Application of Machine Learning for Predicting Clinically Meaningful Outcome After Arthroscopic Femoroacetabular Impingement Surgery

Author:

Nwachukwu Benedict U.1,Beck Edward C.2,Lee Elaine K.3,Cancienne Jourdan M.4,Waterman Brian R.2,Paul Katlynn4,Nho Shane J.4

Affiliation:

1. Division of Sports Medicine, Department of Orthopedic Surgery, Hospital for Special Surgery, New York, New York, USA

2. Division of Sports Medicine, Department of Orthopedic Surgery, Wake Forest Baptist Health, Winston-Salem, North Carolina, USA

3. PatientIQ, Chicago, Illinois, USA

4. Division of Sports Medicine, Department of Orthopedic Surgery, Rush University Medical Center, Chicago, Illinois, USA

Abstract

Background: Hip arthroscopy has become an important tool for surgical treatment of intra-articular hip pathology. Predictive models for clinically meaningful outcomes in patients undergoing hip arthroscopy for femoroacetabular impingement syndrome (FAIS) are unknown. Purpose: To apply a machine learning model to determine preoperative variables predictive for achieving the minimal clinically important difference (MCID) at 2 years after hip arthroscopy for FAIS. Study Design: Case-control study; Level of evidence, 3. Methods: Data were analyzed for patients who underwent hip arthroscopy for FAIS by a high-volume fellowship-trained surgeon between January 2012 and July 2016. The MCID cutoffs for the Hip Outcome Score–Activities of Daily Living (HOS-ADL), HOS–Sport Specific (HOS-SS), and modified Harris Hip Score (mHHS) were 9.8, 14.4, and 9.14, respectively. Predictive models for achieving the MCID with respect to each were built with the LASSO algorithm (least absolute shrinkage and selection operator) for feature selection, followed by logistic regression on the selected features. Study data were analyzed with PatientIQ, a cloud-based research and analytics platform for health care. Results: Of 1103 patients who met inclusion criteria, 898 (81.4%) had a minimum of 2-year reported outcomes and were entered into the modeling algorithm. A total of 74.0%, 73.5%, and 79.9% met the HOS-ADL, HOS-SS, and mHHS threshold scores for achieving the MCID. Predictors of not achieving the HOS-ADL MCID included anxiety/depression, symptom duration for >2 years before surgery, higher body mass index, high preoperative HOS-ADL score, and preoperative hip injection (all P < .05). Predictors of not achieving the HOS-SS MCID included anxiety/depression, preoperative symptom duration for >2 years, high preoperative HOS-SS score, and preoperative hip injection, while running at least at the recreational level was a predictor of achieving HOS-SS MCID (all P < .05). Predictors of not achieving the mHHS MCID included history of anxiety or depression, high preoperative mHHS score, and hip injections, while being female was predictive of achieving the MCID (all P < .05). Conclusion: This study identified predictive variables for achieving clinically meaningful outcome after hip arthroscopy for FAIS. Patient factors including anxiety/depression, symptom duration >2 years, preoperative intra-articular injection, and high preoperative outcome scores are most consistently predictive of inability to achieve clinically meaningful outcome. These findings have important implications for shared decision-making algorithms and management of preoperative expectations after hip arthroscopy for FAI.

Publisher

SAGE Publications

Subject

Physical Therapy, Sports Therapy and Rehabilitation,Orthopedics and Sports Medicine

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