Specimen analysis method and specimen analyzer

Abstract

To provide a specimen analysis method and a specimen analyzer for supporting quick evaluation of severity of organ damage caused by an infection and the specimen method and the specimen analyzer capable of outputting information having a high correlation to a score shown by the severity of the organ damage caused by the infection.SOLUTION: A blood cell analyzer 1 includes a measurement part (a measurement unit 2) for irradiating with light a measurement sample including a blood specimen and a fluorescent dye to stain white blood cells included in the blood specimen, detecting fluorescence of the white blood cells included in the measurement sample irradiated with the light, and measuring a fluorescence signal on the basis of the detected fluorescence, an information processing part (a body 40) for generating information on a distribution width of fluorescence intensity of a neutrophil population included in the measurement sample on the basis of the measured fluorescence signal, and determining information on severity of organ damage caused by an infection on the basis of information on the distribution width of the fluorescence intensity of the neutrophil population, and an output part 42 for outputting information on the severity of the organ damage caused by the infection.SELECTED DRAWING: Figure 11

Description

[Technical field]

[0001] The present invention relates to a sample analyzing method and a sample analyzer for analyzing a sample. [Background technology]

[0002] Non-patent document 1 discloses that, among various types of white blood cell data obtained from a multi-parameter automated blood cell analyzer XN-9000 (manufactured by Sysmex Corporation), the fluorescence intensity obtained from neutrophils having an average amount of nucleic acid (NE-SFL) and the scattered light intensity obtained from monocytes having average morphological characteristics (MO-X) are correlated with the sequential organ failure assessment (SOFA) score, which indicates the degree of organ damage. [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] Sabrina Buoro, et al. “Clinical significance of cell population data (CPD) on Sysmex XN-9000 in septic patients with our without liver impairment”, Annals of Translational Medicine, November 2016, Vol 4, No 21, p.1-9 Summary of the Invention [Problem to be solved by the invention]

[0004] The SOFA score is a method proposed by the European society of intensive care medicine (ESICM) to evaluate the severity of organ damage caused by infectious diseases, and is widely used in ICUs. In order to calculate the SOFA score, it is necessary to perform multiple tests including respiratory, coagulation, liver, circulatory, central nervous, and renal functions, and it takes a long time to calculate the score. For this reason, Non-Patent Document 1 proposes a method using NE-SFL and MO-X obtained from a multi-item automated blood cell analyzer XN-9000 as a more rapid test method.

[0005] However, the Spearman rank correlation coefficient between NE-SFL and MO-X and the SOFA score shown in Non-Patent Document 1 was less than 0.4, and NE-SFL and MO-X have not yet been used in clinical settings as a method for assessing the severity of organ damage caused by infectious diseases.

[0006] Therefore, there is a demand for a sample analysis method and sample analysis apparatus that supports the rapid assessment of the severity of organ damage caused by an infectious disease and that can output information that is highly correlated with a score that indicates the severity of organ damage caused by an infectious disease. [Means for solving the problem]

[0007] The sample analysis method of the present invention includes a measurement step of irradiating light onto a measurement sample containing a blood sample and a fluorescent dye that stains white blood cells contained in the blood sample, detecting fluorescence from white blood cells contained in the measurement sample irradiated with the light, and measuring a fluorescent signal based on the detected fluorescence; a generation step of generating information regarding the distribution width of the fluorescent intensity of a neutrophil population contained in the measurement sample based on the fluorescent signal; a determination step of determining information regarding the severity of organ damage caused by an infectious disease based on the information regarding the distribution width of the fluorescent intensity of the neutrophil population; and an output step of outputting the information regarding the severity of organ damage caused by the infectious disease.

[0008] The sample analyzer (1) of the present invention includes a measurement unit (2) that irradiates light onto a measurement sample containing a blood sample and a fluorescent dye that stains white blood cells contained in the blood sample, detects fluorescence from the white blood cells contained in the measurement sample irradiated with light, and measures a fluorescent signal based on the detected fluorescence, an information processing unit (40) that generates information relating to the distribution width of the fluorescent intensity of a neutrophil population contained in the measurement sample based on the measured fluorescent signal, and determines information relating to the severity of organ damage caused by infectious disease based on the information about the distribution width of the fluorescent intensity of the neutrophil population, and an output unit (42) that outputs information relating to the severity of organ damage caused by infectious disease. Effect of the Invention

[0009] According to the present invention, it is possible to provide a sample analysis method and a sample analysis apparatus that support the rapid evaluation of the severity of organ damage caused by an infectious disease, and that can output information that is highly correlated with a score indicating the severity of organ damage caused by an infectious disease. [Brief description of the drawings]

[0010] [Figure 1] 1 is a perspective view showing the appearance of a blood cell analyzer according to a first embodiment of the present invention. [Diagram 2] FIG. 2 is a diagram showing a configuration of a measurement unit. [Diagram 3] FIG. 2 is a diagram showing a configuration of an optical detector. [Figure 4] FIG. 2 is a diagram illustrating a configuration of an information processing unit. [Figure 5A] FIG. 13 is a diagram showing an example of a scattergram. [Figure 5B] FIG. 13 is a diagram showing an example of a scattergram after fractionation processing. [Figure 6] 1 is a graph showing information on the distribution width of the fluorescence intensity of the neutrophil population of hospitalized patients with sepsis (septic patients), hospitalized patients without sepsis (non-septic patients), and healthy subjects versus days since admission (NE-WY). [Figure 7]FIG. 13 is a diagram showing the correlation between information (NE-WY) regarding the distribution width of the fluorescence intensity of the neutrophil population of hospitalized patients (septic and non-septic patients) on day 0 of hospitalization and the SOFA score. [Figure 8] FIG. 13 is a diagram showing the correlation between information on the distribution width of the fluorescence intensity of the neutrophil population on each day (NE-WY) and the SOFA score. [Figure 9] 13 shows an example of a first conversion table in which information (NE-WY) regarding the distribution width of the fluorescence intensity of the neutrophil population is associated with the estimated SOFA score. [Figure 10A] FIG. 2 is a diagram showing an example of a blood sample analysis result screen according to the first embodiment of the present invention. [Figure 10B] FIG. 11 is a diagram showing another example of the blood sample analysis result screen according to the first embodiment of the present invention. [Figure 11] 13 is an example of an operation flowchart of an information processing unit. [Figure 12] FIG. 11 is a diagram showing an example of a blood sample analysis result screen according to the second embodiment of the present invention. [Figure 13] 13 is an example of a second conversion table in which information (NE-WY) regarding the distribution width of the fluorescence intensity of the neutrophil group is associated with the possibility of sepsis in multiple stages. [Figure 14] FIG. 13 is a diagram showing an example of a blood sample analysis result screen according to the third embodiment of the present invention. [Figure 15] FIG. 13 is a diagram showing an example of a blood sample analysis result screen according to the fourth embodiment of the present invention. [Figure 16] FIG. 13 is a diagram showing the correlation between information (NE-WY) regarding the distribution width of the fluorescence intensity of the neutrophil population of hospitalized patients on each day and the difference between the SOFA score on each day and the SOFA score in a healthy state. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A sample analyzer according to an embodiment will now be described with reference to the drawings. The sample analyzer according to the embodiment is a blood cell analyzer that analyzes blood cells in a blood sample.

[0012] [1. First embodiment] [1-1. Outline configuration] FIG. 1 is a perspective view showing the appearance of a blood cell analyzer according to the first embodiment. The blood cell analyzer 1 is an apparatus for analyzing blood cells in a blood sample. Specifically, the blood cell analyzer 1 is a multi-item blood cell analyzer that classifies the types of white blood cells contained in a blood sample, counts the number of each type of white blood cell, counts red blood cells and platelets, and measures the hemoglobin concentration. In the following description, the counting of red blood cells and platelets and the measurement of hemoglobin concentration will be omitted. For example, a measurement unit described in U.S. Pat. No. 8,968,653 can be used to count red blood cells and platelets and measure hemoglobin concentration, and the publication is incorporated herein by reference.

[0013] The blood cell analyzer 1 includes a measurement unit 2, a transport unit 3, and an information processing unit 4.

[0014] The transport unit 3 is disposed in front of the measurement unit 2 and supplies blood samples to the measurement unit 2. Specifically, the transport unit 3 transports a sample rack L supporting a plurality of sample containers (blood collection tubes) T containing blood samples to a position P1 (see FIG. 2) in front of the measurement unit 2. The blood sample is peripheral blood collected from a subject. The subject is a person from whom peripheral blood is collected, such as a patient. The patient is, for example, a person who may develop organ damage caused by an infectious disease.

[0015] The measurement unit 2 mixes a blood sample with a reagent containing a fluorescent dye that stains white blood cells to prepare a measurement sample to be used in the measurement. The measurement unit 2 irradiates the prepared measurement sample with light and measures the scattered light signals and fluorescent signals of the white blood cells contained in the measurement sample. The measurement unit 2 is connected to the information processing unit 4 so as to be able to communicate with it, and transmits the measurement results to the information processing unit 4.

