Comparing the Impact of Atropine Drops and Amitriptyline Tablets in Treatment of Clozapine-Induced Sialorrhea: A Randomized Double-Blind Placebo Controlled Clinical Trial
Bibliographic record
Abstract
Clozapine is an atypical antipsychotic employed to treat patients with psychotic disorders. It is associated with sialorrhea as a problematic adverse effect in 30-80% of cases. Various medications such as atropine and amitriptyline have been suggested for its treatment. We aimed to compare the effects of atropine drops and amitriptyline tablets in the treatment of clozapine-induced sialorrhea. The present double-blind, randomized clinical trial aimed to evaluate the effect of atropine drops and amitriptyline tablets in reducing clozapine-induced sialorrhea in patients with psychotic disorders. Forty-six patients were treated for 4 weeks in two groups: group “A”(atropine drops and placebo tablets) and group “B” (amitriptyline tablets and placebo drops). Toronto Nocturnal Hypersalivation Scale (TNHS) and Clinical Global Impression (CGI) rating scale were used for measurement of the severity and frequency of sialorrhea and global symptom severity and treatment response, respectively. Kolmogorov–Smirnov, Chi-square and Fisher's exact tests were used for statistical analyses. Demographic information of the two groups had no significant difference (P>0.05). There was no patient with adverse effects that interfered with the study. Mean TNHS and Meier scores in groups “A” and “B” were 3.48±0.21 vs.3.24±0.18, and 1.9±0.07 vs.1.86±0.07, respectively, and the difference was not statistically significant (P=0.35 vs. P=0.67). In patients with clozapine-induced sialorrhea, 1% atropine drops (1.7 mg sublingual drops daily) can be just as effective as amitriptyline tablets (29.08 mg daily, oral) in controlling sialorrhea.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 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) | 0.007 | 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".