Levels of 14 proteins in the blood of critically ill COVID-19 patients are associated with survival. Machine learning approach was used to find associations between the measured proteins and patient survival. 15 of the patients in the cohort died; the average time from admission to death was 28 days. For patients who survived, the median time of hospitalization was 63 days. The researchers pinpointed 14 proteins which, over time, changed in opposite directions for patients who survive compared to patients who do not survive on intensive care. The team then developed a machine learning model to predict survival based on a single time-point measurement of relevant proteins and tested the model on an independent validation cohort of 24 critically ill patients. The model demonstrated high predictive power on this cohort. . . .
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