Clozapine once- versus multiple-daily dosing: a two-center cross-sectional study, systematic review and meta-analysis
Bibliographic record
Abstract
Evidence regarding effectiveness and safety of clozapine once- vs. multiple-daily dosing is limited. We compared demographic and clinical parameters between patients with once- vs. multiple-daily dosing in the Department of Psychiatry and Psychotherapy, University of Regensburg, Germany (AGATE dataset), and the Department of Psychiatry, Lausanne University Hospital, Switzerland, using non-parametric tests. Effectiveness and safety outcomes were available in the AGATE dataset. We performed a systematic review in PubMed/Embase until February 2022, meta-analyzing studies comparing clozapine once- vs. multiple-daily-dosing. We estimated a pooled odds ratio for adverse drug-induced reactions (ADRs) and meta-analyzed differences regarding clinical symptom severity, age, percentage males, smokers, clozapine dose, and co-medications between patients receiving once- vs. multiple-daily dosing. Study quality was assessed using the Newcastle-Ottawa-Scale. Of 1494 and 174 patients included in AGATE and Lausanne datasets, clozapine was prescribed multiple-daily in 74.8% and 67.8%, respectively. In the AGATE cohort, no differences were reported for the clinical symptoms severity or ADR rate (p > 0.05). Meta-analyzing eight cohorts with a total of 2810 clozapine-treated individuals, we found more severe clinical symptoms (p = 0.036), increased ADR risk (p = 0.01), higher clozapine doses (p < 0.001), more frequent co-medication with other antipsychotics (p < 0.001), benzodiazepines (p < 0.001), anticholinergics (p = 0.039), and laxatives (p < 0.001) in patients on multiple- vs. once-daily dosing. Of six studies, five were rated as good, and one as poor quality. Patients responding less well to clozapine may be prescribed higher doses multiple-daily, also treated with polypharmacy, potentially underlying worse safety outcomes. Patient preferences and adherence should be considered during regimen selection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".