Medical Resident University of Toronto Temerty Faculty of Medicine Toronto, Ontario, Canada
Background: Respiratory syncytial virus (RSV) is a common acute respiratory infection (ARI) in infants and young children resulting in numerous hospital admissions with significant associated morbidity. After the relaxation of COVID-19 pandemic restrictions, children’s hospitals worldwide experienced unprecedented volumes and severity in presentation of children admitted with ARIs. It is unknown whether the increase in volumes was associated with changes in the typical demographic, severity and outcomes of patients with RSV. These potential changes may have downstream implications for how clinicians approach the prevention and treatment of RSV ARI. Objective: To identify risk factors associated with severe disease in children hospitalized with RSV associated ARI. Design/Methods: The study was approved by the research ethics board at both institutions. Observational cohort of children and adolescents aged 0-18 years admitted to two large Canadian children’s hospitals between July 1, 2022–June 30, 2023, who had microbiological evidence of RSV infection. Detailed demographic and clinical information are collected, including diagnoses, diagnostic tests, interventions, and respiratory settings. Clinical outcomes and complications are collected, including length of hospital stay, disposition, pediatric intensive care unit admission, need for invasive mechanical ventilation or high-flow nasal cannula, and death; the latter three variables which will serve as a composite variable for severe disease.
Categorical variables are to be described using frequencies and proportions, while continuous variables with measures of central tendency and dispersion. Patient characteristics will be compared by disease severity with between-group differences assessed using chi-square tests and Fisher’s exact tests for categorical variables, and t-tests or Wilcoxon rank-sum tests for continuous variables as appropriate. Risk factors for severe disease will be identified using robust Poisson regression and reported with risk ratios. Data collection is ongoing and set to be completed by December 2023.
