Method, system, and computer program product for testing blood

Abstract

To provide a computer-implemented method of testing blood of a subject.SOLUTION: A method provided herein comprises obtaining a plurality of hematological parameters for blood, performing plausibility check of the hematological parameters, and outputting an indication of a determined probability of an infectious response of a subject based on the parameters according to a result of the plausibility check.SELECTED DRAWING: Figure 6

Description

[Technical field]

[0001] The present invention relates to a computer-implemented method for testing blood. ,blood A ball counting device system, and a computer program product. [Background technology]

[0002] Systemic Inflammatory Response Syndrome (SIRS) is a condition in which a subject experiences a severe inflammatory response throughout the body due to infectious or non-infectious trauma.

[0003] SIRS accompanied by an infectious inflammatory response includes sepsis. If sepsis is not treated appropriately at an early stage, symptoms may progress to severe sepsis, septic shock, and multiple organ dysfunction (MOD), and may ultimately lead to death. Therefore, when a subject is diagnosed with SIRS, early determination of whether the response is an infectious inflammatory response or a non-infectious inflammatory response, particularly early diagnosis of whether the subject has a bacterial or viral infection, has a significant impact on the treatment given to the subject. Furthermore, determining whether an inflammatory response is an infectious response or a non-infectious response may also have a significant impact on the treatment given to a subject who does not have SIRS. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] European Patent No. 2302378 Summary of the Invention [Problem to be solved by the invention]

[0005] Patent Document 1 describes a blood cell counter and a diagnostic support method that determine diagnostic support information, for example in the form of an index (ICIS: Intensive Care Infection Score), based on several measured hematological parameters to help determine whether an inflammatory response of a subject is an infectious inflammatory response, in particular whether an infectious inflammatory response is caused by bacteria or viruses. If bacterial or viral infections are not treated immediately and appropriately, they can rapidly progress to serious, life-threatening conditions such as sepsis. Medical professionals will try to determine whether inflammation is caused by bacterial or viral infections and make a diagnosis of sepsis or SIRS in other cases.

[0006] In the methodology of Patent Document 1, an ICIS index is determined based on measured hematological parameters, and the ICIS index is output as diagnostic support information. However, since the ICIS index is output without technically assessing the reliability of the determined ICIS index, there is a possibility that an inappropriate ICIS index value will be output and the assessment of the likelihood of an infectious reaction such as sepsis will be unreliable.

[0007] Against this background, the object of the present invention is to overcome these limitations. [Means for solving the problem]

[0008] The problem of the invention is solved by the subject matter as defined in the claims.

[0009] According to the present invention, Using a hemocytometer The method for testing the subject's blood is as follows: The blood is mixed with a reagent for classifying white blood cells to prepare a measurement sample, and the measurement sample is measured by a flow cytometry method to obtain a measurement result including at least a first parameter related to neutrophils and a second parameter related to other blood cells. obtaining a plurality of hematological parameters; Multiple At least one of the hematological parameters Based on the first parameter performing a reliability test; and In response to passing the test, the plurality of hematological parameters Based on the infectious response of the subject of possibility Calculate the index value for It is also important to be prepared.

[0010] According to the present invention Hematology System Is blood and a reagent for classifying white blood cells to prepare a measurement sample, and the measurement sample is measured by a flow cytometry method to obtain a measurement result including at least a first parameter related to neutrophils and a second parameter related to other blood cells. Acquire multiple hematological parameters Hematology Analyzer And the above Multiple At least one of the hematological parameters Based on the first parameter Reliability inspection stomach , the reliability inspection In response to passing the test, the plurality of hematological parameters Based on the subject's infectious response of possibility Calculate the index value for do Diagnostic support Device and, Equipped with.

[0012] A computer program product according to the present invention comprises a computer-readable medium having stored thereon instructions capable of causing a general purpose computer to perform the operations of the methods described above.

[0013] The solutions according to the first, second, third and fourth aspects ensure that only valid and reliable numerical parameter values ​​are used to determine a subject's likelihood of an infectious response. [Brief description of the drawings]

[0014] [Figure 1] 1 is a front view showing a schematic configuration of a blood cell counting device system according to an embodiment. FIG. [Diagram 2] 2 is a block diagram showing the configuration of a detection device of the blood cell counting device system according to the embodiment. FIG. [Diagram 3] FIG. 2 is a schematic plan view showing the configuration of a detection unit of the detection device according to the embodiment. [Figure 4] FIG. 2 is a block diagram showing the configuration of a first diagnosis support device of the blood cell counting device system according to the embodiment. [Diagram 5] FIG. 2 is a block diagram showing the configuration of a second diagnosis support device of the blood cell counting device system according to the embodiment. [Figure 6] 6 is a flowchart showing a series of processes performed by a second diagnosis support device of the blood cell counting device system according to the embodiment. [Figure 7]13 is a flowchart showing a series of processes performed by a second diagnosis support device of the blood cell counting device system according to another embodiment. [Figure 8] FIG. 2 is a diagram showing a RET scattergram created by a detection device of the blood cell counter system according to the embodiment. [Figure 9] FIG. 13 is a diagram showing a DIFF scattergram created by a detection device of the blood cell counter system according to the embodiment. [Figure 10] FIG. 2 is a diagram showing a WBC / BASO scattergram created by a detection device of the blood cell counter system according to the embodiment. [Figure 11] FIG. 13 is a diagram showing an example of an output screen for showing the measurement results of a blood sample. [Figure 12] FIG. 13 is a diagram showing another example of an output screen for showing the measurement results of a blood sample. [Figure 13] 13 is a flowchart showing a series of processes performed by a first diagnosis support device of a blood cell counting device system according to another embodiment. [Figure 14] 13 is a flowchart showing a series of processes performed by a first diagnosis support device of a blood cell counting device system according to another embodiment. [Figure 15A] FIG. 13 is a diagram showing an example of a DIFF scattergram for explaining a reliability inspection. [Figure 15B] FIG. 13 is a diagram showing an example of a DIFF scattergram for explaining a reliability inspection. [Figure 16A] FIG. 13 is a diagram showing an example of a RET scattergram for explaining a reliability test. [Figure 16B] FIG. 13 is a diagram showing an example of a RET scattergram for explaining a reliability test. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] A diagnosis support device, a diagnosis support method, and a computer program according to an embodiment of the present invention will be specifically described below with reference to the drawings. The following embodiment is not intended to limit the invention defined by the claims, and it goes without saying that all of the combinations of features described in the embodiment are not necessarily essential to the solution.

[0016] FIG. 1 is a front view showing a schematic configuration of a blood cell counting device system according to an embodiment of the present invention. As shown in FIG. 1, the blood cell counting device system 1 according to an embodiment of the present invention includes a blood detection device 2, a first diagnosis support device 3, and a second diagnosis support device 3'. The blood detection device 2 is, for example, a device that detects blood cells in the blood of a subject exhibiting an inflammatory reaction. The first diagnosis support device 3 and the second diagnosis support device 3' support determining whether the inflammatory reaction is caused by an infection or not. The first diagnosis support device 3 may be a computer that may be called an information processing device (IPU), which receives detection data from the blood detection device 2 and analyzes the detection data. The second diagnosis support device 3' is a computer that may be called a working area manager (WAM), which receives a measurement command for calculating the ICIS index value of the subject from an external device (clinical laboratory information system (LIS)) and transmits the measurement command to the first diagnosis support device 3.

