Guidelines for Discontinuation of Antipsychotics in Patients Who Recover From First-Episode Schizophrenia Spectrum Disorders: Derived From the Aggregated Opinions of Asian Network of Early Psychosis Experts and Literature Review
Bibliographic record
Abstract
OBJECTIVE: Antipsychotic discontinuation has been a long-standing clinical and medicolegal issue. The Asian Network of Early Psychosis developed guidelines for antipsychotic discontinuation in patients who recover from first-episode non-affective psychosis. We reviewed the existing studies and guidelines on antipsychotic discontinuation to develop guidelines for antipsychotic discontinuation in such patients. METHODS: We reviewed the relevant studies, reviews, guidelines, and ongoing trials related to antipsychotic discontinuation in patients with first-episode psychosis or schizophrenia. The quality of randomized controlled trials was assessed using the Grading of Recommendations Assessment, Development, and Evaluation approach. RESULTS: Most studies had low to very low quality, and 2 had moderate quality. All studies, except 1, advised against antipsychotic discontinuation because of higher relapse rates in the antipsychotic discontinuation group (19%-82% at 1-year follow-up) than the treatment maintenance group compared with the maintenance group. Based on expert opinion and Grading of Recommendations Assessment, Development, and Evaluation evidence of trials, guidelines have been recommended for future discontinuation studies on patients with first-episode schizophrenia spectrum disorders. CONCLUSIONS: Currently, there are no recommendations for antipsychotic discontinuation in patients with first-episode schizophrenia spectrum disorders. However, there is a pressing need to conduct more rigorous research in remitted patients using more stringent criteria of full recovery, which can form the basis of guidelines on when and how antipsychotics should be tapered and discontinued. Studies that evaluate the patient characteristics and biomarkers that predict successful antipsychotic discontinuation are also needed.
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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 | 0.055 | 0.126 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.015 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".