Nomogram for Acute Bilirubin Encephalopathy Risk in Newborns With Extreme Hyperbilirubinemia - Qu, Yangming; Huang, Shuhan; Fu, Xin; Wang, Youping; Wu, Hui (Frontiers in Neurology, 2020)
Background and Objectives To develop a predictive model of neonatal acute bilirubin encephalopathy. Methods We retrospectively analyzed the data of extreme hyperbilirubinemia (EHB) newborns hospitalized in the first hospital of jilin university from January 1, 2012 to December 31, 2019. The demographic characteristics、pathological information and admission examination results of newborns were collected to analyze the factors affecting acute bilirubin encephalopathy and to establish a predictive model. Results A total of 517 newborns were included in this study, of which 102 (19.7%) had acute bilirubin encephalopathy. T1 signal enhancement (18.819[8.838-40.069]), Mother's age＞35 year (2.618[1.096-6.2530]), abnormal of WBC (6.503[.226-18.994]), TSB level (1.340[1.242-1.445]) and albumin level (0.812[0.726-0.907]) were independently associated with ABE; All independently associated risk factors were used to form an ABE risk estimation nomogram. The bootstrap validation method was used to internally validate the resulting model. The nomogram demonstrated good accuracy in predicting the risk of ABE, with an unadjusted C index of 0.943 (95% CI, 0.919-0.962) and a bootstrap-corrected C index of 0.900. Conclusion A nomogram was constructed using five risk factors of ABE. This model can help clinicians determine the best treatment for neonatal hyperbilirubinemia.