Is Plasma Renin Activity Associated with Worse Outcomes in Acute Heart Failure? A Secondary Analysis from the BLAST-AHF Trial
Bibliographic record
Abstract
AIMS: Neurohormonal activation characterizes chronic heart failure (HF) and is a well-established therapeutic target. Neurohormonal activation may also play a key role in acute HF (AHF). We aim to describe the association between plasma renin activity (PRA) and three AHF outcomes: (i) worsening HF or death through day 5 of hospitalization; (ii) HF rehospitalization or death through day 30; and (iii) all-cause death through day 30. METHODS AND RESULTS: . The primary trial was neutral, with no differential effect of study drug by PRA levels. Baseline PRA levels were grouped into tertiles. Adjusted Cox proportional hazard model determined the association of PRA levels with outcomes (α set at P < 0.05). Of 618 randomized patients, 578 (93.5%) had a baseline PRA. PRA was modestly, but significantly, associated with each outcome without adjustment [worsening HF or death through day 5: hazard ratio (HR) 1.11, 95% confidence interval (CI) 1.01-1.23, P = 0.04; HF rehospitalization or death through day 30: HR 1.13, 95% CI 1.02-1.26, P = 0.02; all-cause death through day 30: HR 1.18, 95% CI 1.02-1.37, P = 0.03]. After multivariable adjustment, PRA was only significantly associated with HF rehospitalization or death through day 30 (HR 1.15, 95% CI 1.01-1.32, P = 0.04). CONCLUSION: Baseline PRA levels are associated with increased risk for the composite of 30-day HF rehospitalization or death in patients with AHF.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".