Abstract

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 units (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 Virtual Pediatric System (VPS) dashboard 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 CPA count was converted to frequency using the state's population. Univariate and multivariate regression analyses were performed to assess the association between CPA frequency and admission endpoints. Results A total of 205 CPAs were reported by 167 PICUs across 48 states. The estimated CPA frequency was 2.8 per million children in a one-month period. A total of 3,235 tests were conducted of which 6.3% were positive. 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%) involved 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). Multivariate analyses also demonstrated an association between pediatric type 1 diabetes mellitus with increased CPA duration requiring advanced respiratory support (beta coefficient 5.1, p < 0.01) and intubation (beta coefficient 4.6, p < 0.01). Conclusions Inpatient mortality during PICU CPAs is relatively low at 1.4%. CPA frequency seems to be impacted by population density. Type 1 DM appears to be associated with increased duration of HFNC and intubation. These factors should be included in future studies using patient-level data.

Highlights

  • Intensive care has played a pivotal role during the COVID-19 pandemic as many patients developed severe pulmonary complications

  • The main finding of this study is that inpatient mortality during pediatric intensive care unit (PICU) COVID-19 positive admission (CPA) is relatively low at 1.4%, CPA frequency appears to be impacted by population density, and type 1 diabetes mellitus (DM) appears to be associated with increased duration of high-flow nasal cannula (HFNC) and intubation with slightly over half of CPAs required intubation

  • The population should follow the recommendations from local municipalities. These analyses offer an early look at COVID-19 PICU admissions and offer some descriptive insight into these admissions as well as use state-wide data to investigate associations between CPA characteristics with comorbidities, environmental factors, and socioeconomic factors

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Summary

Introduction

Intensive care has played a pivotal role during the COVID-19 pandemic as many patients developed severe pulmonary complications. Type 1 DM appears to be associated with increased duration of HFNC and intubation These factors should be included in future studies using patient-level data. González-Dambrauskas et al described a preliminary report of the CAKE (Critical Coronavirus and Kids Epidemiologic) study that involves 60 centers in 20 countries from Europe and the Americas This international report provided clinical and laboratory data of 17 patients admitted to the PICU and concluded that COVID-19 in children is a variable disease but with general better outcomes than adults [5]. There is limited information on COVID-19 positive admissions (CPAs) to pediatric intensive care units (PICUs) regarding patient characteristics, respiratory support required, and their impact on outcomes. The purpose of this study is to better characterize CPAs to PICUs in the US and to determine factors that may impact those admissions

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