Application of boosted trees to the prognosis prediction of COVID-19.

Background and Aims: The precise prediction of COVID-19 prognosis remains a clinical challenge. In this regard, early identification of severe cases facilitates the triage and management of COVID-19 cases. The present paper aims to explore the prognosis of COVID-19 patients based on routine laboratory tests taken when patients are admitted. Methods: A data set including 1455 COVID-19 patients (727 male, 728 female) and their routine laboratory tests conducted upon hospital admission, age, Intensive Care Unit (ICU) admission, and outcome were gathered. The data set was randomly split into the train (75% of the data) and test data set (25% of the data). The explainable boosting machine (EBM) and extreme gradient boosting (XGBoost) were used for predicting the mortality and ICU admission of COVID-19 cases. Also, feature importance was extracted using EBM and XGBoost. Results: The EBM and XGBoost achieved 86.38% and 88.56% accuracy in the test data set, respectively. In addition, EBM and XGBoost predicted the ICU admission with an accuracy of 89.37%, and 79.29% in the test data set for COVID-19 patients, respectively. Also, obtained models indicated that aspartate transaminase (AST), lymphocyte, blood urea nitrogen (BUN), and age are the most significant predictors of COVID-19 mortality. Furthermore, the lymphocyte count, AST, and BUN level were the most significant ICU admission predictors of COVID-19 patients. Conclusions: The current study indicated that both EBM and XGBoost could predict the ICU admission and mortality of COVID-19 cases based on routine hematological and clinical chemistry evaluation at the time of admission. Also, based on the results, AST, lymphocyte count, and BUN levels could be used as early predictors of COVID-19 prognosis.

COVID-19 and hematology findings based on the current evidences: A puzzle with many missing pieces.

In December 2019, a new type of coronavirus was detected for the first time in Wuhan, Hubei Province, China. According to the reported data, the emerging coronavirus has spread worldwide, infecting more than fifty-seven million individuals, leading to more than one million deaths. The current study aimed to review and discuss the hematological findings of COVID-19. Laboratory changes and hematologic abnormalities have been reported repeatedly in COVID-19 patients. WBC count and peripheral blood lymphocytes are normal or slightly reduced while these indicators may change with the progression of the disease. In addition, several studies demonstrated that decreased hemoglobin levels in COVID-19 patients were associated with the severity of the disease. Moreover, thrombocytopenia, which is reported in 5%-40% of patients, is known to be associated with poor prognosis of the disease. COVID-19 can present with various hematologic manifestations. In this regard, accurate evaluation of laboratory indicators at the beginning and during COVID-19 can help physicians to adjust appropriate treatment and provide special and prompt care for those in need.