Incidence and Risk Factors for Severe Outcomes in Pediatric Patients With COVID-19

Abstract

Objectives: Throughout the pandemic, children with COVID-19 have experienced hospitalization, ICU admission, invasive respiratory support, and death. Using a multisite, national dataset, we investigate risk factors associated with these outcomes in children with COVID-19.

Methods: Our data source (Optum deidentified COVID-19 Electronic Health Record Dataset) included children aged 0 to 18 years testing positive for COVID-19 between January 1, 2020, and January 20, 2022. Using ordinal logistic regression, we identified factors associated with an ordinal outcome scale: nonhospitalization, hospitalization, or a severe composite outcome (ICU, intensive respiratory support, death). To contrast hospitalization for COVID-19 and incidental positivity on hospitalization, we secondarily identified patient factors associated with hospitalizations with a primary diagnosis of COVID-19.

Results: In 165 437 children with COVID-19, 3087 (1.8%) were hospitalized without complication, 2954 (1.8%) experienced ICU admission and/or intensive respiratory support, and 31 (0.02%) died. We grouped patients by age: 0 to 4 years old (35 088), and 5 to 11 years old (75 574), 12 to 18 years old (54 775). Factors positively associated with worse outcomes were preexisting comorbidities and residency in the Southern United States. In 0- to 4-year-old children, there was a nonlinear association between age and worse outcomes, with worse outcomes in 0- to 2-year-old children. In 5- to 18-year-old patients, vaccination was protective. Findings were similar in our secondary analysis of hospitalizations with a primary diagnosis of COVID-19, though region effects were no longer observed.

Conclusions: Among children with COVID-19, preexisting comorbidities and residency in the Southern United States were positively associated with worse outcomes, whereas vaccination was negatively associated. Our study population was highly insured; future studies should evaluate underinsured populations to confirm generalizability.