Web-based calculator for biliary atresia screening in neonates and infants with cholestasis

用于筛查新生儿和胆汁淤积婴儿胆道闭锁的在线计算器

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Abstract

BACKGROUND: Distinguishing biliary atresia from non-biliary atresia in patients with cholestasis is challenging, as these conditions have a similar clinical presentation. We developed and externally validated a screening model for biliary atresia and devised a web-based calculator for use in clinical settings. METHODS: A screening model was developed based on data from 227 cholestatic infants (82 and 145 with and without biliary atresia, respectively) and validated in 234 infants (90 and 144 with and without biliary atresia, respectively) admitted to three hospitals. Variables were selected from routine examination results using the least absolute shrinkage and selection operator method and entered into a logistic regression model to construct a biliary-atresia-risk-predicting equation. Cutoff values for risk stratification were estimated using model sensitivity, derived from the receiver-operating characteristic curves. RESULTS: The final screening model included seven variables (i.e., weight at admission, clay-colored stools, γ-glutamyl transpeptidase and albumin levels at admission, abnormal gallbladder, triangular cord sign, and change in total bilirubin levels). The model generated an area under the curve of 0.94 with a sensitivity of 91.46 and specificity of 86.62 in the derivation cohort. This was confirmed in the validation cohort, as we found an area under the curve of 0.93 with a sensitivity of 93.1 and specificity of 80.15. Patients were stratified into three risk groups (low-, moderate-, and high-risk groups). Biliary atresia was excluded in the low-risk group. The high-risk group showed a higher detection rate of biliary atresia compared to the stool color screening method alone. This model was integrated into a user-friendly web-based system. CONCLUSIONS: The screening tool had a high predictive value and may help in decision-making by physicians at tertiary and community hospitals.

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