Botulinum Toxin A: A Novel Therapeutic Modality for Upper Extremity Chronic Regional Pain Syndrome
Bibliographic record
Abstract
Background: Complex regional pain syndromes (CRPS) is a disease that is poorly understood. It is a chronic pain syndrome characterized by sympathetic disruptions as well as CNS sensitization. Botulinum Toxin-A has been shown to have efficacy in Raynaud's as well as other neuropathic pain disorders. Perhaps BTX-A warrants experimentation in the treatment of CRPS. Methods: Patients with CRPS refractory to 2 or more regional sympathetic nerve blocks in 2007 were included in the study. Patient's were asked to rank their initial pain on a visual analog scale of 0 to 10 (10 being the worst pain). "Tenderness maps" were marked on patient's areas of most pain in 1 by 1 centimeter grids. Each box on the grid was injected with 10 IU of BTX-A after nerve blocks with 1% lidocaine. Treatment sessions occured on a monthly basis with VAS pain scores being re-assessed immediately before the new treatment. t Test, linear regression, and Cohen's D-test were used to analyze the correlation of the data. Results: Study sample was 20 patients. Etiology of CRPS was 6 amputations, 4 crush injuries, 4 penetrating injuries, and 2 lacerations. Average pain reduction on VAS scale achieved was 2.05 points. Average percentage pain reduction was 22.94%. Cohen's D Test also showed a meaningful difference with a score of 1.01. Linear regression R2 = 0.491. Maximum pain reduction, on average, was achieved by treatment 9. Conclusion: Despite the esoteric etiology of CRPS, BTX-A has a well-demonstrated mechanism of effect. BTX-A should be further explored as a treatment modality for CRPS.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".