Midterm Outcomes Following Hip Labral Augmentation
Bibliographic record
Abstract
Objectives: Arthroscopic hip labral preservation techniques have evolved over the last decade. Arthroscopic hip labral augmentation with iliotibial band (ITB) autograft placed into a labral defect with viable circumferential fibers is a novel treatment option to restore the hip suction seal and improve functionality. The purpose of this study is to determine midterm (3-5 year follow up) outcomes of arthroscopic hip labral augmentation procedure. Methods: Patients who underwent arthroscopic hip labral augmentation from August 2011 to March 2017 were prospectively evaluated. Pre- and post-operative patient reported outcome scores were compared and included SF12 PCS, SF12 MCS, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Modified Harris Hip Score (mHHS), Hip Outcome Score (HOS) (Activities of Daily Living (ADL) and Sport). Post-operative Tegner Activity Scale and patient satisfaction (1 – 10) were also evaluated. Results: One hundred and six patients underwent arthroscopic hip labral augmentation with minimum 3-year follow-up. Mean follow-up was 5-year follow-up (range, 3 to 9.2 years). All patient reported outcomes improved after labral augmentation (SF12 PCS 39±8 vs. 50±10, p>0.01; mHHS 59±15 vs. 79±21, p<0.01; WOMAC 31±16 vs. 16±17, p<0.01; HOS ADL 64±17 vs. 84±21, p<0.01; HOS Sport 41±22 vs. 71±29, p<0.01). Median post-operative Tegner score was 4. Median post-operative patient satisfaction was 9 out of 10 (range, 1-10). In terms of survivorship, 12 patients (11%) required revision surgery and 6 (5.7%) converted to total hip arthroplasty (THA). Conclusions: Arthroscopic hip labral augmentation is a successful treatment option for patients that have viable circumferential fibers present at the time of arthroscopy. This technique continues to show improved patient reported outcomes and is another hip labral preservation technique that may help reestablish the intra-articular fluid suction seal.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".