A clinical model to predict fibrosis on liver biopsy in paediatric subjects with nonalcoholic fatty liver disease.
A clinical model to predict fibrosis on liver biopsy in paediatric subjects with nonalcoholic fatty liver disease.
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DOI：
10.1111/cob.12472
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发表时间：
2021-10
期刊：
影响因子：
3.3
通讯作者：
DeBosch BJ
中科院分区：
文献类型：
--
作者：
Kulkarni S;Naz N;Gu H;Stoll JM;Thompson MD;DeBosch BJ
儿童非酒精性脂肪性肝病（NAFLD）的发病率正在迅速上升。肝纤维化是一种不良预后特征，可独立预测肝硬化。第一次就诊和活检之间的时间限制了多模式治疗。本研究旨在确定非侵入性参数来预测晚期NAFLD和纤维化。我们对640例接受肝活检的儿童患者进行了一项为期10年的单中心回顾性分析。55例患者，年龄3-21岁，活检证实为NAFLD。我们通过线性回归、二元截止值和多变量logistic回归纤维化预测模型评估主要结局、NAFLD活度评分（NAS）和纤维化评分，以对照非侵入性参数。NAS与血小板和女性性别相关。纤维化评分与血小板计数、谷氨酰基转移酶（GGT）和超声剪切波速相关。25-羟基维生素D和GGT分化轻度与中度至晚期纤维化。我们基于多元逻辑回归模型的评分系统预测F2或更高（参数：BMI%、维生素D、血小板、GGT），敏感性和特异性分别为0.83和0.95 （ROC曲线下面积为0.944）。我们确定了一种临床模型来确定高风险患者进行快速活检。对患者进行分层以缩短活检时间可以减少对高危患者进行积极治疗的延迟。
The incidence of Nonalcoholic fatty liver disease (NAFLD) in children is rapidly increasing. Liver fibrosis is a poor prognostic feature that independently predicts cirrhosis. The time that intercedes the first medical encounter and biopsy is rate-limiting to multi-modal treatment. This study aimed to identify non-invasive parameters to predict advanced NAFLD and fibrosis. We conducted a single-center, retrospective 10-year analysis of 640 pediatric patients who underwent liver biopsy. Fifty-five patients, age 3-21 years, had biopsy-confirmed NAFLD. We assessed primary outcomes, NAFLD activity score (NAS) and fibrosis scores, against non-invasive parameters by linear regression, by using binary cutoff values, and by a multivariate logistic regression fibrosis prediction model. NAS correlated with platelets and female sex. Fibrosis scores correlated with platelet counts, gamma glutamyl transferase (GGT), and ultrasound shear wave velocity. 25-hydroxy-vitamin D and GGT differentiated mild vs moderate-to-advanced fibrosis. Our multivariate logistical regression model-based scoring system predicted F2 or higher (parameters: BMI%, Vitamin D, Platelets, GGT), with sensitivity and specificity of 0.83 and 0.95 (area under the ROC curve, 0.944). We identify a clinical model to identify high-risk patients for expedited biopsy. Stratifying patients to abbreviate time-to-biopsy can attenuate delays in aggressive therapy for high-risk patients.