The impact of anticholinergics on cognitive function in patients with neurogenic lower urinary tract dysfunction: A narrative review
Bibliographic record
Abstract
This narrative review discusses the relationship between anticholinergic medications and cognitive change specifically in patients with neurogenic lower urinary tract dysfunction (NLUTD). NLUTD is prevalent in various conditions, including spinal cord injury (SCI), spina bifida (SB), multiple sclerosis (MS), Parkinson's, stroke, and dementia and often requires anticholinergic overactive bladder (OAB) medications. In the general population, and among those with OAB, several studies have found a significant association between this class of medications and cognitive side effects, mostly when used for > 90 days. These cognitive side effects may be particularly relevant to people with NLUTD due to their higher baseline risk of cognitive impairment. Two studies (one in people with SCI and another in MS) found evidence of cognitive impairment with the use of OAB anticholinergics (specifically oxybutynin and tolterodine). People with dementia commonly use OAB anticholinergics, and there is evidence that oxybutynin and tolterodine may impair cognition in this population. Two recent studies in children with SB studied 12 months of solifenacin and 6 months of fesoterodine/oxybutynin and found there was no significant change in neuropsychological testing. Clinical studies in people with Parkinson's disease and prior stroke have not shown that trospium, darifenacin, or fesoterodine have a significant impact on cognitive measures. In summary, oxybutynin and tolterodine may pose a higher risk of cognitive impairment than newer OAB anticholinergics in people with NLUTD; there is no evidence that children with SB experience cognitive impairment with OAB anticholinergics. Further study is necessary to confirm cognitive safety, particularly as the NLUTD population may have a high exposure to OAB anticholinergics. Advocating for potentially safer OAB medications is necessary if there is concern about cognitive risks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".