ABSTRACT
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.
ABSTRACT
The information gained from the Human Genome Project has facilitated molecular as well as cellular studies not only to find the origins of Breast Cancer (BC), but also to create novel, and effective treatments. In order to provide an infrastructure for local and international research in this area, Iranian Center for Breast Cancer (ICBC) has established a Bio-Bank (BB) for BC. This article describes the aim, structure, and activities in general, and the challenging issues confronting the bank as a model for the establishment of Bio-Banks in developing countries in particular. The methods employed by the Bank could be explained in the following categories: Blood and Tissue sampling, Preparation and Banking of collected Samples, Clinical and Histopathology data collection, Collaboration Protocol, Challenging issues, and the programs to confront the problems. During the five-year activity of the bank, 110 families were enrolled for genetic counseling, from whom 600 biologic samples were obtained, including 387 blood samples and 213 tissue samples. Of 387 blood samples, 317 (82%) were found to belong to the BC patients and the remaining 70 (18%) belonged to their available relatives. The number of samples increased over the study period partly as a result of the programs designed to confront the problems. During the study period, there were some finished research studies using the samples of BB, and many other studies which are still ongoing. ICBC-BB is a model of biologic sample banking which provides a significant number of biological samples for local and international collaborative research projects regarding molecular and cellular aspects of BC. In establishing the ICBC-BB we have experienced problems and challenges, some general and some local. Some were expected and others not, but we have identified solutions.
