Long-term prognostic value of biological age in patients undergoing transcatheter aortic valve replacement
T Furusawa, H Kiriyama, S Minatsuki, Y Manabe, T Kamon, A Saito, S Kodera, M Ando, H Yamauchi, K Nakanishi, J Ishida, M Ono, N TakedaAbstract
Background
Transcatheter aortic valve replacement (TAVR) was initially developed for elderly patients and those at high surgical risk. As population’s annual aging and indications for TAVR expand to younger and lower-risk patients, longer lifetime management has become increasingly important. Accordingly, there is a growing need for risk stratification to predict longer-term outcomes after TAVR to guide treatment strategies; however, there is no established long-term prognostic indicator following TAVR. Recent studies suggest that phenotypic age, which serves as a surrogate marker of biological aging, may better reflect vulnerability and long-term prognosis than chronological age across a range of cardiovascular diseases. Nonetheless, the prognostic value of biological age in patients undergoing TAVR remains unclear.
Purpose
This study aimed to evaluate the utility of phenotypic age as a novel indicator for predicting long-term prognosis in patients undergoing TAVR.
Methods
We retrospectively analyzed 328 patients with severe aortic stenosis who underwent TAVR between October 2015 and December 2023 at our hospital. Phenotypic age was calculated from chronological age and nine biomarkers (albumin, creatinine, glucose, CRP, WBC, MCV, lymphocyte percent, RDW, and ALP), using baseline laboratory data upon admission. PhenoAgeAccel, which was defined as the residual from a linear regression model of phenotypic age on chronological age, was also calculated. The primary outcome was a composite of all-cause mortality, myocardial infarction, stroke, and heart failure hospitalization. A multivariable Cox proportional hazards regression model adjusted for PhenoAgeAccel, chronological age, sex, body mass index, LogBNP, LVEF and mitral regurgitation was performed to evaluate the association between the biological age and long-term outcome after TAVR.
Results
The median age of the entire cohort was 84.8 years, and 63.4 % of patients were female. Mean Phenotypic age was 85.2 years and PhenoAgeAccel was 0.05. Patients was categorized into three groups based on the degree of PhenoAgeAccel: Low-PhenoAgeAccel group (PhenoAgeAccel <-5.64, n=109), Intermediate-PhenoAgeAccel group (-5.64≦ PhenoAgeAccel <3.47, n=110), High-PhenoAgeAccel group (3.47≦ PhenoAgeAccel, n=109). Over a median follow-up of 595 days, the primary outcome occurred in 17 (15.6%), 42 (38.2%), and 50 (45.9%) patients in the Low-, Intermediate-, and High-PhenoAgeAccel groups, respectively (log-rank p< 0.001: Figure). According to the multivariable Cox regression analysis, PhenoAgeAccel was independently associated with the primary outcome (Hazard ratio 1.04, 95 % Confidence Interval 1.02-1.06; p < 0.001).
Conclusion
Biological age, assessed via PhenoAgeAccel, was a strong predictor of long-term outcome following TAVR. Incorporating biological age into determining TAVR eligibility and preprocedural assessment provides crucial insights for lifetime management strategies.Figure