Dry mouth effects from drugs used for depression, anxiety, schizophrenia and bipolar mood disorder in adults: systematic review
Bibliographic record
Abstract
BACKGROUND: Poor oral health is increasingly recognised as an important comorbidity in people with psychiatric illness. One risk factor is psychotropic-induced dry mouth. AIMS: To perform a systematic review of the severity of dry mouth due to psychotropic drugs in adults (CRD42021239725). Study quality was assessed using the Cochrane risk of bias tool. METHOD: We searched the following databases: PubMed, EMBASE, PsycINFO, Cochrane Central Register of Controlled Trials, CINAHL and Web of Science. We included randomised controlled trials (RCTs) measuring the severity of drug-induced hyposalivation and xerostomia. RESULTS: Eighteen RCTs with 605 participants were included. Severity of drug-induced dry mouth was compared among eight drug classes and/or against placebo. All studies were published 20 to 40 years ago and included tricyclic antidepressants (TCAs), serotonin specific reuptake inhibitors (SSRIs) and other drug classes. Meta-analysis was not feasible owing to design heterogeneity. TCAs caused more severe dry mouth, both objectively and subjectively, than placebo or other drug classes. SSRIs were generally associated with less severe symptoms. However, there was no information on antipsychotics or more recently available antidepressants, and there was minimal information on mood stabilisers. Most studies were on healthy subjects, limiting the generalisability of findings. Only one study measured both objective and subjective dry mouth, which have different clinical implications. CONCLUSIONS: Psychotropic-induced dry mouth is a poorly researched area, and well-designed RCTs of newer psychotropic drugs using standardised objective and subjective measures are indicated. Given the ongoing use of TCAs for treatment-resistant depression, prescribers need to remain vigilant for xerostomia.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".