Tardive neurotoxicity of anticholinergic drugs: A review
Bibliographic record
Abstract
The cholinergic system is a complex neurotransmitter system with functional involvement at multiple levels of the nervous system including the cerebral cortex, spinal cord, autonomic nervous system, and neuromuscular junction. Anticholinergic medications are among the most prescribed medications, making up one-third to one-half of all medications prescribed for seniors. Recent evidence has linked long-term use of anticholinergic medications and dementia. Emerging evidence implicates the cholinergic system in the regulation of cerebral vasculature as well as neuroinflammation, suggesting that anticholinergic medications may contribute to absolute risk and progression of neurodegenerative diseases. In this review, we explore the involvement of the cholinergic system in various neurodegenerative diseases and the possible detrimental effects of anticholinergic medications on the onset and progression of these disorders. We identified references by searching the PubMed and Cochrane database between January 1990 and September 2019 for English-language animal and human studies including randomized clinical trials (RCTs), meta-analyses, systematic reviews, and observational studies. In addition, we conducted a manual search of reference lists from retrieved studies. Long-term anticholinergic medication exposure may have detrimental consequences beyond well-documented short-term cognitive effects, through a variety of mechanisms either directly impacting cholinergic neurotransmission or through receptors expressed on the vasculature or immune cells, providing a pathophysiological framework for complex interactions across the entire neuroaxis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".