Qatar Cardiometabolic Retrospective Cohort-Analysis Using Artificial Intelligence

NCT07515807 | Not Yet Recruiting

• 1 other identifier: 25-00019
• Study Type: observational
• Target: 10,000
• Locations: 1 country
• Sites: 1

Brief 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 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.

Conditions

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

Outcome Measures

Primary Outcomes (2)

• Incidence of 3-point Major Adverse Cardiovascular Events (MACE) in Acute Coronary Syndrome Patients

  Composite endpoint defined as the occurrence of cardiovascular death, non-fatal myocardial infarction, or non-fatal stroke. Events will be identified using electronic medical records, hospital admission data, and follow-up assessments during the study period. These outcomes will serve as endpoints for the development and validation of predictive machine learning models.

  5 years

• Incidences of 2-point Major Adverse Cardiovascular Events (MACE) in Heart Failure Patients

  Composite endpoint defined as cardiovascular death or hospitalization for heart failure. Events will be ascertained through hospital records, clinical documentation, and follow-up data collection. These outcomes will be used as endpoints for predictive model development and validation.

  5 years

Secondary Outcomes (9)

• Major Adverse Cardiovascular Events

  5 years

• Unstable angina requiring hospitalization

  5 years

• Arrhythmic events

  5 years

• Coronary revascularization

  5 years

• Post-Percutaneous Coronary Intervention (PCI) or Coronary Artery Bypass Grafting (CABG) complications (stent/graft thrombosis or repeat revascularization)

  5 years

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Participants admitted at Hamad Medical Corporation for Acute Coronary Syndrome (ACS) or Acute Heart Failure (AHF).

You may qualify if:

• Age ≥ 18
• Qatari and Arab participants
• Participants admitted for Acute Coronary Syndrome (ACS) or Acute Heart Failure (AHF)
• Metabolic disease: Diabetes (HbA1C ≥ 6.5% or any HbA1C if a patient is on an antidiabetic agent) or pre-diabetes: 5.7% ≤ HbA1c ≤ 6.4%

You may not qualify if:

• Non-Qatari or non-Arab participants
• Non-diabetic: HbA1C \< 5.7%
• This chart review involves no direct interaction with individuals. Prisoners are not a focus of this study, and incarceration status is not identifiable in the records reviewed.

Sponsors & Collaborators

• Weill Cornell Medical College in Qatar: lead
• Hamad Medical Corporation: collaborator

Study Sites (1)

Hamad Medical Corporation

Doha, Qatar

Location

MeSH Terms

Conditions

Acute Coronary Syndrome; Diabetes Mellitus, Type 2; Glucose Intolerance

Condition Hierarchy (Ancestors)

Myocardial Ischemia; Heart Diseases; Cardiovascular Diseases; Vascular Diseases; Diabetes Mellitus; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases; Hyperglycemia

Study Officials

• Charbel Abi Khalil

  Weill Cornell Medicine-Qatar

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Charbel Abi Khalil Prof

CONTACT

+ 974 4492 8484; cha2022@qatar-med.cornell.edu

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: OTHER
• Target Duration: 2 Years
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: March 31, 2026
• First Posted: April 7, 2026
• Study Start (Estimated): July 16, 2026
• Primary Completion (Estimated): July 16, 2030
• Study Completion (Estimated): July 16, 2030
• Last Updated: April 21, 2026

Record last verified: 2026-03

Locations

QA (1)