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Risk factors for disease severity among children with Covid-19: a clinical prediction model

David Chun-Ern Ng1, Chuin-Hen Liew2, Kah Kee Tan3

  • 1Hospital Tuanku Ja'afar, Negeri Sembilan, Ministry of Health, Jalan Rasah, 70300, Seremban, Malaysia. davidngce@gmail.com.

BMC Infectious Diseases
|June 12, 2023
PubMed

Insights

This study identified key risk factors for moderate to severe COVID-19 in children. A predictive nomogram was developed to aid in early identification of severe disease in pediatric patients.

Area of Science:

  • Pediatric infectious diseases
  • Epidemiology
  • Clinical prediction modeling

Background:

  • Children represent a significant portion of COVID-19 hospitalizations.
  • Limited data exists on predictors of severe COVID-19 in pediatric populations.
  • Understanding these predictors is crucial for effective management.

Purpose of the Study:

  • To identify risk factors associated with moderate to severe COVID-19 in children.
  • To develop a predictive nomogram for moderate/severe COVID-19 in pediatric patients.
  • To aid in early clinical decision-making for hospitalized children.

Main Methods:

  • Retrospective cohort study of children (≤12 years) hospitalized with COVID-19 in Malaysia (2021).
  • Multivariate logistic regression analysis to identify independent risk factors for moderate/severe disease.
  • Development and validation of a nomogram for predicting moderate/severe COVID-19, assessing AUC, sensitivity, specificity, and accuracy.

Main Results:

  • 1,234 pediatric patients with COVID-19 (211 moderate/severe) were analyzed.
  • Nine independent risk factors identified: comorbidities, shortness of breath, vomiting, diarrhea, rash, seizures, temperature, chest recessions, and abnormal breath sounds.
  • The nomogram demonstrated good predictive performance with an AUC of 0.86.

Conclusions:

  • A nomogram incorporating clinical parameters can effectively predict moderate/severe COVID-19 in children.
  • This tool can assist clinicians in making individualized treatment decisions.
  • Further validation in diverse populations is warranted.
Abstract

Keywords:
COVID-19NomogramPediatricPredictor severity

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