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Stratified care in hip arthroscopy: can we predict successful and unsuccessful outcomes? Development and external temporal validation of multivariable prediction models
  1. Lasse Ishøi1,
  2. Kristian Thorborg1,
  3. Thomas Kallemose2,
  4. Joanne L Kemp3,
  5. Michael P Reiman4,
  6. Mathias Fabricius Nielsen1,
  7. Per Hölmich1
  1. 1Sports Orthopaedic Research Center–Copenhagen (SORC-C), Arthroscopic Center, Department of Orthopedic Surgery, Hvidovre Hospital, Copenhagen University Hospital, Hvidovre, Denmark
  2. 2Department of Clinical Research, Hvidovre Hospital, Copenhagen University Hospital, Hvidovre, Denmark
  3. 3Latrobe Sports Exercise Medicine Research Centre, School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, Victoria, Australia
  4. 4Department of Orthopedic Surgery, Duke University, Duke University Medical Center, Durham, North Carolina, USA
  1. Correspondence to Mr Lasse Ishøi, Sports Orthopaedic Research Center–Copenhagen (SORC-C), Arthroscopic Center, Department of Orthopedic Surgery, Copenhagen University Hospital, Hvidovre Hospital, Hvidovre, Denmark; lasse.ishoei{at}regionh.dk

Abstract

Objective Although hip arthroscopy is a widely adopted treatment option for hip-related pain, it is unknown whether preoperative clinical information can be used to assist surgical decision-making to avoid offering surgery to patients with limited potential for a successful outcome. We aimed to develop and validate clinical prediction models to identify patients more likely to have an unsuccessful or successful outcome 1 year post hip arthroscopy based on the patient acceptable symptom state.

Methods Patient records were extracted from the Danish Hip Arthroscopy Registry (DHAR). A priori, 26 common clinical variables from DHAR were selected as prognostic factors, including demographics, radiographic parameters of hip morphology and self-reported measures. We used 1082 hip arthroscopy patients (surgery performed 25 April 2012 to 4 October 2017) to develop the clinical prediction models based on logistic regression analyses. The development models were internally validated using bootstrapping and shrinkage before temporal external validation was performed using 464 hip arthroscopy patients (surgery performed 5 October 2017 to 13 May 2019).

Results The prediction model for unsuccessful outcomes showed best and acceptable predictive performance on the external validation dataset for all multiple imputations (Nagelkerke R2 range: 0.25–0.26) and calibration (intercept range: −0.10 to −0.11; slope range: 1.06–1.09), and acceptable discrimination (area under the curve range: 0.76–0.77). The prediction model for successful outcomes did not calibrate well, while also showing poor discrimination.

Conclusion Common clinical variables including demographics, radiographic parameters of hip morphology and self-reported measures were able to predict the probability of having an unsuccessful outcome 1 year after hip arthroscopy, while the model for successful outcome showed unacceptable accuracy. The externally validated prediction model can be used to support clinical evaluation and shared decision making by informing the orthopaedic surgeon and patient about the risk of an unsuccessful outcome, and thus when surgery may not be appropriate.

  • Hip
  • Arthroscopy
  • Groin
  • Sports medicine
  • Surveys and Questionnaires

Data availability statement

Data may be obtained from a third party and are not publicly available.

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Data availability statement

Data may be obtained from a third party and are not publicly available.

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Footnotes

  • Twitter @LasseIshoei, @KThorborg, @JoanneLKemp, @MikeReiman, @Physiomathias, @PerHolmich

  • Contributors Authors contributed to the concept and design (LI, KT, MPR, JLK, MN and PH), acquisition of the data (LI, KT and PH), analysis (LI and TK) and interpretation (all authors), drafting and revision (all authors), final approval (all authors) and agreement to be accountable (all authors). The guarantor (PH) accepts full responsibility for the work and/or the conduct of the study, had access to the data, and controlled the decision to publish. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • © Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.