For Children Hospitalized with COVID-19, Factors Identified for Progression to Severe Illness

The JAMA Network Open research article includes several key data points:

• Data was collected from the National COVID Cohort Collaborative, with 1,068,410 children tested for COVID-19 and 167,262 (15.6%) testing positive for the virus
• Among the 10,245 children who were hospitalized, 13.9% met criteria for severe illness (7.8% were placed on mechanical ventilation, 8.5% received vasoactive-inotropic support, 0.4% were placed on extracorporeal membrane oxygenation, and 1.3% died)
• Male sex (odds ratio 1.37); Black race (odds ratio 1.25); obesity (odds ratio 1.19); and several pediatric complex chronic conditions including cardiovascular, oncologic, and respiratory conditions were associated with higher severity illness in hospitalized children
• Male sex (odds ratio 1.59), Black race (odds ratio 1.44), age under 12 (odds ratio 1.81), obesity (odds ratio 1.76), and not having a pediatric complex condition (odds ratio 0.72) were associated with increased risk for MIS-C
• Compared with children who were hospitalized without severe illness, hospitalized children with severe illness had more abnormal values for several vital signs at the beginning of their hospitalization, including systolic and diastolic blood pressure (lower), oxygen saturation as measured by pulse oximetry (lower), heart rate (higher), and respiratory rate (higher)
• Compared with children who were hospitalized without severe illness, hospitalized children with severe illness had more abnormal values for many laboratory test results at the beginning of their hospitalization. In particular, children with severe illness had test results that indicated organ dysfunction such as brain-type natriuretic peptide (higher), creatinine (higher), and platelets (lower), and inflammation such as ferritin (higher), C-reactive protein (higher), and procalcitonin (higher).

“In this cohort study of U.S. children with SARS-CoV-2, there were observed differences in demographic characteristics, preexisting comorbidities, and initial vital sign and laboratory values between severity subgroups. Taken together, these results suggest that early identification of children likely to progress to severe disease could be achieved using readily available data elements from the day of admission,” the JAMA Network Open research article’s co-authors wrote.

Interpreting the data

The findings of the research should help in the clinical care of children hospitalized with COVID-19, the lead author of the JAMA Network Open research article told HealthLeaders.

“We hope that our study will assist clinicians in identifying children at higher risk of developing severe disease once hospitalized with SARS-CoV-2. Specifically, we found that children who were male, Black/African American, obese, and who have a history of prior chronic medical conditions, specifically prior cardiovascular, oncologic, respiratory, and technology dependent conditions, are at higher risk for progressing to severe disease once hospitalized,” said Blake Martin, MD, pediatric critical care attending physician at Children’s Hospital Colorado and a member of the Society of Critical Care Medicine.

It was surprising that not having preexisting comorbidities was associated with increased odds of a MIS-C diagnosis, he said.

“It would have been reasonable to assume that children who are more medically fragile might be more susceptible to MIS-C, but it ended up being the opposite: that children without significant prior complex medical conditions were at increased risk for receiving an MIS-C diagnosis among children presenting to care with a positive SARS-CoV-2 test. Much of the discussion around children and SARS-CoV-2 has been that otherwise healthy children do relatively well and are unlikely to have a poor outcome. While this is definitely true overall, I think it is worth noting that ‘otherwise healthy kids’ are still at risk for MIS-C,” Martin said.

Future research should focus on developing clinical decision support tools to help clinicians identify hospitalized children with COVID-19 who could progress to severe illness, he said.

“We now know that there are many pieces of data in the electronic health record that are associated with an increased odds of severe disease once a child is hospitalized with SARS-CoV-2. The data elements identified in this study (demographics, comorbidities, and day of admission vital sign and lab values) are all readily available and could be used to design a clinical decision support tool or computer algorithm that automatically identifies high-risk children at the time of their hospital admission. Many research teams are now working on the creation of these predictive models, which we hope will allow clinicians across the country to identify high-risk children that might be candidates for more aggressive, earlier treatment and closer monitoring.”