Underexposure of Seniors to Heart Failure Drug Therapy.
Bibliographic record
Abstract
BACKGROUND: Little is known about exposure to heart failure (HF) treatment among seniors with ischemic heart disease. OBJECTIVES: In a population of seniors, we: 1) estimated the association between age and exposure to HF drug therapy at 6, 12, 36 and 60 month intervals after HF diagnosis, and 2) determined the influence of the passage of time on exposure to drug therapy. METHODS: Using the Quebec provincial administrative databases, we conducted a population-based inception cohort study that included all individuals aged ≥ 65 with a first HF diagnosis between 2000 and 2009 and an ischemic heart disease diagnosis in the year before HF diagnosis. We assessed exposure to HF drug therapy and to drug therapy at target doses at 6, 12, 36 and 60 month intervals after HF diagnosis. Adjusted prevalence ratios (aPR) between age at diagnosis and exposure to drug therapy and the influence of time (6-month periods) were assessed using multivariate modified Poisson regressions. RESULTS: Among the 86,428 seniors, those who were older were less likely to be exposed to both HF drug therapy and drug therapy at target doses at each time point, than were the younger ones (aged 65-69). The aPRs for exposure to drug therapy for the 90+ age group were 0.64, 0.64, 0.56 and 0.53 at the 6, 12, 36 and 60 month intervals, respectively. After HF diagnosis, exposure increased by a maximum of 8% per 6-month period. CONCLUSION: Increasing age is associated with a decrease in exposure to drug therapy, with only slight improvement in exposure after HF diagnosis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".