Comparison of pregabalin with doxepin in the management of uremic pruritus: a randomized single blind clinical trial
Bibliographic record
Abstract
INTRODUCTION: Pruritus is one of the frustrating skin manifestations of advanced renal failure. Many options have been used for the management of uremic pruritus (UP) such as pregabalin. There are some studies that reported beneficial effects of pregabalin in reducing UP; however, most of them did not have a comparator arm. Therefore, we designed this study to compare antipruritic effects of pregabalin with doxepin in the management of pruritus in hemodialysis patients. METHODS: Seventy-two patients suffering from UP were randomly assigned to receive pregabalin (50 mg every other day) or doxepin (10 mg per day) for 4 weeks. Severity of pruritus and its effect on quality of life were assessed by visual analog scale (VAS), 5-D itch scale and dermatology life quality index (DLQI) at baseline and after 1 week, 2 weeks and 4 weeks of the treatment. FINDINGS: Mean scores of the VAS decreased from 7.5± 1.4 and 7.1 ± 1.3 at baseline to 2.1 ± 2.6 and 4.2 ± 2.6 at the end of the study (P < 0.001) in the pregabalin and doxepin groups, respectively. Similarly, pregabalin significantly reduced mean scores of the 5-D itch scale and the DLQI compared to doxepin. The most reported side effect in each group was somnolence which occurred in similar rates in the both groups. DISCUSSION: Pregabalin was more effective than doxepin in reducing the severity of uremic pruritus and improving the quality of life of patients in this study, so we suggest that clinician can consider pregabalin prior to using antihistamine drugs in the management of severe itch in hemodialysis patients.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".