Association between fibrosis-4 index and 30-day all-cause mortality in critically ill patients hospitalised with acute heart failure: a retrospective cohort study from the MIMIC-IV database
Department of Cardiology, Jiangdu People’s Hospital of Yangzhou, Yangzhou, China
Department of Cardiology, Subei People’s Hospital of Jiangsu Province, Yangzhou, China
Introduction
The Fibrosis-4 index (Fib-4), a non-invasive liver fibrosis biomarker, is increasingly linked to cardiovascular risk, but its role in acute heart failure (AHF) remains unclear.
Aim
We evaluated its association with 30-day all-cause mortality in critically ill patients with AHF.
Material and methods
This retrospective observational study enrolled 1535 ICU patients with AHF from the MIMIC-IV database. The primary endpoint was all-cause mortality within 30 days from the date of hospital admission. Baseline characteristics, comorbidities, laboratory data, and clinical information were extracted. Patients were divided into survival and mortality groups, and baseline differences were compared. Lasso regression identified variables influencing prognosis, which were then included in a restricted cubic splines (RCS) model. Three multivariable logistic regression models (Model 1 unadjusted; Model 2 adjusted for INR, age, BUN, nd potassium; Model 3 fully adjusted for po2 max, WBC, lymphocytes, BUN, calcium, glucose, anion gap, potassium, INR, ALP, CRRT, CK-MB, age, peripheral vascular disease, and CHA2DS2-VASc score) were constructed. Receiver operating characteristic (ROC) curve analysis assessed the predictive performance of Fib-4. Subgroup analysis evaluated potential differences across population subgroups. Sensitivity analyses using complete-case analysis and multiple imputation were performed to address missing data.
Results
The mortality group (n = 219, 14.3%) exhibited significantly higher Fib-4 values than the survival group (n = 1316). Lasso regression identified 16 variables influencing prognosis, including Fib-4. RCS analysis showed a positive correlation between Fib-4 and 30-day mortality risk (p-overall = 0.006, p-nonlinear = 0.330). After adjustment for confounders, logistic regression demonstrated that Fib-4 was an independent risk factor (Model 1: OR = 1.10, 95% CI: 1.07–1.13, p < 0.001; Model 2: OR = 1.08, 95% CI: 1.05–1.11, p < 0.001; Model 3: OR = 1.05, 95% CI: 1.02–1.09, p = 0.002). The area under the ROC curve (AUC) for Fib-4 predicting 30-day mortality was 0.665, indicating modest predictive value. The optimal cutoff was 2.25 (sensitivity 74.0%, specificity 51.4%). Quartile analysis showed a dose-response relationship (Q4 vs. Q1: OR = 2.51, 95% CI: 1.28–4.92, p = 0.007 in Model 3). Subgroup analyses revealed no significant interaction. Sensitivity analyses confirmed the robustness of the findings.
Conclusions
In critically ill patients with AHF, the Fib-4 index is independently associated with 30-day mortality but provides only modest predictive discrimination. This readily available, cost-effective marker may offer adjunctive information for early risk stratification, but its clinical utility should be interpreted with caution given the limited AUC.
Keywords
Fibrosis-4 index, acute heart failure, mortality, MIMIC-IV database, intensive care unit
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