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Preoperative risk model and nomogram for 30‑Day mortality after TAVR: development and internal validation in a
Haochao Li1, Chenyu Liu1, Pengfei Chen1
1Department of Cardiovascular Surgery, Fuwai Hospital, National Center for Cardiovascular Diseases, National Clinical Research Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beilishi Road No. 167, Xicheng District, Beijing, 100037, China.
Background:
Accurate prediction of 30‑day mortality after transcatheter aortic valve replacement (TAVR) remains challenging. Existing models often overlook key preoperative laboratory variables. We aimed to develop and internally validate a preoperative risk prediction model using routinely available variables measured before the procedure.We state that predictors were preoperative‑only.
Methods:
We retrospectively analyzed 1,673 consecutive patients who underwent TAVR at Fuwai Hospital between 2013 and 2023. Patients were randomly split into a training cohort (n = 1,171) and an internal hold out validation cohort (n = 502). Candidate predictors were prespecified as routinely available preoperative variables. All candidate predictors, including laboratory parameters (troponin, D‑dimer, HbA1c, uric acid, etc.), were collected during the preoperative evaluation, within 3 days prior to the TAVR procedure. Independent predictors of 30-day mortality were identified using multivariable logistic regression. Performance was assessed with receiver operating characteristic (ROC) analysis, calibration assessment (calibration plots and Hosmer Lemeshow test), and bootstrap optimism correction; a nomogram was constructed from the final model.
Results:
30-day mortality was 3.4% in both the training (40/1,171) and validation (17/502) cohorts. The final preoperative model retained STS score, HbA1c, D-dimer, and uric acid as independent predictors. Discrimination was good (AUC=0.84 in the training cohort; AUC=0.78 in the internal validation cohort), with acceptable calibration (Hosmer-Lemeshow p = 0.211); optimism corrected performance closely matched the hold out out results. The resulting nomogram provides individualized risk estimates for 30-day mortality based on these preoperative predictors.
Conclusions:
We developed and internally validated a parsimonious preoperative risk model and nomogram for 30-day mortality after TAVR using routinely available clinical and laboratory variables. This tool may support individualized risk stratification in elective/non salvage TAVR candidates. External validation particularly beyond East-Asian populations is essential before broader application.