[0017] The first diagnostic support device 3 sends a measurement command for the subject to the detection device 2, receives data including the result of the detection performed by the detection device 2, and performs an analysis process. The blood cell counting device system 1 is installed in a medical institution such as a hospital or a hematology research institute. The detection device 2 and the first diagnostic support device 3 can be connected via a transmission cable 3a so as to be able to communicate data with each other. Similarly, the first diagnostic support device 3 and the second diagnostic support device 3' can be connected via a transmission cable 3a' so as to be able to communicate data with each other. Note that the connection between the detection device 2 and the first diagnostic support device 3 and / or the connection between the first diagnostic support device 3 and the second diagnostic support device 3' is not limited to a direct wired connection formed by the transmission cables 3a and 3a', respectively. For example, they may be connected by a wireless connection such as a dedicated line using a telephone line, a LAN, or a communication network such as the Internet.

[0018] A blood collection tube setting section 2a is provided at the lower right of the front of the detection device (or blood analysis device) 2, where a blood collection tube containing the subject's blood can be set. When an operator presses a push button switch 2b provided near the blood collection tube setting section 2a, the blood collection tube setting section 2a moves toward the operator, so that the operator can set the blood collection tube thereon. When the operator presses the push button switch 2b again after setting the blood collection tube, the blood collection tube setting section 2a moves toward the detection device 2 and is stored in the detection device 2. However, the detection device 2 is not limited to one in which the blood collection tube is manually set. Alternatively, the blood collection tubes may be collected in a sample rack and moved to the detection device 2 by a transport band or transport conveyor, where each blood collection tube may be set in the detection device 2.

[0019] FIG. 2 is a block diagram showing the configuration of the detection device 2 of the blood cell counting device system 1 according to the embodiment of the present invention. Referring to FIG. 2, the detection device 2 includes a sample supply unit 4, a detection unit 5, a control unit 8, and a communication unit 9. The sample supply unit 4 is a fluid unit including a sample preparation device 4a including a chamber, a plurality of solenoid valves, a diaphragm pump, and the like. The sample preparation device 4a prepares a detection sample by mixing the subject's blood with a reagent. The sample supply unit 4 supplies the detection sample prepared by the sample preparation device 4a to the detection unit 5. The control unit 8 controls the operation of each component of the detection device 2. The communication unit 9 may be, for example, an RS-232C interface, a USB interface, or an Ethernet (registered trademark) interface, and transmits / receives data to / from the diagnosis support device 3.

[0020] FIG. 3 is a schematic plan view showing the configuration of the detection unit 5 of the blood cell counting device system 1 according to the embodiment of the present invention. Referring to FIG. 3, the detection unit 5 is an optical flow cytometer that detects white blood cells (WBC), reticulocytes (RET), mature red blood cells (RBC), and platelets (PLT) in blood by a flow cytometry method using a semiconductor laser. The term "red blood cells" is used here as including "reticulocytes (RET)" and "mature red blood cells (RBC)" for classification purposes. The detection unit 5 includes a flow cell 51 for forming a liquid flow of the detection sample. The flow cell 51 is formed in a tubular shape from a translucent material such as quartz, glass, or synthetic resin. The flow cell 51 has a flow path through which the detection sample and sheath liquid flow. The detection unit 5 includes a semiconductor laser light source 52 arranged to output a laser beam toward the flow cell 51. An illumination lens system 53 consisting of a plurality of lenses is provided between the semiconductor laser light source 52 and the flow cell 51. The illumination lens system 53 collects the parallel beam output from the semiconductor laser light source 52 to form a beam spot. The optical axis extends linearly from the semiconductor laser light source 52 through the flow cell 51. The photodiode 54 is provided on the optical axis so as to be located on the opposite side of the illumination lens system 53 from the flow cell 51. The beam stopper 54a is provided so as to block the light directly coming from the semiconductor laser light source 52.

[0021] When the detection sample flows through the flow cell 51, scattered light and fluorescence are generated based on the laser light. Of the scattered light and fluorescence, light in the direction of irradiation of the laser light (i.e., forward) is photoelectrically converted by the photodiode 54. Of the light traveling along the optical axis extending linearly from the semiconductor laser light source 52, light arriving directly from the semiconductor laser light source 52 is blocked by the beam stopper 54a. Only scattered light traveling substantially along this optical axis direction (hereinafter referred to as forward scattered light) is incident on the photodiode 54. The forward scattered light emitted from the detection sample flowing through the flow cell 51 is photoelectrically converted into an electric signal by the photodiode 54. Each photoelectrically converted electric signal (hereinafter referred to as a forward scattered light signal) is amplified by the amplifier 54b and output to the control unit 8. The intensity of the forward scattered light signal indicates the size of the blood cells.

[0022] The side collecting lens 55 is provided on the side of the flow cell 51, and is located in the direction of an optical axis intersecting with the optical axis extending linearly from the semiconductor laser light source 52 to the photodiode 54. The side collecting lens 55 collects the side light (i.e., the light output in the direction of the optical axis intersecting with the optical axis extending linearly from the semiconductor laser light source 52 to the photodiode 54) generated when the laser light is emitted to the detection sample flowing through the flow cell 51. A dichroic mirror 56 is provided downstream of the side collecting lens 55. The light collected by the side collecting lens 55 is separated into a scattered light component and a fluorescent component by the dichroic mirror 56. A photodiode 57 for receiving the side scattered light is provided in the optical axis direction along which the light reflected by the dichroic mirror 56 travels (i.e., the optical axis direction intersecting with the optical axis passing through the side collecting lens 55 and the dichroic mirror 56). On the optical axis passing through the side collecting lens 55 and the dichroic mirror 56, an optical filter 58a and a photodiode 58 for receiving the fluorescent light are provided.

[0023] The light reflected by the dichroic mirror 56 is side scattered light, which is photoelectrically converted into an electrical signal by the photodiode 57. Each photoelectrically converted electrical signal (hereinafter referred to as a side scattered light signal) is amplified by the amplifier 57a and output to the control unit 8. Each side scattered light signal indicates internal information of the blood cell (such as the size of the nucleus). The light transmitted through the dichroic mirror 56 is fluorescent light, which is wavelength selected by the optical filter 58a, and then photoelectrically converted into an electrical signal by the photodiode 58. Each photoelectrically converted electrical signal (hereinafter referred to as a fluorescent signal) is amplified by the amplifier 58b and output to the control unit 8. Each fluorescent signal indicates the degree of staining of the blood cell.

