Using machine learning to find sleep apnea patients at risk for heart disease
Application of Machine Learning to Identify Obstructive Sleep Apnea Subgroups at Risk for Atherosclerosis Progression and Cardiovascular Disease Events (OSA-GRANDE)
['FUNDING_R01'] · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · NIH-11041046
This study is looking at how advanced computer technology can help find people with obstructive sleep apnea who might be more likely to develop heart problems, so that doctors can tailor treatments to each person's needs and improve their care.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI (nih funded) |
| Locations | 1 site (NEW YORK, UNITED STATES) |
| Trial ID | NIH-11041046 on ClinicalTrials.gov |
What this research studies
This research investigates how machine learning can analyze various data sources to identify patients with obstructive sleep apnea (OSA) who are at higher risk for developing cardiovascular disease (CVD). By examining multimodal data beyond traditional sleep studies, the project aims to create predictive tools that can forecast CVD events and understand how different patients respond to CPAP treatment. The goal is to enhance patient care by personalizing treatment strategies based on individual risk profiles. Participants will be monitored and their health records will be used to validate the effectiveness of these predictive models.
Who could benefit from this research
Good fit: Ideal candidates for this research include adults diagnosed with obstructive sleep apnea who are at risk for cardiovascular disease.
Not a fit: Patients without obstructive sleep apnea or those who do not have cardiovascular disease risk factors may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to better-targeted treatments for sleep apnea patients, potentially reducing their risk of heart disease.
How similar studies have performed: Previous research has shown promise in using machine learning for health predictions, suggesting that this approach could yield significant insights in the context of sleep apnea and cardiovascular risk.
Where this research is happening
NEW YORK, UNITED STATES
- ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI — NEW YORK, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: SHAH, NEOMI A — ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- Study coordinator: SHAH, NEOMI A
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.
Conditions: acute coronary syndrome