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序贯算法在超重/肥胖代谢相关脂肪性肝病中分层评估肝纤维化风险。

Sequential algorithm to stratify liver fibrosis risk in overweight/obese metabolic dysfunction-associated fatty liver disease.

机构信息

Department of Medicine, School of Clinical Medicine, University of Hong Kong, Queen Mary Hospital, Hong Kong, Hong Kong SAR, China.

State Key Laboratory of Pharmaceutical Biotechnology, University of Hong Kong, Hong Kong, Hong Kong SAR, China.

出版信息

Front Endocrinol (Lausanne). 2023 Jan 6;13:1056562. doi: 10.3389/fendo.2022.1056562. eCollection 2022.

Abstract

BACKGROUND

Non-diabetic overweight/obese metabolic dysfunction-associated fatty liver disease (MAFLD) represents the largest subgroup with heterogeneous liver fibrosis risk. Metabolic dysfunction promotes liver fibrosis. Here, we investigated whether incorporating additional metabolic risk factors into clinical evaluation improved liver fibrosis risk stratification among individuals with non-diabetic overweight/obese MAFLD.

MATERIALS AND METHODS

Comprehensive metabolic evaluation including 75-gram oral glucose tolerance test was performed in over 1000 participants from the New Hong Kong Cardiovascular Risk Factor Prevalence Study (HK-NCRISPS), a contemporary population-based study of HK Chinese. Hepatic steatosis and fibrosis were evaluated based on controlled attenuation parameter and liver stiffness (LS) measured using vibration-controlled transient elastography, respectively. Clinically significant liver fibrosis was defined as LS ≥8.0 kPa. Our findings were validated in an independent pooled cohort comprising individuals with obesity and/or polycystic ovarian syndrome.

RESULTS

Of the 1020 recruited community-dwelling individuals, 312 (30.6%) had non-diabetic overweight/obese MAFLD. Among them, 6.4% had LS ≥8.0 kPa. In multivariable stepwise logistic regression analysis, abnormal serum aspartate aminotransferase (AST) (OR 7.95, p<0.001) and homeostasis model assessment of insulin resistance (HOMA-IR) ≥2.5 (OR 5.01, p=0.008) were independently associated with LS ≥8.0 kPa, in a model also consisting of other metabolic risk factors including central adiposity, hypertension, dyslipidaemia and prediabetes. A sequential screening algorithm using abnormal AST, followed by elevated HOMA-IR, was developed to identify individuals with LS ≥8.0 kPa, and externally validated with satisfactory sensitivity (>80%) and negative predictive value (>90%).

CONCLUSION

A sequential algorithm incorporating AST and HOMA-IR levels improves fibrosis risk stratification among non-diabetic overweight/obese MAFLD individuals.

摘要

背景

非糖尿病超重/肥胖代谢相关脂肪性肝病(MAFLD)代表了具有异质性肝纤维化风险的最大亚组。代谢功能障碍促进肝纤维化。在这里,我们研究了在非糖尿病超重/肥胖 MAFLD 个体中,将额外的代谢危险因素纳入临床评估是否能改善肝纤维化风险分层。

材料和方法

对来自当代香港华人基于人群的香港心血管危险因素流行研究(HK-NCRISPS)的 1000 多名参与者进行了全面的代谢评估,包括 75 克口服葡萄糖耐量试验。通过受控衰减参数和振动控制瞬态弹性成像测量的肝硬度(LS)分别评估肝脂肪变性和纤维化。临床显著纤维化定义为 LS≥8.0kPa。我们的发现在包含肥胖症和/或多囊卵巢综合征患者的独立汇总队列中得到了验证。

结果

在招募的 1020 名社区居民中,312 名(30.6%)患有非糖尿病超重/肥胖 MAFLD。其中,6.4%的人 LS≥8.0kPa。在多变量逐步逻辑回归分析中,血清天冬氨酸转氨酶(AST)异常(OR 7.95,p<0.001)和稳态模型评估的胰岛素抵抗(HOMA-IR)≥2.5(OR 5.01,p=0.008)与 LS≥8.0kPa 独立相关,该模型还包括其他代谢危险因素,包括中心性肥胖、高血压、血脂异常和糖尿病前期。使用异常 AST 随后是升高的 HOMA-IR 的顺序筛查算法被开发用于识别 LS≥8.0kPa 的个体,并在外部验证中具有令人满意的敏感性(>80%)和阴性预测值(>90%)。

结论

纳入 AST 和 HOMA-IR 水平的序贯算法可改善非糖尿病超重/肥胖 MAFLD 个体的纤维化风险分层。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b2be/9853017/ef65e0a9a611/fendo-13-1056562-g001.jpg

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