Related Experiment Video
Updated: Jul 19, 2026
Rapid Molecular Detection and Differentiation of Influenza Viruses A and B
Published on: January 30, 2017
Development of a nomogram for severe influenza in previously healthy children: a retrospective cohort study
Wenyun Huang1,2, Wensi Niu2, Hongmei Chen1
1Department of Emergency Medicine, Children's Hospital of Soochow University, Suzhou, China.
Insights
This study developed a nomogram to predict severe influenza risk in children. Key predictors include wheezing, neutrophils, and fever, aiding early identification of high-risk pediatric patients.
Area of Science:
- Pediatric infectious diseases
- Epidemiology
- Biostatistics
Background:
- Developing accurate predictive tools for severe influenza in children is crucial for timely intervention.
- Previously healthy children remain susceptible to severe influenza complications.
Approach:
- A retrospective cohort study analyzed 1135 hospitalized children with influenza.
- A nomogram was developed using logistic regression in a training cohort and validated in a separate cohort.
Key Points:
- Predictors for severe influenza included wheezing rales, elevated neutrophils, procalcitonin > 0.25 ng/mL, Mycoplasma pneumoniae infection, fever, and albumin.
- The nomogram demonstrated good predictive ability with AUCs of 0.725 (training) and 0.721 (validation).
- The model showed good calibration, indicating reliable risk predictions.
Conclusions:
- The developed nomogram shows potential for predicting severe influenza risk in previously healthy children.
- This tool can assist clinicians in identifying children at higher risk for severe disease progression.
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.
Related Concept Videos
01:23Dosage Regimen Designs: Nomograms and Tabulations
01:27Influenza
01:29Respiratory Syncytial Virus Disease