Alpha angle correction in femoroacetabular impingement
Bibliographic record
Abstract
PURPOSE: The predictive value of the alpha angle, currently the most validated magnetic resonance imaging parameter for CAM-impingement FAI, remains to be systematically evaluated in the orthopaedic literature. A systematic review was conducted to determine whether alpha angle correction influences clinical outcomes in patients with FAI. METHODS: We searched three databases (MEDLINE, EMBASE and PubMed) for English clinical studies published up to August 2012, reporting surgical correction of the alpha angle in patients with a primary diagnosis of FAI. Two independent assessors reviewed eligible studies. Where applicable, the Newcastle-Ottawa Scale was used to perform a quality assessment. Descriptive statistics are presented. RESULTS: Of the 1,103 studies initially retrieved, 14 fulfilled our eligibility criteria. Majority of studies (86 %) were case-control designs, with no randomized controlled trials. Variability existed in the surgical techniques and modalities used to measure pre- and post-operative alpha angles. All 14 studies reported a mean measured post-operative restoration of a normal alpha angle (equal to or less than 55°). Failure due to inadequate osseous correction was cited in 3/14 included studies. Correction resulted in significant improvements in range of motion and patient Visual Analog Scales, non-arthritic hip scores, Harris Hip Scores and the short-form-12. CONCLUSION: Based on this review, there is evidence supporting that precise surgical restoration of the alpha angle in CAM-type FAI to a minimum of less than 55° will lead to improved patient outcomes. The alpha angle is a good predictor of outcome and represents a simple, reproducible and inexpensive guide that can be used intra-operatively and post-operatively.
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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 | 0.008 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".