Background: Decisions regarding the evaluation of children with influenza infection rely on the likelihood of severe disease. The role of early vital signs as predictors of severe influenza infection in children is not well known. Our objectives were to determine the value of vital signs in predicting hospitalization/recurrent emergency department (ED) visits due to influenza infection in children.

Methods: We conducted a prospective study of children aged 6 months to 8 years of age with influenza like illness evaluated at an ED/UC from 2016-2018. All children underwent influenza testing by PCR. We collected heart rate, respiratory rate and temperature, and converted heart rate (HR) and respiratory rate (RR) to z-scores by age. HR z scores were further adjusted for temperature. Our primary outcome was hospitalization/recurrent ED visits within 72 hours. Vital sign predictors with p< 0.2 and other clinical covariates were entered into a multivariable logistic regression model to determine odds ratios (OR) and 95% CI; model performance was assessed using the Brier score and discriminative ability with the C statistic.

Results: Among 1478 children, 411 (27.8%) were positive for influenza, of which 42 (10.2%) were hospitalized or had a recurrent ED visit. In multivariable analyses, adjusting for age, high-risk medical condition and school/daycare attendance, higher adjusted respiratory rate (OR 2.09, 95%CI 1.21-3.61, p = 0.0085) was a significant predictor of influenza hospitalization/recurrent ED visits.

Conclusions: Higher respiratory rate adjusted for age was the most useful vital sign predictor of severity among young children with PCR-confirmed influenza.


Conflict of interest statement
Bruce Innis was employed by the GlaxoSmithKline Biologicals SA group of companies at the time of study conception and planning. Edwin Asturias received research support from the GSK group of companies and receives research support from Pfizer. Suchitra Rao received funding support from the GSK group of companies and Biofire. Molly Lamb received funding support from the GSK group of companies and Biofire. This does not alter our adherence to PLOS ONE policies on sharing data and materials All other authors have no conflicts of interest to disclose.