Clozapine-Associated Obsessive-Compulsive Symptoms and Their Management: A Systematic Review and Analysis of 107 Reported Cases
Bibliographic record
Abstract
BACKGROUND: It is not uncommon to find obsessive-compulsive symptoms (OCS) in patients treated with clozapine. These symptoms are attributed to anti-serotonergic effects of clozapine. The objective of this study was to conduct a systematic review of reported cases of clozapine-associated OCS to better understand the nature and management of these symptoms. METHODS: MEDLINE, Embase, and PsycINFO databases were searched with no publication year or language restrictions. Studies reporting cases of clozapine-associated OCS, either de novo or exacerbation of preexisting OCS, were included. The final search date was July 11, 2019. RESULTS: Fifty-seven studies, involving 107 cases (75 de novo, 32 exacerbated OCS), were included. Clozapine triggered moderate-severe OCS at varying doses (100-900 mg/day) and treatment durations (median 6 months, interquartile range 2-24 months). Higher severity was significantly associated with preexisting OCS, poorer insight into OCS, and active psychosis at the time of OCS. Common strategies to treat clozapine-associated OCS included adding selective serotonin reuptake inhibitors, clomipramine, or aripiprazole, often accompanied by clozapine dose reduction. The rate of response to antidepressants was 49% (29/59), where younger age, shorter duration of underlying illness, shorter cloza-pine treatment duration, better insight into OCS, and presence of taboo thoughts were significantly associated with antidepressant response. Subsequent clozapine dose reduction was effective in many non-responders, where aripiprazole was simultaneously added in 50% (8/16). CONCLUSIONS: Clozapine can trigger severe OCS. Adding aripiprazole with/without clozapine dose reduction may be a good alternative to antidepressants for managing clozapine-associated OCS. Clinicians should be more vigilant about these adverse effects and administer appropriate treatments.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.015 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".