[0024] Fig. 4 is a block diagram showing the configuration of the first diagnosis support device 3 of the blood cell counting device system 1 according to the embodiment of the present invention. As shown in Fig. 4, the first diagnosis support device 3 includes at least a data processing unit (control unit) 31 including a CPU (central processing unit) and the like, an image display unit 32, and an input unit 33. The data processing unit 31 includes a CPU 31a, a memory 31b, a hard disk 31c, a readout device 31d, an input / output interface 31e, an image output interface 31f, a communication interface 31g, and an internal bus 31h. In the data processing unit 31, the CPU 31a is connected to each of the memory 31b, the hard disk 31c, the readout device 31d, the input / output interface 31e, the image output interface 31f, and the communication interface 31g via the internal bus 31h.

[0025] The CPU 31a controls the operation of each of the above-mentioned hardware components, and processes data received from the detection device 2 in accordance with a computer program 34 stored in the hard disk 31c.

[0026] The memory 31b is configured as a volatile memory such as an SRAM or a flash memory. A load module is loaded into the memory 31b when the computer program 34 is executed. The memory 31b stores temporary data and the like that is generated when the computer program 34 is executed.

[0027] The hard disk 31c is configured as a fixed storage device or the like, and is incorporated into the first diagnosis support device 3. The computer program 34 is downloaded from a portable storage medium 35, such as a DVD, a CD-ROM, or a USB flash drive, which stores information such as programs and data, by a reading device 31d, which is a portable disk drive. The computer program 34 is then stored in the hard disk 31c. The computer program 34 is loaded from the hard disk 31c into the memory 31b and executed. The computer program 34 may be a computer program downloaded from an external computer via the communication interface 31g.

[0028] The input / output interface 31e is connected to an input unit 33 configured as a keyboard, a tablet, or the like. The image output interface 31f is connected to an image display unit 32 which may be a CRT monitor, an LCD, or the like. Alternatively, the input unit 33 and the image display unit 32 may be included in a single device such as a touch-type monitor.

[0029] The communication interface 31g is connected to the internal bus 31h, and is connected to an external network such as the Internet, a LAN, or a WAN, thereby transmitting / receiving data to / from an external computer such as a second diagnosis support device 3' (described later) or the detection device 2. For example, the above-mentioned hard disk 31c is not limited to being incorporated in the first diagnosis support device 3, and may be an external storage medium such as an external storage device connected to the first diagnosis support device 3 via the communication interface 31g.

[0030] FIG. 5 is a block diagram showing the configuration of the second diagnosis support device 3' of the blood cell counting device system 1 according to the embodiment of the present invention. The second diagnosis support device 3' may have the same hardware configuration as the above-mentioned first diagnosis support device 3, and therefore detailed description will be omitted. As shown in FIG. 5, the communication interface 31g' transmits / receives data to / from the first diagnosis support device 3. In addition, the hard disk 31c' may store a message indicating an ICIS index. This message further includes an index indicating that the subject has or has a high probability of an infectious reaction, and a message indicating that the subject has or has a high probability of a non-infectious reaction, as diagnostic support information for supporting the output of an index (ICIS index) of the possibility determined for the infectious reaction of the subject. The hard disk 31c' may also store a score threshold (described later) for one or more of the multiple hematological parameters used to score the multiple hematological parameters for determining whether the reaction of the subject is an infectious reaction or a non-infectious reaction, and a threshold for a reliability test (described later).

[0031] The operation of the blood cell counting device system 1 according to the embodiment of the present invention will be described below. First, the sample supply unit 4 of the detection device 2 aspirates blood from a blood collection tube set in the blood collection tube set unit 2a, divides the aspirated blood into a plurality of aliquots according to a measurement command, and adds a specific dedicated reagent to each aliquot to prepare, for example, a RET detection sample, a DIFF detection sample, and a WBC / BASO detection sample. The RET detection sample is prepared by diluting the blood and staining it with a dedicated reagent for detecting reticulocytes. The DIFF detection sample is prepared by diluting the blood, hemolyzing it with a dedicated reagent for hemolyzing red blood cells, and staining it with a dedicated reagent for classifying white blood cells into a number of subgroups. The WBC / BASO detection sample is prepared by diluting the blood and hemolyzing it with a dedicated reagent for hemolyzing red blood cells. The sample supply unit 4 supplies the prepared detection sample to the flow cell 51 of the detection unit 5.

[0032] Fig. 6 is a flow chart showing a series of processes performed by the CPU 31a' of the data processing unit 31' of the second diagnosis support device 3' of the blood cell counting device system 1 according to the embodiment of the present invention. As shown in Fig. 6, the CPU 31a' first acquires a number of hematological parameters for the subject's blood, such as NEUT#, NE-SFL, RET#, HFLC#, IG#, EO#, Delta-He, RBC-He, and PLT (S31). This can be performed as follows.

[0033] When a detection sample is supplied to the flow cell 51, the CPU 31a of the first diagnosis support device 3 receives the forward scattered light signal, side scattered light signal, and fluorescent light signal data output by the detection unit 5 of the detection device 2 via the communication interface 31g and stores the data in the memory 31b. The CPU 31a creates a plurality of scattergrams based on the forward scattered light signal, side scattered light signal, and fluorescent light signal data detected by the detection unit 5 and stored in the memory 31b. The multiple scattergrams created by the CPU 31a include, for example, at least a RET scattergram (see FIG. 8) in which the Y axis indicates the intensity of the forward scattered light signal output by the detection unit 5 and the X axis indicates the intensity of the fluorescent signal output by the detection unit 5, a DIFF scattergram (see FIG. 9) in which the Y axis indicates the intensity of the fluorescent signal output by the detection unit 5 and the X axis indicates the intensity of the side scattered light signal output by the detection unit 5, and a WBC / BASO scattergram (see FIG. 10) in which the Y axis indicates the intensity of the forward scattered light signal output by the detection unit 5 and the X axis indicates the intensity of the side scattered light signal output by the detection unit 5. Alternatively, the X and Y axes of each scattergram may be reversed.

[0034] Next, the CPU 31a of the first diagnosis support device 3 determines a plurality of hematological parameters for the subject's blood using the scattergram as the detection result. Examples of such hematological parameters include NEUT#, NE-SFL, RET#, HFLC#, IG#, EO#, Delta-He, RBC-He, and PLT (described in detail later).

[0035] FIG. 8 shows a RET scattergram created by the blood cell counting device system 1 according to the embodiment of the present invention. Based on the RET scattergram, the CPU 31a of the first diagnosis support device 3 calculates the reticulocyte hemoglobin equivalent (RET-He) and the difference (Delta-He) between the reticulocyte hemoglobin equivalent (RET-He) and the hemoglobin equivalent of mature red blood cells (RBC-He). Both are hematological parameters obtained as follows. As shown in FIG. 8, the CPU 31a of the first diagnosis support device 3 uses the RET scattergram to identify three regions, a mature red blood cell (RBC) region 60, a platelet (PLT) region 61, and a reticulocyte (RET) region 62. Based on the RET scattergram, the CPU 31a determines RBC-He, which is the median forward scattered light intensity of all cells contained in the mature red blood cell region 60 (RBC), and RET-He, which is the median forward scattered light intensity of all cells contained in the reticulocyte region 62 (RET). The CPU 31a of the first diagnosis support device 3 calculates the reticulocyte count (RET#) from the reticulocyte region 62 as one of a plurality of hematological parameters. The CPU 31a of the first diagnosis support device 3 further calculates the platelet count (PLT) from the platelet region 61 as one of a plurality of hematological parameters. An example of such calculation is shown in Patent Document 1.