[0016] The information processing unit 4 is communicatively connected to the measurement unit 2, the transport unit 3, and the host computer 5 (see FIG. 2). The information processing unit 4 controls the operation of the measurement unit 2 and the transport unit 3, performs analysis based on the measurement results of the measurement unit 2, and outputs the analysis results by the output unit 42 and transmits them to the host computer 5. The information processing unit 4 includes a main body 40 (see FIG. 4), an input unit 41, and an output unit 42. The input unit 41 is, for example, a keyboard and a mouse. The output unit 42 is, for example, a display. The display can be, for example, a liquid crystal display, an organic EL display, or a mini LED display. The input unit 41 and the output unit 42 may be touch panels.

[0017] [1-2. Detailed configuration] (Measuring unit) 2 is a diagram showing the configuration of the measurement unit 2. The measurement unit 2 includes a hand section 21, a specimen container setting section 22, a barcode unit 23, a specimen aspirating section 24, a sample preparing section 25, and a detection section 26. Each section 21 to 26 is controlled by an information processing unit 4.

[0018] The hand unit 21 grasps the sample container T positioned at position P1, extracts the sample container T from the sample rack L, and rocks it. The sample container setting unit 22 receives the sample container T rocked by the hand unit 21 above position P1. The barcode unit 23 reads the sample number from the barcode label attached to the sample container T. The sample number is information associated with the analysis result of the blood sample. The sample aspirating unit 24 has an aspirating tube 24a, and aspirates the blood sample from the sample container T. The sample preparing unit 25 has a mixing chamber MC and a heater H, and prepares a measurement sample to be used in the measurement by mixing a reagent with the blood sample (hereinafter sometimes simply referred to as the "sample") in the sample container T. The detecting unit 26 has an optical detector D, and detects fluorescence and scattered light of white blood cells from the measurement sample.

[0019] The operation of such a measurement unit 2 will be described, and the sample preparation section 25 and detection section 26 will be described in detail.

[0020] The sample container T positioned at position P1 by the transport unit 3 is gripped by the hand unit 21 and pulled upward from the sample rack L. The hand unit 21 then swings to agitate the sample in the sample container T. After agitation, the sample container T is set by the hand unit 21 in the sample container setting unit 22 positioned above position P1. The sample container T is then transported to position P2 by the sample container setting unit 22.

[0021] When the specimen container T is positioned at position P2, the barcode unit 23 installed near position P2 reads the specimen number from the barcode label affixed to the specimen container T. Thereafter, the specimen container T is transported to position P3 by the specimen container setting unit 22. When the specimen container T is positioned at position P3, a predetermined amount of specimen is aspirated from the specimen container T via the aspirating tube 24a by the specimen aspirating unit 24. When the aspirating of the specimen is completed, the specimen container T is transported forward by the specimen container setting unit 22 and returned to the original support position of the sample rack L by the hand unit 21. After the aspirating tube 24a is moved to the position of the mixing chamber MC, a predetermined amount of the specimen aspirated via the aspirating tube 24a is discharged into the mixing chamber MC by the specimen aspirating unit 24.

[0022] The sample preparation unit 25 is connected to a reagent container 251 containing a first reagent, a reagent container 252 containing a second reagent, and a reagent container 253 containing a sheath liquid (dilution liquid) via tubes. The sample preparation unit 25 is also connected to a compressor (not shown), and the pressure generated by the compressor makes it possible to extract each reagent from the reagent containers 251 to 253. The sample preparation unit 25 mixes the blood sample and the reagent in the mixing chamber MC, and heats the mixture by the heater H for a predetermined time to prepare a measurement sample. The measurement sample prepared by the sample preparation unit 25 is supplied to the optical detector D of the detection unit 26.

[0023] The reagents include a first reagent that stains the nucleic acid of white blood cells, and a second reagent that hemolyzes red blood cells and damages the cell membrane of the white blood cells to an extent that allows the fluorescent dye to penetrate the cell membrane.

[0024] The first reagent contains a fluorescent dye capable of staining nucleic acid, and is a reagent for fluorescently staining the nucleic acid of nucleated cells such as white blood cells in a blood sample treated with a second reagent described below. By treating the blood sample with the first reagent, blood cells having nucleic acid such as white blood cells are stained.

[0025] The fluorescent dye is not particularly limited as long as it can stain nucleic acids, and can be appropriately selected according to the wavelength of light emitted from a light source (semiconductor laser D31 described later). Examples of such fluorescent dyes include propidium iodide, ethidium bromide, ethidium-acridine heterodimer, ethidium diazide, ethidium homodimer-1, ethidium homodimer-2, ethidium monoazide, trimethylenebis[[3-[[4-[[(3-methylbenzothiazol-3-ium)-2-yl]methylene]-1,4-dihydroquinolin]-1-yl]propyl]dimethylaminium]·tetraiodide (TOTO-1), 4-[(3-methylbenzothiazol-2(3H)-ylidene)methyl]-1-[3-(trimethylaminio)propyl]quinolinium, and the like. ium diiodide (TO-PRO-1), N,N,N',N'-tetramethyl-N,N'-bis[3-[4-[3-[(3-methylbenzothiazol-3-ium)-2-yl]-2-propenylidene]-1,4-dihydroquinolin-1-yl]propyl]-1,3-propanediaminium tetraiodide (TOTO-3), or 2-[3-[[1-[3-(trimethylaminio)propyl]-1,4-dihydroquinolin]-4-ylidene]-1-propenyl]-3-methylbenzothiazol-3-ium diiodide (TO-PRO-3) and the fluorescent dye represented by the following general formula (I). Among them, the fluorescent dye represented by the general formula (I) is preferred.

[0026] [ka] In the above formula (I), R 1 and R 4 are the same or different and each is a hydrogen atom, an alkyl group, an alkyl chain having a hydroxyl group, an alkyl chain having an ether group, an alkyl chain having an ester group, or a benzyl group which may have a substituent. 2 and R 3 are the same or different and are a hydrogen atom, a hydroxyl group, a halogen, an alkyl group, an alkenyl group, an alkynyl group, an alkoxy group, an alkylsulfonyl group, or a phenyl group; Z is a carbon atom having a sulfur atom, an oxygen atom, or a methyl group; n is 0, 1, 2, or 3; and X - is an anion.

[0027] In this embodiment, the alkyl group may be either linear or branched. 1 and R 4 When either one of them is an alkyl group having 6 to 18 carbon atoms, the other is preferably a hydrogen atom or an alkyl group having less than 6 carbon atoms. Among alkyl groups having 6 to 18 carbon atoms, alkyl groups having 6, 8 or 10 carbon atoms are preferred.

[0028] In addition, in the above formula (I), R 1 and R 4 Examples of the substituent on the benzyl group include an alkyl group having 1 to 20 carbon atoms, an alkenyl group having 2 to 20 carbon atoms, or an alkynyl group having 2 to 20 carbon atoms. Among these, a methyl group or an ethyl group is particularly preferred.

[0029] In addition, in the above formula (I), R 2 and R 3 Examples of the alkenyl group include alkenyl groups having 2 to 20 carbon atoms. 2 and R 3 The alkoxy group includes an alkoxy group having a carbon number of 1 to 20. Among them, a methoxy group or an ethoxy group is particularly preferable.

[0030] In addition, in the above formula (I), the anion X- As, F - , Cl - , Br - and I - Halogen ions such as CF 3 SO 3 - , B.F. 4 - etc.

[0031] Furthermore, the fluorescent dye in the first reagent may be of one type, or of two or more types.

[0032] The concentration of the fluorescent dye in the first reagent can be appropriately set depending on the type of the fluorescent dye, but is usually 0.01 to 100 pg / μL, preferably 0.1 to 10 pg / μL. For example, when the fluorescent dye represented by the above formula (I) is used as the fluorescent dye in the first reagent, the concentration of the fluorescent dye in the first reagent is preferably 0.2 to 0.6 pg / μL, more preferably 0.3 to 0.5 pg / μL.

[0033] The first reagent can be obtained by dissolving the fluorescent dye in an appropriate solvent to the above concentration. The solvent is not particularly limited as long as it can dissolve the fluorescent dye, and examples of the solvent include water, organic solvents, and mixtures thereof. Examples of the organic solvent include alcohol, ethylene glycol, dimethyl sulfoxide (DMSO), etc. Note that the fluorescent dye may have poor storage stability in an aqueous solution, so it is preferable to dissolve it in an organic solvent.

[0034] Alternatively, a commercially available staining reagent for classifying white blood cells may be used as the first reagent, for example, Fluorocell WDF manufactured by Sysmex Corporation.

[0035] The second reagent contains a surfactant, such as at least one of a cationic surfactant, a nonionic surfactant, and an anionic surfactant, or a combination thereof, for hemolyzing red blood cells and damaging the cell membrane of white blood cells to an extent that the fluorescent dye in the first reagent can penetrate. Furthermore, the second reagent preferably contains an aromatic organic acid at a concentration of 20 mM or more and less than 50 mM. Here, when the concentration of the aromatic organic acid is 20 mM or more and less than 30 mM, the pH of the second reagent is preferably 5.5 or more and 6.4 or less, and when the concentration of the aromatic organic acid is 30 mM or more and 50 mM or less, the pH of the second reagent is preferably 5.5 or more and 7.0 or less.

[0036] In this embodiment, when the concentration of the aromatic organic acid in the second reagent is 20 mM or more and less than 30 mM, the pH of the second reagent is preferably 5.5 to 6.4, more preferably 5.5 to 6.2. Also, when the concentration of the aromatic organic acid in the second reagent is 30 mM or more and 50 mM or less, preferably 40 mM or more and 50 mM or less, the pH of the second reagent is preferably 5.5 to 7.0. More preferably, when the concentration of the aromatic organic acid in the second reagent is 40 mM or more and 50 mM or less, the pH of the second reagent is preferably 5.5 to 6.2.

