Association of Time-to-Intravenous Furosemide with Mortality in Acute Heart Failure: Data from REPORT-HF
Bibliographic record
Abstract
Abstract Aim Acute heart failure can be a life-threatening medical condition. Delaying administration of intravenous furosemide (time-to-diuretics) has been postulated to increase mortality, but prior reports have been inconclusive. We aimed to evaluate the association between time-to-diuretics and mortality in the international REPORT-HF registry. Methods and results We assessed the association of time-to-diuretics within the first 24 h with in-hospital and 30-day post-discharge mortality in 15 078 patients from seven world regions in the REPORT-HF registry. We further tested for effect modification by baseline mortality risk (ADHERE risk score), left ventricular ejection fraction (LVEF) and region. The median time-to-diuretics was 67 (25th–75th percentiles 17–190) min. Women, patients with more signs and symptoms of heart failure, and patients from Eastern Europe or Southeast Asia had shorter time-to-diuretics. There was no significant association between time-to-diuretics and in-hospital mortality (p > 0.1). The 30-day mortality risk increased linearly with longer time-to-diuretics (administered between hospital arrival and 8 h post-hospital arrival) (p = 0.016). This increase was more significant in patients with a higher ADHERE risk score (pinteraction = 0.008), and not modified by LVEF or geographic region (pinteraction > 0.1 for both). Conclusion In REPORT-HF, longer time-to-diuretics was not associated with higher in-hospital mortality. However, we did found an association with increased 30-day mortality, particularly in high-risk patients, and irrespective of LVEF or geographic region. Clinical Trial Registration: ClinicalTrials.gov Identifier NCT02595814.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".