Polypharmacy in clozapine-treated patients: A retrospective analysis of 667 patients in Ottawa, Canada
Bibliographic record
Abstract
• Clozapine polypharmacy was found in over 80 % of TRS patients in this sample. • Over 50 % of TRS patients received clozapine in combination with at least one other antipsychotic. • Schizoaffective diagnosis, older age and female sex were associated with increased polypharmacy risk. • Polypharmacy correlated with comorbid diabetes and respiratory disease. • Data from 667 clozapine-treated patients in Canada fills a key knowledge gap. Clozapine is the gold standard for treatment-resistant schizophrenia (TRS), yet only 40 % of patients respond. Clinicians often add other psychotropics despite limited evidence and possible harms. Canadian data on this practice remains sparse. We retrospectively reviewed charts of 667 adults prescribed clozapine between 2017-2020 in Ottawa, Canada. Clozapine augmentation was defined as prescription of ≥1 other psychotropic medication. Descriptive statistics summarized medication class frequences; X 2 or Wilcoxon tests assessed associations with demographic and clinical variables. After excluding four charts without medication data, 550/663 patients (83 %) received at least one add-on class (median 2 classes, IQR 1-3). Anti-psychotics were the commonest add-ons with 354 patients (53.4 % of all; 64.4 % of the augmented group) receiving clozapine plus another antipsychotic, most often aripiprazole (n=83). Valproate/divalproex was the commonest add-on (n=115). Clozapine with Paliperidone was the most frequent two - drug combination (n=29). Augmentation was more frequent in schizoaffective disorder than schizophrenia (91 vs. 81 %, p =0.010), in older adults (median 46 vs. 38 yrs, p <0.001), in females (88 vs. 81 %, p =0.028), and in patients with respiratory disease ( p =0.015) or diabetes ( p =0.019). Residence in supported or inpatient housing was also associated with augmentation ( p <0.001). Recent hospitalization, current smoking, and self-reported ethnicity showed no association with augmentation ( p ≥0.33). Clozapine polypharmacy is common in patients treated at this Canadian psychiatric hospital, with more than half of clozapine-treated patients receiving an additional antipsychotic. This high prevalence highlights a need for evidence-based guidelines and integrated monitoring to balance symptomatic benefit against additive pharmacologic risk in TRS.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".