Botulinum toxin A versus bupivacaine trigger point injections for the treatment of myofascial pain syndrome: A randomised double blind crossover study
Bibliographic record
Abstract
The treatment of myofascial pain syndrome (MPS) is diverse and includes trigger point injections of various substances including local anesthetics, steroids and Botulinum toxin A (BTX A). The purpose of this study was to compare the effectiveness of trigger point injections using BTX A versus bupivacaine, both in combination with a home-based rehabilitation program. To be enrolled, subjects first had to demonstrate responsiveness to bupivacaine trigger point injection. In this single center, double blind, randomized, cross-over trial, 18 patients with MPS received trigger point injections of either 25 units Botulinum toxin A or 0.5 ml of 0.5% bupivacaine per trigger point. A maximum of eight trigger points were injected per subject. Subjects were followed until their pain returned to 75% or more of their pre-injection pain for two consecutive weeks, after which there was a 2 week wash-out period. The subjects then crossed over and had the same trigger points injected with the other agent. All subjects participated in a home exercise program involving static stretches of the affected muscles. Both treatments were effective in reducing pain when compared to baseline (P=0.0067). There was, however, no significant difference between the BTX A and 0.5% bupivacaine groups in duration or magnitude of pain relief, function, satisfaction or cost of care (cost of injectate excluded). Considering the high cost of BTX A, bupivacaine is deemed a more cost-effective injectate for MPS.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".