Detection of COVID-19 by Machine Learning Using Routine Laboratory Tests.

Objectives: The present study aimed to develop a clinical decision support tool to assist coronavirus disease 2019 (COVID-19) diagnoses with machine learning (ML) models using routine laboratory test results.

Methods: We developed ML models using laboratory data (n = 1,391) composed of six clinical chemistry (CC) results, 14 CBC parameter results, and results of a severe acute respiratory syndrome coronavirus 2 real-time reverse transcription-polymerase chain reaction as a gold standard method. Four ML algorithms, including random forest (RF), gradient boosting (XGBoost), support vector machine (SVM), and logistic regression, were used to build eight ML models using CBC and a combination of CC and CBC parameters.

Clinical Features of SARS-CoV-2 Infection in Patients Undergoing Solid-Organ Transplant: Baskent University Experience.

Objectives: The clinical features and treatment approaches, outcomes, and mortality predictors of COVID-19 in solid-organ transplant recipients have not been well defined. This study investigated the clinical features of COVID-19 infection in solid-organ transplant recipients at our center in Turkey.

Materials And Methods: Our study included 23 solidorgan transplant recipients and 336 nontransplant individuals (143 previously healthy and 193 patients with at least 1 comorbidity) who were hospitalized due to COVID-19 disease in our hospital between March 2020 and January 2021.

Risk Factors for Urinary Tract Infection After Kidney Transplant: A Retrospective Analysis.

Objectives: Urinary tract infections are the most common type of infections in kidney transplant recipients. They are also important factors for increased morbidity and mortality. The aims of this study were to evaluate the number of urinary tract infections, to identify possible donor/receiver-based risk factors, and to evaluate the impact of these infections on graft function.

Evaluation of 28 cases of mucormycosis.

Mucormycosis is a rare but invasive fungal disease with high mortality. The present study aimed to retrospectively investigate the demographic characteristics, as well as the clinical, radiological and laboratory features and the results of treatment, in the patients followed in our hospital because of mucormycosis. The present study retrospectively evaluated 28 cases, which were followed in our hospital because of mucormycosis between January 2002 and July 2013.