医学
瞬态弹性成像
非酒精性脂肪肝
代谢综合征
脂肪性肝炎
内科学
脂肪肝
疾病
2型糖尿病
重症监护医学
糖尿病
风险评估
肝病
纤维化
胃肠病学
肝纤维化
肥胖
内分泌学
计算机安全
计算机科学
作者
Zobair M. Younossi,Naim Alkhouri,Kenneth Cusi,Scott Isaacs,Fasiha Kanwal,Mazen Noureddin,Rohit Loomba,Natarajan Ravendhran,Brian Lam,Khalil Nader,Andrei Racila,Fatema Nader,Linda Henry
摘要
Patients with nonalcoholic fatty liver disease (NAFLD) with type 2 diabetes (T2D) or other components of metabolic syndrome are at high risk for disease progression. We proposed an algorithm to identify high-risk NAFLD patients in clinical practice using noninvasive tests (NITs).Evidence about risk stratification of NAFLD using validated NITs was reviewed by a panel of NASH Experts. Using the most recent evidence regarding the performance of NITs and their application in clinical practice were used to develop an easy-to-use algorithm for risk stratification of NAFLD patients seen in primary care, endocrinology and gastroenterology practices.The proposed algorithm uses a three-step process to identify NAFLD patients who are potentially at high risk for adverse outcomes. The first step is to use clinical data to identify most patients who are at risk for having potentially progressive NAFLD (e.g. having T2D or multiple components of metabolic syndrome). The second step is to calculate the FIB-4 score as a NIT that can further risk stratifying individuals who are at low risk for progressive liver disease and can be managed by their primary healthcare providers to manage their cardiometabolic comorbidities. The third step is to use second-line NITs (transient elastography or enhanced liver fibrosis tests) to identify those who at high risk for progressive liver disease and should be considered for specially care by providers with NASH expertise.The use of this simple clinical algorithm can identify and assist in managing patients with NAFLD at high risk for adverse outcomes.
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