Department of Neonatology, Xinhua Hospital, Shanghai JiaoTong University School of Medicine, 1665 Kong Jiang Road, Shanghai, 200092, China.
Department of Ultrasound, Xinhua Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China.
Eur Radiol. 2020 Jul;30(7):3852-3861. doi: 10.1007/s00330-020-06751-7. Epub 2020 Mar 11.
It is challenging to early differentiate biliary atresia from other causes of cholestasis. We aimed to develop an algorithm with risk stratification to distinguish biliary atresia from infantile cholestasis.
In this study, we enrolled infants with cholestasis into 2 subgroups from January 2010 to April 2019. A prospective cohort (subgroup 2) of 187 patients (107 with biliary atresia and 80 without biliary atresia) underwent acoustic radiation force impulse elastography. Stepwise regression was used to identify significant predictors of biliary atresia. A sequential algorithm with risk stratification was constructed.
Among 187 patients, shear wave speed > 1.35 m/s and presence of the triangular cord sign were considered high risk for biliary atresia (red), in which 73 of 78 patients (accuracy of 93.6%) with biliary atresia were identified. Afterwards, γ-GT, abnormal gallbladder, and clay stool were introduced into the algorithm and 55 intermediate-risk infants were identified (yellow) with a diagnostic accuracy of 60% for biliary atresia. Of the remaining 54 infants who were classified as low-risk patients (green), the accuracy for excluding biliary atresia was 98.1%. By applying a three-color risk stratification tool, 70.6% patients were identified as either high risk or low risk for biliary atresia (area under the curve, 0.983; sensitivity, 98.7%; specificity, 91.4%). We also estimated the risk of biliary atresia in different color groups, which was 94.7% (95%CI, 94.3-95.5%) in the red group and 7.2% (95%CI, 6.6-8.3%) in the green group.
Our simple noninvasive approach was able to identify biliary atresia with high accuracy.
• Five predictors, namely shear wave speed, triangle cord sign, γ-glutamyl transferase, abnormal gallbladder, and clay stool, were selected to identify biliary atresia in cholestasis. • Shear wave speed > 1.35 m/s and presence of the triangle cord sign were considered high-risk patients with a diagnostic accuracy of 93.6% for biliary atresia. • Risk for biliary atresia was high (red), intermediate (yellow), or low (green). In the red and green group, we achieved an extremely high diagnostic performance (area under the curve, 0.983; sensitivity, 98.7%; specificity, 91.4%).
早期鉴别胆道闭锁与其他类型的胆汁淤积具有挑战性。本研究旨在建立一种具有风险分层的算法,以区分胆道闭锁与婴儿胆汁淤积。
本研究纳入了 2010 年 1 月至 2019 年 4 月期间患有胆汁淤积的婴儿,将其分为 2 个亚组。前瞻性队列(亚组 2)包括 187 例患者(107 例胆道闭锁,80 例非胆道闭锁)接受声辐射力脉冲弹性成像检查。采用逐步回归法识别胆道闭锁的显著预测因素。构建了具有风险分层的序贯算法。
在 187 例患者中,剪切波速度>1.35 m/s 和出现三角索征被认为是胆道闭锁的高风险(红色),其中 78 例胆道闭锁患者中的 73 例(诊断准确性为 93.6%)得到了识别。之后,γ-谷氨酰转移酶、异常胆囊和黏土样粪便被引入算法,55 例中危患儿(黄色)被识别为胆道闭锁的诊断准确性为 60%。剩余的 54 例被归类为低危患儿(绿色),排除胆道闭锁的准确性为 98.1%。通过应用三色风险分层工具,70.6%的患者被确定为胆道闭锁的高风险或低风险(曲线下面积为 0.983;敏感性为 98.7%;特异性为 91.4%)。我们还估计了不同颜色组的胆道闭锁风险,红色组为 94.7%(95%CI,94.3-95.5%),绿色组为 7.2%(95%CI,6.6-8.3%)。
我们的简单非侵入性方法能够准确识别胆道闭锁。
5 个预测因素,即剪切波速度、三角索征、γ-谷氨酰转移酶、异常胆囊和黏土样粪便,被用于识别胆汁淤积中的胆道闭锁。
剪切波速度>1.35 m/s 和出现三角索征被认为是胆道闭锁的高风险患者,其诊断准确性为 93.6%。
胆道闭锁风险高(红色)、中危(黄色)或低危(绿色)。在红色和绿色组中,我们获得了极高的诊断性能(曲线下面积为 0.983;敏感性为 98.7%;特异性为 91.4%)。