First-Fill Medication Discontinuations and Nonadherence to Antihypertensive Therapy: An Observational Study
Bibliographic record
Abstract
BACKGROUND: Medication nonadherence is a barrier to successfully managing hypertension, but little is known about the contribution that immediate discontinuations have on antihypertensive (AHT) nonadherence. The purpose of this study was to determine the proportion of new AHT users who discontinue after a single dispensation, and to examine potential predictors of these discontinuations. METHODS: This retrospective cohort study utilizing linked administrative data from Saskatchewan, Canada. Subjects were ≥40 years of age and received a new AHT between 1994-2002. The primary end point was the proportion of subjects who discontinued their AHT after the first dispensation (first-fill discontinuation). The proportion of nonadherence attributed to first-fill discontinuations was then calculated. Multivariate regression identified factors associated with first-fill discontinuations. RESULTS: 52,039 subjects were included in the analyses. Mean age was 59.4 (s.d. 12.5) years, and 42% were male. Overall, 25,812/52,039 (50%) subjects were nonadherent at 1 year; first-fill discontinuations accounted for 39.1% (10,081/25,812) of this nonadherence. Approximately 20% (10,081/52,039) of all subjects discontinued all AHT therapy after the first fill. A higher chronic disease score (adjusted odds ratio (OR) 1.09, 95% confidence interval (CI) 1.08-1.11) and antidepressant medication usage during the observation year (adjusted OR 1.17, 95% CI 1.09-1.26) was associated with increased risk for first-fill discontinuations. Older age, starting AHT therapy after 1994, frequent physician visits, or use of a statin, acetylsalicylic acid, warfarin or antihyperglycemic during the observation year was associated with a lower risk for first-fill discontinuations. CONCLUSION: A substantial proportion of nonadherence to AHT medications is due to discontinuations after only a single dispensation.
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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 | 0.002 | 0.005 |
| 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 | 0.001 |
| 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".