Evaluation of the relationship between TAFI level and prognosis in COVID-19 patients.

OBJECTIVE: Serum thrombin-activated fibrinolysis inhibitor (TAFI) levels were measured in coronavirus disease 2019 (COVID-19) patients requiring intensive care, clinical hospitalization, and outpatient follow-up. The relationships between serum TAFI levels and prognosis were determined. PATIENTS AND METHODS: Ninety patients who had positive COVID-19 PCR test results were randomly selected and included in the study. Subgroups were formed according to the clinical characteristics of the patients as follows: mild, moderate, and severe. Venous blood samples were taken from all patients, and serum C-reactive protein (CRP), lactate dehydrogenase (LDH), fibrinogen, D-dimer, ferritin, and TAFI levels were measured. The results were evaluated by comparing each group. RESULTS: The one-way ANOVA test to determine differences between subgroups resulted in p-values lower than 0.05 for all biochemical analytes (CRP, LDH, fibrinogen, D-dimer, ferritin, and TAFI). Regarding serum TAFI levels, there were significant differences in the severe group (853.04 ± 338.58 ng/mL) compared to the mild group (548.33 ± 264.17 ng/mL). ROC curve analysis to predict mortality revealed that TAFI levels were able to detect 85% of deaths. In addition, ROC analysis revealed that serum TAFI levels could detect 86% of intubated cases. CONCLUSIONS: The disease progression is more severe in patients with high TAFI levels, and high TAFI levels are associated with mortality and intubation rates. Further studies are needed to determine serum TAFI levels as a biomarker of prognosis in COVID-19 patients.

Interleukin-28 as a Promising Marker for Predicting Invasive Mechanical Ventilation Requirement and Mortality in COVID-19 Patients

OBJECTIVE: The study aimed to evaluate serum interleukin-28 levels in COVID-19 patients and correlate the results with disease severity. MATERIAL AND METHODS: This study included 90 patients who presented to the COVID-19 outpatient clinics, hospital wards, and intensive care units. Serum interleukin-28, C-reactive protein, lactate dehydrogenase, fibrinogen, d-dimer, and ferritin levels were mea-sured. Patients were divided into 3 groups based on clinical severity to mild, moderate, and severe groups (each group consisted of 30 patients). RESULT(S): There were significant differences in serum C-reactive protein, lactate dehydrogenase, fibrinogen, d-dimer, ferritin, and inter-leukin-28 levels between all groups. The mean serum interleukin-28 levels of all patients were 383.74 +/- 63.58 ng/L. The mean serum interleukin-28 levels were 335.52 +/- 42.12 ng/L in the mild group, 366.88 +/- 41.27 ng/L in the moderate group, and 453.46 +/- 36.78 ng/L in the severe group. CONCLUSION(S): There were significant differences in comparisons of all pairs (P < .05). Interleukin-28 may be a promising biomarker for detecting disease severity in COVID-19 patients.Copyright © 2023, AVES. All rights reserved.

The relationship between COVID-19 and the complement system: mannose-binding lectin.

OBJECTIVE: Mannose-binding lectin (MBL) is one of the important parts of the complement system. In our study, we aimed to determine serum MBL levels and their relationship with intensive care hospitalization. PATIENTS AND METHODS: Ninety COVID-19-positive patients from outpatient clinics and clinics were included in this study. The patients were evaluated in three groups as mild, moderate, and severe groups. Each group consisted of 30 patients. A venous blood sample was taken once from each patient. Serum MBL, C-reactive protein (CRP), lactate dehydrogenase (LDH), fibrinogen, D-dimer, and ferritin levels were measured. RESULTS: The mean serum MBL levels of all patients were 695.46±324.42 ng/mL. One-way ANOVA test resulted in significant differences in serum CRP, LDH, fibrinogen, D-dimer, ferritin, and MBL levels between groups (p<0.05 for all comparisons). Post-hoc Tukey analysis showed significant differences in serum MBL levels between mild and severe groups and moderate and severe groups. CONCLUSIONS: MBL may be used as a prognostic biomarker in COVID-19 patients. Further studies are needed to determine MBL in treatment strategies.

CLASSIFICATION OF STUDENTS’ ACHIEVEMENT VIA MACHINE LEARNING BY USING SYSTEM LOGS IN LEARNING MANAGEMENT SYSTEM

During emergency remote teaching (ERT) process, factors affecting the achievement of students have changed. The purposes of this study are to determine the variables that affect the classification of students according to their course achievements in ERT during the pandemic process and to examine the classification performance of machine learning techniques. For these purposes, the logs from the learning management system were used. In the study, analyzes were carried out with various machine learning techniques and their performances were compared. As a result of the study, it was observed that Fisher’s Linear Discriminant Analysis was the best technique in classification according to F measure performance criteria. As another result, the most effective variable, in classifying students, is the average number of days logged into the system per month and week. It has been observed that total activity duration (min), total number of weeks and total number of page views during the semester are less influential factors. Accordingly, it could be suggested to check the monthly and weekly follow-up of the lectures instead of the total follow-ups per semester. In addition, students’ interaction patterns can be monitored with course tracking systems. © 2022. Turkish Online Journal of Distance Education. All Rights Reserved.