Data from: Pediatric intensive care unit admissions for COVID-19: insights using state-level data

Introduction Intensive care has played a pivotal role during the COVID-19
pandemic as many patients developed severe pulmonary complications. The
availability of information in pediatric intensive care (PICUs) remains
limited. The purpose of this study is to characterize COVID-19 positive
admissions (CPAs) in the United States and to determine factors that may
impact those admissions.   Materials and Methods This is a
retrospective cohort study using data from the COVID-19 dashboard virtual
pediatric system) containing information regarding respiratory support and
comorbidities for all CPAs between March and April 2020. The state level
data contained 13 different factors from population density, comorbid
conditions and social distancing score. The absolute CPAs count was
converted to frequency using the state’s population. Univariate and
multivariate regression analyses were performed to assess the association
between CPAs frequency and endpoints.   Results A total of 205
CPAs were reported by 167 PICUs across 48 states. The estimated CPAs
frequency was 2.8 per million children. A total of 3,235 tests were
conducted with 6.3% positive tests. Children above 11 years of age
comprised 69.7% of the total cohort and 35.1% had moderated or severe
comorbidities. The median duration of a CPA was 4.9 days [1.25-12.00
days]. Out of the 1,132 total CPA days, 592 [52.2%] were for mechanical
ventilation. The inpatient mortalities were 3 [1.4%]. Multivariate
analyses demonstrated an association between CPAs with greater population
density [beta-coefficient 0.01, p<0.01] and increased percent of
children receiving the influenza vaccination [beta-coefficient 0.17,
p=0.01].   Conclusions Inpatient mortality during PICU CPAs is
relatively low at 1.4%. CPA frequency seems to be impacted by population
density while characteristics of illness severity appear to be associated
with ultraviolet index, temperature, and comorbidities such as Type 1
diabetes. These factors should be included in future studies using
patient-level data.