The dimensions of the hip labrum can be reliably measured using magnetic resonance and computed tomography which can be used to develop a standardized definition of the hypoplastic labrum
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to examine the existing literature to determine the dimensions of the acetabular labrum, with a focus on hypotrophic labra, including the modalities and accuracy of measurement, factors associated with smaller labra, and any impacts on surgical management. METHODS: Four databases (PubMed, Ovid [MEDLINE], Cochrane Database, and EMBASE) were searched from database inception to January 2020. Two reviewers screened the literature independently and in duplicate. Methodological quality of included papers was assessed using the Methodological Index for Non-Randomized Studies (MINORS) criteria. Where possible, data on labral size were combined using a random effects model. RESULTS: Twenty-one studies (5 level II, 9 level III, 7 level IV) were identified. This resulted in 6,159 patients (6,436 hips) with a mean age of 34.3 years (range 8.4-85). The patients were 67.3% female with an average follow-up of 57.3 months. There was no consistent definition of labral size quoted throughout the literature. The mean width on MRI/MRA was 7.3 mm (95% CI 6.9-7.8 mm), on computed tomography arthrography was 8.7 mm (95% CI 8.0-9.3), and during arthroscopy was 5.0 mm (95% CI 4.9-5.2). Inter-observer reliability was good to excellent in all modalities. Labral hypotrophy may be associated with increased acetabular coverage. Hypertrophic labra were highly associated with acetabular dysplasia (r = - 0.706, - 0.596, - 0.504, respectively; P < 0.001). CONCLUSION: Labral width can reliably be measured utilizing imaging techniques including magnetic resonance and computed tomography. The pooled mean labral width was 6.2 mm, and height 4.6 mm. The establishment of a gold-standard of measurement on arthroscopy and advanced imaging would aid in clinical decision-making regarding treatment options for patients presenting with a painful hip, particularly those with hypoplastic labra, and provide radiological guidelines for standardized labrum size classifications. LEVEL OF EVIDENCE: Level IV.
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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 | 0.042 | 0.182 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.023 | 0.015 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".