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Updated: Feb 14, 2026

An In vitro Model to Study Immune Responses of Human Peripheral Blood Mononuclear Cells to Human Respiratory Syncytial Virus Infection
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A Clinical Prediction Model for Bacterial Coinfection in Children with Respiratory Syncytial Virus Infection: A

Di Lian1, Jianxing Wei1, Dong Wang1

  • 1Fujian Children's Hospital (Fujian Branch of Shanghai Children's Medical Center), College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou 350014, China.

Diagnostics (Basel, Switzerland)
|February 13, 2026
PubMed

Insights

This study developed a model using neutrophil-to-lymphocyte ratio, C-reactive protein, and serum amyloid A to accurately identify bacterial coinfection in children with respiratory syncytial virus (RSV) infections, aiding antibiotic stewardship.

Area of Science:

  • Pediatric Infectious Diseases
  • Clinical Microbiology
  • Biomarker Discovery

Background:

  • Respiratory syncytial virus (RSV) is a major cause of pediatric lower respiratory tract infections.
  • Bacterial coinfection in RSV cases complicates diagnosis and contributes to antibiotic overuse.
  • Accurate identification of bacterial coinfection is crucial for appropriate treatment.

Purpose of the Study:

  • To develop and validate a clinical prediction model for early identification of bacterial coinfection in children with RSV.
  • To utilize common laboratory biomarkers for improved diagnostic accuracy.
  • To support targeted antibiotic stewardship in pediatric RSV cases.

Main Methods:

  • Retrospective cohort study of 518 hospitalized children with RSV infection.
  • Development and validation of a prediction model using LASSO and multivariable logistic regression.
  • Biomarkers including neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), and serum amyloid A (SAA) were analyzed.

Main Results:

  • The prediction model integrated NLR, CRP, and SAA.
  • The model demonstrated strong discrimination with an AUC of 0.832 in the training set and 0.811 in the test set.
  • The model showed good calibration and clinical utility, with a developed nomogram for practical application.

Conclusions:

  • A reliable model integrating NLR, CRP, and SAA was established for early bacterial coinfection detection in RSV-infected children.
  • This tool can guide targeted antibiotic stewardship, potentially improving clinical outcomes.
  • The findings support the use of this model in clinical practice for better management of pediatric RSV cases.

Keywords:
C-reactive proteinbacterial coinfectionneutrophil-to-lymphocyte rationomogramprediction modelrespiratory syncytial virusserum amyloid A

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