Qatar Cardiometabolic Retrospective Cohort-Analysis Using Artificial Intelligence

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Conditions studied: Cardio Vascular Disease, Acute Coronary Syndromes (ACS), Type 2 Diabetes, Pre Diabetes, Artifical Intelligence

In brief

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 participants 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 participants with cardiometabolic disease. These models will integrate clinical, biochemical, imaging, and other non-invasive data routinely collected during participants care to identify predictors of cardiovascular events.

Key facts

Study ID
NCT07515807
Run by
Weill Cornell Medical College in Qatar
People needed
10000
Starts
2026-07-16
Expected to finish
2030-07-16
Last updated by the study team
2026-04-21

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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