The Effect of Digoxin on Mortality in Congestive Heart Failure Patients in Normal Sinus Rhythm
Bibliographic record
Abstract
Digoxin is an antiarrhythmic medication that has been used to manage chronic heart failure. Despite more than 200 years of research, the role of digoxin in patients with heart failure and sinus rhythm remains controversial. Recent studies have shown digoxin to reduce heart failure associated morbidity without having any effect on mortality. The purpose of our study was to study the impact of digoxin on mortality in heart failure patients in sinus rhythm. Objective• Effect of digoxin on mortality in heart failure patients in sinus rhythm• Study impact of covariates such as age, gender, race, previous MI, and NYHA classMethods: Heart failure patients with LVEF ≤0.45 were randomly assigned to digoxin group (n=3392) or placebo group (n=3401) and were followed on average for 38.4 months. Patients were enrolled at multiple clinical centers in the United States and Canada.Results: In the study, mortality was unaffected. There were 1180 deaths in the digoxin group (34.77%) and 1194 deaths in the placebo group (35.09%). The adjusted hazard ratio (AHR) for the digoxin group compared with placebo group was 0.981 (p=0.6425) which was not statistically significant. The unadjusted median survival time for the placebo group was 58.37 months. The median survival time for the treatment group could was not reported because the group did not reach 50% survival probability during the study.Conclusions: After controlling for age, gender, race, previous MI, and NYHA functional class, we found no difference in the hazard of death between those receiving digoxin and those receiving placebo. Our study demonstrated that digoxin did not reduce the overall mortality and has no survival benefit in the management of 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 | 0.003 |
| 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".