An Evidence-Based Update on Anticholinergic Use for Drug-Induced Movement Disorders
Bibliographic record
Abstract
Drug-induced movement disorders (DIMDs) are associated with use of dopamine receptor blocking agents (DRBAs), including antipsychotics. The most common forms are drug-induced parkinsonism (DIP), dystonia, akathisia, and tardive dyskinesia (TD). Although rare, neuroleptic malignant syndrome (NMS) is a potentially life-threatening consequence of DRBA exposure. Recommendations for anticholinergic use in patients with DIMDs were developed on the basis of a roundtable discussion with healthcare professionals with extensive expertise in DIMD management, along with a comprehensive literature review. The roundtable agreed that "extrapyramidal symptoms" is a non-specific term that encompasses a range of abnormal movements. As such, it contributes to a misconception that all DIMDs can be treated in the same way, potentially leading to the misuse and overprescribing of anticholinergics. DIMDs are neurobiologically and clinically distinct, with different treatment paradigms and varying levels of evidence for anticholinergic use. Whereas evidence indicates anticholinergics can be effective for DIP and dystonia, they are not recommended for TD, akathisia, or NMS; nor are they supported for preventing DIMDs except in individuals at high risk for acute dystonia. Anticholinergics may induce serious peripheral adverse effects (e.g., urinary retention) and central effects (e.g., impaired cognition), all of which can be highly concerning especially in older adults. Appropriate use of anticholinergics therefore requires careful consideration of the evidence for efficacy (e.g., supportive for DIP but not TD) and the risks for serious adverse events. If used, anticholinergic medications should be prescribed at the lowest effective dose and for limited periods of time. When discontinued, they should be tapered gradually.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".