Methodological quality of systematic reviews addressing femoroacetabular impingement
Bibliographic record
Abstract
PURPOSE: As the body of literature on femoroacetabular impingement (FAI) continues to grow, clinicians turn to systematic reviews to remain current with the best available evidence. The quality of systematic reviews in the FAI literature is currently unknown. The goal of this study was to assess the quality of the reporting of systematic reviews addressing FAI over the last 11 years (2003-2014) and to identify the specific methodological shortcomings and strengths. METHODS: A search of the electronic databases, MEDLINE, EMBASE and PubMed, was performed to identify relevant systematic reviews. Methodological quality was assessed by two reviewers using the revised assessment of multiple systematic reviews (R-AMSTAR) scoring tool. An intraclass correlation coefficient (ICC) with 95 % confidence intervals (CI) was used to determine agreement between reviewers on R-AMSTAR quality scores. RESULTS: A total of 22 systematic reviews were assessed for methodological quality. The mean consensus R-AMSTAR score across all studies was 26.7 out of 40.0, indicating fair methodological quality. An ICC of 0.931, 95 % CI 0.843-0.971 indicated excellent agreement between reviewers during the scoring process. CONCLUSIONS: The systematic reviews addressing FAI are generally of fair methodological quality. Use of tools such as the R-AMSTAR score or PRISMA guidelines while designing future systematic reviews can assist in eliminating methodological shortcomings identified in this review. These shortcomings need to be kept in mind by clinicians when applying the current literature to their patient populations and making treatment decisions. Systematic reviews of highest methodological quality should be used by clinicians when possible to answer clinical questions.
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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 | 0.304 | 0.669 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.019 |
| Bibliometrics | 0.029 | 0.024 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".