Role of Biological Age in the Determination of Long-Term Cause-Specific Death Following Percutaneous Coronary Interventions.

Abstract

Background: We tested whether biologic age, as estimated by deficits, functional impairments, or Age-Gap or their combination, provide improved estimation of cause-specific death as compared with chronological age.

Methods: Cardiovascular and noncardiovascular deficits, functional impairments, and Age-Gap were prospectively collected in 535 patients aged ≥55 years undergoing percutaneous coronary interventions between August 1, 2014, and March 31, 2018. Age-Gap was calculated as the difference between chronological age and age estimated by artificial intelligence ECG using a convolutional neural network. The full biological age model included deficits, functional impairments, and Age-Gap >2 SD. A multivariable reduced model with the least number of variables was also created to provide a comparable C index to the full model.

Results: The average chronological age was 72.1±9.5 years, and there were 68% of men. During a median follow-up of 2.61 years, 124 (23%) patients died. There was a modest correlation between Age-Gap and biological age (r=0.28 [95% CI, 0.20-0.35]; P<0.001). When modeled with chronologic age as a covariate, Age-Gap predicted all-cause (hazard ratio [HR], 1.07 [95% CI, 1.04-1.10]; P<0.001) and cardiovascular (HR, 1.07 [95% CI, 1.04-1.11]; P<0.001) mortality. As compared with chronological age, the full biological age model noted significant improvement in the prediction of long-term overall (95% CI, 0.65-0.78), cardiovascular (95% CI, 0.69-0.77), and noncardiovascular (95% CI, 0.55-0.86) mortality. In the reduced models, most prognostic information for noncardiovascular mortality (C index: 0.79) was obtained by subjective difficulty in performing tasks, whereas the deficit-based estimation predicted cardiovascular mortality (C index: 0.72).

Conclusions: Estimated biological age from deficits and functional impairments was superior to chronological age in predicting long-term cause-specific mortality following percutaneous coronary interventions.