Effectiveness of antipsychotic drug therapy for treating psychosis in people with epilepsy: A systematic review
Bibliographic record
Abstract
Individuals with epilepsy are at risk of developing preictal, ictal, postictal and interictal psychoses. Antipsychotic drugs (APDs) are the main class of drugs used to treat psychosis and schizophrenia. The efficacy and safety of APDs as a treatment for epileptic psychosis is not well understood. This systematic review aimed to assess the effectiveness and adverse effects of APDs for treating psychosis in people with epilepsy. We adhered to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched MEDLINE, Embase, PsycInfo, and AMED (Allied and Complementary Medicine) from database inception to June 20, 2023. We contacted experts in the field and performed citation searches to identify additional records. Title, abstract, full-text review, and data analysis were conducted in duplicate, with conflicts resolved by discussion among authors. Given the considerable heterogeneity of study designs, meta-analysis was not deemed appropriate; instead, the results were tabulated in a narrative synthesis. The Joanna Briggs Institute Risk of Bias tool and GRADE (Grading of Recommendations Assessment, Development, and Evaluation) framework were used to assess study quality. We identified 13 studies with a total of 1180 participants. In the four case series included, the psychotic symptoms of 25 of 28 patients treated with APDs partially improved or fully resolved. Three of the four cohort studies reported an association between antipsychotic use and longer duration of psychotic episodes, two found similar results in both APD and non-APD groups, and two did not report control psychosis outcomes. When reported, seizure frequency was observed to remain unchanged or decrease following APD treatment. The evidence on the effectiveness of antipsychotics in the treatment of psychosis in epilepsy is inconclusive and may reflect confounding by indication. However, most studies suggest that antipsychotics were not associated with a marked worsening in seizure frequency. It remains unclear whether antipsychotics should be used in epilepsy, and well-controlled cohort studies and randomized controlled trials are necessary to draw definitive conclusions.
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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 | 0.009 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".