An international model to predict recurrent cardiovascular disease

Area of Science:

• Cardiology
• Epidemiology
• Preventive Medicine

Background:

• Prediction models for cardiovascular events and death are lacking for patients with established cardiovascular disease.
• The REduction of Atherothrombosis for Continued Health (REACH) Registry provides a global dataset of such patients.

Purpose of the Study:

• To establish and validate a cardiovascular prediction model for patients with established atherothrombotic disease.
• To identify key risk factors and protective elements for secondary cardiovascular events and death.

Main Methods:

• Utilized data from 49,689 participants in the REACH Registry.
• Developed a prediction model using 2-year follow-up data from a randomly selected subset (33,419 participants).
• Validated the model in the remaining 16,270 participants.

Main Results:

• Identified risk factors including number of diseased vascular beds, diabetes, smoking, low BMI, atrial fibrillation, cardiac failure, and recent prior cardiovascular events.
• Statin and acetylsalicylic acid therapy were associated with reduced cardiovascular event risk.
• The model accurately predicted cardiovascular events and death in the validation cohort.

Conclusions:

• A validated risk model can now predict secondary cardiovascular events and death in outpatients with established atherothrombotic disease.
• Traditional risk factors, disease burden, treatment status, and geography influence cardiovascular risk.