[0036] Next, the CPU 31a of the first diagnosis support device 3 calculates the neutrophil count (NEUT#) as one of a plurality of hematological parameters using the DIFF scattergram and the WBC / BASO scattergram. The term "granulocyte" is used herein to include both "mature granulocytes" and "immature granulocytes" in classification. "Mature granulocytes" include neutrophils (NEUT), eosinophils (EO), and basophils (BASO) in classification.

[0037] FIG. 9 shows a DIFF scattergram created by a white blood cell differential measurement by the blood cell counter system 1 according to the embodiment of the present invention. FIG. 10 shows a WBC / BASO scattergram created by the blood cell counter system 1 according to the embodiment of the present invention. As shown in FIG. 9, in the DIFF scattergram, blood cells are classified into six regions, namely, a monocyte (MONO) region 71, a lymphocyte (LYMPH) region 72, a neutrophil (NEUT) + basophil (BASO) region 73, an eosinophil (EO) region 74, an immature granulocyte (IG) region 75, and a highly fluorescent lymphocyte cell (HFLC) region 76. The sum of the number of neutrophils (NEUT) and the number of basophils (BASO) can be calculated by counting the number of white blood cells in the neutrophil (NEUT) + basophil (BASO) region 73 based on the DIFF scattergram. Here, the CPU 31a of the first diagnosis support device 3 further calculates the eosinophil count (EO#) from the eosinophil region 74 as one of a plurality of hematological parameters.

[0038] In order to calculate the neutrophil count (NEUT#) from the sum of the neutrophil count (NEUT) and the basophil count (BASO) according to the region 73 in FIG. 9 as one of the hematological parameters, the CPU 31a of the first diagnosis support device 3 determines the basophil count (BASO) using the WBC / BASO scattergram. As shown in FIG. 10, in the WBC / BASO scattergram, white blood cells are classified into two regions: a monocyte (MONO)+lymphocyte (LYMPH)+neutrophil (NEUT)+eosinophil (EO) region 81, and a basophil (BASO) region 82. Therefore, the number of basophils (BASO) in the basophil (BASO) region 82 can be calculated by counting the number of white blood cells in the basophil (BASO) region 82 based on the WBC / BASO scattergram. The neutrophil count (NEUT#), as one of several hematological parameters, can be obtained by subtracting the number of basophils (BASO) calculated based on the WBC / BASO scattergram from the sum of the number of neutrophils (NEUT) and the number of basophils (BASO) calculated based on the DIFF scattergram.

[0039] Next, the CPU 31a of the first diagnosis support device 3 calculates a value indicating the fluorescence intensity (NE-SFL) of neutrophils in blood, which is one of a plurality of hematological parameters, using the DIFF scattergram. In detail, the value (NE-SFL) in FIG. 9 can be obtained by calculating the median value of the fluorescence intensity of all cells contained in the neutrophil (NEUT) + basophil (BASO) region 73 (i.e., neutrophils (NEUT) and basophils (BASO)) based on the DIFF scattergram. The obtained value (NE-SFL) includes the influence of the fluorescence intensity of basophils (BASO), but since the number of basophils (BASO) is small, the influence is small.

[0040] Next, the CPU 31a of the first diagnosis support device 3 calculates the immature granulocyte count (IG#), which is one of a plurality of hematological parameters for granulocytes in blood, using the DIFF scattergram. In detail, the immature granulocyte count (IG#) can be obtained by counting the number of cells in the immature granulocyte (IG) region 75 based on the DIFF scattergram.

[0041] Next, the CPU 31a of the first diagnosis support device 3 calculates the high fluorescent lymphocyte cell count (HFLC#) for the antibody-synthesizing lymphocytes, which is one of a plurality of hematological parameters of blood, using the DIFF scattergram. In detail, the high fluorescent lymphocyte cell count (HFLC#) can be obtained by counting the number of cells in the high fluorescent lymphocyte cell (HFLC) region 76 based on the DIFF scattergram.

[0042] Those skilled in the art will appreciate that the above examples of obtaining multiple hematological parameters are not limiting and that other scattergrams and other hematological parameters may be determined.

[0043] Returning to FIG. 6, in step S31, the second diagnostic support device 3' acquires multiple hematological parameters, such as NEUT#, NE-SFL, RET#, HFLC#, IG#, EO#, Delta-He, RBC-He, and PLT, from the first diagnostic support device 3 by receiving the determined hematological parameters (as described above) via the communication interface 31g'.

[0044] Then, in step S32 of FIG. 6, the CPU 31a' of the second diagnosis support device 3' performs a reliability test on at least one of the hematological parameters acquired in step S31.

[0045] In particular, reliability tests may be performed on hematological parameters derived from white blood cell differential measurements, such as NE-SFL and NEUT#. Additionally, reliability tests may be performed on hematological parameters for white blood cell count, such as NEUT#, and / or red blood cell count, such as RET#.

[0046] The reliability test may be performed by comparing at least one of the hematological parameters with a threshold value, or a lower threshold value and an upper threshold value. That is, the reliability test may be performed by comparing the value of each hematological parameter used for the reliability test with a corresponding threshold value, or a corresponding lower threshold value and an upper threshold value. The threshold value(s) are predefined and set to ensure that the hematological parameters have valid or reliable values ​​that meet the quality requirements for the ICIS index value. In other words, the threshold value(s) are set to exclude unreliable values ​​that lead to erroneous determination of the ICIS index value.

[0047] Next, in step S33, the CPU 31a' of the second diagnosis support device 3' determines whether or not at least one of the hematological parameters has passed a reliability test, i.e., whether or not the acquired at least one hematological parameter is greater than a predetermined threshold or within a specific parameter range defined as a lower threshold and an upper threshold.

[0048] If the reliability test is passed (Yes in step S33), the CPU 31a' of the second diagnosis support device 3' determines an ICIS index value indicative of the possibility of an infectious reaction, in particular the ICIS index value indicative of the certainty of a bacterial infection (details to be described later) in the following step S34. On the other hand, if the reliability test is not passed (No in step S33), the CPU 31a' does not output an indication of the determined possibility (ICIS index) in the following step S36, but outputs a corresponding error code or error message (details to be described later). In addition, if the reliability test is not passed (No in step S33), the CPU 31a' may output the measurement result of at least one hematological parameter that fails the reliability test (see later for FIG. 12).

[0049] If the reliability test is passed, the CPU 31a' determines an ICIS index value that is associated with the possibility of an infectious reaction, in particular the likelihood of a bacterial infection, based on the acquired hematological parameters (step S34), and outputs the ICIS index value as output diagnostic support information in step S35.

