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We read with great interest the recent article by Caricchio et al reporting preliminary predictive criteria for COVID-19 cytokine storm (COVID-CS).1 Early risk stratification for disease course and mortality is important especially in critically ill patients with severe COVID-19 to guide physicians in their evaluation to define patients at risk not surviving COVID-19 who may benefit from specific interventions.2 To develop a predictive model, the authors used univariate logistic regressions to identify variables and clusters associated with COVID-CS, resulting in defined optimal cut-off values.1 The model identified patients at risk for COVID-CS, associated with longer hospitalisation and increased mortality. While ferritin and C-reactive protein (CRP) did not add predictive power, these parameters were included in the final criteria per expert preference for clinical reassurance of ongoing systemic inflammation. Therefore, we here describe the performance of the COVID-CS predictive model for the requirement of intensive care unit (ICU) supportive care and mortality in a single-centre cohort of 20 critically ill patients with confirmed SARS-CoV-2 infection. …
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