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Corresponding Author: Email: Benjamin.Shneider@bcm.edu

The authors have declared that no competing interests exist.

Research Funding:

Funding provided by the following National Institute of Diabetes and Digestive and Kidney Diseases (https://www.niddk.nih.gov/) grants: U01DK103149 (BLS); U01DK062456 (JCM); U01DK062470 and UL1TR000454 (SJK); U01DK062453 and UL1TR001082 (RJS); U01DK062436 and UL1TR000150 (PFW); U01DK062503, UL1TR000424 (KS); U01DK062497 and UL1TR000077 (JAB); U01DK062445 (NK RA); U01DK062500 and UL1TR000004 (PR); U01DK062452 and UL1TR000448 (YPT); U01DK084536 and UL1TR001108 (JPM); U01DK084575, UL1TR000423 and UL1RR025014 (KFM); U01DK062466 and UL1TR000005 (RHS); U01DK103135 (BMK); U01DK062481 (KML); U01DK103140 (SLG).

Initial assessment of the infant with neonatal cholestasis-Is this biliary atresia?

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Journal Title:

PLoS ONE

Volume:

Volume 12, Number 5

Publisher:

, Pages e0176275-e0176275

Type of Work:

Article | Final Publisher PDF

Abstract:

INTRODUCTION: Optimizing outcome in biliary atresia (BA) requires timely diagnosis. Cholestasis is a presenting feature of BA, as well as other diagnoses (Non-BA). Identification of clinical features of neonatal cholestasis that would expedite decisions to pursue subsequent invasive testing to correctly diagnose or exclude BA would enhance outcomes. The analytical goal was to develop a predictive model for BA using data available at initial presentation. METHODS: Infants at presentation with neonatal cholestasis (direct/conjugated bilirubin >2 mg/dl [34.2 μM]) were enrolled prior to surgical exploration in a prospective observational multi-centered study (PROBE-NCT00061828). Clinical features (physical findings, laboratory results, gallbladder sonography) at enrollment were analyzed. Initially, 19 features were selected as candidate predictors. Two approaches were used to build models for diagnosis prediction: a hierarchical classification and regression decision tree (CART) and a logistic regression model using a stepwise selection strategy. RESULTS: In PROBE April 2004-February 2014, 401 infants met criteria for BA and 259 for Non-BA. Univariate analysis identified 13 features that were significantly different between BA and Non-BA. Using a CART predictive model of BA versus Non-BA (significant factors: gamma-glutamyl transpeptidase, acholic stools, weight), the receiver operating characteristic area under the curve (ROC AUC) was 0.83. Twelve percent of BA infants were misclassified as Non-BA; 17% of Non-BA infants were misclassified as BA. Stepwise logistic regression identified seven factors in a predictive model (ROC AUC 0.89). Using this model, a predicted probability of >0.8 (n = 357) yielded an 81% true positive rate for BA; <0.2 (n = 120) yielded an 11% false negative rate. CONCLUSION: Despite the relatively good accuracy of our optimized prediction models, the high precision required for differentiating BA from Non-BA was not achieved. Accurate identification of BA in infants with neonatal cholestasis requires further evaluation, and BA should not be excluded based only on presenting clinical features.

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This is an Open Access work distributed under the terms of the Creative Commons Universal : Public Domain Dedication License (http://creativecommons.org/publicdomain/zero/1.0/).

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