Liver Fibrosis and 8-Year All-Cause Mortality Trajectories in the Aging Cohort of the Salus in Apulia Study

普利亚大区萨卢斯研究老龄化队列中的肝纤维化和 8 年全因死亡率轨迹

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作者:Roberta Zupo, Fabio Castellana, Sara De Nucci, Giovanni De Pergola, Madia Lozupone, Ilaria Bortone, Marco Castellana, Giancarlo Sborgia, Luisa Lampignano, Gianluigi Giannelli, Francesco Panza, Rodolfo Sardone

Abstract

Age is a major contributor to the liver fibrosis rate and its adverse health-related outcomes, including mortality, but older populations are still under-explored. We investigated multimorbidity and inflammatory biomarkers in relation to the increasing liver fibrosis risk to delineate 8-year all-cause mortality trajectories in 1929 older adults from the population-based Salus in Apulia Study. Liver fibrosis risk was assumed using the fibrosis-4 (FIB-4) score, assigned to three liver fibrosis risk groups (low, intermediate, high). In the secondary analyses, the APRI score was also calculated to allow for comparisons. Male subjects (prevalence difference: -13.49, 95% confidence interval (CI): -18.96 to -8.03), a higher multimorbidity burden (effect size, ES: -0.14, 95% CI: -0.26 to -0.02), a higher prevalence of physical frailty (ES: 6.77, 95% CI: 0.07 to 13.47), and a more pronounced inflammatory pattern as indicated by tumor growth factor-α circulating levels (ES: -0.12, 95% CI: -0.23 to -0.01) were significantly more common in the highest-risk FIB-4 score group. Liver function characterized by lipid profile and platelet levels worsened with increasing FIB-4 risk score. The 8-year risk of death was nearly double in subjects in the highest-risk FIB-4 score group, even after controlling for possible confounders. Furthermore, a steeper mortality curve was clearly observed for FIB-4 scores as compared with the APRI scoring system with respect to liver fibrosis risk. In conclusion, using a scoring tool based on simple routine biomarkers to detect liver fibrosis risk may enhance biological knowledge of age-related outcomes of chronic liver disease and be helpful in the clinical setting to identify subjects at risk for adverse health-related outcomes, including mortality.

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