Prosthetic designs that use porous metals possess an extremely high surface area and through capillary effect may potentially ‘absorb’ and later elute analgesic solution, serving as a surgical site drug depot. This study aimed to determine if a highly porous acetabular component submerged in an aqueous-based analgesic solution prior to implantation reduced postoperative pain scores and opioid consumption in the early post-operative period. Using our IRB approved database, 200 consecutive opioid naïve primary THA patients operated on by a single surgeon at two institutions using the same acetabular component were identified. 100 patients had a standard volume/concentration of an analgesic cocktail soft-tissue injection at closure (control). 100 patients had their acetabular components submerged into the same cocktail prior to implantation (treatment) and the balance of the volume injected. Postoperative protocols were otherwise identical. Groups were compared for visual analog pain scores (VAS), opioid consumption, 1-year radiographic findings and surgical revision rates.Introduction
Methods
Postoperative recovery after routine total hip arthroplasty (THA) can lead to the development of prolonged opioid use but there are few tools for predicting this adverse outcome. The purpose of this study was to develop machine learning algorithms for preoperative prediction of prolonged post-operative opioid use after THA. A retrospective review of electronic health records was conducted at two academic medical centers and three community hospitals to identify adult patients who underwent THA for osteoarthritis between January 1st, 2000 and August 1st, 2018. Prolonged postoperative opioid prescriptions were defined as continuous opioid prescriptions after surgery to at least 90 days after surgery. Five machine learning algorithms were developed to predict this outcome and were assessed by discrimination, calibration, and decision curve analysis.Background
Methods
