Key result
Positive AI-ECG age gap linked to ~20% higher all-cause mortality in repeat AVR.
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Why the study?
Outcomes of redo SAVR versus ViV TAVR for failed stented bioprostheses and the prognostic value of preoperative AI-ECG age on mortality were not well characterized.
Does valve-in-valve transcatheter aortic valve replacement improve outcomes compared to redo surgical aortic valve replacement in patients with failed stented bioprostheses, and does AI-ECG age predict mortality?
Cohort (n=613)
Does valve-in-valve transcatheter aortic valve replacement improve outcomes compared to redo surgical aortic valve replacement in patients with failed stented bioprostheses, and does AI-ECG age predict mortality?
Hazard Ratio: 1.2 (95% CI 1.16–1.24)
p-value: p=<0.001
A positive AI-ECG age gap is an independent predictor of mortality following repeat aortic valve replacement, providing noninvasive prognostic information beyond chronological age.
OBJECTIVE To analyze outcomes of patients with failed stented bioprostheses undergoing redo surgical aortic valve replacement (redo SAVR) versus valve-in-valve transcatheter AVR (ViV TAVR) and evaluate the impact of preoperative artificial-intelligence electrocardiogram (AI-ECG) age on all-cause mortality. METHODS Between 2010 and 2025, 1558 patients underwent repeat AVR for a failed bioprosthesis. To obtain a more homogenous cohort, patients with concomitant procedures were excluded, leaving 244 redo SAVR and 369 ViV TAVR cases. Propensity score matching (1:1) was then applied, yielding 167 balanced pairs. Preoperative ECGs were analyzed using a convolutional neural network to estimate AI-ECG age. The age gap was defined as AI-ECG age minus chronological age, with positive values indicating a physiologically older age. RESULTS The matched cohort had a mean chronological age of 72±11 years and AI-ECG age of 68±10 years. Mean age gap was -3.6 ± 9 years (range, -22 to +15). Compared to redo SAVR, ViV TAVR was associated with higher median predismissal gradients (13 [9-19] vs 9 [7-13] mm Hg, P<0.001), and more frequent severe prosthesis-patient mismatch (PPM) (25% vs 11%, P<0.001). Operative mortality was 2.4% for redo-SAVR and 0.6% for ViV (P=0.37). A positive age gap was an independent predictor of all-cause mortality (HR: 1.20; 95% CI: 1.16-1.24; P<0.001). No significant interaction between treatment modality and age gap was observed (HR: 1.02, 95% CI 0.96-1.07; P=0.571). An increasing age gap was associated with measures of postoperative outcomes, including atrial fibrillation, blood product transfusion, prolonged ICU stay, and prolonged hospitalization. CONCLUSIONS AI-ECG age gap is independently associated with mortality following repeat aortic valve replacement and provides prognostic information beyond chronological age. Increasing age gap is also associated with several markers of postoperative outcomes, supporting its role as a noninvasive measure of physiologic reserve.
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Danesh et al. (2026) conducted a cohort in Failed stented bioprostheses (n=613). Positive AI-ECG age gap vs. Negative or lower age gap was evaluated on All-cause mortality (HR 1.20, 95% CI 1.16-1.24, p=<0.001). A positive AI-ECG age gap independently predicted all-cause mortality (HR 1.20; 95% CI 1.16-1.24; P<0.001) in patients undergoing repeat AVR, with similar operative mortality between ViV and SAVR.
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