Identifying Risk Factors for Complicated Post-operative Course in Tetralogy of Fallot Using a Machine Learning Approach.

ABSTRACT: Introduction: Tetralogy of Fallot (TOF) repair is associated with excellent operative survival. However, a subset of patients experiences post-operative complications, which can significantly alter the early and late post-operative course. We utilized a machine learning approach to identify risk factors for post-operative complications after TOF repair. Methods: We conducted a single-center prospective cohort study of children <2 years of age with TOF undergoing surgical repair. The outcome was occurrence of post-operative cardiac complications, measured between TOF repair and hospital discharge or death. Predictors included patient, operative, and echocardiographic variables, including pre-operative right ventricular strain and fractional area change as measures of right ven

SUBMITTER: Faerber JA 

PROVIDER: S-EPMC8339319 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature