Targeted Anticytokine Therapy in Patients With Chronic Heart Failure
Bibliographic record
Abstract
BACKGROUND: Studies in experimental models and preliminary clinical experience suggested a possible therapeutic role for the soluble tumor necrosis factor antagonist etanercept in heart failure. METHODS AND RESULTS: Patients with New York Heart Association class II to IV chronic heart failure and a left ventricular ejection fraction < or =0.30 were enrolled in 2 clinical trials that differed only in the doses of etanercept used. In RECOVER, patients received placebo (n=373) or subcutaneous etanercept in doses of 25 mg every week (n=375) or 25 mg twice per week (n=375). In RENAISSANCE, patients received placebo (n=309), etanercept 25 mg twice per week (n=308), or etanercept 25 mg 3 times per week (n=308). The primary end point of each individual trial was clinical status at 24 weeks. Analysis of the effect of the 2 higher doses of etanercept on the combined outcome of death or hospitalization due to chronic heart failure from the 2 studies was also planned (RENEWAL). On the basis of prespecified stopping rules, both trials were terminated prematurely owing to lack of benefit. Etanercept had no effect on clinical status in RENAISSANCE (P=0.17) or RECOVER (P=0.34) and had no effect on the death or chronic heart failure hospitalization end point in RENEWAL (etanercept to placebo relative risk=1.1, 95% CI 0.91 to 1.33, P=0.33). CONCLUSIONS: The results of RENEWAL rule out a clinically relevant benefit of etanercept on the rate of death or hospitalization due to chronic heart failure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 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".