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Qatar Cardiometabolic Retrospective Cohort-Analysis Using Artificial Intelligence
Sponsor: Weill Cornell Medical College in Qatar
Summary
Cardiovascular disease is the leading cause of death worldwide, and individuals with diabetes or other cardiometabolic conditions are at increased risk of adverse cardiovascular outcomes. Although advances in prevention and treatment have reduced cardiovascular events globally, cardiometabolic disease continues to represent a significant health burden, particularly in regions with high diabetes prevalence.In Qatar and other Gulf Cooperation Council countries, the prevalence of diabetes and obesity is increasing, contributing to a high proportion of patients presenting with acute coronary syndrome who have type 2 diabetes or prediabetes.This observational study will use electronic medical record data from patients hospitalized at the Heart Hospital with acute coronary syndrome and a concomitant diagnosis of diabetes or prediabetes. The study will assess trends in cardiovascular risk factors and cardiovascular events, including readmission and mortality.An artificial intelligence component will be used to develop and validate machine-learning-based risk prediction models to forecast adverse cardiovascular outcomes in patients with cardiometabolic disease. These models will integrate clinical, biochemical, imaging, and other non-invasive data routinely collected during patient care to identify predictors of cardiovascular events.
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
10000
Start Date
2026-07-16
Completion Date
2030-07-16
Last Updated
2026-04-07
Healthy Volunteers
No
Conditions
Locations (1)
Hamad Medical Corporation
Doha, Qatar