瞬态弹性成像
医学
非酒精性脂肪肝
内科学
肝硬化
纤维化
置信区间
接收机工作特性
体质指数
胃肠病学
算法
肝活检
脂肪肝
活检
疾病
计算机科学
作者
Tina Reinson,Janisha Patel,Mead Mathews,Derek Fountain,Ryan Buchanan,Christopher D. Byrne
出处
期刊:Journal of clinical and translational hepatology
[Xia & He Publishing]
日期:2023-02-24
卷期号:000 (000): 000-000
被引量:1
标识
DOI:10.14218/jcth.2022.00335
摘要
Liver fibrosis is a key risk factor for cirrhosis, hepatocellular carcinoma and end stage liver failure. The National Institute for Health and Care Excellence guidelines for assessment for advanced (≥F3) liver fibrosis in people with nonalcoholic fatty liver disease recommend the use of enhanced liver fibrosis (ELF) test, followed by vibration-controlled transient elastography (VCTE). Performance of ELF at predicting significant (≥F2) fibrosis in real-world practice is uncertain. To assess the accuracy of ELF using VCTE; investigate the optimum ELF cutoff value to identify ≥F2 and ≥F3; and develop a simple algorithm, with and without ELF score, for detecting ≥F2.Retrospective evaluation of patients referred to a Community Liver Service for VCTE, Jan-Dec 2020. Assessment included: body mass index (BMI), diabetes status, alanine aminotransferase (ALT) levels, ELF score and biopsy-validated fibrosis stages according to VCTE.Data from 273 patients were available. n=110 patients had diabetes. ELF showed fair performance for ≥F2 and ≥F3, area under the curve (AUC) = 0.70, 95% confidence interval (CI) 0.64-0.76 and AUC=0.72, 95% CI: 0.65-0.79 respectively. For ≥F2 Youden's index for ELF=9.85 and for ≥F3, ELF=9.95. Combining ALT, BMI, and HbA1c (ALBA algorithm) to predict ≥F2 showed good performance (AUC=0.80, 95% CI: 0.69-0.92), adding ALBA to ELF improved performance (AUC=0.82, 95% CI: 0.77-0.88). Results were independently validated.Optimal ELF cutoff for ≥F2 is 9.85 and 9.95 for ≥F3. ALT, BMI, and HbA1c (ALBA algorithm) can stratify patients at risk of ≥F2. ELF performance is improved by adding ALBA.
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