[0037] In this embodiment, the aromatic organic acid means an acid having at least one aromatic ring in the molecule and its salt. Examples of the aromatic organic acid include aromatic carboxylic acid and aromatic sulfonic acid. In this embodiment, phthalic acid, benzoic acid, salicylic acid, hippuric acid, p-aminobenzenesulfonic acid, benzenesulfonic acid, and salts thereof are preferably used. The aromatic organic acid in the second reagent may be one type or two or more types. When the second reagent contains two or more types of aromatic organic acids, the total concentration of the acids may be 20 mM or more and 50 mM or less.

[0038] As the cationic surfactant, for example, a quaternary ammonium salt type surfactant or a pyridinium salt type surfactant can be used.

[0039] An example of the quaternary ammonium salt surfactant is a surfactant having a total of 9 to 30 carbon atoms and represented by the following formula (II).

[0040] [ka] In the above formula (II), R 1 is an alkyl or alkenyl group having 6 to 18 carbon atoms. 2 and R 3 are the same or different and each is an alkyl or alkenyl group having 1 to 4 carbon atoms. 4 is an alkyl or alkenyl group having 1 to 4 carbon atoms, or a benzyl group; X - is a halogen atom.

[0041] In the above formula (II), R 1 As R, alkyl or alkenyl groups having 6, 8, 10, 12, or 14 carbon atoms are preferred, and linear alkyl groups are particularly preferred. 1 Examples of R include octyl, decyl and dodecyl groups. 2 and R 3 R is preferably a methyl group, an ethyl group, or a propyl group. 4 As the alkyl group, a methyl group, an ethyl group and a propyl group are preferable.

[0042] An example of the pyridinium salt surfactant is a surfactant represented by the following formula (III).

[0043] [ka] In the above formula (III), R 1 is an alkyl or alkenyl group having 6 to 18 carbon atoms, and X - is a halogen atom.

[0044] In the above formula (III), R 1As R, alkyl or alkenyl groups having 6, 8, 10, 12, or 14 carbon atoms are preferred, and linear alkyl groups are particularly preferred. 1 Examples of the alkyl group include octyl, decyl and dodecyl groups.

[0045] The concentration of the cationic surfactant in the second reagent can be appropriately adjusted depending on the type of surfactant, but is usually 10 to 10,000 ppm, preferably 100 to 1,000 ppm.

[0046] As the nonionic surfactant, a polyoxyethylene-based nonionic surfactant represented by the following formula (VI) is preferred.

[0047] R 1 -R 2 -(CH 2 CH 2 O) n -H (VI) In the above formula (VI), R 1 is an alkyl group, an alkenyl group, or an alkynyl group having 8 to 25 carbon atoms, and R 2 is an oxygen atom, -COO- or

[0048] [ka] and n is an integer from 10 to 50.

[0049] Specific examples of the nonionic surfactant include polyoxyethylene alkyl ethers, polyoxyethylene sterols, polyoxyethylene castor oil, polyoxyethylene sorbitol fatty acid esters, polyoxyethylene alkylamines, polyoxyethylene polyoxypropylene alkyl ethers, and the like.

[0050] The concentration of the nonionic surfactant in the second reagent is usually 10 to 100,000 ppm, preferably 100 to 10,000 ppm, and more preferably 1,000 to 5,000 ppm.

[0051] The second reagent may contain a buffer to keep the pH constant. Examples of such buffers include citrate, HEPES, and phosphate. The aromatic organic acids may exhibit a buffering effect. When such aromatic organic acids are used, the addition of a buffer to the second reagent is optional.

[0052] The osmotic pressure of the second reagent is not particularly limited, but is preferably 20 to 150 mOsm / kg from the viewpoint of efficiently hemolyzing red blood cells.

[0053] The second reagent can be obtained by dissolving the above surfactant and aromatic organic acid or its salt, and optionally the above buffer, in a suitable solvent to obtain the above aromatic organic acid concentration, and adjusting the pH using NaOH, HCl, etc. The solvent is not particularly limited as long as it can dissolve the above components, and examples of the solvent include water, organic solvents, and mixtures thereof. Examples of the organic solvent include alcohol, methanol, ethylene glycol, DMSO, etc.

[0054] Alternatively, the second reagent may be a commercially available hemolytic reagent for classifying white blood cells, such as Lysercell WDF and Lysercell WDF II manufactured by Sysmex Corporation.

[0055] The second reagent configured as described above hemolyzes red blood cells and damages the cell membranes of white blood cells to an extent that the fluorescent dye in the first reagent can pass through. The first reagent configured as described above also stains the nucleic acids of the white blood cells whose cell membranes have been damaged by the second reagent. This makes it possible to detect the four subclasses of white blood cells by the optical detector D.

[0056] The detection unit 26 is connected via a tube to a reagent container 253 that contains sheath liquid (dilution liquid). The detection unit 26 is also connected to a compressor (not shown), and the pressure generated by the compressor makes it possible to extract the sheath liquid (dilution liquid) from the reagent container 253. The extracted sheath liquid is used in the optical detector D.

[0057] 3 is a diagram showing the configuration of the optical detector. The optical detector D employs a flow cytometry method using a semiconductor laser, and includes a flow cell D1, a sheath flow system D2, a beam spot forming system D3, a forward scattered light receiving system D4, a side scattered light receiving system D5, a fluorescent light receiving system D6, and a signal processing circuit D7.

[0058] The flow cell D1 is a tubular member made of a light-transmitting material. The sheath flow system D2 is configured to send a measurement sample wrapped in a sheath liquid into the flow cell D1 and generate a liquid flow in the flow cell D1. The beam spot forming system D3 is configured to irradiate the flow cell D1 with light emitted from a semiconductor laser D31, which is a light source, through a collimator lens D32 and a condenser lens D33. This causes the blood cells contained in the liquid flow passing through the flow cell D1 to be irradiated with the laser light. The beam spot forming system D3 also includes a beam stopper D34.

[0059] The forward scattered light receiving system D4 is configured to collect light (forward scattered light) scattered forward by blood cells irradiated with laser light using a forward collecting lens D41, and receive the light that passes through a pinhole D42 using a photodiode D43. The photodiode D43 outputs an electrical signal having a magnitude according to the intensity of the received light. The electrical signal output from the photodiode D43 is sampled multiple times by the signal processing circuit D7 while each blood cell passes through the laser light irradiated area in the flow cell D1, converted into a digital signal, and transmitted to the information processing unit 4. This digital signal (waveform signal) is a measurement result of the received forward scattered light, and indicates a forward scattered light signal.

[0060] The side scattered light receiving system D5 is configured to collect light scattered to the side by blood cells irradiated with laser light (side scattered light) using a side collecting lens D51, reflect it using a dichroic mirror D52, and receive it using a photodiode D53. The photodiode D53 outputs an electrical signal having a magnitude corresponding to the intensity of the received light. The electrical signal output from the photodiode D53 is sampled multiple times by the signal processing circuit D7 while each blood cell passes through the laser light irradiated area in the flow cell D1, converted into a digital signal, and transmitted to the information processing unit 4. This digital signal (waveform signal) is a measurement result of the received side scattered light, and indicates a side scattered light signal.

[0061] Light scattering is a phenomenon that occurs when a particle such as a blood cell exists as an obstacle in the direction of light travel, causing the light to change its direction of travel. By detecting this scattered light, information on the size and material of the particle can be obtained. In particular, information on the size of the particle (blood cell) can be obtained from the forward scattered light. Specifically, the higher the forward scattered light intensity, the larger the size of the cell (e.g., white blood cell). Also, from the side scattered light, information on the inside of the particle can be obtained. When a blood cell particle is irradiated with laser light, the side scattered light intensity depends on the complexity of the inside of the cell (the shape, size, density of the nucleus, and the amount of granules). For example, the higher the side scattered light intensity, the higher the density of the cell (blood cell) and the more granules the cell (blood cell) contains. Also, the higher the side scattered light intensity, the more complex the shape of the nucleus and the more nuclear lobules it contains.

[0062] The fluorescence receiving system D6 is configured to receive the fluorescence emitted by irradiating the blood cells with stained nucleic acid with laser light, via the dichroic mirror D52 and the spectral filter D61, with the photodiode D62, which is an avalanche photodiode. The photodiode D62 outputs an electric signal having a magnitude according to the intensity of the received light. The electric signal output from the photodiode D62 is sampled by the signal processing circuit D7 multiple times while each blood cell passes through the laser light irradiation area in the flow cell D1, converted into a digital signal, and transmitted to the information processing unit 4. This digital signal (waveform signal) is the measurement result of the received fluorescence, and indicates a fluorescence signal. The photodiode D62 does not need to be an avalanche photodiode, and may be, for example, a photomultiplier.

[0063] When light is applied to blood cells whose nucleic acid has been stained with a fluorescent substance, the fluorescent substance emits fluorescence. The intensity of the fluorescence increases with the amount of stained nucleic acid, so by measuring the fluorescent signal, blood cells can be classified based on the amount of nucleic acid they contain.

[0064] Returning to FIG. 2, the measurement results including the forward scattered light signal, the side scattered light signal, and the fluorescent light signal measured by the optical detector D are transmitted to the information processing unit 4.

