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.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Johns Hopkins University NIH-funded |
| Lab location | 1 site (Baltimore, United States) |
| Project start | January 1, 2021 |
| Project end | November 30, 2025 |
| Funding year | 2023 |
| Award (this year) | $1,516,672 |
| NIH project number | 3R33HD105591-03S1 |
| Project ID | NIH-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
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Using data science to improve diagnosis and management of MIS-C in children
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 it aims to create helpful tools for doctors to better diagnose and treat kids who show signs of MIS-C or Kawasaki disease.
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.