Pre-existing medical conditions as well as "medical complexity" increase risk for severe COVID-19 illness and hospitalization in children.
Although severe cases of COVID-19are uncommon among children, those with pre-existing medical conditions, including type 1 diabetes and cardiac congenital anomalies, or meeting criteria for "medical complexity", are at increased risk for severe illness and hospitalization, according to a new study by investigators from the US Centers for Disease Control and Prevention (CDC).
Lyudmyla Kompaniyets, PhD, COVID-19 Response, CDC, Atlanta, Georgia, and colleagues found that previous studies on risk factors among children were limited by small sample sizes, and so undertook the current study with a large, all-payer database covering both emergency and inpatient departments of more than 900 geographically dispersed US hospitals.
"By using a large electronic administrative health care data set, we sought to describe common underlying medical conditions and medical complexity as well as their associations with the risk of hospitalization or severe illness among children seeking care in the hospital," Kompaniyets and colleagues explained.
Their patient sample comprised over 43,000 children in emergency medicine department or inpatient encounters with primary or secondary discharge diagnosis of COVID-19 in the period of March 1, 2020 through January 31, 2021. The median age was 12 years; 52.8% were female; 33% were Hispanic or Latino; 24.1% were non-Hispanic Black individuals. Hospitalization was required for 9.9% (4,302), of whom 29.6% had an intensive care unit (ICU) admission, 6.4% received invasive mechanical ventilation (IMV), and 0.9% died.
Kompaniyets and colleagues found that children with the highest risk of severe COVID-19 illness, marked by ICU admission, IMV, or death, were those with type 1 diabetes (Adjusted Risk Ratio [aRR] 2.38; 95% Confidence Interval [CI], 2.06-2.76); cardiac and circulatory congenital anomalies (aRR 1.72; 95% CI 1.48-199); and epilepsy and/or convulsions (aRR, 1.71; 95% CI 1.41-2.08).
The investigators also assessed the relation of severe COVID-19 illness to the presence of medical complexity, defined using the validated pediatric medical complexity algorithm (PMCA) for presence or absence of complex and noncomplex chronic disease. Medical complexity was associated with risk of hospitalization and severe illness when hospitalized. Compared with children without chronic illness, children with non-complex chronic disease and complex chronic disease 2.91 times (95% CI, 2.63-3.23) and 7.86 times (95% CI, 6.91-8.95 more likely to be hospitalized, respectively.
"Our finding that levels of medical complexity represent a risk factor for severe COVID-19 illness identifies a previously unidentified higher risk population, not clearly described in prior literature," Kompaniyets and colleagues claim.
In accompanying, invited commentary, Jennifer Schuster, MD, MSc, Division of Pediatric Infectious Diseases, Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO, and Annabelle de St Maurice, MD, MPH, Division of Pediatric Infectious Diseases, Department of Pediatrics, University of California, Los Angeles, Los Angeles, CA, welcomed the addition to previously limited data on pediatric risk factors for COVID-19 hospitalization.
They agree that a large database can be leveraged to provide information about uncommon diseases, including severe pediatric COVID-19, but also point out some limitations.They note, for example, that attributing associations can be difficult.In this study, they point out that most children were adolescents and that risk factors differed when the data were age stratified, suggesting that recommendations for COVID-19 management and prevention should also vary by age.
"This study identifies factors associated with severe pediatric COVID-19 and highlights the need for multicenter collaborations and dedicated funding to study pediatric COVID-19," Schuster and de St Maurice indicate."To provide the best care for children, we need pediatric-specific data."