Development and external validation of a machine learning model for predicting postoperative hydrocephalus in 1,073 posterior fossa tumor patients.

Postoperative hydrocephalus is a common complication following posterior fossa tumor resection, affecting 7-40% of patients.

We therefore developed and externally validated a model to provide supplementary preoperative risk stratification using routinely available variables.

We initially screened 30 perioperative variables from the multicenter dataset and then selected a clinically implementable model restricted to variables available before tumor resection.

The model may support preoperative risk communication and postoperative surveillance planning, but should not be used as a stand-alone indication for cerebrospinal fluid diversion.