Project Details

Predictors of life-threatening illness in infants with Respiratory Syncytial Virus infection

Fausto Ferolla, MD

Summary

BACKGROUND: Acute lower respiratory infection (ARI) due to Respiratory Syncytial Virus (RSV) is the most frequent cause of hospitalization in infants and no specific treatment is available; ~99% of deaths occur in developing countries. Despite that selected groups of infants have increased risk for life-threatening disease (LTD) and mortality, the majority of children hospitalized with RSV ARI are previously healthy with no known risk factors. GAP: The mechanism by which RSV produces a wide range of disease severity in previously healthy infants is likely multi-factorial but is largely unknown. Identifying predictors of RSV LTD could help to decide timely hospitalization when needed and to define priorities for individualized future prevention and treatment strategies. HYPOTHESIS: Socioeconomic, biological, immunological variables and their interplay are associated with LTD in previously healthy infants hospitalized with RSV. The absence or low titers in serum of neutralizing antibodies, different cytokine profiles and/or higher viral titers in respiratory samples could predict LTD. METHODS: Prospective cohort study. Previously healthy full-term infants under 12 months old, hospitalized at Ricardo Gutierrez Children’s Hospital with an episode of RSV ARI, will be invited to participate during the 2017 and 2018 RSV seasons. Nasal and blood samples will be obtained and a questionnaire will be completed for epidemiological and clinical data; ambulatory patients with RSV infection will serve as controls. RESULTS: Pending. IMPACT: A better understanding of the factors affecting the course of RSV infection and their interplay, and the determination of them as predictors of LTD, should allow implementation of new guidelines for timely identification of patients who need hospitalization, and definition of priorities for development of preventive strategies and effective therapies reaching the populations at greatest risk.