To date, coronavirus disease 2019 (COVID-19) has affected over 100 million people globally. COVID-19 can present with a variety of different symptoms leading to manifestation of disease ranging from mild cases to a life-threatening condition requiring critical care-level support. At present, a rapid prediction of disease severity and critical care requirement in COVID-19 patients, in early stages of disease, remains an unmet challenge. Therefore, we assessed whether parameters from a routine clinical hematology workup, at the time of hospital admission, can be valuable predictors of COVID-19 severity and the requirement for critical care. Hematological data from the day of hospital admission (day of positive COVID-19 test) for patients with severe COVID-19 disease (requiring critical care during illness) and patients with non-severe disease (not requiring critical care) were acquired. The data were amalgamated and cleaned and modeling was performed. Using a decision tree model, we demonstrated that routine clinical hematology parameters are important predictors of COVID-19 severity. This proof-of-concept study shows that a combination of activated partial thromboplastin time, white cell count-to-neutrophil ratio, and platelet count can predict subsequent severity of COVID-19 with high sensitivity and specificity (area under ROC 0.9956) at the time of the patient’s hospital admission. These data, pending further validation, indicate that a decision tree model with hematological parameters could potentially form the basis for a rapid risk stratification tool that predicts COVID-19 severity in hospitalized patients.
【저자키워드】 COVID-19, Critical care, machine learning, hematological parameters, Blood, Platelet count, activated partial thromboplastin time, AI in healthcare, 【초록키워드】 coronavirus disease, disease severity, COVID-19 severity, Symptom, hospitalized patients, risk stratification, ROC, Sensitivity and specificity, severity of COVID-19, Patient, Platelet, Hospital admission, predictor, disease, Critical, early stage, predict, severe COVID-19 disease, COVID-19 patients, Combination, white cell, Support, life-threatening, positive COVID-19, parameter, affected, the patient, subsequent, was performed, activated, variety, demonstrated, hematological parameter, hematology parameter, mild case, 【제목키워드】 routine,