Potentially Inappropriate Drug Duplication in a Cohort of Older Adults with Dementia
Bibliographic record
Abstract
BACKGROUND: Concurrent use of 2 nonsteroidal anti-inflammatory drugs, selective serotonin reuptake inhibitors, loop diuretics, angiotensin-converting enzyme inhibitors, or anticoagulants is considered potentially inappropriate by Screening Tool of Older Persons' Prescriptions and Screening Tool to Alert to Right Treatment criteria. OBJECTIVE: The objective was to examine drug duplication in a cohort of older adults with dementia. METHODS: Cohort entry for Nova Scotia Seniors' Pharmacare Program beneficiaries was the date an International Classification of Diseases ninth edition or 10th edition code for dementia was recorded in accessed databases between March 1, 2005, and March 31, 2015. Medication dispensation and sociodemographic data were captured from the Nova Scotia Seniors' Pharmacare Program database between April 1, 2010, and March 31, 2015. Duplication was considered when 2 drugs from the same class were dispensed such that the supply in the patient's possession could overlap for more than 30 days. We reported number of cases of duplication and duration of overlap. Sex differences in drug duplication were assessed with bivariate logistic regression. RESULTS: In the cohort of 28,953 Nova Scotia Seniors' Pharmacare Program beneficiaries with dementia, we documented concurrent use in 101 (1.7%) nonsteroidal anti-inflammatory drugs users (mean duration = 75.6 days), 95 (1.0%) selective serotonin reuptake inhibitors users (mean duration = 146.6 days), 5 (0.07%) loop diuretic users (mean duration = 530.6 days), 183 (2.0%) angiotensin-converting enzyme inhibitor users (mean duration = 123.9 days), and 160 (3.5%) anticoagulant users (mean duration = 63.6 days). Nonsteroidal anti-inflammatory drug pairs were most commonly celecoxib with naproxen or diclofenac. Selective serotonin reuptake inhibitors duplication was most commonly sertraline with citalopram. No sex differences in risk for drug duplication were identified. CONCLUSIONS: . 2021; 82:XXX-XXX).
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".