Predictors of Failure After Surgical Treatment of Femoroacetabular Impingement: Results of a Multicenter Prospective Cohort of 621 Hips
Bibliographic record
Abstract
Objectives: Surgical treatment of femoroacetabular impingement attempts to improve patients’ symptoms through treatment of intra-articular labrochondral pathology and correction of underlying bony deformity. The purpose of the current study was to determine independent predictors of failure after surgical treatment of femoroacetabular impingement in a large prospective multicenter cohort study. Methods: A prospective cohort study of the surgical treatment of FAI was performed. A total of 760 hips undergoing primary surgical treatment of FAI were enrolled across seven surgeons. Patient characteristics, baseline patient reported outcomes (PROs), imaging findings, intraoperative pathology, and surgical treatments were prospectively recorded. A total of 621 hips (81.6%) with minimum one year follow-up were included in the current study (mean 4.3 years). The mHHS was assessed relative to the minimally clinically important difference (MCID, 8 points) and patient acceptable symptom state (PASS, 74 points). Univariate analyses were performed to identify factors significantly associated with failure. Multivariate logistic regression was performed to identify independent predictors of failure. Results: A total of 621 hips undergoing surgical treatment of FAI were assessed at a mean 4.2 years postoperatively. This cohort had a mean age of 29.8 and included 56.8% females. Multivariate logistic regression identified independent predictors of each failure definition. Failure A (THA) was independently associated with increasing age, acetabular microfracture (both p<0.001), and femoral head chondroplasty (p=0.02). Failure B (THA or revision surgery) was independently associated only with lower preoperative mHHS (p<0.001) (p=0.01). A lower failure C (clinical failure) was independently associated with participation in competitive athletics (p=0.01), BMI (p<0.001), and male gender (p<0.001). Conclusion: This large multicenter cohort demonstrates the outcomes of FAI treatment at a mean of 4.3 years postoperative. Rates of THA and revision surgery were 4.0% and 6.9%. An additional 14.8% of patients demonstrates clinical failure based on patient-reported outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".