Predicting severe COVID-19 illness in children using saliva analysis and AI.
Severity Predictors Integrating salivary Transcriptomics and proteomics with Multi neural network Intelligence in SARS-CoV2 infection in Children (SPITS MISC)
This study is looking at how changes in saliva can help us understand which kids might get more seriously ill from COVID-19, so we can find ways to help them sooner.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Central Michigan University NIH-funded |
| Lab location | 1 site (Mount Pleasant, United States) |
| Project ID | NIH-10733697 on NIH RePORTER |
What this research studies
This research investigates how salivary biomarkers and clinical data can be used to predict the severity of COVID-19 in children. By analyzing changes in microRNA profiles in saliva, the study aims to identify which children are at higher risk for severe illness, including Multisystem Inflammatory Syndrome (MIS-C). The approach combines advanced artificial intelligence techniques with biological data to create a predictive model. This could lead to earlier interventions for those at risk, improving health outcomes.
Who could benefit from this research
Good fit: Ideal candidates for this research are children aged 0-21 who have been exposed to SARS-CoV-2.
Not a fit: Patients who have not been exposed to SARS-CoV-2 or are over the age of 21 may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could enable early identification and treatment of children at risk for severe COVID-19 complications.
How similar studies have performed: While research on salivary biomarkers is ongoing, this specific integration of AI with salivary analysis for predicting COVID-19 severity in children is a novel approach.
Where this research is happening
Mount Pleasant, United States
- Central Michigan University — Mount Pleasant, United States (Active)
Researchers
- Principal investigator: Sethuraman, Usha — Central Michigan University
- Study coordinator: Sethuraman, Usha
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 below.