Pregabalin versus gabapentin in the treatment of neuropathic pruritus in maintenance haemodialysis patients: A prospective, crossover study
Bibliographic record
Abstract
AIM: Pruritus is common in dialysis patients. Peripheral neuropathy is also prevalent in this patient population. However, the role of neuropathy in the genesis of uraemic itch has not been adequately studied to date. Therefore, we aimed to investigate the effects of gabapentin and pregabalin on uraemic pruritus along with neuropathic pain in patients receiving haemodialysis. METHODS: This is a 14 week long randomized, prospective, cross-over trial. Haemodialysis patients with established neuropathy and/or neuropathic pain were included. Fifty patients were randomly assigned to gabapentin 300 mg after each haemodialysis session and pregabalin 75 mg daily. After 6 weeks of treatment, cross-over was performed and patients received the other drug for another 6 weeks. Short Form of McGill Pain Questionnaire and Visual Analogue Scale were used to evaluate pain and pruritus, respectively. At each week's visit, patients were interrogated in terms of adverse effects of study drugs. Baseline laboratory data and demographic characteristics were recorded from patient charts. RESULTS: Forty (12 males, 28 females) out of 50 patients completed the study. Mean age was 58.2 ± 13.7. Overall, 29 out of 40 patients (72.5%) had pruritus symptoms at baseline evaluation. Fifteen patients (37.5%) were diabetic. Thirty-one out of 40 patients (77.5%) had electromyography (EMG)-proven peripheral neuropathy. Twenty three patients (57.5%) had both EMG-proven neuropathy and pruritus. Gabapentin and pregabalin improved both neuropathic pain and pruritus significantly. There was no difference between the study drugs in terms of efficacy against pain and pruritus. CONCLUSION: Treatment of neuropathic pain with either pregabalin or gabapentin effectively ameliorates uraemic itch.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.002 | 0.002 |
| 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".