Review of cognitive impairment with antimuscarinic agents in elderly patients with overactive bladder
Bibliographic record
Abstract
Overactive bladder (OAB) will become an increasingly prevalent problem as the proportion of older people in the population increases over the next 20 years. In addition to the urological symptoms (urinary urgency, with or without urgency incontinence, usually with increased daytime frequency and nocturia), OAB is associated with other problems in older patients, especially an increased risk of falls and fractures. The bother caused by OAB needs not be an inevitable consequence of ageing, because the symptoms can usually be alleviated, even in frail older people. Pharmacological treatment for OAB involves the use of antimuscarinic agents, whose efficacy and safety profiles depend on their interactions with muscarinic receptors that are widely distributed throughout the body. Interactions between antimuscarinics and M(1) receptors in the central nervous system may have the potential to cause cognitive impairment in older people, depending on muscarinic receptor binding profiles, lipophilicity and the ability to cross the blood brain barrier. Concerns over the possibility of cognitive impairment have contributed to an under-utilisation of antimuscarinics in the geriatric population, despite the high prevalence and severity of OAB in older subjects. Antimuscarinic agents should be actively considered for elderly patients with OAB, but it is desirable to establish the cognitive risk for every type of antimuscarinic, using robust cognition assessment methods.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| 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 | 0.002 |
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".