Physiologic profile associated with severe multisystem inflammatory syndrome in children: a retrospective study.

OBJECTIVE: The purpose of this study was to describe the clinical presentation and physiologic profile of individuals with varying degrees of severity of multisystem inflammatory syndrome in children (MIS-C). METHODS: We performed a retrospective study of children diagnosed with MIS-C admitted to a single quaternary children's hospital from May 2020 to April 2021. We created an MIS-C severity score using the following parameters: hospital admission status (e.g., floor vs intensive care unit), need for inotropic or vasoactive medications, and need for mechanical ventilation. Univariate and multivariate analyses were performed to associate risk factors corresponding to the MIS-C severity score. RESULTS: The study included 152 children who were followed for 14 days post hospital admission. A stepwise forward selection process identified seven physiologic variables associated with "severe" MIS-C according to a logistic regression. Specifically, a combination of elevated creatinine (p = 0.013), international normalized ratio (p = 0.002), brain natriuretic peptide (p = 0.001), white blood cell count (p = 0.009), ferritin (p = 0.041), respiratory rate (p = 0.047), and decreased albumin (p = 0.047) led to an excellent discrimination between mild versus severe MIS-C (AUC = 0.915). CONCLUSION: This study derived a physiologic profile associated with the stratification of MIS-C severity. IMPACT: Based on a cohort of 152 individuals diagnosed with MIS-C, this study derived a nomenclature that stratifies the severity of MIS-C. Investigated demographic, presentational vital signs, and blood analytes associated with severity of illness. Identification of a multivariate physiologic profile that strongly associates with MIS-C severity. This model allows the care team to recognize patients likely to require a higher level of intensive care.

Social and Demographic Disparities in the Severity of Multisystem Inflammatory Syndrome in Children.

Social constructs are known risk factors for multisystem inflammatory syndrome in children. A review of 206 patients demonstrated that children who were non-Hispanic Black, over the age of 12 years or living in a disadvantaged neighborhood associated with severe multisystem inflammatory syndrome in children (intensive care unit admission, intubation and/or vasopressor use).

Serum biomarkers for prediction of mortality in patients with COVID-19.

BACKGROUND: There is limited information regarding the role of biomarker levels at predicting mortality in patients with the coronavirus disease (COVID-19) pandemic. The purpose of this study is to determine the differences in serum biomarker levels in adults with COVID-19 who survived hospitalization from those who did not. METHODS: A comprehensive search was completed on PubMed, EMBASE and Cochrane libraries to identify studies of interest. Endpoints of interest were blood counts, hepatic function test, acute phase reactants, cytokines and cardiac biomarkers. RESULTS: A total of 10 studies with 1584 patients were included in the pooled analyses. Biomarkers that were noted to be significantly higher in those who died from coronavirus disease included: white blood cell count, neutrophil count, C-reactive protein, high sensitivity C-reactive protein, procalcitonin, ferritin, D-dimer, interleukin-6, lactate dehydrogenase, creatine kinase, prothrombin time, aspartate aminotransferase, alanine aminotransferase, total bilirubin and creatinine. Lymphocyte count, platelet count and albumin were significantly lower in patients who died. CONCLUSION: This pooled analysis of 10 studies including 1584 patients identified significant differences in biomarkers on admission in patients who survived from those who did not. Further research is needed to develop risk stratification models to help with judicious use of limited health-care resources.

Disparities in case frequency and mortality of coronavirus disease 2019 (COVID-19) among various states in the United States.

OBJECTIVE: To utilize publicly reported, state-level data to identify factors associated with the frequency of cases, tests, and mortality in the USA. MATERIALS AND METHODS: Retrospective study using publicly reported data collected included the number of COVID-19 cases, tests and mortality from March 14th through April 30th. Publicly available state-level data was collected which included: demographics comorbidities, state characteristics and environmental factors. Univariate and multivariate regression analyses were performed to identify the significantly associated factors with percent mortality, case and testing frequency. All analyses were state-level analyses and not patient-level analyses. RESULTS: A total of 1,090,500 COVID-19 cases were reported during the study period. The calculated case and testing frequency were 3332 and 19,193 per 1,000,000 patients. There were 63,642 deaths during this period which resulted in a mortality of 5.8%. Factors including to but not limited to population density (beta coefficient 7.5, p < .01), transportation volume (beta coefficient 0.1, p < .01), tourism index (beta coefficient -0.1, p = .02) and older age (beta coefficient 0.2, p = .01) are associated with case frequency and percent mortality. CONCLUSIONS: There were wide variations in testing and case frequencies of COVID-19 among different states in the US. States with higher population density had a higher case and testing rate. States with larger population of elderly and higher tourism had a higher mortality. Key messages There were wide variations in testing and case frequencies of COVID-19 among different states in the USA. States with higher population density had a higher case and testing rate. States with larger population of elderly and higher tourism had a higher mortality.

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 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.

Factors associated with deep venous thrombosis in patients infected with coronavirus disease 2019: a meta-analysis.

Coronavirus disease 2019 (COVID-19) has affected more than 6 million patients worldwide. Deep venous thrombosis (DVT) has been increasingly recognized complication in these patients and is associated with increased morbidity and mortality. However, the factors associated with development of DVT in patients with COVID-19 have not been elucidated due to the novelty of the virus. We performed a meta-analysis of published studies comparing laboratory results in COVID-19 patients with and without DVT with the aim of identifying risk factors. We searched major databases for studies evaluating DVT in COVID-positive patients and performed a meta-analysis of baseline laboratory markers associated with development of DVT. A total of six studies with 678 patients were included in the pooled analyses. Of the 678 patients, 205 of patients had a DVT. Patients diagnosed with DVT were more likely to be older [mean difference 4.59 years, 95% confidence interval (CI) 1.25-7.92], and needing admission to ICU (relative risk 1.96, 95% CI 1.09-3.51). Patients with DVT had significantly higher white cell count (mean difference 1.36 × 109/l, 95% CI 0.33-2.40) and d-dimer levels (mean difference 3229.8, 95% CI 1501.5-4958.1). Lymphocyte count was lower in patients with DVT (mean difference -0.19 × 109/l, 95% CI -0.37 to -0.02). Patients with COVID-19 who develop DVT are more likely to be older and have leukocytosis with lymphopenia. Moreover, d-dimer is statistically higher and patients that are admitted to the ICU are at great risk to develop DVT.

COVID-19 and Hyperinflammatory Syndrome in Children: Kawasaki Disease with Macrophage Activation Syndrome in Disguise?

A hyperinflammatory syndrome has been described in times of COVID-19 in children. In the setting of uncertainty due to a new virus, the so-called hyperinflammatory syndrome has been coined as a novel entity by some and is being referred to as pediatric inflammatory multisystem syndrome (PIMS). However, the characteristics of the syndrome resemble those of Kawasaki disease (KD), an inflammatory syndrome in children that can lead to coronary artery abnormalities due to a subsequent vasculitis. Furthermore, Kawasaki disease may occasionally trigger macrophage activation syndrome (MAS), a condition in which there is uncontrolled activation and proliferation of macrophages and other cell types, and could lead to multiorgan system dysfunction. This study provides a review of the data regarding COVID-19, Kawasaki disease, and macrophage activation syndrome to demonstrate the similarities and differences between the inflammatory syndrome seen with COVID-19 and KD. In addition, a framework for diagnosis and evaluation is provided that focuses on the pathway previously established for KD and MAS. The authors believe that based on current knowledge, KD treatment delays may carry deleterious effects in the near future for children with COVID-19-related Kawasaki disease.