Botulinum toxin therapy for management of phantom and residual limb pain following amputation: A systematic review
Bibliographic record
Abstract
Chronic pain following amputation is debilitating. Due to its mechanisms in modulating muscle contraction and pain, botulinum toxin has been investigated as a treatment option for phantom limb pain (PLP) and residual limb pain (RLP). The objective of this study was to determine the efficacy of botulinum toxin injection in the management of PLP and RLP following major limb amputation using a systematic review of the literature. The databases Medline, CINAHL, EMBASE, Scopus, Web of Science, and Cochrane were searched from inception through October 30, 2023. The search identified 50 articles; 37 underwent full-text review, and 11 were included in the final review. Eighty-nine individuals with pain were investigated by the included studies; 53 had RLP and 63 had PLP. There was significant variation in botulinum toxin type, injection method, and dosage. Twenty-one (53.9%) and 27 (64.3%) participants had improvement in PLP and RLP following botulinum toxin injection, respectively. Therefore, there is potential for use of botulinum toxin for the treatment of PLP and RLP. However, due to the minimal number of studies, small sample sizes, and heterogenous methodologies, our ability to conclude with certainty the efficacy of botulinum toxin injection on the treatment of PLP and RLP following amputation is limited.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".