Topical 2% Amitriptyline and 1% Ketamine in Neuropathic Pain Syndromes
Bibliographic record
Abstract
BACKGROUND: A double-blind, randomized, placebo-controlled 3-week study evaluated the efficacy of topical 2% amitriptyline, 1% ketamine, and a combination of both in treating patients with neuropathic pain. METHODS: Ninety-two patients with diabetic neuropathy, postherpetic neuralgia, or postsurgical/posttraumatic neuropathic pain with allodynia, hyperalgesia, or pinprick hypesthesia were randomly assigned to receive one of four creams (placebo, 2% amitriptyline, 1% ketamine, or 2% amitriptyline-1% ketamine combined). The primary outcome measure was change in average daily pain intensity (baseline week vs. final week) using an 11-point numerical pain rating scale. Secondary outcomes included the McGill Pain Questionnaire, measures of allodynia and hyperalgesia, and patient satisfaction. RESULTS: A reduction in pain scores of 1.1-1.5 units was observed in all groups, and there was no difference between groups. Blood concentrations revealed no significant systemic absorption. Minimal side effects were encountered. CONCLUSION: This randomized, placebo-controlled trial examining topical 2% amitriptyline, 1% ketamine, and a combination in the treatment of neuropathic pain revealed no difference between groups. Optimization of doses may be required, because another study has revealed that higher concentrations of these agents combined do produce significant analgesia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".