Effect of Carvedilol on Survival in Severe Chronic Heart Failure
Bibliographic record
Abstract
BACKGROUND: Beta-blocking agents reduce the risk of hospitalization and death in patients with mild-to-moderate heart failure, but little is known about their effects in severe heart failure. METHODS: We evaluated 2289 patients who had symptoms of heart failure at rest or on minimal exertion, who were clinically euvolemic, and who had an ejection fraction of less than 25 percent. In a double-blind fashion, we randomly assigned 1133 patients to placebo and 1156 patients to treatment with carvedilol for a mean period of 10.4 months, during which standard therapy for heart failure was continued. Patients who required intensive care, had marked fluid retention, or were receiving intravenous vasodilators or positive inotropic drugs were excluded. RESULTS: There were 190 deaths in the placebo group and 130 deaths in the carvedilol group. This difference reflected a 35 percent decrease in the risk of death with carvedilol (95 percent confidence interval, 19 to 48 percent; P=0.00013, unadjusted; P=0.0014, adjusted for interim analyses). A total of 507 patients died or were hospitalized in the placebo group, as compared with 425 in the carvedilol group. This difference reflected a 24 percent decrease in the combined risk of death or hospitalization with carvedilol (95 percent confidence interval, 13 to 33 percent; P<0.001). The favorable effects on both end points were seen consistently in all the subgroups we examined, including patients with a history of recent or recurrent cardiac decompensation. Fewer patients in the carvedilol group than in the placebo group withdrew because of adverse effects or for other reasons (P=0.02). CONCLUSIONS: The previously reported benefits of carvedilol with regard to morbidity and mortality in patients with mild-to-moderate heart failure were also apparent in the patients with severe heart failure who were evaluated in this trial.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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 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".