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Unveiling the prognostic power of FIB-4 index: a new frontier in heart failure mortality
Wen Lu1,2, Changxi Wang3,4,5, Hansong Zhu6
1The Shengli Clinical Medical College, Fujian Medical University, Fuzhou, 350001, Fujian, China.
Insights
The Fibrosis-4 (FIB-4) index effectively predicts mortality in heart failure (HF) patients. Higher FIB-4 levels correlate with increased all-cause death risk at 30 days, 90 days, and 1 year.
Area of Science:
- Cardiology
- Biomarkers
- Medical Informatics
Background:
- The Fibrosis-4 (FIB-4) index is recognized for predicting cardiovascular events in type 2 diabetes.
- Its predictive utility for mortality in heart failure (HF) patients requires further investigation.
Purpose of the Study:
- To evaluate the predictive power of the FIB-4 index for all-cause mortality in patients diagnosed with heart failure.
- To explore the dose-response relationship between FIB-4 levels and mortality risk.
Main Methods:
- Utilized data from the MIMIC-IV database, stratifying 6658 patients into FIB-4 quartiles.
- Employed Cox regression and Kaplan-Meier survival analyses to assess mortality at 30 days, 90 days, and 1 year.
- Applied Restricted Cubic Spline analysis to determine the dose-response relationship and conducted subgroup analyses.
Main Results:
- A significant association was found between higher FIB-4 index values and increased all-cause mortality at all time points (30 days, 90 days, 1 year).
- The highest FIB-4 quartile demonstrated the poorest survival rates.
- A nonlinear dose-response relationship between FIB-4 and mortality was confirmed, consistent across various subgroups.
Conclusions:
- The FIB-4 index serves as a reliable and independent predictor of all-cause mortality in patients with heart failure.
- FIB-4 can aid in risk stratification and clinical decision-making for HF management.
Background:
The fibrosis-4 (FIB-4) index is valuable in predicting cardiovascular events in individuals with type 2 diabetes. This paper was to ascertain the predictive power of FIB-4 for mortality in patients with heart failure (HF).
Methods:
Patient data were sourced from the MIMIC-IV database and allocated to quartiles based on FIB-4 values. All-cause deaths at 30 days, 90 days, and 1 year after patient admission were the endpoints. Cox models, adjusted for multiple factors, were leveraged to examine the link between FIB-4 and mortality in HF patients. Kaplan-Meier (K-M) survival curves were utilized to unveil differences in mortality among different FIB-4 subgroups. Restricted cubic spline (RCS) was adopted to testify the dose-response relationship between FIB-4 and mortality. Subgroup analyses were implemented to evaluate the consistency of results across age and sex subgroups.
Result:
A total of 6658 patients were enrolled, with 56% women and 68% whites. Cox analyses revealed considerable links of the FIB-4 index with all-cause deaths at 30 days, 90 days, and 1 year in HF patients. K-M survival analysis showed that the highest FIB-4 quartile (Q4) had the poorest survival. RCS analysis revealed a nonlinear dose-response relationship between FIB-4 and mortality. Risk-stratified analyses in multiple subgroups confirmed consistent results with overall results, with high FIB-4 levels being linked to an increased risk of death.
Conclusion:
FIB-4 is a reliable predictor of all-cause deaths in HF patients.
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