Neurosurgeons sorely need a robust predictor for the risk of requiring VPS after resection of PFTs. 4, 5 While some studies from single institutions suggest predictors for postoperative HCP after PFT resection, no novel, machine-learning techniques have been used to predict the need for VPS after PFT surgery. Neurosurgeons employ preoperative VPS/endoscopic third ventriculostomy, pre-/postoperative external ventricular drainage (EVD), and avoiding subtotal resection (STR) and intraventricular hemorrhage (IVH) to combat the risk of postoperative HCP. Diagnosing persistent HCP and surgery for VPS may increase hospitalization times and the cost of care for patients with PFTs. 1–3 Postoperative HCP can necessitate long-term cerebrospinal fluid (CSF) diversion, which is treated with the ventriculoperitoneal shunt (VPS). These data will continue to make our models more robust, and therefore more applicable to future patients.Ī well-known complication after resection of posterior fossa tumors (PFTs) is postoperative hydrocephalus (HCP). We will next develop a web-based application to help clinicians predict which patients will require a VPS. We applied multiple machine-learning algorithms to retrospectively collected data and found that ANNs could be used to best predict need for long-term CSF diversion after PFT resection. Defining patients at high risk of ventriculoperitoneal shunt (VPS) will decrease hospital stay time and healthcare expenditures. Clinicians need a durable method to predict the occurrence of CSF diversion in this population.
Hydrocephalus is a prevalent complication after resection of PFTs.
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