Are anticholinergic medications used for overactive bladder associated with new onset depression? A population‐based matched cohort study
Bibliographic record
Abstract
PURPOSE: Prior research has suggested that anticholinergic medications used for overactive bladder are associated with depression. Our objective was to test this hypothesis by comparing rates of new onset depression among anticholinergic medication users and those who were prescribed an alternative class of overactive bladder medication. METHODS: We used administrative data records from the province of Ontario, Canada and a matched cohort design. We matched patients who were newly prescribed an oral anticholinergic to those prescribed a beta-3 agonist medication in a 2:1 ratio which included a propensity score that incorportated 75 baseline characteristics. The primary outcome of depression was measured using a validated definition, and the at-risk period for our outcome of interest was between the initial date the prescription was filled, and up to 3 months after the end of continuous usage of that medication. Hazard ratios (HRs) were estimated using Cox proportional hazards regression. RESULTS: We matched 23 622 beta-3 agonist users (mirabegron) to 47 324 anticholinergic users (most commonly tolterodine, oxybutynin, and solifenacin). The rate of depression was similar among beta-3 agonist users (11.2 per 1000 patient-years) and anticholinergic users (11.9 per 1000 patient-years). In our primary analysis, the risk of depression among anticholinergic users was not significantly different compared to beta-3 agonist users (HR 1.08 [95% CI 0.92-1.28, P = .35]). CONCLUSION: Contrary to a previous report, overactive bladder anticholinergic medications do not appear to be associated with new onset depression.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".