# Diagnosing and predicting risk in children with SARS-CoV-2- related illness

> **NIH NIH R61** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2022 · $400,000

## Abstract

In the wake of COVID-19 pandemic, Multisystem Inflammatory Syndrome in Children (MIS-C) has
evolved as a new threat to children exposed to SARS-CoV-2. Currently there are no diagnostic
tests to readily identify these patients nor are there tools to predict disease progression. Through
established, funded, multi-center consortia in the U.S. (CHARMS: Characterization of MIS-C and
its Relationship to Kawasaki Disease funded by PCORI) and the UK (DIAMONDS), we have
collected clinical data and samples to support development and testing of diagnostic and
prognostic tests for MIS-C. In phase 1 of this project (R61HD105590, years 1-2), we used these
data to devise machine learning-based clinical decision support tool (KIDMATCH) to assist
clinicians in diagnosis of MIS-C and other causes of fever in children. This proposal focuses on
the development of a Software as a Medical Device (SaMD) and clinical deployment of this SaMD
in a clinical setting. Additionally, we aim to develop a quality management system (QMS) to
minimize and manage unintentional outcomes related to patient safety as required for FDA
regulatory approval. To this end, this proposal aims to further develop a cross-platform SMART-
on-FHIR app for display of the KIDMATCH outputs for integration within electronic health records.
In close collaboration between our clinical and data science teams, we will evaluate the
KIDMATCH app set-up, user workflow and physician preferences through structured interviews,
simulations, and direct feedback. Finally, we aim to complete an ongoing application for
Emergency Use Authorization (EUA) to enable wider deployment and commercialization of the
KIDMATCH SaMD. The synergistic expertise of the investigative team in this proposal provides
a unique opportunity to create diagnostic tools for children suffering from the spectrum of SARS-
CoV-2 illnesses.
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## Key facts

- **NIH application ID:** 10653509
- **Project number:** 3R61HD105590-02S1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** JANE C BURNS
- **Activity code:** R61 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $400,000
- **Award type:** 3
- **Project period:** 2021-01-01 → 2022-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10653509

## Citation

> US National Institutes of Health, RePORTER application 10653509, Diagnosing and predicting risk in children with SARS-CoV-2- related illness (3R61HD105590-02S1). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/10653509. Licensed CC0.

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