[0065] As described above, the measurement unit 2 functions as a preparation section that prepares a measurement sample containing a blood sample and a fluorescent dye that stains white blood cells contained in the blood sample, and a measurement section that irradiates light onto the measurement sample, detects the fluorescence of white blood cells contained in the measurement sample irradiated with light, and measures a fluorescent signal based on the detected fluorescence.

[0066] (Information Processing Unit) 4 is a diagram showing the configuration of the information processing unit 4. The information processing unit 4 includes a computer, and is provided with a main body 40, an input unit 41, and an output unit 42. The explanation of the input unit 41 and the output unit 42 is omitted since they have been described above.

[0067] The main body 40 includes a CPU 401 , a ROM 402 , a RAM 403 , a storage device 404 , a read-out device 405 , an image output interface 406 , an input / output interface 407 , and a communication interface 408 .

[0068] The CPU 401 executes computer programs stored in the ROM 402 and computer programs loaded into the RAM 403. The RAM 403 is used to read out computer programs recorded in the ROM 402 and the storage device 404. The RAM 403 is also used as a working area for the CPU 401 when executing these computer programs.

[0069] The storage device 404 is a solid state drive (SSD), a hard disk drive (HDD), or a combination thereof. The storage device 404 stores an operating system (OS), a computer program to be executed by the CPU 401, and data used to execute the computer program. The storage device 404 also stores a program 404a for executing the processing of the information processing unit 4 shown in FIG. 11. The reading device 405 is configured with a CD drive, a DVD drive, or the like, and can read out the computer program and data recorded in the recording medium 405a. Note that, when the program 404a is recorded in the recording medium 405a, the program 404a read from the recording medium 405a by the reading device 405 is stored in the storage device 404.

[0070] The image output interface 406 outputs a video signal according to the data to the output unit 42, and the output unit 42 displays an image based on the data output from the image output interface 406. A user inputs instructions via the input unit 41, and the input / output interface 407 accepts the signal input via the input unit 41. The communication interface 408 is connected to the measurement unit 2, the transport unit 3, and the host computer 5, and the CPU 401 transmits and receives control signals and data to and from these devices via the communication interface 408.

[0071] The main body 40 functions as a control unit that controls the measurement unit 2 and the transport unit 3 by receiving user instructions via the input unit 41 and / or executing a computer program by the CPU 401 through each of the components 401 to 408, and also functions as an information processing unit by executing a computer program by the CPU 401.

[0072] In other words, the information processing unit 4 controls the operation of the measurement unit 2 and the transport unit 3 through the main body 40, and performs analysis based on the measurement results (e.g., forward scattered light signals, side scattered light signals, and fluorescent light signals) received from the measurement unit 2. In this analysis, white blood cells present in a blood sample are classified into four subclasses, namely, (1) lymphocytes (LYMPH), (2) monocytes (MONO), (3) a blood cell group consisting of neutrophils (NEUT) and basophils (BASO), and (4) eosinophils (EO). The classification procedure will be described below.

[0073] The information processing unit 4 extracts a digital signal indicating the peak value of each blood cell from each of the forward scattered light signals of each blood cell (digital signals sampled multiple times while each blood cell passes through the laser light irradiation area in the flow cell D1) received from the measurement unit 2, and obtains the extracted digital signal as the forward scattered light intensity of each blood cell. Similarly, the information processing unit 4 extracts a digital signal indicating the peak value of each blood cell from each of the side scattered light signals of each blood cell, and obtains the extracted digital signal as the side scattered light intensity of each blood cell, and extracts a digital signal indicating the peak value of each blood cell from each of the fluorescence signals of each blood cell, and obtains the extracted digital signal as the fluorescence intensity of each blood cell. Thereafter, the information processing unit 4 generates a scattergram. The scattergram is a distribution diagram in which each blood cell is plotted based on the forward scattered light intensity, the side scattered light intensity, and the fluorescence intensity. The information processing unit 4 can generate three-dimensional scattergrams with the forward scattered light intensity, side scattered light intensity, and fluorescent light intensity as their respective axes, and two-dimensional scattergrams with the side scattered light intensity and fluorescent light intensity as their axes, etc. The scattergrams in this embodiment are two-dimensional scattergrams.

[0074] Fig. 5A is a diagram showing an example of a scattergram. As shown in Fig. 5A, the scattergram of this embodiment is generated by plotting the side scattered light intensity and the fluorescence intensity of each blood cell measured by the measurement unit 2 at positions corresponding to the side scattered light intensity and the fluorescence intensity on a two-dimensional diagram with the horizontal axis representing the side scattered light intensity (SSC) and the vertical axis representing the fluorescence intensity (SFL).

[0075] Next, the information processing unit 4 performs a fractionation process on the scattergram by the main body 40. The fractionation process is a process for classifying the white blood cells in the scattergram into any one of the clusters and dividing them on the scattergram. The procedure and technique of the fractionation process will be described.

[0076] FIG. 5B is a diagram showing an example of a scattergram after fractionation. First, the information processing unit 4 removes points corresponding to debris consisting of hemolyzed red blood cells from the points plotted on the scattergram. Specifically, points included in a predetermined region DB set in advance are removed. Next, the information processing unit 4 classifies the points on the scattergram from which the blood cells in the region DB have been removed into one of four clusters (groups) corresponding to the four subclasses of white blood cells. As shown in FIG. 5B, the four clusters are (1) a cluster A11 of lymphocytes (LYMPH), (2) a cluster A12 of monocytes (MONO), (3) a cluster A13 of blood cells consisting of neutrophils (NEUT) and basophils (BASO), and (4) a cluster A14 of eosinophils (EO).

[0077] Specifically, the information processing unit 4 calculates the degree of belonging of each blood cell to a cluster from the distance between the point corresponding to each blood cell plotted on the scattergram and the center of gravity of each cluster set in advance, and assigns each blood cell to each cluster according to the degree of belonging. Such a method of classifying each blood cell is described in detail in U.S. Patent No. 5,555,196, which is incorporated herein by reference.

[0078] When each blood cell is classified into one of the four clusters corresponding to the four subclasses of white blood cells, the points plotted on the scattergram are divided into clusters A11 to A14 shown in FIG. 5B.

[0079] The information processing unit 4 counts the number of blood cells in each cluster. Specifically, the information processing unit 4 counts the number of points included in each of the clusters A11 to A14 (the number of blood cells belonging to each cluster) using the main body 40. This allows the numbers of lymphocytes, monocytes, blood cell groups consisting of neutrophils and basophils, and eosinophils to be obtained. The information processing unit 4 also counts the number of white blood cells (i.e., the total number of points included in each of the clusters A11 to A14) and calculates the ratios of lymphocytes, monocytes, blood cell groups consisting of neutrophils and basophils, and eosinophils to white blood cells using the main body 40.

[0080] The information processing unit 4 generates information on the distribution width of the fluorescence intensity of the neutrophil group based on the fluorescence intensity of blood cells belonging to cluster A13 by the main body 40. The neutrophil group is a blood cell group consisting of neutrophils and basophils, and is a blood cell group included in cluster A13. In general, peripheral blood contains overwhelmingly more neutrophils than basophils, so the blood cell group in cluster A13 can be considered to be a neutrophil group. Note that blood cells corresponding to basophils may be excluded from the blood cell group in cluster A13, and the remaining blood cell group may be regarded as a neutrophil group.

[0081] The information on the distribution width of the fluorescence intensity of the neutrophil group is an index showing the distribution width of the fluorescence intensity of the neutrophil group. The index showing the distribution width of the fluorescence intensity of the neutrophil group is (1) the distance DW (see FIG. 5B) from the upper limit of the Y axis of the neutrophil group on the X axis passing through the center of gravity G of the neutrophil group (see FIG. 5B) to the lower limit of the Y axis, and (2) the distance DW from the center of gravity G to the upper limit of the Y axis of the neutrophil group on the X axis passing through the center of gravity G. 1 (See FIG. 5B) (3) The distance DW from the center of gravity G to the lower limit of the Y axis of the neutrophil group on the X axis passing through the center of gravity G 2 (See FIG. 5B) (4) The distance DW from the center of gravity G to the upper limit of the Y axis of the neutrophil group on the X axis passing through the center of gravity G 1 and the distance DW from the center of gravity G to the lower limit of the Y axis of the neutrophil group on the X axis passing through the center of gravity G. 2 and the average thereof. The center of gravity G is calculated by the information processing unit 4 using the main body 40. Furthermore, an index showing the distribution width of the fluorescence intensity of the neutrophil group may be, regardless of the center of gravity G, either (5) the distance in the Y-axis direction between the blood cell with the maximum fluorescence intensity of the neutrophil group and the blood cell with the minimum fluorescence intensity. As information on the distribution width of the fluorescence intensity of the neutrophil group, for example, NE-WY output in the same manner as that of the XN series (XN-1000, XN-2000, etc.) of Sysmex Corporation's automated blood cell analyzer may be used.

[0082] The present inventors have found that the distribution width of the fluorescence intensity of the neutrophil population is highly correlated with the SOFA score (Sequential Organ Failure Assessment Score), which is used to evaluate the severity of organ damage caused by an infectious disease. In addition, by examining the SOFA score of a patient at the early stage of hospitalization, the present inventors have found that the distribution width of the fluorescence intensity of the neutrophil population tends to be larger in patients with severe organ damage caused by an infectious disease. The experiments and analyses that led to these findings are described below.