[0050] In particular, for calculating the ICIS index value, the CPU 31a' may set ICIS points for the hematological parameters (Delta-He, RBC-He, NEUT#, EO#, PLT, NE-SFL, IG#, HFLC#) acquired in step S31, and calculate the ICIS index value by summing up the set ICIS points. This can be done by implementing parameter-specific ICIS rules as follows:

[0051] a) ICIS Rules for HFLC# Here, the CPU 31a' determines the ICIS point for the hematological parameter HFLC# based on the following rules.

[0052] [Table 1]

[0053] The first ICIS rule applies certain score thresholds M1, M2, and M3. Those skilled in the art will appreciate that the actual values ​​of the thresholds M1, M2, and M3 depend on the blood sample and the configuration and accuracy of the detection device 2, etc. Thus, according to the determined high fluorescent lymphocyte count HFLC#, a corresponding first ICIS point 0, 1, 2, or 4 is set.

[0054] b) ICIS rules for IG# and EO# Here, the CPU 31a' determines the ICIS points for the hematological parameters IG# and EO# based on the following rules.

[0055] [Table 2]

[0056] The second ICIS rule applies specific score thresholds M4, M5, M6, and M7. Those skilled in the art will appreciate that the actual values ​​of the thresholds M4, M5, M6, and M7 depend on the blood sample and the configuration and accuracy of the detection device 2. Thus, according to the determined immature granulocyte count IG# and the determined eosinophil count EO#, the corresponding second ICIS point 0, 1, 2, or 4 is set.

[0057] c) ICIS rules for NE-SFL Here, the CPU 31a' determines the ICIS point for the hematological parameter NE-SFL based on the following rules.

[0058] [Table 3]

[0059] The third ICIS rule applies certain score thresholds M8, M9, and M10. Those skilled in the art will appreciate that the actual values ​​of the thresholds M8, M9, and M10 depend on the blood sample and the configuration and accuracy of the detection device 2, etc. Thus, according to the determined median fluorescence value NE-SFL, a corresponding third ICIS point 0, 1, 2, or 4 is set.

[0060] d) ICIS Rules for Delta-He and RBC-He Here, the CPU 31a' determines the ICIS points for the hematological parameters Delta-He and RBC-He based on the following rules.

[0061] [Table 4]

[0062] The fourth ICIS rule applies specific score thresholds M11, M12, M13, and M14. Those skilled in the art will appreciate that the actual values ​​of the thresholds M11, M12, M13, and M14 depend on the blood sample and the configuration and accuracy of the detection device 2, etc. Thus, according to the determined Delta-He and RBC-He values, the corresponding fourth ICIS point 0, 1, 2, or 4 is set.

[0063] e) ICIS Rules for NEUT#, EO# and PLT Here, the CPU 31a' determines the ICIS points based on the following rules for the hematological parameters NEUT#, EO#, and PLT: With respect to the ICIS index, the total neutrophil granulocyte count may be understood as the sum of the IG# and NEUT# values ​​("immature and mature granulocytes"), hereafter referred to as NEUT#.

[0064] [Table 5]

[0065] The fifth ICIS rule applies certain score thresholds M15, M16, M17, M18, M19, and M20. Those skilled in the art will appreciate that the actual values ​​of the thresholds M15, M16, M17, M18, M19, and M20 depend on the blood sample and the configuration and accuracy of the detection device 2, etc. Thus, according to the determined NEUT#, EO#, and PLT values, the corresponding fifth ICIS point 0, 1, 2, or 4 is set.

[0066] As explained, in order to calculate the ICIS index value in step S34, a respective score threshold is set for the hematological parameters by applying a number of ICIS rules that compare the hematological parameters obtained in step S31 with respective score thresholds pre-stored in the hard disk 31c'. The patent document 1 further details how such score thresholds can be determined based on, for example, a ROC (Receiver Operating Characteristic) analysis using a ROC curve to determine the score thresholds, but a person skilled in the art will understand that other methods are equally applicable for determining the above score thresholds.

[0067] Therefore, the CPU 31a' can calculate the ICIS index value by summing up each ICIS point as determined according to the ICIS rules as described above. The minimum score is 0 points, indicating that the inflammatory response is very unlikely to be caused by an infection. The maximum score is 20 points. As described in Patent Document 1, those skilled in the art can understand that the closer the score is to 20 points, the higher the possibility that the inflammatory response is caused by an infection, such as a bacterial infection. The determination of the ICIS index is not limited to the above examples. In particular, those skilled in the art can understand that the determination of the ICIS index can be based on more or fewer hematological parameters or other ICIS rules.

[0068] According to a further embodiment, the CPU 31a' of the second diagnostic support device 3' may determine the type of infectious reaction, such as whether the inflammatory reaction of the subject is an infectious reaction or a non-infectious reaction, for example, whether the inflammatory reaction is an infectious reaction or a non-infectious inflammatory reaction, or whether the inflammatory reaction is a bacterial infectious reaction or a non-bacterial infectious reaction, based on the index (ICIS) calculated in step S34. Then, the output diagnostic support information may include both the ICIS index and the type of infectious reaction.

[0069] In a further embodiment, the CPU 31a' may determine whether the subject's reaction is an infectious reaction or a non-infectious inflammatory reaction based on the index (ICIS). In particular, the CPU 31a' may determine that the subject's reaction is an infectious reaction or is highly likely to be an infectious reaction if the index (ICIS) is equal to or greater than a judgment threshold stored in the hard disk 31c, and may determine that the subject's reaction is a non-infectious reaction or is highly likely to be an infectious reaction if the index (ICIS) is less than the judgment threshold.

[0070] Here, the explanation returns to the diagnostic support information output process performed by the CPU 31a' of the second diagnostic support device 3' (see FIG. 6). If the reliability test in step S33 is passed, the CPU 31a' outputs the diagnostic support information to the image display unit 32' via the image output interface 31f', and outputs it to another computer or a printer, etc., via the communication interface 31g' (step S35). In detail, the diagnostic support information includes the specific ICIS index value calculated in step S34, and may further include the type of infectious reaction determined.

[0071] Furthermore, if the reliability test is not passed, the CPU 31a' of the second diagnostic support device 3' reads out an error code or an error message from the hard disk 31c', outputs the error code or error message to the image display unit 32' via the image output interface 31f', and outputs it to another computer, a printer, etc. via the communication interface 31g' (step S36).

[0072] Although the above embodiment describes examples of hematological parameters NEUT#, NE-SFL, RET#, HFLC#, IG#, EO#, Delta-He, RBC-He, PLT, those skilled in the art will appreciate that the ICIS index value may be determined based on more or fewer hematological parameters, and in particular, not all of the above hematological parameters need to be used for the ICIS index value. For example, in the above embodiment, RET# is used for reliability testing, but may not be required for determining the ICIS index value.

