应用瞬时弹性成像和生化联合策略判断小儿肠衰竭相关肝纤维化。

Use of a combined transient elastography and biochemical strategy to determine liver fibrosis in pediatric intestinal failure.

机构信息

The Group for Improvement of Intestinal Function and Treatment (GIFT), Transplant and Regenerative Medicine Centre, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada; Brussels Centrum for Intestinal Failure in Children (B-CIRC), Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel (VUB), Brussels, Belgium.

The Group for Improvement of Intestinal Function and Treatment (GIFT), Transplant and Regenerative Medicine Centre, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.

出版信息

Clin Nutr. 2023 Feb;42(2):136-142. doi: 10.1016/j.clnu.2022.12.002. Epub 2022 Dec 9.

DOI:10.1016/j.clnu.2022.12.002

PMID:36563562

Abstract

BACKGROUND & AIMS: Non-invasive monitoring of intestinal failure (IF) associated liver disease is an ongoing challenge in children with IF. Our objective was to develop a combined algorithm of clinical, transient elastography (TE) and biochemical parameters to identify liver fibrosis in this population.

METHODS

A retrospective cohort study of IF patients followed by our intestinal rehabilitation program between November 2015 to October 2019. Patients with a liver biopsy and TE were included. Demographic and liver function tests were collected. Fibrosis on liver biopsies was graded using the modified Scheuer score. Decision tree based algorithms classified low (F0-F1) versus high (F2-F4) fibrosis scores based on a combination of TE, biochemical and demographic parameters, using 6-fold classification error, sensitivity and specificity cross-validation (CV) scores.

RESULTS

42 patients (74% male, median age 7.6 (4.6; 42.7) months) were evaluated. Median length of PN therapy was 182 (121; 556) days. High fibrosis was present in 40.5% with a median TE of 12.1 (6.7; 12.9) kPa in high fibrosis children. An algorithm, based on cut-off values for TE of 11.3 kPa and AST of 40 U/L, and grouping of the underlying etiology resulted in a correct classification of 88.1% of the pathology scores; with sensitivity 0.82 (95% CI 0.57; 0.96), specificity 0.92 (95% CI 0.74; 0.99), positive predictive value 0.88 (95% CI 0.64; 0.96) and negative predictive value 0.88 (95% CI 0.73; 0.96). The CV classification error was 28.6%, CV sensitivity 72.2% and CV specificity 75.5%.

CONCLUSIONS

This algorithm shows promising results that could simplify non-invasive monitoring of liver fibrosis in children with IF. Validation in additional IF cohorts is needed.

摘要

背景与目的

在患有肠衰竭（IF）的儿童中，对与 IF 相关的肝病进行非侵入性监测是一项持续存在的挑战。我们的目标是开发一种结合临床、瞬时弹性成像（TE）和生化参数的综合算法，以识别该人群中的肝纤维化。

方法

这是一项回顾性队列研究，纳入了 2015 年 11 月至 2019 年 10 月期间接受我们肠康复计划治疗的 IF 患者。纳入了接受肝活检和 TE 的患者。收集了人口统计学和肝功能检查结果。使用改良的 Scheuer 评分对肝活检中的纤维化进行分级。决策树算法基于 TE、生化和人口统计学参数的组合，将纤维化评分分为低（F0-F1）和高（F2-F4）两组，使用 6 倍分类误差、敏感性和特异性交叉验证（CV）评分进行分类。

结果

共评估了 42 名患者（74%为男性，中位年龄 7.6（4.6；42.7）个月）。PN 治疗的中位时间为 182（121；556）天。40.5%的患者存在高纤维化，高纤维化儿童的 TE 值中位数为 12.1（6.7；12.9）kPa。基于 TE 截断值 11.3 kPa 和 AST 截断值 40 U/L，以及基础病因分组的算法，正确分类了 88.1%的病理评分；敏感性为 0.82（95%CI 0.57；0.96），特异性为 0.92（95%CI 0.74；0.99），阳性预测值为 0.88（95%CI 0.64；0.96），阴性预测值为 0.88（95%CI 0.73；0.96）。CV 分类误差为 28.6%，CV 敏感性为 72.2%，CV 特异性为 75.5%。