[0083] The present inventor analyzed blood samples taken on each day during the early stages of hospitalization of hospitalized patients suspected of sepsis and blood samples taken from healthy subjects by the method using the above-described blood cell analyzer 1. For this analysis, blood samples from 44 hospitalized patients suspected of sepsis and 39 healthy subjects were used. The breakdown of the hospitalized patients suspected of sepsis included 23 septic patients who were diagnosed with sepsis after hospitalization and 21 non-septic patients who were suspected of sepsis but did not actually have sepsis.

[0084] The inclusion criteria for hospitalized patients suspected of sepsis were those with fever (38°C or higher) and a qSOFA (quick SOFA) score of 2 or more. However, patients receiving steroids were clearly specified when enrolled. qSOFA is a simpler sepsis screening method than SOFA, consisting of three items: respiratory rate, mental state, and systolic blood pressure. The exclusion criteria for hospitalized patients suspected of sepsis were patients in the final stage of chronic disease, patients with neutropenia, patients on dialysis, patients receiving Actemra (registered trademark) (humanized anti-human IL6 receptor monoclonal antibody), and patients receiving TNFα inhibitors.

[0085] The selection criteria for healthy subjects were as follows: those without fever at the time of sample collection, those not suspected of having an infectious disease, those without chronic inflammatory diseases, those with normal coagulation function, and those not taking anticoagulants. There were no exclusion criteria for healthy subjects.

[0086] Specifically, the inventor collected blood samples from hospitalized patients suspected of sepsis on the first day of hospitalization (day 0), day 1, and day 3, which are the initial stage of hospitalization, and collected blood samples from healthy individuals only once. Furthermore, tests were performed on each hospitalized patient to obtain a SOFA score, and the SOFA scores were obtained for each day (day 0, day 1, and day 3). The inventor also used the collected blood samples to prepare measurement samples for hospitalized patients on each day and measurement samples for healthy individuals using a method based on the measurement unit 2, measured side scattered light signals and fluorescent signals, and calculated white blood cell-related parameters including information on the distribution width of the fluorescent intensity of the neutrophil population (NE-WY) using a method based on the information processing unit 4. A multi-item automated blood cell analyzer XN-2000 manufactured by Sysmex Corporation was used for these preparations, the measurement of side scattered light signals and fluorescent signals, and the calculation of white blood cell-related parameters including NE-WY.

[0087] FIG. 6 is a graph showing information on the distribution width of the fluorescence intensity of the neutrophil population of hospitalized patients with sepsis (septic patients), hospitalized patients without sepsis (non-septic patients), and healthy subjects with respect to the number of days since admission (NE-WY). The graph in FIG. 6 is a box plot. The horizontal lines shown at the top of the graph in FIG. 6 indicate two groups for which the P value is less than 0.05 when the difference between each data group is tested by the Steel-Dwass method. For example, the first horizontal line from the top indicates that the P value of the NE-WY data group of the healthy subject and the NE-WY data group of the septic patient on the third day of hospitalization is less than 0.05 when tested by this method. The second horizontal line from the top indicates that the P value of the NE-WY data group of the healthy subject and the NE-WY data group of the septic patient on the first day of hospitalization is less than 0.05, and the third horizontal line from the top indicates that the P value of the NE-WY data group of the healthy subject and the NE-WY data group of the septic patient on the zeroth day of hospitalization is less than 0.05. The sixth horizontal line from the top indicates that the P value of the NE-WY data group of non-septic patients on day 0 of hospitalization and the NE-WY data group of septic patients on day 0 of hospitalization is less than 0.05, and the seventh horizontal line from the top indicates that the P value of the NE-WY data group of non-septic patients on day 1 of hospitalization and the NE-WY data group of septic patients on day 1 of hospitalization is less than 0.05. As shown in FIG. 6, it was found that the NE-WY of the septic patient group on day 0 of hospitalization was significantly larger than the NE-WY of the healthy group and the non-septic patient group on day 0 of hospitalization. Similarly, it was found that the NE-WY of the septic patient group on day 1 of hospitalization was significantly larger than the NE-WY of the healthy group and the non-septic patient group on day 1 of hospitalization. Thus, it was found that the NE-WY of the septic patient group on days 0 and 1 of hospitalization, which are the early stages of hospitalization, was significantly larger than the NE-WY of the healthy group and the non-septic patient group on day 1 of hospitalization. Since the higher the fluorescence intensity, the greater the amount of nucleic acid, it is presumed that the wider the distribution width of the fluorescence intensity of the neutrophil population, the greater the diversity of neutrophils, which means that there are neutrophils with a high amount of nucleic acid and neutrophils with a low amount of nucleic acid. The reason why neutrophil diversity occurs in sepsis is thought to be as follows, although it is not limited to this. That is, in sepsis, immature neutrophils are mobilized to the peripheral blood. The peripheral blood contains mobilized immature neutrophils and neutrophils that have undergone cell death such as apoptosis and necrosis.Immature neutrophils contain a large amount of nucleic acid, whereas neutrophils that have undergone apoptosis contain a small amount of nucleic acid. This suggests that the distribution range of the fluorescence intensity of the neutrophil population becomes wider in sepsis.

[0088] FIG. 7 is a diagram showing the correlation between information (NE-WY) on the distribution width of the fluorescence intensity of the neutrophil population of hospitalized patients (septic patients and non-septic patients) on the 0th day of hospitalization and the SOFA score. In FIG. 7, the white dots are data on septic patients, and the black dots are data on non-septic patients. The P value when the F-test for the significance of the regression was performed was less than 0.05. The Spearman's rank correlation coefficient r, which indicates the correlation between NE-WY and the SOFA score, was 0.70, and a high correlation was observed between the two. Therefore, it was found that the corresponding SOFA score can be estimated from the information on the distribution width of the fluorescence intensity of the neutrophil population. The inventor also calculated a regression equation from the data of septic patients and non-septic patients shown in FIG. 7. The regression equation was y=0.013x-7.1. Here, the x-axis was NE-WY and the y-axis was SOFA score.

[0089] FIG. 8 is a diagram showing the correlation between NE-WY and SOFA score on each day. In FIG. 8, the leftmost graph is the same as the graph shown in FIG. 7. The center graph and the rightmost graph in FIG. 8 are graphs showing the correlation between NE-WY and SOFA score of hospitalized patients (septic patients and non-septic patients) on the first day of hospitalization and the third day of hospitalization, respectively. The white dots in each graph are data of septic patients, and the black dots are data of non-septic patients. The Spearman's rank correlation coefficient r, which indicates the correlation between NE-WY and SOFA score, was 0.70 on the first day of hospitalization (day 0), 0.54 on the first day of hospitalization, and 0.27 on the third day of hospitalization. The highest correlation was confirmed on the first day of hospitalization (day 0), followed by the second highest correlation on the first day of hospitalization. It was also confirmed that the correlation decreased with each passing day from hospitalization. The reason why the correlation decreased over time is thought to be because drug treatment was administered from the first day of hospitalization to suppress the infection, and the infection subsided according to the treatment. The inventors also calculated regression equations from the data of septic patients and non-septic patients on each day shown in Figure 8. The regression equations for the first day of hospitalization (day 0), the first day of hospitalization, and the third day of hospitalization were y = 0.013x-7.1, y = 0.015x-8.3, and y = 0.023x-12.1, respectively. Here, the x-axis represents NE-WY, and the y-axis represents the SOFA score for each day.

[0090] Returning to the description of the information processing unit 4, the information processing unit 4 determines information on the severity of organ damage caused by an infectious disease based on information on the distribution width of the fluorescence intensity of the neutrophil population by the main body 40. The information on the severity of organ damage caused by an infectious disease is, for example, information on the severity of organ damage in a subject suffering from an infectious disease. Specifically, the information on the severity of organ damage caused by an infectious disease includes flag information indicating that the subject of the blood sample is suspected of having sepsis, and / or an estimated score width indicating the severity of organ damage caused by an infectious disease. The estimated score indicating the severity of organ damage caused by an infectious disease is an estimated value of the SOFA score (hereinafter, also simply referred to as "estimated SOFA score").

[0091] Specifically, the storage device 404 stores a first conversion table in which information on the distribution width of the fluorescence intensity of the neutrophil group is associated with the estimated SOFA score. FIG. 9 shows an example of this first conversion table. In the example of FIG. 9, when the information (NE-WY) on the distribution width of the fluorescence intensity of the neutrophil group is 500 or more and less than 700, 700 or more and less than 1000, 1000 or more and less than 1300, or 1300 or more, the estimated SOFA scores are associated with 0 or more and less than 2, 2 or more and less than 6, 6 or more and less than 10, and 10 or more. In this way, in the first conversion table, the larger the distribution width of the fluorescence intensity of the neutrophil group, the larger the estimated score indicating the severity of organ damage caused by infection. The first conversion table can be created by obtaining a regression equation of data of septic patients and non-septic patients obtained by the method described in the above experimental method. For example, the first conversion table of FIG. 9 is derived from the regression equation shown in FIG. 7.

