Cognitive aging
Can ML flag high-risk AS+HFpEF after TAVR?
Open access · cc by · source: Europe PMC
In 326 TAVR patients, an 8-feature SVM reached validation AUC 0.756 for 12-month MACCE, explained with SHAP.
How this study connects
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Study at a glance
- Design
- Cohort — Multicenter retrospective TAVR cohort with train/validation ML risk models
- N
- N=326 · 195 derivation + 131 external validation patients
- Population
- Older patients with severe aortic stenosis and HFpEF undergoing TAVR
- Outcome
- 12-month major adverse cardiovascular and cerebrovascular events predicted by explainable ML
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Inspect source passages
Can ML flag high-risk AS+HFpEF after TAVR?
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326 patients; train n=195; validation n=131.
This multicenter cohort study included 326 patients diagnosed with severe AS and HFpEF who underwent TAVR between January 2017 and December 2023. Patients were allocated to training (n=195) and independent validation (n=131) sets based on hospital affiliation.
SVM validation AUC was 0.756 (95% CI 0.631–0.881).
achieving an area under the curve of 0.756 (95% CI 0.631-0.881) in the independent validation set
Key findings
SVM performed best (AUC 0.756); features centered on age, NT-proBNP, and metabolic lipid-glucose indices; good calibration/net benefit claimed vs alternatives.
Methodology
Selected features via LASSO+Boruta, trained five ML models on 195 patients, validated on 131 from other hospitals, and interpreted with SHAP.
Limitations
Prospective deployment benefit, or psychology-primary mechanisms (cardiac cohort framed for aging risk markers).
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