# US 11,114,205 B2 · Infection detection and differentiation systems and methods > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,114,205 B2 - Document ID: US11114205B2 - Status: Granted - Kind: B2 - Application number: 16/073,757 - Filed: 2017-01-24 - Published: 2019-11-14 - Granted: 2021-09-07 - Earliest claimed: 2016-01-28 - Assignees: Beckman Coulter, Inc. - Applicants: Beckman Coulter, Inc. - Inventors: Robert T. Magari; Diana B. Careaga; Fernando P. Chaves; Liliana M. Tejidor - Web page: https://patentgrep.com/patent/US11114205B2 ## CPC - G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems - G01N 15/0266: {with electrical classification} - G01N 15/1031: by measuring electrical or magnetic effects - G01N 15/12: by observing changes in resistance or impedance across apertures when traversed by individual particles, e.g. by using the Coulter principle - G01N 15/1429: Signal processing - G01N 15/1434: Optical arrangements - G01N 15/1459: {the analysis being performed on a sample stream} - G16H 10/40: for data related to laboratory analysis, e.g. patient specimen analysis - G16H 50/30: for calculating health indices; for individual health risk assessment - G01N 2015/012: {Red blood cells} - G01N 2015/014: {Reticulocytes} - G01N 2015/016: {White blood cells} - G01N 2015/018: {Platelets} - G01N 2015/1006: {for cytology} - G01N 2015/1024: {Counting particles by non-optical means} - G01N 2015/1029: {Particle size} - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA - G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q) ## Abstract Embodiments may include an automated method for evaluating an infection status associated with a blood sample obtained from an individual. Methods may include determining, using a first module, a white blood cell concentration associated with the blood sample. In addition, methods may include determining, using a second module, a monocyte volume measure associated with the blood sample. Methods may include evaluating, using a data processing module, the infection status associated with the blood sample. The data processing module may include a processor and a computer readable medium. The computer readable medium may be programmed with a computer application. This computer application, when executed by the processor, may cause the processor to calculate a parameter using a function comprising the white blood cell concentration and the monocyte volume measure. The computer application may also cause the processor to evaluate the infection status associated with the blood sample based on the parameter. ## Claims ### Claim 1 An automated method for evaluating an infection status associated with a blood sample obtained from an individual, the method comprising: delivering a hydrodynamically focused stream of the blood sample toward a cell interrogation zone of an optical element; determining, using a first module, a cell count or concentration associated with the blood sample; determining, using a second module, a monocyte volume measure associated with the blood sample, wherein the second module determines the monocyte volume measure based on measurements of cells of the blood sample passing individually through the cell interrogation zone; and evaluating, using a data processing module, the infection status associated with the blood sample, wherein the data processing module comprises a processor and a tangible non-transitory computer readable medium, and the computer readable medium is programmed with a computer application that, when executed by the processor, causes the processor to calculate a parameter using a function comprising exp ⁡ ( c - a × VMo - b × CoC ) 1 + exp ⁡ ( c - a × VMo - b × CoC ) where: VMo is the monocyte volume measure, CoC is the cell count or concentration, and a, b, and c are real number constants and to evaluate the infection status associated with the blood sample based on the parameter. ### Claim 2 (depends on 1) The automated method of claim 1, wherein the cell count or concentration comprises a white blood cell count. ### Claim 3 (depends on 1) The automated method of claim 1, wherein the cell count or concentration comprises a neutrophil concentration. ### Claim 4 (depends on 1) The automated method of claim 1, wherein the monocyte volume measure is a standard deviation of monocyte volume associated with the blood sample. ### Claim 5 (depends on 2) The automated method of claim 2, wherein the monocyte volume measure is a standard deviation of monocyte volume. ### Claim 6 (depends on 1) The automated method of claim 1, wherein evaluating an infection status comprises an area under the curve in a receiver operating characteristic curve of 0.85 or higher. ### Claim 7 (depends on 1) The automated method of claim 1, wherein evaluating an infection status comprises a specificity for an infection greater than 0.80. ### Claim 8 (depends on 1) The automated method of claim 1, wherein evaluating an infection status comprises a sensitivity for an infection greater than 0.80. ### Claim 9 (depends on 1) The automated method of claim 1, wherein the infection status is a sepsis status. ### Claim 10 (depends on 1) The automated method of claim 1, wherein the infection status is a post-surgical infection status. ### Claim 11 (depends on 1) The automated method of claim 1, wherein excluding the monocyte volume measure, calculating the parameter does not comprise using a mean corpuscular volume, a platelet concentration, a mean neutrophil volume, a standard deviation of neutrophil volume, or a mean monocyte volume. ### Claim 12 (depends on 1) The automated method of claim 1, wherein the method does not comprise using a biomarker. ### Claim 13 (depends on 1) The automated method of claim 1, wherein evaluating the infection status associated with the blood sample comprises comparing the parameter to a cutoff. ### Claim 14 (depends on 13) The automated method of claim 13, wherein the cutoff is calculated by maximizing an estimated value of sensitivity for an infection for a value of specificity for an infection. ### Claim 15 (depends on 13) The automated method of claim 13, further comprising evaluating that an infection is not present in the blood sample when the parameter is less than the cutoff. ### Claim 16 (depends on 13) The automated method of claim 13, further comprising evaluating that an infection is present in the blood sample when the parameter is greater than or equal to the cutoff. ### Claim 17 (depends on 15) The automated method of claim 15, wherein the cutoff is 0.91 or greater. ### Claim 18 (depends on 15) The automated method of claim 15, wherein the individual has systemic inflammatory response syndrome. ### Claim 19 (depends on 15) The automated method of claim 15, wherein evaluating the infection status comprises determining the individual does not have sepsis. ### Claim 20 (depends on 1) The automated method of claim 1, further comprising: measuring, with an electrode assembly, current (DC) impedance of cells of the blood sample passing individually through the cell interrogation zone; wherein the second module determines the monocyte volume measure based on the DC impedance measurement of cells of the blood sample. ### Claim 21 An automated system for evaluating an infection status associated with a blood sample obtained from an individual, the system comprising: a first module configured to receive the blood sample via a blood sampling valve and to determine a cell count or concentration of the blood sample; a second module comprising an optical element comprising an interrogation zone adapted to receive a hydrodynamically focused stream of the blood sample and to determine a monocyte volume measure based on measurements of cells of the blood sample passing individually through the interrogation zone; and a data processing module in connectivity with the first module and the second module, the data processing module comprising a processor and a tangible non-transitory computer readable medium, the tangible non-transitory computer readable medium programmed with a computer application that, when executed by the processor, causes the processor to calculate a parameter using a function comprising exp ⁡ ( c - a × VMo - b × CoC ) 1 + exp ⁡ ( c - a × VMo - b × CoC ) where: VMo is the monocyte volume measure, CoC is the cell count or concentration, and a, b, and c are real number constants, and to evaluate the infection status associated with the blood sample based on the parameter. ### Claim 22 An automated system for evaluating the infection status associated with a blood sample obtained from an individual, the system comprising: a conduit configured to receive and direct movement of the blood sample through an aperture; an optical element comprising an interrogation zone adapted to receive a hydrodynamically focused stream of the blood sample; and a data processing module configured to evaluate the infection status based on a parameter calculated using a function comprising exp ⁡ ( c - a × VMo - b × CoC ) 1 + exp ⁡ ( c - a × VMo - b × CoC ) where: VMo is a monocyte volume measure based on measurements of cells of the blood sample passing individually through the cell interrogation zone, CoC is a cell count or concentration associated with the blood sample directed through the aperture, and a, b, and c are real number constants.