ArticleESC heart failure2025
Predicting 1-year heart failure hospitalization and mortality post-discharge from the intensive cardiac care unit.
Article in ESC heart failure, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Predicting 1-year heart failure hospitalization and mortality post-discharge from the intensive cardiac care unit.ESC heart failure · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
28 authors.
Funding
Abstract
aimsDespite the high risk of rehospitalization for heart failure (HF) and death among patients admitted to the intensive cardiac care unit (ICCU), no accurate prediction score for these outcomes exists. We aimed to develop a risk score to predict unplanned HF hospitalization and death 1-year post-discharge in an unselected cohort of patients admitted to the ICCU.
methodsBased on a national, multicentre study, we included all consecutive patients admitted to the ICCUs in 39 French centres from 7 to 22 April 2021. We randomly selected a training cohort of 21 centres (n = 1008) to develop the ICCU-HF score and a validation cohort of eight other centres (n = 463). The primary composite outcome was unplanned hospitalization for HF and cardiovascular death at 1-year follow-up after discharge. Using the score, patients were stratified into three risk groups to evaluate the prognostic value.
resultsUsing a least absolute shrinkage and selection operator (LASSO) regression approach, we identified seven predictors: left ventricular ejection fraction, significant valvular disease grade 2+, Killip score >1, NT-proBNP, creatinine level, previous ventricular arrhythmia and use of inotropes during hospitalization. In 1471 patients (63 ± 15 years, 70% men), 99 (6.7%) experienced the primary outcome. The ICCU-HF score outperformed NT-proBNP, the strongest individual predictor (area under the curve [AUC] 0.77, 95% CI [0.71-0.83] vs. AUC 0.72, 95% CI [0.66-0.79], P = 0.008), demonstrating excellent performance with an AUC of 0.83 (95% CI: 0.77-0.89) to predict outcomes in the validation cohort. Compared with the low-risk group, the intermediate-risk and high-risk groups had significantly higher risks of the composite outcome (HR 4.09, 95% CI [2.23-7.50], P < 0.001 and 12.69, 95% CI [7.02-22.95], P < 0.001), proving strong risk stratification capability of the ICCU-HF score.
conclusionsThe ICCU-HF score showed good performance in predicting the 1-year risk of unplanned HF hospitalization and death in a large cohort of unselected patients admitted to the ICCU, with excellent results in the validation cohort. This score effectively stratifies patients into risk groups, enhancing its utility in clinical decision-making.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.