[0073] FIG. 7 is a flow chart showing a series of processes performed by the CPU 31a' of the data processing unit 31' of the second diagnosis support device 3' of the blood cell counter system 1 according to another embodiment of the present invention. Here, unlike the flow of the process of FIG. 6, the reliability test is performed in step S32a only for a subset of the hematological parameters obtained in step S31. For example, as described above with reference to FIG. 6, even if a set of nine hematological parameters, NEUT#, NE-SFL, RET#, HFLC#, IG#, EO#, Delta-He, RBC-He, and PLT, is obtained in step S31, the reliability test S32a does not need to be performed for all of the hematological parameters in the hematological parameter set, but can be performed only for a limited subset, for example, for three parameters, NEUT#, NE-SFL, and RET#. Those skilled in the art will understand that since the reliability test is not required for all the obtained hematological parameters, this increases the efficiency of performing the reliability test for the ICIS index of the blood sample.

[0074] More specifically, according to step S32a in FIG. 7, the CPU 31a' of the data processor 31' of the second diagnosis support device 3' obtains a subset of hematological parameters and performs a reliability test on the subset. As described above, when a plurality of hematological parameters such as NEUT#, NE-SFL, RET#, HFLC#, IG#, EO#, Delta-He, RBC-He, and PLT are obtained, the subset of hematological parameters means a limited number of hematological parameters. In this non-limiting example, the subset may correspond to three parameters, NEUT#, NE-SFL, and RET#.

[0075] Here, the reliability must preferably be passed for the entire subset of hematological parameters in order to output the diagnostic support information (ICIS index). In other words, if the reliability test is successful (passed) for, for example, only one or two hematological parameters of the entire subset of hematological parameters, and fails for at least one other hematological parameter of the entire subset, then the reliability test of step 33a is not passed (does not pass).

[0076] The rationale for performing reliability testing on only a limited subset of acquired hematological parameters is based on the inventor's observation that there are relationships between hematological parameters when determining reliability. In particular, by considering the scattergrams generated, it was found that a reliable value for NEUT#, for example, is also relevant in leading to the determination that other hematological parameters are reliable, and vice versa.

[0077] Figures 15A and 15B show examples of this relationship. In particular, according to the scattergram in Figure 15A, it is easy to determine the median of the NE-SFL (see above for Figure 9) since there is a clearly defined population that allows this determination. However, Figure 15B shows a very small number of cases where the center of the neutrophil population is likely not the actual center, and the coefficient of variation between the dots in the scattergram is large, so that when the NEUT# is very small, the NE-SFL is unreliable.

[0078] Those skilled in the art will appreciate that failure of the reliability test for NE-SFL will have implications for other hematological parameters derived from the scattergram, for example, the reliability of IG# classification or HFLC# (compare FIG. 9) would generally be tested through NE-SFL, which is a sensitivity parameter and reflects the fluorescence measurement.

[0079] The reliability of Delta-He or RBC-He will be checked through RET#, since these parameters are obtained from the same RET scattergram and RET# affects the calculation of Delta-He and RBC-He. If the number of RET cells is less than the threshold, there are not enough cells and it is not possible to distinguish a reliable center of the RET population on the Y-axis, resulting in an unreliable Delta-He along with an unreliable RET-He. Here, Figures 16A and 16B show an example of this relationship for RET scattergrams, where Figure 16A shows an example where there is a clear RET population, while Figure 16B shows an example where there is (almost) no RET#, making RET-He unreliable. This unreliability also relates to the hematological parameter Delta-He (RET-He-RBC-He). That is, if RET-He is unreliable, Delta-He is also considered unreliable and therefore is not considered for the ICIS index calculation.

[0080] In step S32a of Fig. 7, each parameter of the subset may be compared with a corresponding threshold, or with a lower and an upper threshold. In the above non-limiting example, the CPU 31a' is configured (and in particular programmed) to check whether the RET# value is greater than a threshold, for example a value reflecting a minimum RET population, to obtain a RET-He value together with a reliable center of the RET population. The threshold is 0.004 x 10 6 / µL, 0.005 x 10 6 / µL, or 0.006 x 10 6 / μL, etc. One of ordinary skill in the art will appreciate that such thresholds will vary with different sample sizes or different analyzer settings.

[0081] If the RET# value is greater than this threshold, then the reliability check is passed for RET# (i.e., RET# has a reliable value). Otherwise, if the RET# value is less than or equal to this threshold, CPU 31a' generates a parameter specific message ("ICIS_RET_UNRELIABLE") as a code or flag indicating that the reliability check for RET has failed and an ICIS score cannot be calculated.

[0082] Furthermore, the CPU 31a' is configured (specifically programmed) to check whether the NE-SFL has a fluorescence intensity between a lower threshold and an upper threshold. If the fluorescence intensity is within the range defined between the lower and upper thresholds, the reliability test for the NE-SFL is passed (i.e., the NE-SFL has a reliable value). Otherwise, if the NE-SFL value is below this lower threshold or above this upper threshold, the CPU 31a' generates a parameter-specific message ("ICIS_NE_SFL_UNRELIABLE") as a code or flag indicating that the reliability test for the NE-SFL has failed and an ICIS score cannot be calculated.

[0083] Furthermore, CPU31a' is configured (specifically programmed) to check whether the NEUT# value is greater than a threshold value. Such threshold value reflects the minimum NEUT population required to obtain a reliable NE-SFL (fluorescence intensity of the NEUT region in the corresponding scattergram). If the NEUT# value is greater than this threshold value, the reliability check for NEUT# is passed (i.e., NEUT# has a reliable value). Otherwise, if the NEUT# value is less than or equal to this threshold value, CPU31a' generates a parameter-specific message ("ICIS_NEUT_UNRELIABLE") as a code or flag indicating that the reliability check for NEUT# has failed and an ICIS score cannot be calculated. The threshold value is 0.4×10 3 / µL, 0.5 x 10 3 / µL, or 0.6 x 10 3 / μL, etc. One of ordinary skill in the art will appreciate that such thresholds will vary with different sample sizes or different analyzer settings.

[0084] Based on this reliability test, CPU31a' determines in step S33a whether the reliability test has passed for all parameters of the subset, i.e., for all three hematological parameters, NEUT#, NE-SFL, and RET# in the above example.

[0085] If the reliability check passes for all parameters of the subset (Yes in step S33a), the CPU 31a' continues with the ICIS index calculation in step S34 (as described in FIG. 6) and the remaining steps described above in FIG.

[0086] Otherwise, if the reliability check is not passed for one or more parameters of the subset (No in step S33a), the CPU 31a' then outputs an error code (flag) or an output message, such as ICIS_NEUT_UNRELIABLE, ICIS_NE_SFL_UNRELIABLE, ICIS_RET_UNRELIABLE, etc., in the following step S36, identifying which parameters of the subset failed the reliability check as described in FIG. 7.

