Chest X-rays help distinguish COVID-19 from other types of viral respiratory infections
Increased infections of COVID-19 and other respiratory viruses in kids are filling up children’s hospitals, pushing them to critical occupancy nationwide. As schools open, the community spread of viral infections has become more common, and the rapid differentiation of pediatric COVID-19 from other viruses is — more than ever — relevant to pediatric clinicians.
“Pediatric cases have increased exponentially and currently represent over 15% of the total cases, and about 26% of the new infections in the U.S. Chest imaging is a powerful tool for determining their status.” said Marius George Linguraru, D.Phil., M.A., M.Sc., principal investigator in the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children’s National Hospital.
In a new peer-reviewed study, researchers from Children’s National found novel and clinically relevant data regarding the specific lung imaging patterns of pediatric COVID-19 on chest radiographs (CXR), their relationship to clinical outcomes and the possible differences from infections caused by other respiratory viruses in children.
“While most studies have focused on clinical manifestations and lung imaging of COVID-19 in adults, this study is the first to define specific patterns of clinical disease and imaging signatures in CXR in different age groups of children infected with COVID-19,” said Gustavo Nino, M.D., director of sleep medicine at Children’s National.
Lung imaging has become critically important for the early identification and treatment of pediatric patients affected by COVID-19 and may play an important role in distinguishing COVID-19 infection from viral bronchiolitis.
“The old perception that COVID-19 only affects older patients is no longer true,” said Dr. Nino. “Pediatric intensive care units and emergency departments are overwhelmed with COVID-19 cases, and now hospitals are admitting more children with COVID-19 than ever.”
As next steps, Nino et al. will develop pediatric-centered technology for early identification, risk stratification, and outcome prediction of COVID-19 in children, similar to what the scientific community has done for adults.