Abstract
We developed a tool to guide decision-making for early triage of COVID-19 patients based on a predicted prognosis, using a Korean national cohort of 5,596 patients, and validated the developed tool with an external cohort of 445 patients treated in a single institution. 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. In the external validation, when age, sex, symptoms, and underlying disease were used as predictors, the AUC used as an evaluation metric for our model’s performance was 0.850 in predicting whether a patient will require at least oxygen therapy and 0.833 in predicting whether a patient will need critical care or die from COVID-19. The AUCs improved to 0.871 and 0.864, respectively, when additional information on vital signs and blood test results were also used. In contrast, the protocols currently recommended in Korea showed AUCs less than 0.75. An application for calculating the prognostic score in COVID-19 patients based on the results of this study is presented on our website (https://nhimc.shinyapps.io/ih-psc/), where the results of the validation ongoing in our institution are periodically updated.
Highlights
We developed a tool to guide decision-making for early triage of COVID-19 patients based on a predicted prognosis, using a Korean national cohort of 5,596 patients, and validated the developed tool with an external cohort of 445 patients treated in a single institution
The current protocols recommended for triage and referral of COVID-19 patients in many countries or by World Health Organization (WHO) are based on known risk factors and expert opinion but have not been validated on the actual patient data[2,3,4,5]
We aimed to develop and validate an easy-to-use tool for COVID-19 patient triage based on a predicted prognosis, with the flexibility to adapt to variable availability
Summary
We developed a tool to guide decision-making for early triage of COVID-19 patients based on a predicted prognosis, using a Korean national cohort of 5,596 patients, and validated the developed tool with an external cohort of 445 patients treated in a single institution. In the external validation, when age, sex, symptoms, and underlying disease were used as predictors, the AUC used as an evaluation metric for our model’s performance was 0.850 in predicting whether a patient will require at least oxygen therapy and 0.833 in predicting whether a patient will need critical care or die from COVID-19. The current protocols recommended for triage and referral of COVID-19 patients in many countries or by WHO are based on known risk factors and expert opinion but have not been validated on the actual patient data[2,3,4,5]. There may be limitations, to applying these models for COVID-19 patient triage under some real-world circumstances. Most of these models require patients’ information obtained from. We often need to triage and refer COVID-19 patients immediately after the diagnosis with limited information depending on the situation
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