[0087] FIG. 11 shows an example of an output screen 100 for showing the results of the measurement of a blood sample according to the measurement instructions for calculating an ICIS index value, in which the determined hematological parameters are shown. Here, detailed determined values ​​of the hematological parameters of the blood sample, with specific sample ID, priority, blood collection date, etc., are shown in the output screen 100, for example, for NEUT#, LYMPH#, MONO#, etc. In addition, the ICIS index value is shown by a highlighted box 101, which shows a value of 16 for this blood sample. From this value, a person skilled in the art can understand that the inflammatory reaction of the subject is likely to be an infectious reaction. Since the ICIS index value is output as a result of the fact that it has passed the reliability test, a technically reliable ICIS index value can be provided.

[0088] FIG. 12 shows another example of an output screen 110 for showing the results of the measurement of a blood sample following a measurement command for calculating an ICIS index value, where the determined hematological parameter is, for example, NEUT#=0.31×10 3 / μL. The parameter for NEUT# is 0.31×10 3 / μL, which is less than the corresponding threshold (as described above), and therefore fails the reliability test, no ICIS index value is determined (shown as "not measurable" in the highlighted box 111 of FIG. 12) and the parameter NEUT# is not reliable for the ICIS index ("ICIS_NEUT_UNRELIABLE"). That is, although a specific numerical value was determined for this hematological parameter, the reliability test nevertheless identifies the measurement result as not reliable for the purposes of ICIS calculation and therefore does not output an ICIS index value. Thus, the error message or error code includes information indicating at least one hematological parameter (here, the hematological parameter for the NEUT population) that fails the reliability test. Note that in the output screen 110, the measurement result of the hematological parameter NEUT# that fails the reliability test is displayed even if no ICIS index value is displayed. This is because such NEUT# is considered to be correct and reliable. That is, the NEUT# is smaller than the threshold value determined by the reliability test, so the ICIS calculation is unreliable, but the NEUT# is correct and so is displayed. The same applies to RET measurements. If the RET# does not exist, RET-He and Delta-He are unreliable for ICIS calculations. However, the RET# is correct and so is displayed on the output screen.

[0089] The error message or error code may indicate the particular hematological parameter that failed the reliability test, allowing the operator to understand the cause of the ICIS calculation failure. For example, if the error message or error code indicates NE-SFL as the parameter that failed the reliability test, the operator can conclude that the fluorescence detector may have poor sensitivity or the staining reagent may have deteriorated, allowing the operator to take appropriate action.

[0090] In other embodiments, the reliability check of step S33 of FIG. 6 or step S33a of FIG. 7 may be performed for other conditions.

[0091] For example, the reliability test may include testing a hematological parameter reflecting the operating status of the detection device 2 for measuring blood. In particular, the hematological parameter NE-SFL reflects the sensitivity of detecting fluorescence from cells. Thus, this hematological parameter may indicate the operating status of a sample preparation device or a fluorescence detector in the detection device 2 for staining cells with a fluorescent dye.

[0092] Alternatively or additionally, the reliability check may include checking a parameter reflecting the quality of the reagent mixed with the blood. For example, the hematological parameter NE-SFL (which is a sensitivity parameter for detecting the fluorescent effect in area 73 of FIG. 9) may also reflect the degree of staining of the cells. This parameter may also indicate whether the staining reagent has deteriorated.

[0093] Alternatively or additionally, the reliability test may include testing a particular hematological parameter, the particular hematological parameter having a value related to obtaining a reliable value of another hematological parameter among the plurality of hematological parameters. For example, the inventors have recognized that a minimum NEUT population of a blood sample may be necessary to obtain a reliable NE-SFL. Similarly, the inventors have recognized that a minimum RET population may be necessary to obtain reliable RET-He and Delta-He parameters. This is because if the number of RET cells is less than a threshold, there will not be enough RET cells and thus a reliable center of the RET population on the Y-axis cannot be determined, resulting in an unreliable RET-He as well as an unreliable Delta-He. Such inherent dependencies or relationships between hematological parameters allow the reliability test to be performed on a reduced set of hematological parameters, such as the subsets described above, which further increases the time efficiency of the reliability test.

[0094] Furthermore, reliability tests may be performed not only on the actually acquired (measured) hematological parameters of the subject's blood, but also on the general conditions of the reagents and hematology counter system 1 used. Therefore, additional general reliability tests on the equipment used may be included. Examples of such general reliability tests include one or more of message format errors (indicating that the format of the message from the hematology analyzer (detection device 2) is invalid), aspiration errors, error flags, function errors, suspect samples, missing tests, and / or non-supported parameter units (indicating that the results from the hematology analyzer (detection device 2) include a blood test unit that is not supported for calculating the ICIS score).

[0095] For each of the general reliability tests described above, a corresponding individual error code may be provided. For example, "ICIS_Error_Result" includes a result error flag that indicates a measurement error of the blood analyzer (detection device 2) and makes it impossible to calculate an ICIS score.

[0096] Similarly, the error code "ICIS_ACTION_MESSAGE" from the blood analyzer (detection device 2) may include an action message such as "suspicious sample" or "check sample" that prevents the calculation of an ICIS score.

[0097] An embodiment has been described above in which the blood cell counting device system 1 includes a detection device 2, a first diagnostic support device 3, and a second diagnostic support device 3'. In such a configuration, the first diagnostic support device can evaluate the forward scattered light signal, side scattered light signal, and fluorescent signal data to generate corresponding scattergrams and determine a set of hematological parameters for the subject's blood sample. The second diagnostic support device 3' then obtains the multiple hematological parameters and performs a reliability test as described above.

[0098] According to another embodiment, the blood cell counting device system 1 may include a detection device 2 and a single diagnostic support device 3. In such a configuration, the diagnostic support device 3 may evaluate the forward scattered light signal, side scattered light signal, and fluorescence signal data to generate corresponding scattergrams, and determine a set of hematological parameters for the subject's blood sample to obtain multiple hematological parameters and perform the reliability test as described above.

[0099] Such another embodiment for implementing the method according to the flowchart of Fig. 13 may be used. In particular, according to step S51 of Fig. 13, the CPU 31a of the diagnosis support device 3 may receive data of the forward scattered light signal, the side scattered light signal, and the fluorescent light signal output by the detection unit 5 of the detection device 2 via the communication interface 31g and store the data in the memory 31b. Thereafter, in step S52, the CPU 31a creates at least corresponding scattergrams, for example, a RET scattergram showing the intensity of the forward scattered light signal output by the detection unit 5 on the Y axis and the intensity of the fluorescent signal output by the detection unit 5 on the X axis, a DIFF scattergram showing the intensity of the fluorescent signal output by the detection unit 5 on the Y axis and the intensity of the side scattered light signal output by the detection unit 5 on the X axis, and a WBC / BASO scattergram showing the intensity of the forward scattered light signal output by the detection unit 5 on the Y axis and the intensity of the side scattered light signal output by the detection unit 5 on the X axis.

[0100] Next, the CPU 31a of the diagnosis support device 3 acquires a plurality of hematological parameters of the subject's blood using the scattergram as the detection result. Examples of such hematological parameters include (as described above) NEUT#, NE-SFL, RET#, HFLC#, IG#, EO#, Delta-He, RBC-He, and PLT.

