The effect of transdermal nitroglycerin on pain control in diabetic patients with peripheral neuropathy
Bibliographic record
Abstract
BACKGROUND: Despite high prevalence of diabetic peripheral neuropathy there is no definite treatment for the condition. The present study was conducted to assess the efficacy of transdermal nitroglycerin patch in pain control of patients with DPN. METHODS: This randomized, double-blind, crossover study was conducted on 30 patients with symmetric distal peripheral neuropathy and good glycemic control. The patients were randomly assigned to receive nitroglycerin transdermal and placebo patches in two 4-week stages. The severity of pain and other neuropathic sensory symptoms were assessed at the end of each course. RESULTS: Mean reduction of pain severity was more prominent in the NTG group compared to placebo group of the study (p = 0.048) at least during the first phase of the study. Except for mood and sleep, a significant reduction in all Brief Pain Inventory scores was noted in the drug group (all corrected p < 0.05). SF-MPQ also showed the drug patch to be effective in improving different aspects of pain measured using McGill Pain Questionnaire, except for Role-emotional. CONCLUSIONS: It could be concluded that nitroglycerin plasters can effectively help alleviate pain in patients with diabetic neuropathy. TRIAL REGISTRATION: IRCT201308223213N1.
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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 | 0.001 |
| 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 | 0.000 | 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".