An estimated 14−17% of hospitalized COVID-19 patients develop a severe form of the disease, requiring oxygen support and admission to the intensive care unit. Underlying medical conditions such as diabetes, chronic cardiac diseases, chronic kidney diseases, obesity, and some genetic predispositions contribute to the severity of COVID-19. However, the severity of COVID-19 in a large group of patients cannot be explained only by these factors. At present, it is therefore very difficult to predict if the patient will develop a severe form of the disease. This is a problem, since such prediction and prognosis of the disease development from the first days is very important for providing adequate and timely management to reduce patients’ mortality.
In a recent prospective clinical study, published in Frontiers of Immunology, an interdisciplinary team of immunologists, mathematicians, and clinicians from Belgium and Russia has identified a set of prediction markers which can be used to define the COVID-19 severity at the day of patient admission to the hospital. First author Dr. Olga Krysko (Ghent University): “The advantage of these identified markers is that these markers can be easily measured in most conventional clinical laboratories worldwide, making this prediction analysis accessible for many hospitals wordwide.”
Artificial intelligence analysis
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