Qatar Cardiometabolic Retrospective Cohort-Analysis Using Artificial Intelligence (QCRC-AI)

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.

Study Overview

• Status: Not yet recruiting
• Conditions: Type 2 Diabetes; Pre Diabetes; Cardio Vascular Disease; Acute Coronary Syndromes (ACS); Artifical Intelligence

Detailed Description

This study combines retrospective and prospective designs.

Retrospective:

We use past electronic medical records to identify participants and collect baseline information from their initial visit (using their code or health card number).

Prospective:

From that starting point, we follow the same participants forward in time, updating data every two years and recording new outcomes (mortality, cardiovascular events, rehospitalizations, treatment-related outcomes) at planned checkpoints (approximately 6 months, 1 year, and 2 years).

New eligible participants identified in later data extractions are added and followed in the same manner. Because we only observe and record participants existing records and outcomes without assigning interventions, the study is observational.

• Study Type: Observational
• Enrollment (Estimated): 10000

Contacts and Locations

• Study Contact: Name: Charbel Abi Khalil Prof; Phone Number: + 974 4492 8484; Email: cha2022@qatar-med.cornell.edu

Study Locations

• Qatar
  • Doha, Qatar
    • Hamad Medical Corporation
    • Contact: Nidal Asaad MD; Phone Number: +974 44390220; Email: nasaad@hamad.qa

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

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

Description

Inclusion Criteria:

• 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%

Exclusion Criteria:

• 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.

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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 Outcome Measures

Outcome Measure	Measure Description	Time Frame
Coronary revascularization		5 years
Major Adverse Cardiovascular Events	MACE - Major Adverse Cardiovascular Events	5 years
Unstable angina requiring hospitalization		5 years
Arrhythmic events		5 years
Post-Percutaneous Coronary Intervention (PCI) or Coronary Artery Bypass Grafting (CABG) complications (stent/graft thrombosis or repeat revascularization)		5 years
Development or progression of valvular heart disease (aortic or mitral stenosis/regurgitation)		5 years
New-onset diabetes mellitus		5 years
Change in glycated Hemoglobin A1c (HbA1c)		5 years
Newly diagnosed medical or surgical conditions not present at baseline		5 years

Collaborators and Investigators

• Sponsor: Weill Cornell Medical College in Qatar
• Collaborators: Hamad Medical Corporation
• Investigators: Principal Investigator: Charbel Abi Khalil, Weill Cornell Medicine-Qatar

Study record dates

Study Major Dates

• Study Start (Estimated): July 16, 2026
• Primary Completion (Estimated): July 16, 2030
• Study Completion (Estimated): July 16, 2030

Study Registration Dates

• First Submitted: March 31, 2026
• First Submitted That Met QC Criteria: March 31, 2026
• First Posted (Actual): April 7, 2026

Study Record Updates

• Last Update Posted (Actual): April 21, 2026
• Last Update Submitted That Met QC Criteria: April 15, 2026
• Last Verified: March 1, 2026

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Endocrine System Diseases; Vascular Diseases; Cardiovascular Diseases; Heart Diseases; Metabolic Diseases; Glucose Metabolism Disorders; Diabetes Mellitus; Myocardial Ischemia; Hyperglycemia; Nutritional and Metabolic Diseases; Diabetes Mellitus, Type 2; Acute Coronary Syndrome; Glucose Intolerance
• Other Study ID Numbers: 25-00019

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No