A score for the prediction of cardiovascular events in the hypertensive aged

Area of Science:

• Cardiology
• Geriatric Medicine
• Epidemiology

Background:

• Current cardiovascular disease (CVD) risk assessment tools primarily use data from middle-aged individuals.
• The growing elderly population, many with hypertension, requires specific risk prediction models.
• Existing tools may not accurately reflect CVD risk in older, hypertensive individuals.

Purpose of the Study:

• To develop a novel cardiovascular risk equation tailored for elderly, hypertensive populations.
• To improve the accuracy of CVD risk prediction in older adults.
• To address the limitations of current risk scores in this demographic.

Main Methods:

• Utilized cardiovascular endpoint data from 5,426 hypertensive subjects without prior CVD (Second Australian National Blood Pressure Study - ANBP2).
• Developed a Cox regression-based risk model using 75% of the dataset and validated it internally with the remaining 25%.
• Externally validated the model against the Dubbo Study dataset.

Main Results:

• The final predictive model incorporated sex, age, physical activity, family history, anticoagulant use, specific antihypertensive agents, and diabetes medication.
• The model achieved a C-statistic of 0.65 on the development dataset and 0.62 on the internal validation dataset.
• External validation against the Dubbo Study dataset yielded a C-statistic of 0.68 for CVD.

Conclusions:

• The developed risk models performed comparably across validation datasets.
• Existing cardiovascular risk algorithms could be extended to older age groups for practical implementation.
• Further research may refine risk prediction for elderly hypertensive patients.