NCT07515807

Qatar Cardiometabolic Retrospective Cohort-Analysis Using Artificial Intelligence

• Status: Not Yet Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 10,000 (estimated)
• Sponsor: Weill Cornell Medical College in Qatar · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

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.

Detailed description

This study combines retrospective and prospective designs. Retrospective: we use past electronic medical records to identify patients and collect baseline information from their initial visit (using their code or health card number). Prospective: from that starting point we follow the same patients forward in time updating data every two years and recording new outcomes (mortality, cardiovascular events, rehospitalizations, treatment-related outcomes) at planned checkpoints (about 6 months, 1 year, and 2 years). New eligible patients found in later extractions are added and followed the same way. Because we are only observing and recording patients existing records and outcomes without assigning interventions, the study is observational.

Conditions

• Cardio Vascular Disease
• Acute Coronary Syndromes (ACS)
• Type 2 Diabetes
• Pre Diabetes
• Artifical Intelligence

Timeline

• Start date: 2026-07-16
• Primary completion: 2030-07-16
• Completion: 2030-07-16
• First posted: 2026-04-07
• Last updated: 2026-04-07

Locations

1 site across 1 country: Qatar