Results of Targeted Anti–Tumor Necrosis Factor Therapy With Etanercept (ENBREL) in Patients With Advanced Heart Failure
Bibliographic record
Abstract
BACKGROUND: Previously, we showed that tumor necrosis factor (TNF) antagonism with etanercept, a soluble TNF receptor, was well tolerated and that it suppressed circulating levels of biologically active TNF for 14 days in patients with moderate heart failure. However, the effects of sustained TNF antagonism in heart failure are not known. METHODS AND RESULTS: We conducted a randomized, double-blind, placebo-controlled, multidose trial of etanercept in 47 patients with NYHA class III to IV heart failure. Patients were treated with biweekly subcutaneous injections of etanercept 5 mg/m(2) (n=16) or 12 mg/m(2) (n=15) or with placebo (n=16) for 3 months. Doses of 5 and 12 mg/m(2) etanercept were safe and well tolerated for 3 months. Treatment with etanercept led to a significant dose-dependent improvement in left ventricular (LV) ejection fraction and LV remodeling, and there was a trend toward an improvement in patient functional status, as determined by clinical composite score. CONCLUSION: Treatment with etanercept for 3 months was safe and well-tolerated in patients with advanced heart failure, and it resulted in a significant dose-dependent improvement in LV structure and function and a trend toward improvement in patient functional status.
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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 | 0.002 |
| 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".