Health-Related Quality of Life After Hip Arthroscopy for Femoroacetabular Impingement: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Context: Hip pain from femoroacetabular impingement (FAI) can impair health-related quality of life (HRQL) but can be treated via hip arthroscopy techniques. Objective: To systematically assess the HRQL outcomes after arthroscopic management of FAI. Date Sources: Three online databases (EMBASE, PubMed, and Ovid [MEDLINE]) were searched for relevant literature from database inception until June 2018 and screened by 2 reviewers independently and in duplicate. Study Selection: Level I to IV English studies that investigated HRQL outcomes after hip arthroscopy were included. Data for generic and hip-specific HRQL outcomes were collected. Mean differences were plotted in a forest plot when possible. Study Design: Systematic review. Level of Evidence: Level 4. Results: A total of 29 studies were included for assessment. Of the 6476 patients (6959 hips), the mean age was 32 years (range 9-79 years) and 50.7% were female. Significant improvements were reported in all studies assessing generic HRQL outcomes, including the 12-Item Short Form Health Survey (range of mean postoperative scores, 82.2-89.8), and EuroQOL-5D scores (range of mean postoperative scores, 0.74-0.87) between 12 and 24 months postoperatively. Significant improvements were similarly identified in the hip-specific HRQL outcomes scores, with the majority of studies also reporting improvement between 12 and 24 months postoperatively. Mean improvement in International Hip Outcome Tool–33 scores from preoperative values to postoperative values ranged from 22.7 to 43.2 ( I 2 = 44%), for studies with follow-up between 12 and 24 months. Conclusion: Hip arthroscopy can lead to significant improvement in generic and hip-specific HRQL outcomes at 12 to 24 months postoperatively in patients with FAI who do not have advanced hip osteoarthritis. Confirmatory, high-quality, prospective studies are warranted to compare this observed improvement with other treatment modalities for FAI and to determine long-term outcomes.
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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 | 0.014 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.032 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".