EP1.52 Clinical and Radiographic Predictors of Labral and Cartilage Damage in Femoroacetabular Impingement: A multicenter prospective study
Bibliographic record
Abstract
Abstract Introduction: Femoroacetabular impingement commonly causes labral and cartilage damage. Understanding what clinical and CT-morphological factors are associated with increased labral and acetabular cartilage damage may give insight into the FAI pathophysiology. The present study aims to identify factors associated with labral and cartilage damage. Method: This is a prospective, multicenter cohort of patients undergoing primary arthroscopy for treatment of symptomatic FAI. Enrollment was between 2020 and 2022. The current study investigated predictive factors of advanced labral damage (detachment or full-thickness tear length >4cm) and advanced acetabular cartilage damage (delamination or full-thickness defect ≥200mm2). Finally, we performed external validation for the previously reported RAPID score that predicts high-grade cartilage injury. Results: There were 647 patients in the cohort. For labral injuries, there were 384/647 (59.4%) detachments and 154/647 (23.8%) full-thickness defects, with labral tears ≥4cm was present in 100/558 (17.9%) hips. Older age (OR:1.04, p=0.002), males (OR:1.83,p=0.005), and larger alpha angles at 2:00 (OR:1.02,p=0.04) were associated with full-thickness labral injuries. Older age (OR:1.06,p<0.001) and larger alpha angles at 2:00 (OR:1.03,p=0.01) were associated with tears ≥4cm. 258/679 (38.0%) patients had delamination or full-thickness cartilage defects. Older age (OR:1.09,p<0.001), males (OR:1.91 p=0.003), decreased IRF (OR:0.95,p<0.001), higher femoral version (OR:1.02,p=0.04), and larger alpha angles at 1:30 (OR:1.06,p<0.001) were associated with delamination or defect cartilage injuries. Advanced acetabular cartilage damage ≥200mm2 was present in 109/679 (16.8%) hips and was associated with larger alpha angles at 2:00 (OR:1.07,p<0.001), decreased IRF (OR:0.95,p<0.001), and males (OR:2.52,p=0.002), and age (OR:1.05,p=0.002). For RAPID score external validation, we used our data for their model (sex, Tonnis OA Grade, radiographic alpha angle) and found an AUC of 0.685. With an adjusted model using CT alpha angles, AUC improved to 0.703. Our final model improved the AUC to 0.809 and included age, sex, IRF, femoral version, and CT alpha angles. Conclusion: FAI commonly has associated labral and cartilage injuries. The current study found multiple predictive factors for advanced labral and cartilage injuries as well as for larger lesions. A model including age, sex, IRF, femoral version, and CT alpha angles appears to best predict acetabular cartilage damage. Further research should investigate how these affect outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".