Development of a nomogram for severe influenza in previously healthy children: a retrospective cohort study. Issue 2 (February 2023)

• Record Type: Journal Article
• Authors: Huang, Wenyun; Niu, Wensi; Chen, Hongmei; Jiang, Wujun; Fu, Yanbing; Li, Xiuxiu; Li, Minglei; Hua, Jun; Hu, Chunxia
• Is Part Of: Journal of international medical research. Volume 51:Issue 2(2023)
• Publication Date: 2023-02
• Subjects: Severe influenza -- nomogram -- risk factor -- child -- predictor model -- diagnose; Medicine -- Periodicals; Pharmacology -- Periodicals; 610.5
• DOI: 10.1177/03000605231153768
• Languages: English
• ISSNs: 0300-0605

Abstract

Objective: We aimed to develop a nomogram to predict the risk of severe influenza in previously healthy children. Methods: In this retrospective cohort study, we reviewed the clinical data of 1135 previously healthy children infected with influenza who were hospitalized in the Children's Hospital of Soochow University between 1 January 2017 and 30 June 2021. Children were randomly assigned in a 7:3 ratio to a training or validation cohort. In the training cohort, univariate and multivariate logistic regression analyses were used to identify risk factors, and a nomogram was established. The validation cohort was used to evaluate the predictive ability of the model. Result: Wheezing rales, neutrophils, procalcitonin > 0.25 ng/mL, Mycoplasma pneumoniae infection, fever, and albumin were selected as predictors. The areas under the curve were 0.725 (95% CI: 0.686–0.765) and 0.721 (95% CI: 0.659–0.784) for the training and validation cohorts, respectively. The calibration curve showed that the nomogram was well calibrated. Conclusion: The nomogram may predict the risk of severe influenza in previously healthy children.