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Anthropometric and blood parameters for the prediction of NAFLD among overweight and obese adults

医学 内科学 脂肪肝 人体测量学 腰围 超重 脂联素 脂肪性肝炎 胃肠病学 接收机工作特性 肝硬化 脂肪变性 体质指数 肥胖 疾病 胰岛素抵抗
作者
Tilman Kühn,Tobias Nonnenmacher,Disorn Sookthai,Ruth Schübel,Daniel A. Quintana Pacheco,Oyunbileg von Stackelberg,Mirja E. Graf,Theron Johnson,Christopher L. Schlett,Romy Kirsten,Cornelia M. Ulrich,Rudolf Kaaks,Hans‐Ulrich Kauczor,Johanna Nattenmüller
出处
期刊:BMC Gastroenterology [Springer Nature]
卷期号:18 (1) 被引量:38
标识
DOI:10.1186/s12876-018-0840-9
摘要

Non-alcoholic fatty liver disease (NAFLD) comprises non-progressive steatosis and non-alcoholic steatohepatitis (NASH), the latter of which may cause cirrhosis and hepatocellular carcinoma (HCC). As NAFLD detection is imperative for the prevention of its complications, we evaluated whether a combination of blood-based biomarkers and anthropometric parameters can be used to predict NAFLD among overweight and obese adults.143 overweight or obese non-smokers free of diabetes (50% women, age: 35-65 years) were recruited. Anthropometric indices and routine biomarkers of metabolism and liver function were measured to predict magnetic resonance (MR) - derived NAFLD by multivariable logistic regression models. In addition, we evaluated to which degree the use of more novel biomarkers (adiponectin, leptin, resistin, C-reactive protein, TNF-α, IL-6, IL-8 and interferon-γ) could improve prediction models.NAFLD was best predicted by a combination of age, sex, waist circumference, ALT, HbA1c, and HOMA-IR at an area under the receiver operating characteristic curve (AUROC) of 0.87 (95% CI: 0.81, 0.93) before and 0.85 (95% CI: 0.78, 0.91) after internal bootstrap validation. The use of additional biomarkers of inflammation and metabolism did not improve NAFLD prediction. Previously published indices predicted NAFLD at AUROCs between 0.71 and 0.82.The AUROC of > 0.8 obtained by our regression model suggests the feasibility of a non-invasive detection of NAFLD by anthropometry and circulating biomarkers, even though further increments in the capacity of prediction models may be needed before NAFLD indices can be applied in routine clinical practice.
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