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Background: Infectious mononucleosis (IM), an acute self-limiting disease predominantly caused by Epstein-Barr virus (EBV), is common in children. Liver injury is one of its most frequent complications. Early identification and prediction of the risk of liver injury in children with IM are crucial for timely intervention and improved prognosis. This study aimed to develop and validate a nomogram model for predicting the risk of concurrent liver injury in pediatric patients with IM.
Methods: This retrospective study enrolled 202 pediatric patients with IM who were diagnosed and treated at our hospital between January 2023 and December 2024. Based on serum alanine aminotransferase (ALT) levels, patients were divided into a liver injury group (ALT > 50 U/L, n = 116) and a control group (ALT < 50 U/L, n = 86). General clinical data and laboratory parameters were collected and compared between the two groups. Multivar-iable logistic regression analysis was employed to identify independent risk factors for concurrent liver injury in pediatric patients with IM. Subsequently, a nomogram prediction model was constructed and verified based on these factors.
Results: Among the 202 pediatric patients with IM, the incidence of liver injury was 57.42%. The incidence of he-patosplenomegaly was significantly higher in the liver injury group compared to the control group (p < 0.05). Statistically significant differences were observed between the two groups regarding neutrophil percentage (NEU), lymphocyte percentage (LYM), platelet count (PLT), platelet distribution width (PDW), uric acid (UA), beta2-mi-croglobulin (β2-MG), atypical lymphocytes, and interleukin-6 (IL-6) (p < 0.05). Multivariable logistic regression analysis revealed that PDW, UA, β2-MG, atypical lymphocytes, and IL-6 were independent risk factors for concurrent liver injury in pediatric patients with IM. The nomogram model constructed based on these independent risk factors exhibited great discrimination and calibration, with a concordance index (C-index) of 0.942 (95% CI: 0.877 - 1.007) and an area under the receiver operating characteristic curve (AUC) of 0.960. Decision curve analysis (DCA) showed the model provided substantial net clinical benefit across threshold probabilities ranging from 4% to 100%.
Conclusions: The nomogram model constructed in this study can effectively predict the risk of concurrent liver injury in pediatric patients with IM.
DOI: 10.7754/Clin.Lab.2025.250571
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