[0092] The information processing unit 4 determines the width of the estimated score indicating the severity of organ damage caused by the infection, which corresponds to the information on the distribution width of the fluorescence intensity of the neutrophil population generated by the main body 40, based on the first conversion table and the information on the distribution width of the fluorescence intensity of the neutrophil population generated by the main body 40. For example, when NE-WY is 600, the information processing unit 4 determines the width of the estimated score from 0 to less than 2.

[0093] The information processing unit 4 determines flag information based on the determined estimated score range. The flag information is text indicating that the subject of the blood sample is suspected of having sepsis, and is stored in the storage device 404. The text is, for example, "Sepsis?". Specifically, the information processing unit 4 acquires the flag information when the determined estimated score range is, for example, any one of 2 or more and less than 6, 6 or more and less than 10, and 10 or more.

[0094] The information processing unit 4 displays the analysis results of the blood sample on the output section 42. FIG. 10A is a diagram showing an example of a blood sample analysis result screen. FIG. 10B is a diagram showing another example of a blood sample analysis result screen. The analysis result screen 6 shown in FIG. 10A and FIG. 10B is displayed on the output section 42 by the main body 40. The analysis result screen 6 includes areas 61 to 64 in addition to the sample number and measurement date and time of the blood sample. The area 61 is an area that displays the number of neutrophils (NEUT), lymphocytes (LYMPH), monocytes (MONO), eosinophils (EO), and basophils (BASO) together with the number of white blood cells (WBC), and the ratio of each to the number of white blood cells. The area 62 is an area that displays data on an index that indicates the distribution width of the fluorescence intensity of the neutrophil group. Here, the data of NE-WY is displayed in the area 62. The area 63 is an area that displays information on the severity of organ damage caused by an infectious disease. In the area 63, flag information indicating that the subject of the blood sample is suspected to have sepsis and / or the width of the estimated score indicating the severity of organ damage caused by an infectious disease is displayed. In the example shown in FIG. 10A, the text "Sepsis?" is displayed as flag information indicating that the subject is suspected to have sepsis. When the width of the estimated score is equal to or greater than 0 and less than 2, the flag information regarding the severity of organ damage caused by an infectious disease is not displayed. In the example shown in FIG. 10B, the width of the estimated SOFA score indicating the severity of organ damage caused by an infectious disease (2 to 6 in the example shown in FIG. 10B) is displayed. In the examples shown in FIGS. 10A and 10B, the flag information and the width of the estimated score are displayed separately in the area 63, but both may be displayed. In the area 64, a scattergram generated by the information processing unit 4 is displayed. This scattergram is a two-dimensional scattergram with the horizontal axis representing side scattering intensity and the vertical axis representing fluorescence intensity.

[0095] As described above, the information processing unit 4 functions as an information processing unit that generates information regarding the distribution width of the fluorescence intensity of the neutrophil population contained in the measurement sample based on the measured fluorescent signal, and determines information regarding the severity of organ damage caused by infectious disease based on the information regarding the distribution width of the fluorescence intensity of the neutrophil population, and as an output unit that outputs information regarding the severity of organ damage caused by infectious disease.

[0096] Next, a description will be given of the operation of the information processing unit 4. Fig. 11 is an example of a flowchart of the operation of the information processing unit. It is assumed that the transport unit 3 supplies a blood sample to the measurement unit 2 under the control of the information processing unit 4.

[0097] As shown in FIG. 11, the information processing unit 4 executes measurement process control by the CPU 401 (S1). The measurement process control is a control for causing the measurement unit 2 to execute a measurement process, and includes preparation process control and detection process control. First, the information processing unit 4 executes preparation process control (S1a). Specifically, the information processing unit 4 transmits a first control signal to the measurement unit 2 to cause the measurement unit 2 to execute the preparation process. As described above, the preparation process is a process for preparing a measurement sample by mixing the blood sample, the first reagent, and the second reagent and heating the mixture by the heater H in order to hemolyze red blood cells contained in the blood sample and fluorescently stain the nucleic acid in the white blood cells.

[0098] Next, the information processing unit 4 executes detection process control by the CPU 401 (S1b). Specifically, the information processing unit 4 transmits a second control signal to the measurement unit 2 to cause the measurement unit 2 to execute the detection process. The detection process is a process of detecting blood cells based on the measurement sample, as described above. Specifically, based on the second control signal, the measurement unit 2 flows the measurement sample through the flow cell D1 to generate a liquid flow, and measures forward scattered light signals, side scattered light signals, and fluorescent signals related to each blood cell by the optical detector D. The measurement unit 2 transmits each measured signal and the corresponding specimen number to the information processing unit 4.

[0099] The information processing unit 4 causes the CPU 401 to store in the storage device 404 the forward scattered light signal, side scattered light signal, and fluorescent light signal for each blood cell received from the measurement unit 2 in association with the specimen number received from the measurement unit 2. The information processing unit 4 causes the CPU 401 to generate a scattergram based on the received side scattered light signal and fluorescent light signal (S2), and performs a fractionation process on the generated scattergram (S3). The scattergram generation process and fractionation process are performed by the method described using Figures 5A and 5B.

[0100] The information processing unit 4 counts the number of white blood cells (WBC) contained in the measurement sample and the number of blood cells contained in clusters A11 to A14, and calculates the ratio of blood cells to white blood cells in each cluster (S4). The information processing unit 4 causes the CPU 401 to store the counted number of white blood cells, the number of blood cells in each cluster, and each calculated ratio in the storage device 404 in association with the specimen number (S4).

[0101] The information processing unit 4 generates information on the distribution width of the fluorescence intensity of the neutrophil population based on the fluorescence intensity of the neutrophil population by the CPU 401 (S5). Specifically, the information on the distribution width of the fluorescence intensity of the neutrophil population is NE-WY.

[0102] Next, the information processing unit 4, by the CPU 401, determines information on the severity of organ damage caused by an infectious disease based on information on the distribution width of the fluorescence intensity of the neutrophil group (S6). Specifically, the information processing unit 4, by the CPU 401, refers to the first conversion table stored in the storage device 404, and determines the width of the estimated SOFA score indicating the severity of organ damage caused by an infectious disease corresponding to the NE-WY generated in S5. For example, when the value of the NE-WY generated in step S5 is 500 or more and less than 700, the information processing unit 4 determines that the width of the estimated SOFA score is 0 or more and less than 2, and when the value of the NE-WY is 700 or more and less than 1000, the information processing unit 4 determines that the width of the estimated SOFA score is 2 or more and less than 6. At this time, the information processing unit 4, by the CPU 401, reads out flag information from the storage device 404 when the width of the estimated SOFA score determined is any one of 2 or more and less than 6, 6 or more and less than 10, and 10 or more. Then, the information processing unit 4 generates, by the CPU 401, the analysis result screen 6 of the blood sample including information on the severity of organ damage caused by the infection (in this embodiment, the range of the estimated SOFA score), and outputs (displays) it by the output unit 42 (S7). In the above-mentioned embodiment, the measurement unit 2 transmits the fluorescence signal, which is a waveform signal, to the information processing unit 4, and the information processing unit 4 acquires the fluorescence intensity based on the fluorescence signal, but the measurement unit 2 may acquire the fluorescence intensity as a fluorescence signal and transmit it to the information processing unit 4. The fluorescence intensity is the peak value of the fluorescence signal of each blood cell, but may be a statistical value such as the average value of the fluorescence signal. The information on the severity of organ damage caused by the infection may be output as text data or image data.

[0103] [1-3. Actions and Effects of the First Embodiment] (1) The blood cell analyzer 1 of this embodiment includes a measurement section (measurement unit 2) that irradiates light onto a measurement sample containing a blood specimen and a fluorescent dye that stains white blood cells contained in the blood specimen, detects fluorescence from the white blood cells contained in the measurement sample irradiated with light, and measures a fluorescent signal based on the detected fluorescence, an information processing section (main body 40) that generates information regarding the distribution width of the fluorescent intensity of a neutrophil population contained in the measurement sample based on the measured fluorescent signal, and determines information regarding the severity of organ damage caused by infectious disease based on the information regarding the distribution width of the fluorescent intensity of the neutrophil population, and an output section 42 that outputs information regarding the severity of organ damage caused by infectious disease.

[0104] This makes it possible to provide a sample analysis method and sample analysis apparatus that assist in the rapid assessment of the severity of organ damage caused by an infectious disease, and that can output information that is highly correlated with a score indicating the severity of organ damage caused by an infectious disease.

[0105] (2) Information regarding the severity of organ damage caused by an infectious disease includes flag information indicating that the subject of the blood sample is suspected of having sepsis, which can assist doctors in diagnosing whether the subject has sepsis.

[0106] (3) The information on the severity of organ damage caused by an infectious disease includes a range of estimated scores that indicate the severity of organ damage caused by an infectious disease. This can assist doctors in determining the treatment policy for the subject. For example, the larger the value included in the range of estimated scores, the more it can assist doctors in making the decision to provide more intensive treatment.

[0107] (4) Information on the distribution width of the fluorescence intensity of the neutrophil population is an index showing the distribution width of the fluorescence intensity of the neutrophil population, and the larger this index is, the larger the estimated score indicating the severity of organ damage caused by the infection will be. This allows doctors to make decisions regarding more intensive treatment as the estimated score becomes larger.

[0108] (5) The blood cell analyzer 1 of this embodiment further includes a preparation unit (sample preparation unit 25) that prepares a measurement sample, which makes it easier to analyze white blood cells contained in a blood specimen.

