Hospitalization for Acute Heart Failure During Non-Working Hours Impacts on Long-Term Mortality: The REPORT-HF Registry
Bibliographic record
Abstract
AIMS: Hospital admission during nighttime and off hours may affect the outcome of patients with various cardiovascular conditions due to suboptimal resources and personnel availability, but data for acute heart failure remain controversial. Therefore, we studied outcomes of acute heart failure patients according to their time of admission from the global International Registry to assess medical practice with lOngitudinal obseRvation for Treatment of Heart Failure. METHODS AND RESULTS: Overall, 18 553 acute heart failure patients were divided according to time of admission into 'morning' (7:00-14:59), 'evening' (15:00-22:59), and 'night' (23:00-06:59) shift groups. Patients were also dichotomized to admission during 'working hours' (9:00-16:59 during standard working days) and 'non-working hours' (any other time). Clinical characteristics, treatments, and outcomes were compared across groups. The hospital length of stay was longer for morning (odds ratio: 1.08; 95% confidence interval: 1.06-1.10, P < 0.001) and evening shift (odds ratio: 1.10; 95% confidence interval: 1.07-1.12, P < 0.001) as compared with night shift. The length of stay was also longer for working vs. non-working hours (odds ratio: 1.03; 95% confidence interval: 1.02-1.05, P < 0.001). There were no significant differences in in-hospital mortality among the groups. Admission during working hours, compared with non-working hours, was associated with significantly lower mortality at 1 year (hazard ratio: 0.88; 95% confidence interval: 0.80-0.96, P = 0.003). CONCLUSIONS: Acute heart failure patients admitted during the night shift and non-working hours had shorter length of stay but similar in-hospital mortality. However, patients admitted during non-working hours were at a higher risk for 1 year mortality. These findings may have implications for the health policies and heart failure trials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".