One‐year persistence of potentially inappropriate medication use in older adults: A population‐based study
Bibliographic record
Abstract
AIMS: To assess the 1-year persistence of potentially inappropriate medication (PIM) use and identify associated factors in community-dwelling older adults in Quebec, Canada. METHODS: A population-based cohort study was conducted using the Quebec Integrated Chronic Disease Surveillance System. Individuals insured by the public drug plan and aged ≥66 years who initiated a PIM between 1 April 2014 and 31 March 2015 were followed-up for 1 year. PIMs were identified using the 2015 Beers criteria. One-year persistence of PIM use was defined as continuous treatment with any PIM, without interruption for more than 60 days between prescriptions refills. Poisson regression models were performed to identify factors associated with 1-year persistence of any PIM. RESULTS: In total, 25.1% of PIM initiators were persistent at 1 year. In non-persistent individuals, the median time to PIM discontinuation was 31 days (interquartile range 21-92). Individuals were more persistent at 1 year with antipsychotics (43.9%), long-duration sulphonylureas (40.2%), antiarrhythmics/immediate-release nifedipine (36.5%) and proton pump inhibitors (36.0%). Factors significantly associated with persistence were an increased age, being a man and having a high number of medications and chronic diseases, especially dementia, diabetes and cardiovascular diseases. CONCLUSIONS: One-quarter of community-dwelling older adults are continuously exposed to PIMs. To optimize medication prescribing in the older population, further interventions are needed to limit the use of PIMs most likely to be continued, especially in individuals most at risk of being persistent and also particularly vulnerable to adverse events.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".