The Impact of Age on Clinical Outcomes of Acetabular Microfracture During FAI Surgery
Bibliographic record
Abstract
BACKGROUND: Full-thickness acetabular cartilage lesions are common findings during primary surgical treatment of femoroacetabular impingement (FAI). PURPOSE: To evaluate clinical outcomes after acetabular microfracture performed during FAI surgery in a prospective, multicenter cohort. STUDY DESIGN: Cohort Study; Level of evidence, 3. METHODS: Patients with FAI who had failed nonoperative management were prospectively enrolled in a multicenter cohort. Preoperative and postoperative (mean follow-up, 4.3 years) patient-reported outcome measures were obtained with a follow-up rate of 81.6% (621/761 hips), including 54 patients who underwent acetabular microfracture. Patient characteristics, radiographic parameters, intraoperative disease severity, and operative procedures were analyzed. Propensity matching using linear regression was used to match 54 hips with microfracture to 162 control hips (1:3) to control for confounding variables. Subanalyses of hips ≤35 and >35 years of age with propensity matching were also performed. RESULTS: = .002), and age >35 years was associated with conversion to THA after microfracture. Microfracture performed at or before 35 years of age portended good outcomes with no significant risk of conversion to THA at the most recent follow-up. CONCLUSION: Microfracture of acetabular cartilage defects appears to be safe and associated with reliably improved short- to mid-term results in younger patients; modified expectations should be realized when full-thickness chondral lesions are identified in patients >35 years of age.
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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 | 0.006 |
| 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 | 0.000 | 0.000 |
| 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".