Clinical Profiles and Prognostic Impact of Residual Intravascular and Tissue Congestion in Acute Heart Failure
Bibliographic record
Abstract
AIMS: Residual congestion (RC) is common at discharge after acute decompensated heart failure (ADHF) and is associated with early mortality and rehospitalization. The prognostic value of distinct RC phenotypes (i.e. intravascular and tissue congestion) remains unclear. This analysis investigated RC phenotypes and their outcomes. METHODS AND RESULTS: Patients with congestion at admission from two large ADHF trials, PROTECT (rolofylline; index) and RELAX-AHF-2 (serelaxin; replication), were classified based on clinical signs at day 7/discharge as intravascular (jugular venous pressure) or tissue (pulmonary rales/peripheral oedema) congestion, each alone, combined or neither. Cox regression assessed 180-day mortality after adjusting for risk factors. Overall, 1557 patients with predominantly combined (i.e. tissue and intravascular) congestion at admission were included, with a median age of 72 years. By day 7 or discharge, 580 (37%) patients had RC. In these patients, intravascular congestion (n = 260; 45%) was most common, followed by combined (n = 185; 32%) and tissue (n = 135; 23%) congestion. During hospitalization, patients with solely intravascular RC had greater diuretic responses, shorter hospital stays and received lower doses of intravenous loop diuretics than those with tissue or combined congestion (all p < 0.05). Residual intravascular and tissue congestion were independently associated with increased 180-day mortality (hazard ratio [HR] 1.69, 95% confidence interval [CI] 1.15-2.49, and HR 2.07, 95% CI 1.25-3.41, respectively) compared to decongested patients. In the RELAX-AHF-2 substudy (n = 476), similar findings were observed. CONCLUSIONS: Patients with intravascular RC had better diuretic responses and shorter hospital stays than those with tissue/combined RC, but worse outcomes than decongested patients. This study highlights the importance of RC assessment to identify at-risk patients. Future studies should evaluate phenotype-guided treatments.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".