Ryan C, Minc A, Caceres J, et al. - Researchers aimed at developing a risk-stratification model that may aid in predicting severe Covid-19 related illness, using only presenting symptoms, comorbidities and demographic data. In this case-control study of 556 patients with laboratory confirmed Covid-19, cases were those with severe disease, defined as ICU admission, mechanical ventilation, death or discharge to hospice, and controls were those with non-severe disease. In multivariable logistic regression analysis, following were identified as significant predictors of severe Covid-19 infection: increasing age, dyspnea, male gender, immunocompromised status and CKD. They noted a negative correlation between hyperlipidemia and severe disease. A predictive equation based on these variables showed fair ability to differentiate severe vs non-severe outcomes using only this historical information (AUC: 0.76). These findings suggest that using data obtained from a remote screening, severe Covid-19 illness can be predicted. With validation, this model may allow remote triage to prioritize evaluation based on susceptibility to severe disease while avoiding unnecessary waiting room exposure.