Angiotensin II Receptor Blockers in Congestive Heart Failure
Bibliographic record
Abstract
The benefits of angiotensin-converting enzyme (ACE) inhibitors for the treatment of congestive heart failure (CHF) are well-established. A newer class of medications, angiotensin II receptor blockers (ARBs), may be a suitable replacement for ACE inhibitors as a result of a more complete inhibition of angiotensin II and better tolerability among patients. To examine the current literature on the efficacy and safety of ARBs in the setting of CHF, a Medline search was conducted of the English language literature for the years 1987 to 2005. Clinical trials that reported data on cardiac outcomes were reviewed. The earlier trials were direct ARB to ACE inhibitor comparisons (ELITE I and ELITE II). These studies indicated that ARBs do not confer an improvement in cardiac outcomes over ACE inhibitors. RESOLVD, Val-HeFT, and the 3 separate trials of the CHARM program investigated the addition of an ARB to standard therapy. The RESOLVD trial showed no significant differences in clinical events among ACE inhibitor, ARB, and their combination. Although no mortality benefit was evident in the Val-HeFT trial, a substantial reduction in CHF rehospitalizations was reported among patients who were not receiving ACE inhibitor therapy. The CHARM-Overall program demonstrated a significant benefit in cardiovascular death and hospital admissions for CHF with the addition of ARB to standard therapy, a benefit that was more pronounced in patients with depressed left ventricular ejection fraction. In the setting of CHF, rates of cardiac outcomes do not differ substantially between ARBs and ACE inhibitors. However, their combination may improve outcomes for patients with CHF.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".