aEEG improves the predictive ability of acute bilirubin encephalopathy
This study performed in-depth analysis of the graphic indicators of aEEG, and developed a clinical prediction model of Acute bilirubin encephalopathy (ABE) based on aEEG, which significantly improved the predictive ability of ABE compared to the model based on only the conventional clinical information. The authors found that the graphic indicators of SWC and amplitude may be the most sensitive variables and developed a clinical prediction model with good predictive ability for ABE based on aEEG, including number of SWC within 3 hours, widest bandwidth, duration of 1 SWC, and the type of SWC. It has good predictive ability and may improve the diagnostic accuracy of ABE. which is of great significance for the early detection and diagnosis of ABE.
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