Revisiting the Endoscopic Third Ventriculostomy Success Score using machine learning: can we do better?
Journal:
Journal of neurosurgery. Pediatrics
Published Date:
Dec 6, 2024
Abstract
OBJECTIVE: The Endoscopic Third Ventriculostomy Success Score (ETVSS) is a useful decision-making heuristic when considering the probability of surgical success, defined traditionally as no repeat cerebrospinal fluid diversion surgery needed within 6 months. Nonetheless, the performance of the logistic regression (LR) model in the original 2009 study was modest, with an area under the receiver operating characteristic curve (AUROC) of 0.68. The authors sought to use a larger dataset to develop more accurate machine learning (ML) models to predict endoscopic third ventriculostomy (ETV) success and also to perform the largest validation of the ETVSS to date.