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Stratification of Pediatric COVID-19 Cases Using Inflammatory Biomarker Profiling and Machine Learning.

Devika Subramanian1, Aadith Vittala1, Xinpu Chen2

  • 1Department of Computer Science, Rice University, 6100 Main St. MS 132, Houston, TX 77005, USA.

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|September 9, 2023
PubMed
Summary
This summary is machine-generated.

A novel cytokine/chemokine assay panel accurately identifies multisystem inflammatory syndrome in children (MIS-C) in SARS-CoV-2 infected patients. This sensitive and specific method aids in early MIS-C detection across various COVID-19 variants.

Keywords:
COVID-19SARS CoV-2cytokineinflammationmachine learning

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Area of Science:

  • Pediatric immunology
  • Infectious diseases
  • Biomarker discovery

Background:

  • Multisystem inflammatory syndrome in children (MIS-C) is a rare but serious complication of SARS-CoV-2 infection.
  • Accurate and early identification of MIS-C is crucial for timely intervention and improved patient outcomes.
  • Current diagnostic methods may lack the sensitivity and specificity required for definitive early detection.

Purpose of the Study:

  • To develop and validate an objective assay panel for identifying MIS-C in pediatric patients with SARS-CoV-2 infection.
  • To assess the diagnostic performance of a novel cytokine/chemokine assay compared to standard laboratory markers.
  • To determine if a reduced panel of key biomarkers can maintain high diagnostic accuracy.

Main Methods:

  • Retrospective study involving four groups of pediatric patients: COVID-19, MIS-C, and uninfected controls.
  • Measurement of standard inflammation markers and a novel cytokine/chemokine array in patient blood samples.
  • Development and validation of a logistic regression model using cross-validation and independent patient cohorts across different SARS-CoV-2 variants.

Main Results:

  • The cytokine/chemokine panel achieved a significantly higher diagnostic performance (AUROC 0.95, F1 0.91) than standard markers (AUROC 0.86, F1 0.78) in the training set.
  • The panel demonstrated high accuracy across validation cohorts infected with alpha, delta, and omicron variants (AUROC range 0.89-0.99).
  • A subset of 10 cytokines achieved performance comparable to the full 16-cytokine panel, and adding standard markers did not improve results.

Conclusions:

  • A 16-cytokine/chemokine panel offers a highly sensitive and specific method for identifying MIS-C in SARS-CoV-2 infected children.
  • A reduced panel of the top 10 cytokines maintains excellent diagnostic performance.
  • This assay panel provides an objective tool for MIS-C detection, applicable across major SARS-CoV-2 variants.