Safa C Fassihi, Abhay Mathur, Matthew J Best, Aaron Z Chen, Alex Gu, Theodore Quan, Kevin Y Wang, Chapman Wei, Joshua C Campbell, Savyasachi C Thakkar
Purpose: The purpose is to utilize an artificial neural network (ANN) model to determine the most important variables in predicting mortality following total hip arthroplasty (THA). Methods: Patients that underwent primary THA were included from a national database. Demographic, preoperative, and intraoperative variables were analyzed based on their contribution to 30-day mortality with the use of an ANN model. Results: The five most important factors in predicting mortality following THA were preoperative international normalized ratio, age, body mass index, operative time, and preoperative hematocrit...
November 2021: Journal of Orthopaedics