It is difficult to distinguish coronavirus disease‐2019 (COVID‐19) from other viral respiratory tract infections owing to the similarities in clinical and radiological findings. This study aims to determine the clinical importance of platelet count and platelet indices in the differentiation of COVID‐19 from influenza and the value of these parameters in the differential diagnosis of COVID‐19. The medical records of the patients and the electronic patient monitoring system were retrospectively analyzed. Demographic characteristics, admission symptoms, laboratory findings, radiological involvement, comorbidities, and mortality of the patients were recorded. Forty‐three patients diagnosed with influenza and 54 diagnosed with COVID‐19 were included in the study. The average age of the COVID‐19 patients was lower than that of the influenza patients (influenza: 60.5 years, COVID‐19: 52.4 years; pp = 0.024),.024), and the male gender was predominant in the COVID‐19 group (influenza: 42%, COVID‐19: 56%). According to laboratory findings, the mean platelet volume (MPV) and MPV/platelet ratio were statistically significantly lower, whereas the eosinophil count and platelet distribution width levels were significantly higher (p < 0.05) in the COVID‐19 group. It was found that the most common symptom in both groups was dyspnea and that the symptom was more prevalent among influenza patients. In the diagnosis of COVID‐19, the platelet count and platelet indices are easily accessible, inexpensive, and important parameters in terms of differential diagnosis and can help in the differentiation of COVID‐19 from influenza during seasonal outbreaks of the latter.

This study aimed to develop a new intelligent diagnostic approach using an artificial neural network (ANN). Moreover, we investigated whether the learning-method-guided quantitative analysis approa...

The pleura is a serous membrane that surrounds the lungs. The visceral surface secretes fluid into the serous cavity and the parietal surface ensures a regular absorption of this fluid. If this balance is disturbed, fluid accumulation occurs in the pleural space called “Pleural Effusion”. Today, accurate diagnosis of pleural diseases is becoming more critical, as advances in treatment protocols have contributed positively to prognosis. Our aim is to perform computer-aided numerical analysis of Computed Tomography (CT) images from patients showing pleural effusion images on CT and to examine the prediction of malignant/benign distinction using deep learning by comparing with the cytology results. The authors classified 408 CT images from 64 patients whose etiology of pleural effusion was investigated using the deep learning method. 378 of the images were used for the training of the system; 15 malignant and 15 benign CT images, which were not included in the training group, were used as the test. Among the 30 test images evaluated in the system; 14 of 15 malignant patients and 13 of 15 benign patients were estimated with correct diagnosis (PPD: 93.3%, NPD: 86.67%, Sensitivity: 87.5%, Specificity: 92.86%). Advances in computer-aided diagnostic analysis of CT images and obtaining a pre-diagnosis of pleural fluid may reduce the need for interventional procedures by guiding physicians about which patients may have malignancies. Thus, it is cost and time-saving in patient management, allowing earlier diagnosis and treatment.

The aim of study is to investigate whether hematological inflammatory biomarkers could be useful to detect patients with lung cancer. Methods: The contribution of hematological biomarkers to the di...

The COVID-19 pandemic has brought countries’ health services into sharp focus. It was drawn to our group’s attention that healthcare workers (HCWs) had a lower mortality rate against higher COVID-19 incidence compared to the general population in Turkey. Since risk of exposure to tuberculosis bacillus among healthcare workers are higher than the population, we aimed to investigate if there is a relationship between BCG and Mycobacterium tuberculosis exposure history with COVID-19 severity in infected HCWs. This study was conducted with 465 infected HCWs from thirty-three hospitals to assess the relationship between COVID-19 severity (according to their hospitalization status and the presence of radiological pneumonia) and BCG and Mycobacterium tuberculosis exposure history. HCWs who required hospital admission had significantly higher rates of chronic diseases, radiological pneumonia, and longer working hours in the clinics. Higher rates of history of contact and care to tuberculosis patients, history of tuberculosis, and BCG vaccine were observed in hospitalized HCWs. HCWs who had radiological pneumonia had a significantly increased ratio of history of care to tuberculosis patients and a higher family history of tuberculosis. The findings from our study suggest that the lower mortality rate despite the more severe disease course seen in infected HCWs might be due to frequent exposure to tuberculosis bacillus and the mortality-reducing effects of the BCG vaccine.

Introduction. Chronic obstructive pulmonary disease (COPD) is one of the most common causes of morbidity and mortality worldwide. The disease is characterized by progressive airway inflammation, which not only affects the airways but also has systemic effects that are associated with comorbidities. Although comorbid conditions such as hypertension and coronary artery disease are very well-known in COPD patients, diseases of the thyroid gland have not been sufficiently studied. Therefore, thyroid diseases are not considered among the comorbid conditions of COPD. The purpose of this study was to determine the thyroid gland disease (TGD) prevalence in COPD and associated factors. Materials and Method. The study included 309 (297 (96%) male) patients. The patients were subjected to spirometry and thyroid function tests (TFT) in the stable period. The thyroid gland disease they were diagnosed with was recorded after face-to-face meetings and examining their files. Results. The mean age of the patients who were included in the study was (40-90). Thyroid disease was determined in 68 (22%) individuals. There were hypothyroidism in 7 (2%), euthyroidism in 45 (15%), and hyperthyroidism in 16 (%5) patients. No relationship was found between the severity of airflow limitation and the prevalence of TGD. Conclusion. Thyroid abnormalities are commonly observed in COPD. The most frequently encountered TGDs are euthyroid multinodular goiter, euthyroid sick syndrome (ESS), and toxic multinodular goiter.