Publications by authors named "Kevin M Havlin"
Article Synopsis
- A study investigated the impact of pre-existing immunocompromising conditions (ICCs) on pediatric patients with acute COVID-19 admitted to intensive care across 55 hospitals in the U.S.!
- Out of 1,274 patients, 105 had ICCs, which were linked to higher in-hospital mortality (11.4% vs. 4.6%) and longer hospital stays, although initial disease severity was similar between those with and without ICCs.!
- Despite the challenges, most patients with ICCs survived and left the hospital without new severe health issues, highlighting a positive aspect of the outcomes for these vulnerable patients.!
Objectives: Extracorporeal membrane oxygenation (ECMO) has been used successfully to support adults with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related cardiac or respiratory failure refractory to conventional therapies. Comprehensive reports of children and adolescents with SARS-CoV-2-related ECMO support for conditions, including multisystem inflammatory syndrome in children (MIS-C) and acute COVID-19, are needed.
Design: Case series of patients from the Overcoming COVID-19 public health surveillance registry.
Importance: In 2020 during the COVID-19 pandemic, neurologic involvement was common in children and adolescents hospitalized in the United States for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related complications.
Objective: To provide an update on the spectrum of SARS-CoV-2-related neurologic involvement among children and adolescents in 2021.
Design, Setting, And Participants: Case series investigation of patients reported to public health surveillance hospitalized with SARS-CoV-2-related illness between December 15, 2020, and December 31, 2021, in 55 US hospitals in 31 states with follow-up at hospital discharge.
Background: Multisystem inflammatory syndrome in children (MIS-C) consensus criteria were designed for maximal sensitivity and therefore capture patients with acute COVID-19 pneumonia.
Methods: We performed unsupervised clustering on data from 1,526 patients (684 labeled MIS-C by clinicians) <21 years old hospitalized with COVID-19-related illness admitted between 15 March 2020 and 31 December 2020. We compared prevalence of assigned MIS-C labels and clinical features among clusters, followed by recursive feature elimination to identify characteristics of potentially misclassified MIS-C-labeled patients.