In [15], the random forest (RF) algorithm was applied on clinical data from 214 patients with confirmed COVID-19 non-severe type and 148 with severe type yielding increased accuracy, as well as clinical (e.g., age, hypertension, cardiovascular disease, gender, diabetes) and laboratory (e.g., absolute neutrophil count, IL-6, and LDH) risk factors. Here, IL6 is linked to COVID-19.