PURPOSE: The purpose of this study was to develop and validate a model predicting whether patients would have shorter-than-typical or longer-than-typical recoveries after hip arthroscopy for labral tears. METHODS: We retrospectively reviewed 268 cases of hip arthroscopy implemented between 2000 and 2007 by 2 orthopaedic surgeons at our institution. The development cohort consisted of patients with magnetic resonance angiography-identified labral tears and a history and physical examination consistent with either labral pathology or loose bodies. Univariate analysis targeted preoperative patient characteristics correlated with the risk of longer-than-typical recoveries. Multivariate logistic regression was applied to generate an algorithm predicting risk of longer-than-typical recovery based on baseline characteristics. The algorithm was tested in the validation sample of 52 patients who were treated in 2007 and was found to be valid. RESULTS: Five predictors for longer-than-typical recovery were identified: Workers' Compensation status, female gender, use of pain medications, presence of a limp, and presence of a lateral labral tear. The multivariate algorithm was developed and successfully validated. CONCLUSIONS: This study identifies many new predictors of recovery, and it also corroborates those that have already been identified. The 5 predictors for longer-than-typical recovery identified by our validated multivariate algorithm were Workers' Compensation status, female gender, use of pain medications, presence of a limp, and presence of a lateral labral tear. LEVEL OF EVIDENCE: Level IV, therapeutic case series. Copyright 2010 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.
PURPOSE: The purpose of this study was to develop and validate a model predicting whether patients would have shorter-than-typical or longer-than-typical recoveries after hip arthroscopy for labral tears. METHODS: We retrospectively reviewed 268 cases of hip arthroscopy implemented between 2000 and 2007 by 2 orthopaedic surgeons at our institution. The development cohort consisted of patients with magnetic resonance angiography-identified labral tears and a history and physical examination consistent with either labral pathology or loose bodies. Univariate analysis targeted preoperative patient characteristics correlated with the risk of longer-than-typical recoveries. Multivariate logistic regression was applied to generate an algorithm predicting risk of longer-than-typical recovery based on baseline characteristics. The algorithm was tested in the validation sample of 52 patients who were treated in 2007 and was found to be valid. RESULTS: Five predictors for longer-than-typical recovery were identified: Workers' Compensation status, female gender, use of pain medications, presence of a limp, and presence of a lateral labral tear. The multivariate algorithm was developed and successfully validated. CONCLUSIONS: This study identifies many new predictors of recovery, and it also corroborates those that have already been identified. The 5 predictors for longer-than-typical recovery identified by our validated multivariate algorithm were Workers' Compensation status, female gender, use of pain medications, presence of a limp, and presence of a lateral labral tear. LEVEL OF EVIDENCE: Level IV, therapeutic case series. Copyright 2010 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.
Authors: Simon Lee; Gregory L Cvetanovich; Randy Mascarenhas; Thomas H Wuerz; Richard C Mather; Charles A Bush-Joseph; Shane J Nho Journal: J Hip Preserv Surg Date: 2016-10-27
Authors: Jesse C Christensen; Jennifer D Marland; Caitlin J Miller; Brandy S Horton; Daniel R Whiting; Hugh S West Journal: J Hip Preserv Surg Date: 2019-03-20