Better adherence to antihypertensive agents and risk reduction of chronic heart failure
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIMS: Antihypertensive (AH) agents have been shown to reduce the risk of major cardiovascular events including chronic heart failure (CHF). However, the impact of changes in patterns of AH agents use on CHF is unknown. Our objective was to estimate to which different patterns of AH agent use is associated with the occurrence of CHF in a population-based study. METHOD AND RESULTS: A cohort of 82 320 patients was reconstructed using the Régie de l'assurance maladie du Québec's databases. Patients were eligible if they were between 45 to 85 years of age, had no indication of cardiovascular disease and were newly treated with AH therapy between 1999 and 2004. A nested case-control design was used to study the occurrence of CHF. Every case of CHF was matched for age and duration of follow-up to a maximum of 15 randomly selected controls. Adherence level was reported as a medication possession ratio. Conditional logistic regression models were used to estimate the rate ratio (RR) of CHF adjusting for different covariables. The mean patient age was 65 years, 37% were male, 8% had diabetes, 19% had dyslipidaemia and mean time of follow-up at 2.7 years. High adherence level (95%) to AH therapy compared with lower adherence level (60%) was associated with an additional reduction of CHF events (RR: 0.89; 0.80-0.99). Risk factors for CHF were being on social assistance, diabetes, dyslipidaemia, higher chronic disease score and developing a cardiovascular condition during follow-up. CONCLUSION: Our study suggests that a better adherence is associated with a significant risk reduction of CHF. Adherence to AH therapy needs to be improved to optimize benefits.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it