首页|Accurate prediction of biliary atresia with an integrated model using MMP-7 levels and bile acids

Accurate prediction of biliary atresia with an integrated model using MMP-7 levels and bile acids

扫码查看
原文链接
  • NETL
  • NSTL
  • 万方数据
Background Biliary atresia(BA)is a rare fatal liver disease in children,and the aim of this study was to develop a method to diagnose BA early.Methods We determined serum levels of matrix metalloproteinase-7(MMP-7),the results of 13 liver tests,and the levels of 20 bile acids,and integrated computational models were constructed to diagnose BA.Results Our findings demonstrated that MMP-7 expression levels,as well as the results of four liver tests and levels of ten bile acids,were significantly different between 86 BA and 59 non-BA patients(P＜0.05).The computational prediction model revealed that MMP-7 levels alone had a higher predictive accuracy[area under the receiver operating characteristic curve(AUC)=0.966,95％confidence interval(CI):0.942,0.989]than liver test results and bile acid levels.The AUC was 0.890(95％CI 0.837,0.943)for liver test results and 0.825(95％CI 0.758,0.892)for bile acid levels.Furthermore,bile levels had a higher contribution to enhancing the predictive accuracy of MMP-7 levels(AUC=0.976,95％CI 0.953,1.000)than liver test results.The AUC was 0.983(95％CI 0.962,1.000)for MMP-7 levels combined with liver test results and bile acid levels.In addition,we found that MMP-7 levels were highly correlated with gamma-glutamyl transferase levels and the liver fibrosis score.Conclusion The innovative integrated models based on a large number of indicators provide a noninvasive and cost-effective approach for accurately diagnosing BA in children.

Bile aidBiliary atresiaDiagnosisLiver fibrosisLiver testMMP-7

Yi-Jiang Han、Shu-Qi Hu、Jin-Hang Zhu、Xiao Cai、Deng-Ming Lai、Bao-Hai Chen、Kun Zhu、Qiao Tong、Xin-Rui Zhou、Jia-Le Deng、Jin-Fa Tou、Zhuo Fang、Li-Zhong Du

展开 >

Department of Neonatal Surgery,Children's Hospital,Zhejiang University School of Medicine,National Clinical Research Center for Child Health,Hangzhou,China

Department of Data and Analytics,WuXi Diagnostics Innovation Research Institute,Shanghai,China

Department of Information Center,Children's Hospital,Zhejiang University School of Medicine,National Clinical Research Center for Child Health,Hangzhou,China

Department of Pathology,Children's Hospital,Zhejiang University School of Medicine,National Clinical Research Center for Child Health,Hangzhou,China

Department of Neonatology,Children's Hospital,Zhejiang University School of Medicine,National Clinical Research Center for Child Health,Hangzhou,China

展开 >

Key Program of the Independent Design Project of National Clinical Research Center for Child HealthShanghai Pujiang ProgramMinistry of Industry and Information Technology Artificial Intelligence Medical Devices Innovation Program

S20C000421PJ1423100

2024

10.1007/s12519-023-00779-7

世界儿科杂志(英文版)

世界儿科杂志(英文版)

CSTPCD
ISSN：
年,卷(期)：2024.20(8)
  • 1