Clozapine-Induced Hypersalivation: A Review of Treatment Strategies
Bibliographic record
Abstract
OBJECTIVE: Clozapine-induced hypersalivation (CIH) is a significant side effect affecting about one-third of patients treated with clozapine. CIH can be stigmatizing, can affect quality of life, and can result in discontinuation of clozapine treatment. The purpose of this review is to provide an understanding of CIH, specifically, its pathophysiology, measurement, and the evidence for CIH treatment alternatives. METHODS: We searched MEDLINE from 1980 to June 2006 for all reported pharmacologic treatment studies related to CIH. We identified additional references by a manual search of the bibliographies of retrieved articles. RESULTS: Several studies reported improvement of CIH with both selective and nonselective anticholinergic medications. However, with the exception of local anticholinergic agents such as ipratropium bromide and atropine eye drops, potential systemic adverse effects limit the effectiveness of this class of medications. Open-label studies of clonidine, an alpha2 antagonist, suggest that it may be beneficial in managing CIH. Other pharmacologic treatments, such as amisulpride and botulinum toxin, may be useful in refractory CIH cases. CONCLUSION: Although few randomized controlled trials were found in the literature, this review highlights potential treatment alternatives for this common and disabling cause of hypersalivation. Prompt and effective treatment of CIH may assist with treatment tolerability, adherence, and outcomes in patients with treatment-refractory schizophrenia. Information on funding and support and author affiliations appears at the end of the article.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".