A nomogram for predicting severe adenovirus pneumonia in children

Abstract

Adenoviral pneumonia in children was an epidemic that greatly impacted children's health in China in 2019. Currently, no simple or systematic scale has been introduced for the early identification and diagnosis of adenoviral pneumonia. The early recognition scale of pediatric severe adenovirus pneumonia was established based on an analysis of the children's community-acquired pneumonia clinical cohort. This study analyzed the clinical data of 132 children with adenoviral pneumonia who were admitted to the Children's Hospital of Nanjing Medical University. The clinical parameters and imaging features were analyzed using univariate and multivariate logistic regression analyses. A nomogram was constructed to predict the risk of developing severe adenovirus pneumonia in children. There were statistically significant differences in age, respiratory rate, fever duration before admission, percentage of neutrophils and lymphocytes, CRP, ALT, and LDH between the two groups. Logistic regression analysis was conducted using the R language, and respiratory rate, percentage of neutrophils, percentage of lymphocytes, and LDH were used as scale indicators. Using the ROC curve, the sensitivity and specificity of the scale were 93.3% and 92.1%. This scale has good sensitivity and specificity through internal verification, which proves that screening for early recognition of severe adenovirus pneumonia can be realized by scales. This predictive scale helps determine whether a child will develop severe adenovirus pneumonia early in the disease course.