Neha Gupta, MD, FAAP
Assistant Professor
University of Oklahoma Health Sciences Center
Oklahoma City, Oklahoma
Disclosure information not submitted.
Saurabh Talathi, MD, MPH
Physician
University of Oklahoma Health Sciences Center, United States
Disclosure information not submitted.
Title: Factors differentiating active COVID-19 infection from Multisystem Inflammatory Syndrome in children
Introduction: The aim of our study was to identify clinical characteristics and laboratory markers at presentation that differentiate COVID-19 infection from multisystem inflammatory syndrome in children (MIS-C).
Methods: This is a single-center observational study comparing children admitted with diagnosis of ‘MIS-C’ and ‘Active COVID-19 infection’. Multivariate logistic regression was performed to create predictive models for predicting MIS-C. Secondary analysis was performed to compare ‘MIS-C’ and ‘severe/critical COVID-19 (SC-COVID-19) infection’.
Results: Of the 120 patients included in the study, 28 patients (23.3%) had MIS-C. Active COVID-19 cohort had a higher proportion of being overweight/obese (p=0.01), any comorbidity (p=0.04), neurologic comorbidity (p=0.04) and cough (p< 0.05). MIS-C cohort had a higher prevalence of fever, rash and gastrointestinal (GI) symptoms (p< 0.05), mechanical ventilation use (p=0.0006), lower hemoglobin, platelet count, serum electrolytes, and elevated alanine transaminase (ALT), total bilirubin and inflammatory markers. The best model to predict MIS-C included c-reactive protein (CRP), ALT, platelet count and mucocutaneous involvement (performance-0.97). Using sensitivity analysis, CRP >40mg/L and mucocutaneous involvement had specificity of 100% to diagnose MIS-C. Of the 92 patients with active COVID-19 infection, 40 patients (43.5%) had SC-COVID-19 infection. On comparing MIS-C vs SC-COVID-19 infection, MIS-C patients had a higher prevalence of fever, mucocutaneous, cardiac and GI involvement and a lower prevalence of respiratory symptoms (p< 0.05), lower hemoglobin, platelet count, serum electrolytes and elevated inflammatory markers. The best model to predict MIS-C included CRP, platelet count, GI and mucocutaneus involvement and absence of respiratory involvement (performance- 0.94). Using sensitivity analysis, CRP>40mg/L with either platelet count< 150x103/mm3 or mucocutaneous involvement had specificity of 97.5% to diagnose MIS-C.
Conclusions: Elevated CRP and mucocutaneous involvement are highly associated with MIS-C, thus may help in distinguishing patients with MIS-C from active COVID-19 infection. When comparing MIS-C vs SC-COVID-19 infection, elevated CRP with either thrombocytopenia or mucocutaneous involvement at presentation are predictive of MIS-C diagnosis.