The effects of angiotensin-receptor blockers on mortality and morbidity in heart failure: a systematic review
Bibliographic record
Abstract
BACKGROUND: Trials evaluating angiotensin-receptor blockers in heart failure (HF) have shown inconsistent results. OBJECTIVE: To evaluate the effect of angiotensin II (AII) receptor blockers in HF patients on total mortality and HF hospitalisations. METHODS: Systematic search of the literature through MEDLINE (1980-2007) and abstracts of major cardiovascular congresses from 2002 to 2007. ELIGIBILITY CRITERIA: (i) randomised controlled trials with more than 500 patients and follow up > 6 months, (ii) availability of total mortality and/or (iii) availability of hospital admission because of worsening HF. Data retrieved by two independent reviewers. DerSimonian random effects model was used. RESULTS: Mortality data were available from 27,495 patients. When AII receptor blockers plus angiotensin-converting enzyme inhibitors (ACE-I) were compared with ACE-I in chronic HF trials, the relative risk (RR) for death was 0.98 (95% CI: 0.84-1.15). When AII receptor blockers were compared with ACE-I the RR for death was 1.06 (95% CI: 0.56-1.62). Similar results were found for postmyocardial infarction trials. The effects on hospital admission revealed a RR of 0.83 (95% CI: 0.71-0.97) and 1.09 (95% CI: 0.74-1.60) respectively. CONCLUSION: Angiotensin II receptor blockers did not show any beneficial effect on mortality when used in combination with ACE-I or when compared with ACE-I alone. A 17% reduction in hospital admissions was observed.
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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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.008 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".