Early triage of patients diagnosed with COVID-19 based on predicted prognosis: A Korean national cohort study

Abstract We developed a tool for early triage of a COVID-19 patient based on a predicted prognosis, using a Korean national cohort of 5,596 patients. Predictors chosen for our model were older age, male sex, subjective fever, dyspnea, altered consciousness, temperature ≥ 37.5°C, heart rate ≥ 100 bpm, systolic blood pressure ≥ 160 mmHg, diabetes mellitus, heart disease, chronic kidney disease, cancer, dementia, anemia, leukocytosis, lymphocytopenia, and thrombocytopenia. Our model was better in predicting prognosis than protocols that are not based on data. The AUC of our model utilizing all the selected predictors was 0.907 in predicting whether a patient will require at least oxygen therapy and 0.927 in predicting whether a patient will need critical care or die from COVID-19. Even with age, sex, and symptoms alone used as predictors, AUCs were ≥ 0.88. In contrast, the protocols currently recommended in Korea showed AUCs less than 0.75.