Respiratory Syncytial Virus-Load Kinetics and Clinical Course of Acute Bronchiolitis in Hospitalized Infants: Interim Results and Review of the Literature.
Giulia PiccirilliAlessandro RoccaEva Caterina BorgattiLiliana GabrielliDaniele ZamaLuca PierantoniMarta LeoneCamilla TotaroMatteo PavoniLazzarotto TizianaMarcello LanariPublished in: Pathogens (Basel, Switzerland) (2023)
Respiratory Syncytial Virus (RSV) bronchiolitis is the leading cause of hospitalization in infants. The role of RSV load in disease severity is still debated. We present the interim results of a prospective monocentric study enrolling previously healthy infants hospitalized for RSV bronchiolitis, collecting nasopharyngeal aspirates every 48 h from admission to discharge, and evaluating RSV load dynamics in relation to clinical outcome measures of bronchiolitis severity, including: need, type and duration of oxygen therapy, length of hospitalization, and the bronchiolitis clinical score calculated at admission. The results showed that the highest viral replication occurs within the first 48 hours after admission, with a significant decrease at subsequent time points ( p < 0.0001). Moreover, higher RSV-RNA values were associated with the need for oxygen therapy ( p = 0.03), particularly high-flow nasal cannula type ( p = 0.04), and longer duration of respiratory support ( p = 0.04). Finally, higher RSV load values were correlated with lower white blood cells, especially lymphocyte counts and C-reactive protein levels ( p = 0.03, p = 0.04, and p = 0.01, respectively), as well as with patients of a younger age ( p = 0.02). These data suggest that RSV may actively contribute to the clinical severity of bronchiolitis, together with other potential non-viral factors.
Keyphrases
- respiratory syncytial virus
- emergency department
- sars cov
- end stage renal disease
- induced apoptosis
- hepatitis b virus
- liver failure
- chronic kidney disease
- machine learning
- prognostic factors
- extracorporeal membrane oxygenation
- peritoneal dialysis
- stem cells
- newly diagnosed
- artificial intelligence
- intensive care unit
- cell cycle arrest
- big data
- drug induced
- mesenchymal stem cells
- patient reported
- climate change