Machine Learning Multicenter Risk Model to Predict Right Ventricular Failure After Mechanical Circulatory Support: The STOP-RVF Score.

ABSTRACT:

Importance

The existing models predicting right ventricular failure (RVF) after durable left ventricular assist device (LVAD) support might be limited, partly due to lack of external validation, marginal predictive power, and absence of intraoperative characteristics.

Objective

To derive and validate a risk model to predict RVF after LVAD implantation.

Design, setting, and participants

This was a hybrid prospective-retrospective multicenter cohort study conducted from April 2008 to July 2019 of patients with advanced heart failure (HF) requiring continuous-flow LVAD. The derivation cohort included patients enrolled at 5 institutions. The external validation cohort included patients enrolled at a sixth institution within the same period. Study data were analyzed Octobe

SUBMITTER: Taleb I 

PROVIDER: S-EPMC10831631 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature