Non-Invasive Ventilation Failure in Pediatric ICU: A Machine Learning Driven Prediction.

: Non-invasive ventilation (NIV) has emerged as a possible first-step treatment to avoid invasive intubation in pediatric intensive care units (PICUs) due to its advantages in reducing intubation-associated risks. However, the timely identification of NIV failure is crucial to prevent adverse outcomes. This study aims to identify predictors of first-attempt NIV failure in PICU patients by testing various machine learning techniques and comparing their predictive abilities.

Severe bronchiolitis before and after the COVID-19 pandemic: a retrospective database analysis by the Italian Network of PICU study group (TIPNet).

Background: The first post-COVID-19 pandemic year demonstrated an unusual bronchiolitis epidemic in both hemispheres and has been attributed to the removal of barriers implemented during SARS-CoV-2 infection. Several countries reported an increase in respiratory syncytial virus (RSV) bronchiolitis, with more hospitalizations and a greater need for respiratory support. We aimed to evaluate the consequences of the COVID-19 pandemic on the epidemiology and management of severe bronchiolitis in pediatric intensive care units (PICUs) in Italy.