Effects of Digoxin on Morbidity and Mortality in Diastolic Heart Failure
Bibliographic record
Abstract
BACKGROUND: About half of the 5 million heart failure patients in the United States have diastolic heart failure (clinical heart failure with normal or near-normal ejection fraction). Except for candesartan, no drugs have been tested in randomized clinical trials in these patients. Although digoxin was tested in an appreciable number of diastolic heart failure patients in the Digitalis Investigation Group ancillary trial, detailed findings from this important study have not previously been published. METHODS AND RESULTS: Ambulatory chronic heart failure patients (n = 988) with normal sinus rhythm and ejection fraction > 45% (median, 53%) from the United States and Canada (1991 to 1993) were randomly assigned to digoxin (n = 492) or placebo (n = 496). During follow-up with a mean length of 37 months, 102 patients (21%) in the digoxin group and 119 patients (24%) in the placebo group (hazard ratio [HR], 0.82; 95% confidence interval [CI], 0.63 to 1.07; P = 0.136) experienced the primary combined outcome of heart failure hospitalization or heart failure mortality. Digoxin had no effect on all-cause or cause-specific mortality or on all-cause or cardiovascular hospitalization. Use of digoxin was associated with a trend toward a reduction in hospitalizations resulting from worsening heart failure (HR, 0.79; 95% CI, 0.59 to 1.04; P = 0.094) but also a trend toward an increase in hospitalizations for unstable angina (HR, 1.37; 95% CI, 0.99 to 1.91; P = 0.061). CONCLUSIONS: In ambulatory patients with chronic mild to moderate diastolic heart failure and normal sinus rhythm receiving angiotensin-converting enzyme inhibitor and diuretics, digoxin had no effect on natural history end points such as mortality and all-cause or cardiovascular hospitalizations.
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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 | 0.003 | 0.005 |
| 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".