Association of Blood Pressure at Hospital Discharge With Mortality in Patients Diagnosed With Heart Failure
Bibliographic record
Abstract
BACKGROUND: Higher blood pressure in acute heart failure has been associated with improved survival; however, the relationship between blood pressure and survival in stabilized patients at hospital discharge has not been established. METHODS AND RESULTS: In 7448 patients with heart failure (75.2+/-11.5 years; 49.9% men) discharged from the hospital in Ontario, Canada, we examined the association of systolic blood pressure (SBP) and diastolic blood pressure with long-term survival. Parametric survival analysis was performed, and survival time ratios were determined according to discharge blood pressure group. A total of 25 427 person-years of follow-up were examined. In those with left ventricular ejection fraction < or =40%, median survival was decreased by 17% (survival time ratio, 0.83; 95% CI, 0.71 to 0.98; P=0.029) when discharge SBP was 100 to 119 mm Hg and decreased by 23% (survival time ratio, 0.77; 95% CI, 0.62 to 0.97; P=0.024) when discharge SBP was <100 mm Hg, compared with those in the reference range of 120 to 139 mm Hg. Survival time ratios were 0.75 (95% CI, 0.60 to 0.92; P=0.007) and 0.75 (95% CI, 0.53 to 1.07; P=0.12) when discharge SBPs were 140 to 159 and > or =160 mm Hg, respectively. In those with left ventricular ejection fraction >40%, survival time ratios were 0.69 (95% CI, 0.51 to 0.93), 0.83 (95% CI, 0.71 to 0.99), 0.95 (95% CI, 0.80 to 1.14), and 0.76 (95% CI, 0.61 to 0.95) for discharge SBPs <100, 100 to 119, 140 to 159, and > or =160 mm Hg, respectively. CONCLUSIONS: In this long-term population-based study of patients with heart failure, the association of discharge SBP with mortality followed a U-shaped distribution. Survival was shortened in those with reduced or increased values of discharge SBP.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".