[0109] (6) The measurement section (measurement unit 2) includes a flow cell D1 through which a measurement sample flows, and is configured to irradiate light onto the measurement sample flowing through the flow cell D1, thereby making it possible to obtain scattered light signals and fluorescent signals for each blood cell.

[0110] [2. Second embodiment] A blood cell analyzer according to the second embodiment will be described below. Regarding the second embodiment, only the parts that are different from the first embodiment will be described, and the explanation of the parts that are the same as the first embodiment will be omitted.

[0111] The second embodiment differs from the first embodiment in the method of acquiring information on the severity of organ damage caused by an infectious disease. In addition, the information on the severity of organ damage caused by an infectious disease according to the second embodiment includes an estimated score indicating the severity of organ damage caused by an infectious disease. This estimated score is an estimated SOFA score.

[0112] Specifically, the information processing unit 4 generates an estimated SOFA score from a regression equation that associates information (NE-WY) related to the distribution width of the fluorescence intensity of the neutrophil group with the estimated SOFA score by the main body 40. That is, in the second embodiment, instead of the first conversion table of the first embodiment, a computer program including the regression equation is stored in the storage device 404, and the information processing unit 4 executes the computer program including the regression equation by the main body 40 to generate an estimated SOFA score corresponding to NE-WY. This regression equation is, for example, y=0.013x-7.1 described in FIG. 7. Therefore, since the regression equation is a linear equation with a positive slope, the larger NE-WY is, the larger the estimated score indicating the severity of organ damage caused by the infection is. The regression equation may be calculated from data of a sufficient number of septic patients and non-septic patients to be reliable.

[0113] Fig. 12 is a diagram showing an example of a blood sample analysis result screen according to the second embodiment. As shown in Fig. 12, the information processing unit 4 displays the generated estimated SOFA score in an area 63 of the analysis result screen 6. In the example shown in Fig. 12, it is displayed that the estimated SOFA score is 2.

[0114] In this way, even if the information regarding the severity of organ damage caused by an infectious disease includes an estimated score indicating the severity of organ damage caused by an infectious disease, it is possible to provide a sample analysis method and a sample analysis device that support rapid evaluation of the severity of organ damage caused by an infectious disease and that can output information that is highly correlated with the score indicating the severity of organ damage caused by an infectious disease. For example, the larger the estimated score, the more support there is for a doctor in making a decision to provide more intensive treatment.

[0115] In addition, the information on the distribution width of the fluorescence intensity of the neutrophil population is an index showing the distribution width of the fluorescence intensity of the neutrophil population, and the larger this index is, the larger the estimated score showing the severity of organ damage caused by the infection will be. This makes it possible to support doctors in making decisions to provide more intensive treatment as the estimated score value increases.

[0116] [3. Third embodiment] A blood cell analyzer according to the third embodiment will be described below. Regarding the third embodiment, only the parts different from the first embodiment will be described, and the description of the parts that are the same as the first embodiment will be omitted.

[0117] The information on the severity of organ damage caused by an infection according to the third embodiment is different from that according to the first embodiment. That is, the information on the severity of organ damage caused by an infection according to the third embodiment is flag information indicating, in multiple stages, that the subject of the blood sample is suspected of having sepsis.

[0118] Fig. 13 is an example of a second conversion table in which NE-WY and the possibility of sepsis are associated in multiple stages. As shown in Fig. 13, in the second conversion table, when NE-WY is 500 or more and less than 700, 700 or more and less than 1300, and 1300 or more, the possibility of sepsis is associated with Low, Middle, and High, respectively. In the third embodiment, instead of the first conversion table of the first embodiment, a second conversion table is stored in the storage device 404, and the information processing unit 4 determines the degree of the possibility of sepsis of the subject based on NE-WY generated by the main body 40 and the second conversion table.

[0119] Fig. 14 is a diagram showing an example of a blood sample analysis result screen according to the third embodiment. As shown in Fig. 14, the information processing unit 4 displays the acquired degree of possibility of sepsis as flag information in an area 63 of the analysis result screen 6. In the example shown in Fig. 14, it is displayed that the possibility of sepsis is High.

[0120] A sample analysis method and a sample analyzer that support rapid evaluation of the severity of organ damage caused by an infectious disease, even when information regarding the severity of organ damage caused by an infectious disease is flag information indicating the likelihood of sepsis, can output information that is highly correlated with a score indicating the severity of organ damage caused by an infectious disease. For example, the higher the level of severity, the more supportive the doctor's decision to provide more intensive treatment can be provided.

[0121] In this embodiment, the possibility of sepsis is indicated by three stages as flag information, but it may be indicated by two stages, four stages, or five or more stages. Also, the possibility of sepsis may be indicated by a probability.

[0122] [4. Fourth embodiment] A blood cell analyzer according to a fourth embodiment will be described. Regarding the fourth embodiment, only the parts different from the first embodiment will be described, and the description of the parts that are the same as the first embodiment will be omitted.

[0123] The information on the severity of organ damage caused by an infection according to the fourth embodiment is different from that according to the first embodiment. That is, the information on the severity of organ damage caused by an infection according to the fourth embodiment includes flag information indicating that the subject of the blood sample is suspected of having sepsis, and information indicating whether an estimated value of the difference between the SOFA score at the beginning of hospitalization and the SOFA score in a healthy state is equal to or greater than a threshold value.

[0124] Specifically, a threshold value is stored in the storage device 404 instead of the first conversion table. In Sepsis-3, sepsis is defined as a case where an infection and a sudden increase of 2 or more points in the SOFA score are observed, so the threshold value can be, for example, a value of information (NE-WY) on the distribution width of the fluorescence intensity of the neutrophil group, which corresponds to an estimated value of 2 for the difference between the SOFA score at the beginning of hospitalization and the SOFA score in a healthy state. However, the threshold value may be appropriately settable.

[0125] The information processing unit 4 compares the information (NE-WY) on the distribution width of the fluorescence intensity of the neutrophil group generated by the main body 40 with a threshold value read from the storage device 404, and when it is determined that NE-WY is equal to or greater than the threshold value, it displays flag information indicating that the estimated value of the difference between the SOFA score at the beginning of hospitalization and the SOFA score in a healthy state is equal to or greater than the threshold value in an area 63 of the analysis result screen 6 displayed on the output unit 42. When the information processing unit 4 determines that NE-WY is less than the threshold value, it displays flag information indicating that the estimated value of the difference between the SOFA score at the beginning of hospitalization and the SOFA score in a healthy state is less than the threshold value in an area 63 of the analysis result screen 6 displayed on the output unit 42. When NE-WY is less than the threshold value, the flag information may be hidden.

[0126] Fig. 15 is a diagram showing an example of a blood sample analysis result screen according to the fourth embodiment. Fig. 15 shows the analysis result screen 6 when NE-WY is equal to or greater than a threshold. As shown in Fig. 15, "Estimated delta SOFA score ≧2" is displayed in area 63, indicating that the estimated difference between the SOFA score at the beginning of hospitalization and the SOFA score in a healthy state is 2 or more.

[0127] The method of setting the threshold value will be described with reference to FIG.

[0128] FIG. 16 is a diagram showing the correlation between the information (NE-WY) on the distribution width of the fluorescence intensity of the neutrophil group of the hospitalized patient on each day and the difference between the SOFA score on each day and the SOFA score when healthy. In FIG. 16, the leftmost graph, the center graph, and the rightmost graph are graphs showing the correlation between the NE-WY on the 0th day, the 1st day, and the 3rd day of hospitalization, respectively, and the difference between the SOFA score on each day and the SOFA score when healthy. The white dots in each graph are data of septic patients, and the black dots are data of non-septic patients. The septic patients and non-septic patients are the same patients as those in FIG. 8. The calculation method of the information (NE-WY) on the distribution width of the fluorescence intensity of the neutrophil group of the hospitalized patient on each day and the blood cell analyzer used for the calculation are the same as those described above. The SOFA score when healthy is the SOFA score at the time of discharge of each patient. The difference between the SOFA score on each day and the SOFA score in a healthy state was calculated by subtracting the SOFA score in a healthy state from the SOFA score on each day for each patient.

[0129] The Spearman rank correlation coefficient r, which indicates the correlation between the difference between NE-WY and SOFA score and the SOFA score in a healthy state, was 0.67 on the first day of hospitalization (day 0), 0.53 on the first day of hospitalization, and 0.23 on the third day of hospitalization. The highest correlation was confirmed on the first day of hospitalization (day 0), followed by the second highest correlation on the first day of hospitalization. It was also confirmed that the correlation decreased with each passing day from hospitalization. The reason for the decrease in correlation over time is thought to be that since drug treatment is administered from the first day of hospitalization to suppress infection, the infection subsides according to treatment. In addition, the inventor calculated regression equations from the data of septic patients and non-septic patients on each day shown in FIG. 16. The regression equations on the first day of hospitalization (day 0), the first day of hospitalization, and the third day of hospitalization were y=0.013x-7.3, y=0.015x-8.5, and y=0.022x-12.1, respectively. In this case, the x-axis represents NE-WY, and the y-axis represents the difference between the SOFA score on each day and the SOFA score in a healthy state.

