A systematic review of meta-analyses in orthopaedic surgery between 2000 and 2016
Bibliographic record
Abstract
AIMS: The aims of this systematic review were to describe the quantity and methodological quality of meta-analyses in orthopaedic surgery published during the last 17 years. MATERIALS AND METHODS: MEDLINE, EMBASE, and PubMed, between 1 January 2000 and 31 December 2016, were searched for meta-analyses in orthopaedic surgery dealing with at least one surgical intervention. Meta-analyses were included if the interventions involved a human muscle, ligament, bone or joint. RESULTS: A total of 392 meta-analyses met eligibility criteria, for which the mean AMSTAR quality score was 7.1/11. There was a positive correlation between the year of publication and the quality of the meta-analysis (r = 0.238, p < 0.001). Between 2000 and 2011, the mean AMSTAR score corresponded to that of a medium quality review. However, between 2012 and 2016, the mean scores have been consistently equivalent to those of a high-quality review. The number of meta-analyses published increased 10-fold between 2005 and 2014. CONCLUSION: The quantity and quality of meta-analyses in orthopaedic surgery which have been published has increased, reaching a plateau in 2012. Methodological flaws remain to be addressed in future meta-analyses in order to continue increasing the quality of the orthopaedic literature. Cite this article: Bone Joint J 2018;100-B:1270-4.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.548 | 0.150 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.066 | 0.031 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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; both teacher heads 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".