[0101] Next, the CPU 31a of the diagnosis support device 3 also performs the reliability tests of steps S54 and S55, the ICIS index value calculation step (step S56), and the output of the diagnosis support information (step S57) or the output of an error code or an error message (step S58). Steps S54 to S58 correspond to steps S32 to S36 in Fig. 6. Those skilled in the art will appreciate that, unlike the embodiment described with respect to Fig. 6 in which the workload of determining the set of hematological parameters and the reliability test is shared between two diagnosis support devices, all steps in Fig. 13 are performed by a single diagnosis support device 3.

[0102] Another embodiment may be used to implement the method according to the flowchart of FIG. 14. Here, in comparison with FIG. 13, the reliability test of steps S54a and S55a is performed on a subset of hematological parameters, i.e., not on all of the set of hematological parameters as obtained from the scattergram of step S53. As described above, the full set of hematological parameters as obtained by the single diagnostic support device in step S53 may be as follows: NEUT#, NE-SFL, RET#, HFLC#, IG#, EO#, Delta-He, RBC-He, PLT. In this example, the subset of hematological parameters used for the reliability test may correspond to three parameters: NEUT#, NE-SFL, RET#. Even in this other embodiment applying a single diagnostic support device, using only a subset of hematological parameters for the reliability test allows for a more efficient implementation of the reliability test.

[0103] The above-mentioned embodiment has a blood cell counting device system 1 including a detection device 2, and the detection device 2 includes a detection unit 5 configured to detect multiple types of characteristic information of a blood sample, such as forward scattered light, side scattered light, and fluorescence from cells after passing through a flow cell. The detection device 2 may additionally or alternatively include another detection unit configured to measure direct current (DC) impedance of cells of the blood sample individually passing through a cell matching zone. The detection device 2 may additionally or alternatively include yet another detection unit configured to measure radio frequency (RF) conductivity of cells of the blood sample individually passing through a cell matching zone.

[0104] The above embodiment has been described in which the WBC / BASO detection sample for identifying basophils (BASO) is prepared by diluting blood and further performing hemolysis treatment using a dedicated reagent for hemolyzing red blood cells. Alternatively, the detection sample for identifying basophils (BASO) may be prepared by diluting blood, hemolyzing it, and further performing staining treatment using a dedicated reagent for staining blood cells. In this case, a scattergram showing the intensity of the forward scattered light signal on the Y axis and the intensity of the fluorescent signal on the X axis may be prepared for classifying the cells.

[0105] An embodiment has been described above in which both the DIFF scattergram and the WBC / BASO scattergram are analyzed to classify white blood cells into five groups: monocytes (MONO), lymphocytes (LYMPH), neutrophils (NEUT), basophils (BASO), and eosinophils (EO). Alternatively, only the DIFF scattergram may be analyzed to classify white blood cells into the five groups.

[0106] An embodiment has been described above in which if the reliability check passes then the ICIS index value is output to the output screen, whereas if the reliability check fails then the ICIS index value is not output to the output screen. Alternatively, if the reliability check fails then the ICIS index value may be output to the output screen along with a flag indicating that the ICIS index value is not reliable.

[0107] Above are described embodiments in which an ICIS index value is output as an indication of a possible infectious response in a subject. Alternatively, a flag or message indicating a possible infectious response in a subject may be output as this indication.

[0108] The above describes an embodiment in which the hematological parameter NE-SFL is used as a parameter reflecting the quality of the reagent mixed with the blood, since the NE-SFL reflects the degree of staining of cells by the staining reagent. Alternatively or additionally, a hematological parameter reflecting the quality of the lytic reagent may be used. For example, a white blood cell count, such as a monocyte or neutrophil count, may be used as a parameter reflecting the quality of the lytic reagent, since an abnormally high number of monocytes or neutrophils in the presence of excessive debris indicates a lysis failure. [Explanation of symbols]

[0109] 1. Hematology Analyzer System 2a Blood collection tube set section 2b Push button switch 3a, 3a' transmission cable 2. Detection device 3. First diagnostic support device 3' Second diagnostic support device 4. Sample supply section 4a Sample preparation device 5. Detection section 8. Control Unit 9. Communications Department 31, 31' Data processing section 31a, 31a' CPU 31b, 31b' memory 31c, 31c' hard disk 31d, 31d' reading device 31e, 31e' Input / Output Interface 31f, 31f' Image output interface 31g, 31g' communication interface 32, 32' Image display section 33, 33' Input section 34, 34' Computer Program 54b Amplifier 57a Amplifier 58b Amplifier

Claims

1. A method for testing a subject's blood using a blood cell counting system, comprising: preparing a measurement sample by mixing the blood with a reagent for classifying white blood cells, and measuring the measurement sample by a flow cytometry method to obtain a plurality of hematological parameters including at least a first parameter related to neutrophils and a second parameter related to other blood cells; conducting a reliability test based on at least the first parameter of the plurality of hematological parameters; calculating an index value related to a likelihood of an infectious response for the subject based on the plurality of hematological parameters in response to the reliability test being passed; A method for providing the above.

2. The method of claim 1 , wherein the step of performing the reliability test comprises testing a subset of the hematology parameters.

3. 3. The method of claim 1 or 2, wherein the step of performing the reliability check comprises testing hematological parameters derived from a white blood cell differential measurement.

4. The method of claim 1 , wherein the step of performing a reliability test comprises testing the number of neutrophils as the first parameter.

5. 5. The method of claim 1, wherein the step of performing a reliability check comprises testing a hematological parameter whose value is relevant for obtaining a reliable value of another hematological parameter of the plurality of hematological parameters.

6. 6. The method of claim 1, wherein the step of performing the reliability check comprises comparing the value of each of the hematological parameters used in the reliability check with a corresponding threshold value, or with corresponding lower and upper threshold values.

7. 7. The method of claim 1, further comprising outputting a measurement result of at least one hematological parameter that fails the reliability test if the reliability test is not passed.

8. The method of claim 1 , further comprising outputting an error message or error code if the authenticity check is not passed.

9. The method of claim 8 , wherein the error message or error code includes information indicative of at least one hematological parameter that causes the reliability test to fail.

10. 10. The method of claim 1, further comprising performing a general reliability test of the detection device that measures the blood.

11. 11. The method of claim 1, wherein the step of performing the reliability test comprises testing a hematological parameter reflecting an operational state of a detection device that measures the blood or a hematological parameter reflecting a quality of a reagent mixed with the blood.

12. A blood cell counting device which prepares a measurement sample by mixing blood with a reagent for classifying white blood cells, and measures the measurement sample by a flow cytometry method to obtain a plurality of hematological parameters including at least a first parameter related to neutrophils and a second parameter related to other blood cells; conducting a reliability test based on at least the first parameter of the plurality of hematological parameters; and a diagnostic support device that calculates an index value relating to the possibility of an infectious reaction of the subject based on the plurality of hematological parameters in response to passing the reliability test.

13. A computer program product comprising a computer readable medium having stored thereon instructions capable of causing a general purpose computer to perform the operations of the method according to any one of claims 1 to 11.

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