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Hip

DECODING THE TIMELINE: PREDICTING RETURN TO SPORT AFTER PERIACETABULAR OSTEOTOMY WITH PRECISION MODELLING

The International Hip Society (IHS) 2024 Closed Meeting, Athens, Greece, 15–18 May 2024.



Abstract

Periacetabular Osteotomy (PAO) has become the most important surgical procedure for patients with hip dysplasia, offering significant pain relief and improved joint function. This study focuses on recovery after PAO, specifically the return to sports (RTS) timeline, with the objective of identifying preoperative predictors to optimize patient outcomes.

Our prospective, monocentric study from 2019 to 2023 included 698 hips from 606 patients undergoing PAO. Comprehensive preoperative data were collected, including demographic information, clinical assessments (Modified Harris Hip Score (mHHS), International Hip Outcome Tool-12 (iHot-12), Hip Disability and Osteoarthritis Outcome Score (HOOS), UCLA Activity Score) and psychological evaluations (Brief Symptom Inventory (BSI) and SF-36 Health Survey). Advanced logistic regression and machine learning techniques (R Core Team. (2016)) were employed to develop a predictive model.

Multivariate regression analysis revealed that several preoperative factors significantly influenced the RTS timeline. These included gender, invasiveness of the surgical approach, preoperative UCLA Score, preoperative sports activity level, mHHS, and various HOOS subscales (Sport/Recreation, Symptoms, Pain) as well as psychological factors (BSI and SF-36). The subsequent model, using a decision tree approach, showed that the combination of a UCLA score greater than 3 (p<0.001), non-female gender (p=0.003), preoperative sports frequency not less than twice per week (p<0.001), participation in high-impact sports preoperatively (p=0.008), and a BSI anxiety score less than 2 (p<0.001) had the highest likelihood of early RTS with a probability of 71.4% at three months.

Using a decision tree approach, this model provides a nuanced prediction of RTS after PAO, highlighting the synergy of physical, psychological, and lifestyle influences. By quantifying the impact of these variables, it provides clinicians with a valuable tool for predicting individual patient recovery trajectories, aiding in tailored rehabilitation planning and predicting postoperative satisfaction.


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