[0130] The threshold can be determined from a regression equation that associates an index indicating the distribution width of the fluorescence intensity of the neutrophil group with the difference between the SOFA score and the SOFA score in a healthy state, as shown in Fig. 16. For example, NE-WY, which corresponds to a difference of 2, can be used as the threshold. This is because in Sepsis-3, sepsis is defined as a combination of infection and a sudden increase of 2 or more points in the SOFA score.

[0131] The thresholds can be obtained for the first day of hospitalization (day 0), the first day of hospitalization, and the third day of hospitalization, and stored in the storage device 404. The information processing unit 4 may select a threshold depending on the number of days of hospitalization of the subject, and acquire flag information. For example, when the subject is on the first day of hospitalization, the information processing unit 4 accepts an input of information that "the subject is on the first day of hospitalization" from the input unit 41 by the user or the host computer 5, reads out the threshold for the first day of hospitalization from the storage device 404, compares the threshold with NE-WY, and displays flag information of "Estimated delta SOFA score ≧2" or "Estimated delta SOFA score <2" in the area 63 of the analysis result screen 6 displayed on the output unit 42. Note that a common threshold may be used regardless of the number of days from the first day of hospitalization.

[0132] As a first modified example of this embodiment, a regression equation may be created for each number of days since hospitalization, and a computer program including the regression equation may be stored in the storage device 404. In this case, the information processing unit 4 executes the computer program including the regression equation according to the number of days since the subject's hospitalization by the main body 40, and determines flag information indicating whether or not an estimated value of the difference between the SOFA score at the beginning of hospitalization and the SOFA score in a healthy state is equal to or greater than a threshold value. An input of the number of days since the subject's hospitalization is accepted from the input unit 41 or the host computer 5.

[0133] As a second modification of this embodiment, a computer program including a common regression equation that is independent of the number of days since hospitalization may be stored in the storage device 404. In this case, the information processing unit 4 executes the computer program using the main body 40, and determines flag information indicating whether an estimated value of the difference between the SOFA score at the beginning of hospitalization and the SOFA score in a healthy state is equal to or greater than a threshold value.

[0134] As described above, in this embodiment, the flag information includes information indicating whether or not the estimated difference between the SOFA score at the beginning of hospitalization and the SOFA score in a healthy state is equal to or greater than a threshold value. This provides a sample analysis method and a sample analysis device that support rapid evaluation of the severity of organ damage caused by an infectious disease and that can output information that is highly correlated with a score indicating the severity of organ damage caused by an infectious disease. Specifically, it is possible to support a doctor's diagnosis that a subject has sepsis, and to support the doctor's decision on a treatment plan for the subject.

[0135] 5. Other embodiments The above-described embodiments are merely examples for explaining the present invention, and the present invention is not limited to these examples. The present invention can be implemented in various forms without departing from the gist of the present invention. For example, the present invention also includes a combination of two or more of the first to fourth embodiments and their modifications. In addition, in the above-described processes or operations, the order and execution entity of the processes or operations can be freely changed as long as no inconsistency in the processes or operations occurs, such as the use of data that should not yet be available in a certain step. [Explanation of symbols]

[0136] 1 Blood cell analyzer 2. Measurement Unit 21 Hand section 22 Sample container setting section 23 Barcode Unit 24 Sample aspiration section 25 Sample Preparation Section 26 Detection unit D Optical detector D1 Flow Cell D2 Sheath flow system D3 Beam spot forming system D31 Semiconductor Laser D32 Collimator Lens D33 Capacitor Lens D34 Beam stopper D4 Forward scattered light receiving system D41 Front focusing lens D42 Pinhole D43 Photodiode D5 Side scattered light receiving system D51 Side focusing lens D52 Dichroic Mirror D53 Photodiode D6 Fluorescence receiving system D61 Spectral Filter D62 Photodiode D7 Signal processing circuit 3. Transport unit 4. Information Processing Unit 40 Main unit 401 CPU 402 ROM 403 RAM 404 Storage device 404a Program 405 Reading device 405a Recording media 406 Image Output Interface 407 Input / Output Interface 408 Communication Interface 41 Input section 42 Output section 5. Host Computer

Claims

1. a measuring step of irradiating a measurement sample containing a blood specimen and a fluorescent dye that stains white blood cells contained in the blood specimen with light, detecting fluorescence from the white blood cells contained in the measurement sample irradiated with the light, and measuring a fluorescent signal based on the detected fluorescence; a generating step of generating information regarding a distribution width of the fluorescence intensity of a neutrophil population contained in the measurement sample based on the fluorescence signal; determining information regarding the severity of organ damage caused by an infection based on information regarding the distribution width of the fluorescence intensity of the neutrophil population; an output step of outputting information regarding the severity of organ damage caused by the infection; Including, Sample analysis methods.

2. The information regarding the severity of organ damage caused by the infection includes flag information indicating that the subject of the blood sample is suspected of having sepsis or the degree of the possibility of having sepsis. The method for analyzing a sample according to claim 1.

3. The information regarding the severity of organ damage caused by the infectious disease includes an estimated score indicating the severity of organ damage caused by the infectious disease. The method for analyzing a sample according to claim 1.

4. The information regarding the severity of organ damage caused by the infectious disease includes a range of estimated scores indicating the severity of organ damage caused by the infectious disease; The method for analyzing a sample according to claim 1.

5. the information regarding the distribution width of the fluorescence intensity of the neutrophil population indicates a distribution width of the fluorescence intensity of the neutrophil population, and the larger the distribution width, the larger the estimated score indicating the severity of organ damage caused by the infection. The method for analyzing a sample according to claim 3 or 4.

6. The estimated score indicating the severity of organ damage caused by the infection is an estimated SOFA score; The method for analyzing a sample according to claim 3 or 4.

7. The information regarding the severity of the organ damage caused by the infection includes information indicating whether an estimated difference between the SOFA score at the beginning of hospitalization and the SOFA score in a healthy state is equal to or greater than a threshold value. The method for analyzing a sample according to claim 6.

8. The measurement step further includes a preparation step of preparing the measurement sample. The method for analyzing a sample according to claim 1.

9. The measurement step further includes a liquid flow step of flowing the measurement sample through a flow cell, In the measurement step, the measurement sample flowing through the flow cell is irradiated with the light. The method for analyzing a sample according to claim 1.

10. a measurement unit that irradiates light onto a measurement sample containing a blood specimen and a fluorescent dye that stains white blood cells contained in the blood specimen, detects fluorescence from the white blood cells contained in the measurement sample irradiated with the light, and measures a fluorescent signal based on the detected fluorescence; an information processing unit that generates information regarding a distribution width of the fluorescence intensity of a neutrophil population contained in the measurement sample based on the fluorescent signal, and determines information regarding the severity of organ damage caused by an infection based on the information regarding the distribution width of the fluorescence intensity of the neutrophil population; an output unit that outputs information regarding the severity of organ damage caused by the infection; Including, Sample analyzer.

11. The information regarding the severity of organ damage caused by the infection includes flag information indicating that the subject of the blood sample is suspected of having sepsis or the degree of the possibility of having sepsis. The sample analyzer of claim 10.

12. The information regarding the severity of organ damage caused by the infectious disease includes an estimated score indicating the severity of organ damage caused by the infectious disease. The sample analyzer of claim 10.

13. The information regarding the severity of organ damage caused by the infectious disease includes a range of estimated scores indicating the severity of organ damage caused by the infectious disease; The sample analyzer of claim 10.

14. the information regarding the distribution width of the fluorescence intensity of the neutrophil population indicates a distribution width of the fluorescence intensity of the neutrophil population, and the larger the distribution width, the larger the estimated score indicating the severity of organ damage caused by the infection. The sample analyzer according to claim 12 or 13.

15. The estimated score indicating the severity of organ damage caused by the infection is an estimated SOFA score; The sample analyzer of claim 14.

16. The information regarding the severity of organ damage caused by the infection includes information indicating whether an estimated difference between the SOFA score at the beginning of hospitalization and the SOFA score in a healthy state is equal to or greater than a threshold value. The sample analyzer according to claim 12 or 13.

17. The measurement unit further includes a preparation unit that prepares the measurement sample. The sample analyzer of claim 10.

18. The measurement unit includes a flow cell through which the measurement sample flows, and irradiates the measurement sample flowing through the flow cell with the light. The sample analyzer of claim 10.

19. At least one of the following configurations [11] to [18] is included: The sample analyzer of claim 10. [11] The information regarding the severity of organ damage caused by the infection includes flag information indicating that the subject of the blood sample is suspected of having sepsis. [12] The information regarding the severity of organ damage caused by the infectious disease includes an estimated score indicating the severity of organ damage caused by the infectious disease. [13] The information regarding the severity of organ damage caused by the infectious disease includes a range of estimated scores indicating the severity of organ damage caused by the infectious disease. [14] The information relating to the distribution width of the fluorescence intensity of the neutrophil population indicates the distribution width of the fluorescence intensity of the neutrophil population, and the larger the distribution width, the larger the estimated score indicating the severity of organ damage caused by the infection. [15] The estimated score indicating the severity of organ damage caused by the infection is an estimated SOFA score. [16] The flag information includes information indicating whether an estimated value of the difference between the SOFA score at the beginning of hospitalization and the SOFA score in a healthy state is equal to or greater than a threshold value. [17] The measurement unit further includes a preparation unit that prepares the measurement sample. [18] The measurement unit includes a flow cell through which the measurement sample flows, and irradiates the measurement sample flowing through the flow cell with the light.

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