Immediate vs Gradual Discontinuation in Antipsychotic Switching: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Background: Antipsychotic switching is routine in clinical practice, although it remains unclear which is the preferable switching method: immediate discontinuation of the current antipsychotic or a gradual tapering approach. The first strategy has been implicated in rebound/withdrawal symptoms and emergence/exacerbation of symptoms, whereas the gradual approach is thought to pose a risk of additive or synergistic side effects if employed in the context of a crossover approach. Methods: MEDLINE, Embase, and Cochrane Central Register of Controlled Trials were systematically searched. Randomized controlled trials examining immediate vs gradual antipsychotic discontinuation in antipsychotic switching in patients with schizophrenia and/or schizoaffective disorder were selected. Data on clinical outcomes, including study discontinuation, psychopathology, extrapyramidal symptoms, and treatment-emergent adverse events, were extracted. Results: A total of 9 studies involving 1416 patients that met eligibility criteria were included in the meta-analysis. No significant differences in any clinical outcomes were found between the 2 approaches (all Ps > .05). Sensitivity analyses revealed that the findings remained unchanged in the studies where switching to aripiprazole was performed or where immediate initiation of the next antipsychotic was adopted, while some significant differences were observed in switching to olanzapine or ziprasidone. Conclusions: These findings indicate that either immediate or gradual discontinuation of the current antipsychotic medication represents a viable treatment option. Clinicians are advised to choose an antipsychotic switching strategy according to individual patient needs. This said, immediate discontinuation may be advantageous both for simplicity and because a stalled cross-titration process in antipsychotic switching could end up in antipsychotic polypharmacy.
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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 | 0.017 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.049 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".