Mevlut Ture

Myeloperoxidase (MPO) is a lysosomal hemoprotein found in the azurophilic granules in neutrophils. Myeloperoxidase plays an important role in oxygen-dependent killing of bacteria, fungi, virus and malignant cells. Diabetes mellitus (DM) is listed among conditions that may lead to secondary MPO deficiency in neutrophils but inconsistent results concerning MPO activity in diabetic patients have been reported in the literature. In this study, we aimed to evaluate the relationship between glycemic control in patients with type 2 DM and MPO activity in neutrophils from a histochemical perspective. The study included 40 patients with type 2 DM with poor glycemic control, 30 patients with type 2 DM with good glycemic control and 31 healthy controls. Peripheral blood smears were analyzed for each patient included in the study. Myeloperoxidase dye was used for staining. Myeloperoxidase ratios in neutrophil were evaluated for proportions of staining with MPO in 100 neutrophils in each smear. SPSS 16.0 version was used for statistical analyses. Myeloperoxidase ratios in neutrophils were 70 (58.5–80) in type 2 DM patients with poor glycemic control compared to 80 (73.75–90) in those with good glycemic control and 88 (78–92) in healthy controls. The DM group with poor glycemic control was statistically significantly different from the other groups (p < 0.001). Poor glycemic control in diabetic patients results in decreased MPO activity in neutrophils histochemically.

Allergic diseases generally begin early during childhood, but a late diagnosis is common. This study aimed to evaluate the prevalence of asthma and asthma-related symptoms among kindergarten children in Edirne, Turkey. 873 subjects based on a modified ISAAC questionnaire were included. The prevalence of 'wheezing ever' and 'wheezing during the previous year' was 23.3% and 8.6%, respectively. Prior physician diagnoses existed for 36 of 873 (4.1%) children. The prevalence of children undiagnosed with asthma, but reporting asthma-related symptoms was 3.1%, 51.9% of which had previous beta-agonist prescriptions. However, none of these children received inhaled anti-inflammatory medications. In conclusion, it was found that a large population of preschool children had undiagnosed respiratory symptoms suggestive of asthma. Conducting simple surveys of young children is particularly important, as identification of asthma early in the disease course will facilitate effective prevention and treatment.

The purpose of this study is to determine how the major risk factors are related to each other in the development of coronary artery disease (CAD) using Chi-squared Automatic Interaction Detection (CHAID). All patients with suspected CAD seen in the cardiology clinic between January 1999 and February 2003 who underwent coronary angiography were included in the study. A retrospective analysis was performed in 1381 patients. In all patients' sex, age, type II diabetes mellitus, hypercholesterolemia, systemic hypertension, smoking status, family history of CAD, body mass index (BMI) were assessed. According to classification tree, first-level split produced the two initial branches: female (unadjusted presence percentage = 48.07%) versus male (unadjusted presence percentage = 78.02%). For the male aged between 49-81 years and the female aged between 15-48, 49-60 and 61-71 years, diabetes mellitus was the most prominent risk factor. However, hypercholesterolemia was the best predicting variable for the females aged between 72-81 years. For the females of 15-48 years and 49-60 years age categories without diabetes mellitus, smoking status and family history of CAD had important contribution to the model. Sorting the major risk factors of CAD from the most to least according to the classification importance was resulted as sex, age, diabetes mellitus, hypercholesterolemia, family history of CAD and smoking status.

Thyroid hormone dysfunction could affect outcome and increase mortality in critical illness. Therefore, in a prospective, observational study we analyzed and compared the prognostic accuracy of free tri-iodothyronine (fT3), free thyroxine (fT4), thyroid-stimulating hormone (TSH), along with the APACHE II and SOFA scoring systems in predicting intensive care unit (ICU) mortality in critically ill patients. Physiology scores were calculated for the first 24 hours after ICU admission in 206 patients with acute respiratory distress syndrome. APACHE II and SOFA scores were employed to determine the initial severity of illness. Thyroid hormones were measured within the first 24 hours. Logistic regression models were created for APACHE II scores, SOFA scores, and thyroid hormone levels. The models predicted high- and low-risk subgroups. Models that showed a good fit were stratified by Kaplan-Meier survival curves. There were 98 (47.6%) survivors and 108 (52.4%) non-survivors. The survivors had a lower APACHE II score (11.50 vs 15.82, P<0.0005), a lower SOFA score (6.06 vs 9.42, P<0.0005), a younger age (57 vs 70 years, P=0.008), a shorter ICU stay (13 vs 16 days, P=0.012), and a higher fT3 level (2.18 vs 1.72 pg/mL, P=0.002) than non-survivors. ICU survival was most closely predicted by a model that included age and fT3 and a model that included APACHE II and APACHE II*sex. In critically ill patients, serum fT3 concentrations markedly decreased after ICU admission among non-survivors. According to our findings, fT3 levels might have additive discriminatory power to age, SOFA and APACHE II scores in predicting short-term mortality in ARDS patients admitted to ICU.

In this study, we compared performances of logistic regression analysis (LR), flexible discriminant analysis (EAA) and neural networks (SA) in prediction of primary hypertension. Predictor variables were family history, lipoprotein A, triglyceride, smoking and body mass index. The data were collected from Cardiology Clinic of Trakya University Medical Faculty in Turkey, 2001. Logistic regression analysis, flexible discriminant analysis and neural networks were used for prediction of control and hypertension groups. Comparison of the performance of all models was done using receiver operating characteristic (ROC) curve analysis. All models had areas under the ROC curve in the range of 0.793-0.984 and SA had sensitivity, specificity, and accuracy greater than 90% at ideal threshold. ROC curve areas of SA and LR, and SA and EAA were statistically different (p0.05). We concluded that family history, lipoprotein A, triglyceride, smoking and body mass index variables can be used for prediction of control and hypertension groups with statistically better performance of SA over LR and EAA.