Impact of Nitrate Use on Survival in Acute Heart Failure: A Propensity‐Matched Analysis
Bibliographic record
Abstract
BACKGROUND: There is limited evidence that the use of nitrates in acute decompensated heart failure early after presentation to a hospital can improve clinical outcomes. We aimed to determine whether early nitrate exposure is associated with improved survival in a large retrospective cohort study. METHODS AND RESULTS: We examined 11 078 acute decompensated heart failure patients who presented to emergency departments in Ontario, Canada, between 2004 and 2007, in the Enhanced Feedback For Effective Cardiac Treatment and the Emergency Heart failure Mortality Risk Grade studies. In propensity-matched analyses, we examined the effect of nitrate administration in the acute emergency department setting for its impact on death at 7, 30, and 365 days. In propensity-matched analyses, we found no difference in survival between those who received nitrates in the emergency department and the non-nitrate comparator group. Hazard ratios for mortality were 0.76 (95% CI; 0.51, 1.12) over 7 days, 0.97 (95% CI; 0.77, 1.21) over 30 days, and 0.91 (95% CI; 0.82, 1.02) over 1 year of follow-up. There was no significant difference in survival or hospital length of stay between nitrate and non-nitrate controls in extended follow-up. There was also no significant effect of nitrates in subgroups stratified by presence of chest pain, troponin elevation, chronic nitrate use, and known coronary artery disease. CONCLUSIONS: In acute decompensated heart failure, use of nitrates acutely in the emergency department setting was not associated with improvement in short-term or near-term survival. Our study does not support generalized use of nitrates when the primary goal of therapy is to reduce mortality.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".