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.

Background. The course of chronic obstructive pulmonary disease (COPD) is accompanied by acute exacerbations. The purpose of this study is to determine the association of serum magnesium level with acute exacerbations in COPD (COPD-AE).Materials and Methods. Eighty-nine patients hospitalized with COPD-AE were included. Hemogram, biochemical tests, and arterial blood gases were analyzed. Pulmonary function tests were performed in the stable period after discharge. Patients were followed up at 3 monthly periods for one year.Results. Mean age of the patients was70.4±7.8(range 47–90) years. Mean number of COPD-AE during follow-up was4.0±3.6(range 0–15). On Spearman correlation analysis there were significant negative correlations between number of COPD-AE and predicted FEV1% (P=0.001), total protein (P=0.024), globulin (P=0.001), creatinine (P=0.001), and uric acid levels (P=0.036). There were also significant positive correlations between number of COPD-AE and serum magnesium level (P<0.001) and platelet count (P=0.043). According to linear regression analysis predicted FEV1% (P=0.011), serum magnesium (P<0.001), and globulin (P=0.006) levels were independent predictors of number of COPD-AE.Conclusions. In this small prospective observational study we found that serum magnesium level during exacerbation period was the most significant predictor of frequency of COPD-AE.

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.

A nosocomial outbreak of Acinetobacter baumannii (AB) infections occurred among intensive care units (ICU) (surgery, medical, cardiovascular surgery, coronary unit) of Recep Tayyip Erdogan University Medical School (Rize, Turkey) between January 2011 and May 2012. The identification of isolates and clonal relation among them were investigated by molecular techniques.

Purpose: To evaluate the effect of anti-tubercular treatment on retinal nerve fiber layer (RNFL) thickness and the efficiency of optic coherence tomography (OCT) on early diagnosis of optic neuropathy. Methods: Twenty patients diagnosed with either pulmonary or extra-pulmonary tuberculosis which were treated with anti-tubercular treatment (isoniazid (INH), rifampicin, ethambutol (ETM), and pyrazinamide) were enrolled in the study. RNFL thicknesses of the patients were measured via OCT, at baseline (before starting anti-tubercular treatment) and after the two-month treatment period. Standard ophthalmologic examinations were also performed. Results: Compared to baseline values, after the two-month treatment period, thinning was detected in the right eye’s average and superior quadrant RNFLs (p = 0.024 and p = 0.006 respectively) and in the left eye’s average, superior quadrant, and inferior quadrant RNFLs (p = 0.001, p = 0.008, p < 0.001, respectively). Conclusion: We displayed that patients receiving INH and ETM, which were the basic medicines of anti-tubercular treatment, experienced thinning in RNFL after the two-month treatment period. Patients receiving these drugs can be followed via OCT in terms of reduction in RNFL thicknesses for early diagnose of INH and ETM toxicity.

The cigarette smoking and the obesity are the main reasons of mortality and the morbidity. There are limited studies detecting the relationship between smoking and obesity. However the reported results are contradictory. The aim of the study is to investigate the effects of smoking on body mass index and obesity. A total of 983 patients consisting of 464 (47%) male and 519 (53%) female who admitted to department of chest disease outpatient clinic were enrolled in this study. The age, gender, body mass index (BMI), diastolic and systolic blood pressure levels and smoking states of the patients were recorded. The mean age of patients was 50.7±14.8 years (range 20-80). We detected the obesity in 359 (37%) patients. Compared to smoker females, obesity rate was found significantly higher in non-smoker females (p<0.001). Similarly, there was also significant difference between the smoker and non-smoker males, which was lower than the female group (p=0.041). We found significantly lower BMI scores in female smokers, than non-smokers and ex smokers group (p=0.026 and p<0.001 respectively). Similar results were obtained in males (p=0.019, p<0.001 respectively). There was a positive correlation between BMI and age, systolic and diastolic blood pressure. A negative correlation was found between BMI and smoking amount (pack-year) (p<0.001). Systolic and diastolic blood pressures were found to be lower in smokers than non-smokers in both genders (p<0.001). Cigarette smoking causes a decrease in body mass index, obesity rates and blood pressure levels. The substances found in cigarettes and the mechanism of action leading to these effects are unclear. There is a need for further studies on this topic. J. Exp. Clin. Med., 2013; 30:311-315