Development and Validation of a Temporal Progression-based Risk Assessment Tool for Respiratory Syncytial Virus Infection in Infants.

Authors

Shota Kawamoto, Yoshihiko Morikawa, Naohisa Yahagi

Published in

The Pediatric infectious disease journal. Jul 03, 2025. Epub Jul 03, 2025.

Abstract

Respiratory syncytial virus (RSV) causes an estimated 3.2 million infant hospitalizations worldwide annually, with 99% of RSV-associated deaths occurring in developing countries. Although laboratory confirmation remains the standard for diagnosis, resource limitations and the need for prompt infection control measures highlight the importance of reliable symptom-based assessment tools.
In this retrospective cohort study (2009-2015), we analyzed symptom characteristics and progression patterns in infants 12 months of age or younger who underwent RSV rapid antigen testing at a tertiary care center, regardless of subsequent hospitalization status. Through structured electronic questionnaires and chronologically divided development and validation cohorts, a predictive model incorporating symptom features and their sequence patterns was developed using multivariable logistic regression analysis. The model was then transformed into a weighted risk score system, for clinical application.
Among 1650 eligible infants, RSV was detected in 328 patients (19.9%). The model incorporated productive cough, biphasic wheezing and cough-wheezing progression sequences as key predictors. The model demonstrated moderate discriminative ability in the development cohort [area under the receiver operating characteristic curve (AUROC), 0.746; 95% confidence interval (CI): 0.715-0.777] and maintained its performance in the validation cohort (AUROC, 0.712; 95% CI: 0.626-0.798). Risk stratification effectively identified RSV-positive cases, with RSV probability rates of 5.6%, 7.2%, 22.6% and 41.2% across baseline, moderate, elevated and high-risk groups, respectively.
This symptom-based index provides reliable risk stratification for RSV infection through systematic assessment of respiratory symptoms, offering a potential screening method for various clinical settings.

PMID:
40674645
Bibliographic data and abstract were imported from PubMed on 18 Jul 2025.

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