Cardiovascular Risk Prediction in Older Adults.

Purpose of review: This review examines cardiovascular disease (CVD) risk prediction models relevant to older adults, a rapidly expanding population with elevated CVD risk. It discusses model characteristics, performance metrics, and clinical implications.

Recent findings: Some models have been developed specifically for older adults, while several others consider a broader age range, including some older individuals. These models vary in terms of predictors, outcomes, horizon, and statistical approaches, with some accounting for competing risks and considering age-predictor interactions. Discrimination is generally acceptable and more modest in older versus younger individuals. Calibration shows great variation across populations. Accurate CVD risk prediction is essential to guide individualized prevention strategies and support shared decision-making in older adults. CVD risk prediction in this population is challenged by age-related CVD risk heterogeneity, elevated competing risk due to non-CVD mortality, and comorbidities. Further refinement by incorporating geriatric-specific factors may help to enhance discrimination.