Sertraline can reduce uremic pruritus in hemodialysis patient: A double blind randomized clinical trial from Southern Iran
Bibliographic record
Abstract
INTRODUCTION: Uremic pruritus is an undesirable complication of end stage renal disease (ESRD). In spite of introduction of many treatments for this complication, it has no certain cure. The aim of this study was to assess sertraline effect on uremic pruritus. METHODS: In the present clinical trial study, we randomly divided our patients into two groups; trial group that received sertraline and control group that consumed placebo. We measured the severity of pruritus by two scoring systems (visual analogue scale and DUO) at the beginning and during the study with a-2-week interval. Data were analyzed by SPSS 18.0 and a P value < 0.050 considered as significant. FINDINGS: The mean age of our patients was 44.1 ± 16.1 years. Pruritus intensity significantly decreased in both groups (P < 0.001) and both scoring systems. Although the amount of decrease in trial group was significantly more than control group (P < 0.001). We found a direct relation between blood urea nitrogen and phosphorus and the degree of itching in VAS system (P < 0.009). There was a reverse significant relation between itching and calcium in both scoring systems (P < 0.012). Also pruritus intensity was directly correlated with C-reactive protein in both scoring systems (P < 0.05). DISCUSSION: Depends on present study and previous ones, inflammation appears to play a significant role in uremic itching. Sertraline is an effective drug in reducing this complaint possibly due to its effect on reducing inflammatory cytokines. In addition there is no need to adjust sertraline dosage in patients with ESRD. Sertraline might be a treatment for patients with ESRD who do not respond to other routine drugs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".