What is The Impact of PAO Surgery on Patient Function and Activity Levels?
Bibliographic record
Abstract
Objectives: The Bernese periacetabular osteotomy (PAO) is becoming a widely utilized procedure. Patients are younger, highly active, and may desire to return to sport activity. Counseling and managing expectations in these patients is challenging as there is limited information regarding activity level after PAO. The purpose of this study was to analyze physical activity levels after PAO in a large, prospective multicenter cohort. Methods: Assessment of prospectively collected data from a multicenter group included 456 hips treated by PAO for hip dysplasia. After exclusions, 359 hips (80 male, 279 female) remained with a mean age of 25.9 years and mean BMI of 25. Demographics, radiographic measures, and clinical outcomes were evaluated preoperatively, at 1 year follow-up, and at minimum 2 years postoperatively (mean 44.9 months). Activity level was assessed with the University of California-Los Angeles (UCLA) activity score, patients were stratified into low, moderate, and high activity groups based on preoperative function. Descriptive statistics and linear regressions were performed for the primary outcome of change in UCLA. Results: UCLA scores were improved on average 0.6 points at final follow up (p = 0.001). When stratified, the low activity and moderate activity groups had significant improvement in UCLA scores (p<.0001 and p=0007) while the high activity group saw a decrease in UCLA scores (p<.0001). mHHS, HOOS Pain, and HOOS Sports and Recreation scores were significantly improved across all activity levels. Univariable linear regression analysis identified prior ipsilateral surgery, arthroscopy at time of PAO, and preoperative ACEA to be predictors of the change in UCLA score (p<0.05). With the multivariable model, the effect of prior ispilateral surgery was maintained (p = 0.002). Conclusion: The data suggests that improvements in activity level and function can be expected following PAO surgery, with greater gains experienced by patients with lower preoperative level of activity. [Figure: see text][Figure: see text]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".