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Development and internal validation of a nomogram for predicting the severity of community-acquired pneumonia in

Min Wang1,2, Juan Wang1,2, Ping Liu1,2

  • 1Clinical Laboratory, Children's Hospital Affiliated to Shandong University, Jinan, China.

Frontiers in Cellular and Infection Microbiology
|July 6, 2026
PubMed

Insights

Severe community-acquired pneumonia (sCAP) in children is predicted by initial body temperature, D-dimer levels, and mixed infections, particularly Mycoplasma pneumoniae. This finding aids in early diagnosis and treatment of pediatric CAP.

Area of Science:

  • Pediatric infectious diseases
  • Respiratory medicine
  • Clinical epidemiology

Background:

  • Community-acquired pneumonia (CAP) is a significant cause of childhood hospitalization.
  • Identifying risk factors for severe CAP (sCAP) is crucial for timely intervention.
  • Understanding the etiological spectrum and epidemiological characteristics of pediatric CAP is essential.

Purpose of the Study:

  • To investigate the causes and patterns of CAP in hospitalized children.
  • To identify risk factors associated with severe CAP (sCAP).
  • To develop a predictive nomogram model for sCAP in pediatric patients.

Main Methods:

  • Retrospective study of 1486 children with CAP.
  • Analysis of etiological and epidemiological features by age and season.
  • Logistic regression and nomogram construction for sCAP risk factor identification and prediction.

Main Results:

  • Streptococcus pneumoniae and Haemophilus influenzae were common bacteria; rhinovirus and adenovirus were common viruses.
  • Mycoplasma pneumoniae detection rate was 64.06%, with a 50.47% mixed infection rate (predominantly bacteria-virus).
  • Independent risk factors for sCAP included initial body temperature, D-dimer, mixed infection, and Mycoplasma pneumoniae infection.

Conclusions:

  • Initial body temperature, D-dimer, mixed infection, and Mycoplasma pneumoniae are reliable predictors of pediatric sCAP.
  • The developed early prediction model is valuable for clinical diagnosis, treatment, and prognosis of pediatric CAP.
Abstract

Keywords:
community acquired pneumoniaearly prediction modeletiologyinflammatory markernomogram

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