Machine learning-based prediction of 1-year all-cause mortality in patients undergoing CRT implantation: validation of the SEMMELWEIS-CRT score in the European CRT Survey I dataset.

ABSTRACT:

Aims

We aimed to externally validate the SEMMELWEIS-CRT score for predicting 1-year all-cause mortality in the European Cardiac Resynchronization Therapy (CRT) Survey I dataset-a large multi-centre cohort of patients undergoing CRT implantation.

Methods and results

The SEMMELWEIS-CRT score is a machine learning-based tool trained for predicting all-cause mortality in patients undergoing CRT implantation. This tool demonstrated impressive performance during internal validation but has not yet been validated externally. To this end, we applied it to the data of 1367 patients from the European CRT Survey I dataset. The SEMMELWEIS-CRT predicted 1-year mortality with an area under the receiver operating characteristic curve (AUC) of 0.729 (0.682-0.776), which concurred with the p

SUBMITTER: Tokodi M 

PROVIDER: S-EPMC11417478 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature