Anticholinergics in the era of atypical antipsychotics: short-term or long-term treatment?
Bibliographic record
Abstract
Anticholinergic agents are usually prescribed to prevent or treat antipsychotic-induced extrapyramidal symptoms. Their long-term benefits are questionable and they carry diverse adverse effects, including cognitive impairment and worsening of tardive dyskinesia. This literature review explores the impact of anticholinergic medication discontinuation on movement disorders, cognition and psychopathology in patients receiving antipsychotics. Medline, Embase and PsycInfo were searched from 1950 to July 2011 using "cessation /withdrawal /discontinuation /stopping" with "anticholinergic*" or "antiparkinson*" and "neuroleptic*" or "antipsychotic*". Additional articles were obtained by searching the bibliographies of relevant references. Earlier studies of anticholinergic agent discontinuation in patients receiving first-generation antipsychotics reported relapse rates of extrapyramidal symptoms between 4% and 80%, reflecting the heterogeneity of the studies. Two recent studies of patients prescribed second-generation antipsychotics obtained relapse rates of 4% and 33%. Some studies suggest improvement in tardive dyskinesia with cessation of anticholinergics. Four studies examined the effects of anticholinergic agent discontinuation on cognition and all observed an improvement post-discontinuation. Changes in symptoms of schizophrenia with anticholinergic discontinuation are conflicting, with more recent studies suggesting an improvement. Given their questionable benefit with continued use, clinicians should consider a gradual withdrawal of anticholinergic agents in stable patients receiving antipsychotics.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".