Liver Fibrosis Scores as Predictors of Long-term Outcomes in Patients with ST-segment Elevation Myocardial Infarction

Author:

Zhu Longyang,Chen Yinong,Li Qing,Wang Zhe,Jiao Siqi,Zheng Shuwen,Yang Furong,Sun Yihong

Abstract

Background: Liver fibrosis scores (LFSs) are novel tools for predicting cardiovascular events in patients with coronary artery disease. This study was aimed at examining the prognostic value of LFSs in patients with ST-segment elevation myocardial infarction (STEMI). Methods: Between 2015 and 2019, 866 patients diagnosed with STEMI were consecutively enrolled. The definition of major cardiovascular events (MACEs) was all-cause death, nonfatal myocardial infarction, nonfatal ischemic stroke, and acute limb ischemia. We evaluated the predictive values of LFSs for MACEs with receiver operating characteristic (ROC) curve and restricted cubic spline (RCS) analysis. Kaplan-Meier (K-M) analysis was conducted to explore the relationship between LFSs and MACEs. Results: During a median follow-up of 4 years, 155 MACEs were observed. K-M analysis of MACEs revealed significantly lower event-free survival rates in patients with intermediate or high, rather than low, NFS, FIB-4, BARD, and Forns scores. The multivariable-adjusted hazard ratios (95% CI) for MACEs in patients with high versus low risk scores were 1.343 (0.822–2.197) for NFS, 1.922 (1.085–3.405) for FIB-4, 2.395 (1.115–5.142) for BARD, and 2.271 (1.250–4.125) for Forns. The ROC curve indicated that the predictive ability for MACEs was non significantly improved by addition of the NFS (AUC = 0.7274), FIB-4 (AUC = 0.7199), BARD (AUC = 0.7235), and Forns (AUC = 0.7376) scores into the basic model (AUC = 0.7181). RCS revealed a tendency toward a nonlinear positive association of MACEs with NFS, FIB-4, and particularly Forns scores. Conclusion: LFSs have potential utility for predicting adverse outcomes in patients with STEMI, thus indicating the importance of managing metabolic dysregulation.

Publisher

Compuscript, Ltd.

Subject

General Medicine

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