Botulinum Toxin for Shoulder Pain: A Cochrane Systematic Review
Bibliographic record
Abstract
OBJECTIVE: To perform a Cochrane Systematic Review of benefits and harms of botulinum toxin for shoulder pain. METHODS: We included clinical trials of adults with shoulder pain (population), comparing botulinum toxin (intervention) to placebo or other therapies (comparison), and reporting benefits or harms (outcomes). We calculated relative risk (RR) for categorical outcomes and mean differences (MD) for continuous outcomes. RESULTS: Six randomized controlled trials (RCT) with 164 patients all comparing single botulinum toxin type A injections to placebo were included. Five RCT in patients with post-stroke shoulder pain found that an intramuscular injection of botulinum toxin type A significantly reduced pain at 3-6 months (MD -1.2 points on 0-10 scale, 95% CI -2.4 to -0.07) and improved shoulder external rotation at 1 month (MD 9.8°, 95% CI 0.2° to 19.4°). Number of adverse events did not differ between groups (RR 1.46, 95% CI 0.6 to 24.3). One RCT in arthritis-related shoulder pain showed that single intraarticular botulinum toxin type A injection reduced pain (MD -2.0 on 0-10 scale, 95% CI -3.7 to -0.3) and shoulder disability (MD -13.4 on 0-100 scale, 95% CI -24.9 to -1.9) and improved shoulder abduction (MD 13.8°, 95% CI 3.2° to 44.0°) at 1 month, compared with placebo. Serious adverse events did not differ between groups (RR 0.35, 95% CI 0.11, 1.12). CONCLUSION: With evidence from few studies with small sample sizes and medium to high risk of bias, botulinum toxin type A injections decreased pain and improved shoulder function in patients with chronic shoulder pain due to spastic hemiplegia or arthritis.
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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 | 0.010 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.009 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".