MIS-C Evaluation Using Monocyte Scatter Parameters
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Solution Overview
Problem
Current methods for diagnosing Multisystem Inflammatory Syndrome in Children (MIS-C) associated with SARS-CoV-2 are time-consuming and require intensive laboratory resources, with laboratory tests being non-specific and less informative at the time of critical clinical decision making.
Innovation Solution
An automated system using light scatter detectors and data processing to analyze monocyte or granulocyte cell population parameters in a body fluid sample, enabling rapid evaluation of MIS-C based on monocyte or granulocyte population parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive laboratory evaluation is performed to assess MIS-C, then diagnostic accuracy is improved, but time consumption and laboratory resource usage increase
Solution Approach 1:
The patent extracts and focuses on specific cell population parameters (monocyte distribution width, immature granulocyte counts) from the comprehensive laboratory evaluation. By isolating these key parameters that are most indicative of MIS-C, the system achieves rapid diagnosis within minutes while maintaining diagnostic accuracy, eliminating the need to perform all recommended laboratory tests
Solution Approach 2:
The system performs preliminary analysis of cell population parameters using automated hematology analyzers before committing to more time-consuming comprehensive laboratory evaluation. This preliminary screening identifies patients who likely have MIS-C based on characteristic cell population abnormalities, enabling early intervention while reducing overall time consumption
2Measurement precision
If comprehensive laboratory evaluation is performed to assess MIS-C, then diagnostic accuracy is improved, but laboratory resource usage increases
Solution Approach 1:
The patent extracts and focuses on specific cell population parameters (monocyte distribution width, immature granulocyte counts) from the comprehensive laboratory evaluation. By isolating these key parameters that are most indicative of MIS-C, the system achieves rapid diagnosis within minutes while maintaining diagnostic accuracy, eliminating the need to perform all recommended laboratory tests
Solution Approach 2:
The system leverages existing automated hematology analyzer capabilities to perform the MIS-C assessment using routine complete blood count parameters. By utilizing equipment and parameters that are already part of standard laboratory workflows, the system minimizes additional laboratory resource requirements while maintaining diagnostic accuracy
3Speed
If specific cell population parameters are analyzed using automated systems, then diagnostic speed is improved, but measurement specificity must be maintained
Solution Approach 1:
The patent utilizes changes in cell population parameters (monocyte distribution width, immature granulocyte counts) that occur in MIS-C patients. By monitoring these specific parameter changes rather than requiring comprehensive cellular analysis, the system achieves rapid diagnosis while maintaining measurement specificity through established reference ranges and diagnostic criteria
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Provides rapid and informative detection of MIS-C, reducing the time required for diagnosis and minimizing the need for intensive laboratory resources.
Implementation Method 1
one or more light scatter detector units (350A) configured to measure light scattered from the light source scattered by the cells in the body fluid sample
Data Source
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AI summary
Systems and methods for identifying Multisystem Inflammatory Syndrome in Children (MIS-C) may use various hematological parameters and combinations of hematological parameters. Such parameters and combinations may use monocyte distribution width (MDW), though other parameters may also be used. Using this approach, area under curve values of 0.8 or greater may be achieved. Such parameters may also be used in treatment of MIS-C, including evaluation of status of hospitalized patients to determine when such patients may be safely discharged.