Angiotensin II Receptor Blockers for the Treatment of Heart Failure: A Class Effect?
Bibliographic record
Abstract
STUDY OBJECTIVE: To examine the class effect of angiotensin II receptor blockers (ARBs) on mortality in patients with heart failure who were aged 65 years or older. DESIGN: Retrospective population-based study. DATA SOURCE: Administrative database that stores information on hospital discharge summaries for the Canadian provinces of Quebec, Ontario, and British Columbia. PATIENTS: A total of 6876 patients aged 65 years or older who were discharged with a primary diagnosis of heart failure between January 1, 1998, and March 31, 2003, and who filled at least one prescription for an ARB within 90 days of discharge. MEASUREMENTS AND MAIN RESULTS: Times to all-cause death in patients receiving individual ARBs were compared. Models were adjusted for demographic, clinical, physician, and hospital characteristics; models were also adjusted for dosage categories, which were represented by time-dependent variables. The cohort of 6876 patients had a mean +/- SD age of 78 +/- 7 years, and most (62%) were women. Losartan was the most frequently prescribed ARB (61%), followed by irbesartan (14%), valsartan (13%), candesartan (10%), and telmisartan (2%). Irbesartan, valsartan, and candesartan were associated with better survival rates than losartan (adjusted hazard ratios [HRs] and 95% confidence intervals [CIs] 0.65 [0.53-0.79], 0.63 [0.51-0.79], and 0.71 [0.57-0.90], respectively). No difference was noted in mortality in patients prescribed telmisartan compared with those receiving losartan (HR 0.92 [95% CI 0.55-1.54]). CONCLUSIONS: Elderly patients with heart failure who were prescribed losartan had worse survival rates compared with those prescribed other commonly used ARBs. The absence of a class effect for ARBs is consistent with data showing pharmacologic differences among the drugs.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".