NIH-funded research NIH-funded research

Identifying and managing a serious inflammatory syndrome in children linked to COVID-19.

Official title: A data science approach to identify and manage Multisystem Inflammatory Syndrome in Children (MIS-C) associated with SARS-CoV-2 infection and Kawasaki disease in pediatric patients

Funded at Johns Hopkins University · NIH-10847802 · Data updated 2026-11-12

This study is looking at a condition called Multisystem Inflammatory Syndrome in Children (MIS-C), which has come up during the COVID-19 pandemic, and aims to create helpful tools for doctors to better diagnose and treat kids with MIS-C or Kawasaki disease by using data from past cases.

More SARS-CoV-2 research and trials

Quick facts

Grant typeNIH-funded research
Study typeNIH-funded research
Funding institutionJohns Hopkins University
NIH-funded
Lab location1 site (Baltimore, United States)
Project startJanuary 1, 2021
Project endNovember 30, 2025
Funding year2023
Award (this year)$1,516,672
NIH project number3R33HD105591-03S1
Project IDNIH-10847802 on NIH RePORTER

Who could benefit from this research

Could help

Ideal candidates for this research are pediatric patients aged 0-21 who present with symptoms indicative of MIS-C or Kawasaki disease.

Less likely to help

Patients who do not exhibit symptoms of MIS-C or Kawasaki disease are unlikely to benefit from this research.

What this research studies

This research investigates Multisystem Inflammatory Syndrome in Children (MIS-C), which has emerged during the COVID-19 pandemic and shares similarities with Kawasaki disease. The study aims to develop machine-learning models to improve diagnosis and management of MIS-C by leveraging existing predictive tools for Kawasaki disease. It will involve analyzing clinical data to create decision support systems that help healthcare providers make informed choices for pediatric patients showing symptoms of either condition. The research will validate these models to ensure they are effective in real-world clinical settings.

Why it matters

Potential benefit: If successful, this research could lead to more accurate and timely diagnosis and management of MIS-C in children, potentially improving patient outcomes.

How similar studies have gone: Previous research has shown success in using machine-learning approaches for similar conditions, suggesting a promising avenue for this study.

Where this research is happening

  • Johns Hopkins University
    Baltimore, United States
    Active

Researchers

  • Principal investigator: Manlhiot, Cedric — Johns Hopkins University
  • Study coordinator: Manlhiot, Cedric

Related research

Other NIH-funded projects on the same topics.

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page.
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.