Rate pressure product and the components of heart rate and systolic blood pressure in hospitalized heart failure patients with preserved ejection fraction: Insights from ASCEND‐HF
Bibliographic record
Abstract
BACKGROUND: Heart rate and systolic blood pressure (SBP) are prognostic markers in heart failure (HF) with reduced ejection fraction (HFrEF). Their combination in rate pressure product (RPP) as well as their role in heart failure with preserved ejection fraction (HFpEF) remains unclear. HYPOTHESIS: RPP and its components are associated with HFpEF outcomes. METHODS: We performed an analysis of Acute Study of Clinical Effectiveness of Nesiritide in Subjects With Decompensated Heart Failure (ASCEND-HF; http://www.clinicaltrials.gov NCT00475852), which studied 7141 patients with acute HF. HFpEF was defined as left ventricular ejection fraction ≥40%. Outcomes were assessed by baseline heart rate, SBP, and RPP, as well as the change of these variables using adjusted Cox models. RESULTS: After multivariable adjustment, in-hospital change but not baseline heart rate, SBP, and RPP were associated with 30-day mortality/HF hospitalization (hazard ratio [HR]: 1.17 per 5-bpm heart rate, HR: 1.20 per 10-mm Hg SBP, and HR: 1.02 per 100 bpm × mm Hg RPP; all P < 0.05). Baseline SBP was associated with 180-day mortality (HR: 0.88 per 10-mm Hg, P = 0.028). Though change in RPP was associated with 30-day mortality/HF hospitalization, the RPP baseline variable did not provide additional associative information with regard to outcomes when compared with assessment of baseline heart rate and SBP variables alone. CONCLUSIONS: An increase in heart rate and SBP from baseline to discharge was associated with increased 30-day mortality/HF hospitalization in HFpEF patients with acute exacerbation. These findings suggest value in monitoring the trend of vital signs during HFpEF hospitalization.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".