Botulinum Toxin Type A for Pain in Advanced Parkinson’s Disease
Bibliographic record
Abstract
Background and Objective Pain is a frequent symptom in Parkinson's disease (PD), and the therapeutic alternatives are scarce. The goal of this trial was to measure the effects of botulinum toxin type A (BTXA) in the treatment of limb pain in advanced PD. Methods A randomized double-blind crossover versus placebo study of BTXA for limb pain in advanced Parkinson's disease was conducted. Subjects received individualized BTXA/placebo dosing per pain distribution in limbs. The primary outcome was a measure of change in global pain on a numeric rating scale (NRS) at 4 and 12 weeks postinjection and on a visual analogue scale 12 weeks after treatment. Secondary outcomes included the percentage of responders, physician-rated clinical global impressions, MDS-UPDRS and PDQ-39 scores, and adverse events. Results A total of 12 subjects completed the trial. Treatment with BTXA (average dose=241.66 U) produced a significant reduction in NRS score 4 weeks after the injections (-1.75 points, range from -3 to 7, p=0.033). However, there was no significant difference compared to placebo (p=0.70). Participants with dystonic pain showed a greater reduction in NRS score after 4 weeks when treated with BTXA (2.66 points vs. 0.75 for placebo). There were no significant differences for any of the secondary outcomes or significant adverse events. Conclusions Targeted BTXA injections were safe in patients with limb pain and advanced PD; however, the present study failed to show a significant effect when compared to placebo. Further studies may be focused on evaluating the effect of BTXA particularly in dystonic pain.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".