Predictors of outcome at 2-year follow-up after arthroscopic treatment of femoro-acetabular impingement
Bibliographic record
Abstract
Femoro-acetabular impingement (FAI) is a common cause of hip pain and dysfunction in the young and active population. Despite reports of good short-term outcomes following treatment for FAI, less is known about the possible preoperative predictors of treatment outcome. The purpose of this study was to identify predictors of treatment outcome, using a patient-reported outcome measurement score (PROM) validated for use in a young and active population undergoing arthroscopic surgery for FAI. Patients were prospectively enrolled and analysed using the PROM International Hip Outcome Tool (iHOT-12) preoperatively and at a 2-year follow-up. Predictors of treatment outcome chosen for analysis were age, gender, duration of symptoms until surgery, level of cartilage damage, preoperative score and FAI type. A total of 198 patients, 122 males and 76 females (M: 61.6%, F: 38.4%), with a mean age of 41 ± 12.1 years, were analysed. The preoperative iHOT-12 score correlated with the postoperative iHOT-12 score at the 2-year follow-up. For one iHOT-12 point positive difference preoperatively, an additional 0.65 points were gained postoperatively at the 2-year follow-up (P ≤ 0.001). Age, gender, symptom duration until surgery, level of cartilage damage and FAI type did not have a statistically significant correlation to the postoperative score. Preoperative hip function as measured by the iHOT-12 is a potential predictor of outcome following FAI surgery relative to other factors.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".