Ontology highlight
ABSTRACT: Background & aims
The overlapping features of biliary atresia (BA) and the other forms of neonatal cholestasis (NC) with different causes (non-BA) has posed challenges for the diagnosis of BA. This study aimed at developing new and better diagnostic models for BA.Methods
We retrospectively analyzed data from 1728 newborn infants with neonatal obstructive jaundice (NOJ). New prediction models, including decision tree (DT), random forest (RF), and multivariate logistic regression-based nomogram for BA were created and externally validated in an independent set of 508 infant patients.Results
Fiver predictors, including gender, weight, direct bilirubin (DB), alkaline phosphatase (ALP), and gamma-glutamyl transpeptidase (GGT) were significantly different between the BA and non-BA groups (P?ConclusionsThe nomogram has demonstrated better performance for the prediction of BA, holding promise for future clinical application.
SUBMITTER: Dong R
PROVIDER: S-EPMC6116426 | biostudies-literature | 2018 Aug
REPOSITORIES: biostudies-literature
Dong Rui R Jiang Jingying J Zhang Shouhua S Shen Zhen Z Chen Gong G Huang Yanlei Y Zheng Yijie Y Zheng Shan S
EBioMedicine 20180801
<h4>Background & aims</h4>The overlapping features of biliary atresia (BA) and the other forms of neonatal cholestasis (NC) with different causes (non-BA) has posed challenges for the diagnosis of BA. This study aimed at developing new and better diagnostic models for BA.<h4>Methods</h4>We retrospectively analyzed data from 1728 newborn infants with neonatal obstructive jaundice (NOJ). New prediction models, including decision tree (DT), random forest (RF), and multivariate logistic regression-b ...[more]