The efficacy of oral non-steroidal anti-inflammatory drugs for rotator cuff tendinopathy: A systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To conduct a systematic review and meta-analysis on the efficacy of oral non-steroidal anti-inflammatory drugs for rotator cuff tendinopathy. DESIGN: Systematic review. METHOD: A literature search was conducted in 4 databases for randomized controlled trials published until 05/2013, comparing the efficacy of oral anti-inflammatory drugs to any other intervention. Studies characteristics were extracted using a standardized form and the methodological quality was evaluated. Results were summarized qualitatively or quantitatively. RESULTS: The mean methodological score of the 12 included studies was 53.6 ± 8.8%. The majority of studies included acute cases and were underpowered to detect differences in adverse events. Compared to a placebo, oral non-steroidal anti-inflammatory drugs were found to provide short-term pain relief (pooled mean difference: -2.69; 95% confidence interval: -1.96 to -3.41) but not function. Oral anti-inflammatory- drugs and corticosteroids injections have similar short-term efficacy in terms of pain reduction as well as in function (pooled standardized mean difference: 0.09; 95% confidence interval: -0.25 to 0.44). CONCLUSION: Low to moderate grade evidence exists regarding the efficacy of non-steroidal anti-inflammatory drugs for rotator cuff tendinopathy. Oral anti-inflammatory drugs are effective in reducing short-term pain but not function. In terms of pain and function, oral anti-inflammatory drugs in the short term are as effective as corticosteroid injections.
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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 | 0.019 | 0.042 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.033 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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; 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".