Anticholinergic deprescribing: A case report demonstrating improved cognition and function with minimal adverse withdrawal effects
Bibliographic record
Abstract
Anticholinergic-induced cognitive impairment may be partially reversible upon cessation. A barrier to deprescribing of anticholinergics is the unknown risk of anticholinergic adverse drug withdrawal events (ADWE), with only limited information available on the incidence, timing and severity of anticholinergic ADWE. We report the case of a 76-year-old woman who experienced significant cognitive improvement following deprescribing long-term use of a strong anticholinergic drug, doxepin, and dose reduction of another possible anticholinergic agent. The patient decided to abruptly stop taking doxepin, despite a planned careful taper with twice weekly monitoring, but did not experience any severe anticholinergic ADWE and subsequently had significantly improved cognitive function. Future research should focus on better understanding the risk of anticholinergic ADWE so that anticholinergic deprescribing decisions, including how often and by how much to taper, can be made confidently and safely.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".