVID-19) is seriously ill, regardless of the subjective judgment of the patient or the interviewer. , It has become possible to appropriately judge the necessity of intervention and the selection of treatment method.
  • a viral infection eg, COVID-19

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WO2023008503A1 (ja) * 2021-07-28 2023-02-02 慶應義塾 重症化予測装置、重症化予測方法、及びプログラム

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CN115268988A (zh) * 2022-07-28 2022-11-01 上海太阳生物技术有限公司 一种凝血项目检测方法及装置

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