Literature DB >> 31869249

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

Benedict U Nwachukwu1, Edward C Beck2, Elaine K Lee3, Jourdan M Cancienne4, Brian R Waterman2, Katlynn Paul4, Shane J Nho4.   

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.

Entities:  

Keywords:  Hip Outcome Score; MCID; PatientIQ; femoroacetabular impingement syndrome; modified Hip Harris Score; predictive modeling

Mesh:

Year:  2019        PMID: 31869249     DOI: 10.1177/0363546519892905

Source DB:  PubMed          Journal:  Am J Sports Med        ISSN: 0363-5465            Impact factor:   6.202


  9 in total

1.  Prediction of intra-articular pathology and arthroscopic outcomes for femoroacetabular impingement and labral tear based on the response to preoperative anaesthetic hip joint injections.

Authors:  Mingjin Zhong; Kan Ouyang; Weimin Zhu
Journal:  Eur J Orthop Surg Traumatol       Date:  2020-09-12

2.  The minimal clinically important difference for the nonarthritic hip score at 2-years following hip arthroscopy.

Authors:  David A Bloom; Daniel J Kaplan; David J Kirby; Daniel B Buchalter; Charles C Lin; Jordan W Fried; Nainisha Chintalapudi; Thomas Youm
Journal:  Knee Surg Sports Traumatol Arthrosc       Date:  2021-11-05       Impact factor: 4.342

3.  Psychological Healthcare Burden Lessens After Hip Arthroscopy for Those With Comorbid Depression or Anxiety.

Authors:  Anthony J Zacharias; Nicole G Lemaster; Gregory S Hawk; Stephen T Duncan; Katherine L Thompson; Kate N Jochimsen; Austin V Stone; Cale A Jacobs
Journal:  Arthrosc Sports Med Rehabil       Date:  2021-06-17

4.  CORR Insights®: Recurrent Instability and Surgery Are Common After Nonoperative Treatment of Posterior Glenohumeral Instability in NCAA Division I FBS Football Players.

Authors:  Blake M Bodendorfer
Journal:  Clin Orthop Relat Res       Date:  2021-04-01       Impact factor: 4.176

5.  Development of Machine Learning Algorithms to Predict Being Lost to Follow-up After Hip Arthroscopy for Femoroacetabular Impingement Syndrome.

Authors:  Kyle N Kunze; Robert A Burnett; Elaine K Lee; Jonathan P Rasio; Shane J Nho
Journal:  Arthrosc Sports Med Rehabil       Date:  2020-09-22

Review 6.  Evaluation of outcome reporting trends for femoroacetabular impingement syndrome- a systematic review.

Authors:  Ida Lindman; Sarantos Nikou; Axel Öhlin; Eric Hamrin Senorski; Olufemi Ayeni; Jon Karlsson; Mikael Sansone
Journal:  J Exp Orthop       Date:  2021-04-23

7.  Artificial Intelligence Predicts Cost After Ambulatory Anterior Cruciate Ligament Reconstruction.

Authors:  Yining Lu; Kyle Kunze; Matthew R Cohn; Ophelie Lavoie-Gagne; Evan Polce; Benedict U Nwachukwu; Brian Forsythe
Journal:  Arthrosc Sports Med Rehabil       Date:  2021-11-27

8.  Machine Learning for Predicting Lower Extremity Muscle Strain in National Basketball Association Athletes.

Authors:  Yining Lu; Ayoosh Pareek; Ophelie Z Lavoie-Gagne; Enrico M Forlenza; Bhavik H Patel; Anna K Reinholz; Brian Forsythe; Christopher L Camp
Journal:  Orthop J Sports Med       Date:  2022-07-26

9.  Machine-learning algorithm that can improve the diagnostic accuracy of septic arthritis of the knee.

Authors:  Eun-Seok Choi; Jae Ang Sim; Young Gon Na; Jong- Keun Seon; Hyun Dae Shin
Journal:  Knee Surg Sports Traumatol Arthrosc       Date:  2021-01-15       Impact factor: 4.342

  9 in total

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