Continuous versus extended antipsychotic dosing in schizophrenia: Less is more
Bibliographic record
Abstract
Antipsychotic drugs temper psychotic symptoms by interacting with dopamine D2 receptors to reduce dopamine neurotransmission. Currently, the standard of care involves antipsychotic treatment protocols that achieve steady-state levels of medication. Maintaining patients on continuous treatment is thought to be necessary to keep them stabilised. However, continuous antipsychotic exposure increases the risk of adverse effects over time. These effects include metabolic and cardiovascular disorders, extrapyramidal complications, and dopamine receptor supersensitivity, the latter of which could potentially promote both treatment tolerance and psychosis relapse. In the present review, we describe evidence showing that continuous exposure to antipsychotic drugs can not only worsen long-term outcome, but—past acute phase treatment—it is also unnecessary to effectively manage schizophrenia symptoms. We also describe evidence that regular but extended dosing, allowing predictable periods of lower antipsychotic levels/D2 occupancy, is both safe and effective in patients, and it greatly reduces drug exposure overall. Studies in laboratory animals show that compared to continuous antipsychotic exposure, regular but extended dosing actually has superior antipsychotic-like efficacy, and it also substantially reduces the likelihood of both motor side effects and dopamine receptor supersensitivity. We propose that regular, but extended dosing should be considered in the long-term treatment of people with schizophrenia, because the available evidence suggests it can be just as effective as continuous treatment, while decreasing overall drug exposure and potentially reducing harmful side effects.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".