Antihypertensive persistence and drug class.
Bibliographic record
Abstract
BACKGROUND: Noncompliance with antihypertensive therapy is a major problem that hinders successful hypertension management. OBJECTIVE: To study antihypertensive drug persistence for hypertensive patients in routine clinical settings. METHODS: Hypertensive patients were retrospectively studied (1994 through 1998) using databases managed by Saskatchewan Health. The study population (46,458 people) included all patients with an International Classification of Diseases-9 code of 401, 402, 403 or 404, or any four-digit code included in these categories, who received at least one antihypertensive therapy prescription during the first 4.5 years of the study and received no antihypertensive therapy 12 months before the dispensing of the first therapy. Prescriptions were placed into the following drug classes: angiotensin II antagonists, angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers and diuretics. Persistence was determined for four intervals in the patient's therapy at 180, 360, 540 and 720 days. RESULTS: Drug class had a statistically significant (P<0.001) effect on persistence. Angiotensin II antagonists had the highest persistence followed by angiotensin-converting enzyme inhibitors, calcium channel blockers, beta-blockers and diuretics. Persistence decreased as the time interval increased. Females were significantly more persistent than males (P<0.005), and elderly patients were significantly more persistent than younger patients (P<0.001) at each of the four time intervals. For angiotensin II antagonists, age and sex did not affect persistence. CONCLUSIONS: The consistently higher persistence associated with the use of angiotensin II antagonists may improve the management of hypertension.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".