Amitriptyline vs. pregabalin in painful diabetic neuropathy: a randomized double blind clinical trial
Bibliographic record
Abstract
AIMS: To compare the efficacy and safety of pregabalin and amitriptyline in alleviating pain associated with diabetic peripheral neuropathy. METHODS: A randomized, double-blind, crossover, active-control, clinical trial with variable dose titration was carried out (n = 51). Amitriptyline orally, at doses of 10, 25 and 50 mg at night-time and pregabalin orally, at doses of 75, 150 and 300 mg twice daily, by optional titration was used. Each drug treatment was of 5 weeks. There was a placebo washout period for 3 weeks between the two drugs. Assessment for pain relief, overall improvement and adverse events were carried out. RESULTS: Good, moderate and mild pain relief were noted in 21 (48%), 6 (13%) and 7 (15%) patients on pregabalin and 15 (34%), 5 (11%) and 12 (27%) patients on amitriptyline, respectively, by patient's global assessment of efficacy and safety. Patient and physician's global assessment, McGill pain questionnaire, Likert pain scale and Patient Global Impression of Change showed no significant difference between the treatments, although improvement with both treatments was seen from the first week. Of the 52 adverse events reported, 34 (65.4%) were with amitriptyline, drowsiness being the commonest [in 19 (43%) patients]. Pregabalin caused adverse events in 18 (25%), of which drowsiness was the most common in nine (20%) patients. The preferred pregabalin dose was 150 mg twice daily. CONCLUSIONS: As there are few differences between the two treatments in efficacy, pregabalin 150 mg twice daily might be the alternative choice as it is associated with fewer adverse effects in our population.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".