Miodrag Stojanovic

Maternal smoking during pregnancy and socioeconomic factors as predictors of low birth weight in term pregnancies in Nis

BACKGROUND/AIM Low birth weight (LBW) is a result of preterm birth or intrauterine growth retardation, and in both cases is the strongest single factor associated with perinatal and neonatal mortality. It is considered that socioeconomic factors, as well as mothers bad habits, play the most significant role in the development of LBW, which explains notable number of researches focused on this particular problem. The aim of this study was to characterize socioeconomic factors, as well as smoking habits of the mothers, and their connection with LBW. METHODS The questionnaire was carried out among mothers of 2 years old children (n = 956), born after 37 gestational weeks. The characteristics of mothers who had children with LBW, defined as < 2,500 g, (n = 50), were matched with the characteristices of mothers who had children > or = 2,500 g, (n = 906). For defining risk factors, and protective factors as well, we used univariant and multivariant logistic modeles. RESULTS As significant risk factors for LBW in an univariant model we had education level of the mothers, smoking during pregnancy, smoking before pregnancy, the number of daily cigarettes, the number of cigarettes used during pregnancy, paternal earnings and socioeconomic factors. In a multivariant model the most significant factors were socioeconomic factors, education level of the mothers, paternal earnings and mothers smoking during pregnancy. CONCLUSION Smoking during pregnancy and socioeconomic factors have great influence on LBW. Future studies should be carried out in different social groups, with the intention to define their influence on LBW and reproduction, as well. This should be the proper way of adequate health breeding planning for giving up smoking, the prevention of bad habits and melioration of mothers and children health, as the most vulnerable population.

The assessment of renalase: searching for the best predictor of early renal dysfunction by multivariate modeling in stable renal transplant recipients.

BACKGROUND Renal transplant dysfunction has been shown to be an independent risk factor for cardiac, non-cardiovascular, and all-cause mortality in post-transplantation follow-up. MATERIAL AND METHODS We enrolled 73 renal transplant recipients who were more than 12 months post-renal transplant surgery, had stable graft function, and were on standard immunosuppression. The purpose of the study was to observe the relation between renal dysfunction and endothelial dysfunction parameters (nitrates, asymmetric and symmetric dimethylarginine, and endothelial nitric oxide synthase), and renalase, and to hypothesize the best predictor of early renal dysfunction by multivariate modeling. The other aim was to observe differences with regard to immunosuppression. RESULTS Non-adjusted odds ratio showed a significant risk of reduced glomerular filtration rate in transplant recipients with increased renalase concentration (p=0.026); age-adjusted odds ratio showed a significant risk of reduced glomerular filtration rate with increased renalase concentration (p=0.042), also after multivariable adjustment (p=0.032). Increased plasma endothelial nitric oxide synthase concentration was a protective factor for glomerular filtration rate (p=0.011). After adjustment for age (p=0.045), and after multivariate modeling, endothelial nitric oxide synthase was shown to be a protective factor for glomerular filtration rate (p=0.014). Significant differences in immunosuppression were found in plasma renalase in patients maintained on cyclosporine (p=0.027). CONCLUSIONS Renalase was shown to be strong predictor of decreased glomerular filtration rate and was significantly higher in the group of patients on cyclosporine. Endothelial nitric oxide synthase was identified as a strong protective factor for kidney function.

Crosstalk of inflammatory mediators and lipid parameters as early markers of renal dysfunction in stable renal transplant recipients with regard to immunosuppression

BACKGROUND Kidney transplantation is still the treatment of choice for end-stage renal disease, therefore it is important to establish all modifiable risk factors for initiation of renal dysfunction. MATERIAL/METHODS We enrolled 73 renal transplant recipients, who were more than 12 months post-renal transplant surgery, had a stable graft function, had no clinically present cardiovascular disease, and were on standard immunosuppressive therapy. The concentrations of intracellular adhesion molecule-1 (ICAM-1), vascular adhesion molecule-1 (VCAM-1), CRP, lipids, and lipoproteins were measured. We used logistic regression to calculate non-adjusted, age, and multivariable-adjusted ORs and 95% confidence intervals for glomerular filtration rate, GFR <60 ml/min/1.73 m(2). RESULTS Non-adjusted OR showed that there was a significant risk of reduced GFR in patients with total cholesterol higher than 5.19 mmol/L, LDL cholesterol ≥ 4.1 mmol/L, non- HDL ≥ 4.2 mmol/L, and higher VCAM-1 concentration. After adjustment for age and in multivariable model, OR showed a significant risk for reduced GFR in patients with total cholesterol ≥ 5.2 mmol/L, LDL ≥ 4.1 mmol/L, non-HDL ≥ 4.2 mmol/L, and higher VCAM-1 concentration. HDL, triglycerides, CRP, and lipoprotein ratios did not have any significance as predictors of renal dysfunction. There were no differences in all evaluated parameters between groups in regard to immunosuppressive therapy. CONCLUSIONS Total cholesterol, LDL, non-HDL, and VCAM-1 are strong and independent predictors of renal dysfunction in stable renal transplant recipients. In contrast, HDL, CRP, triglycerides, and ICAM-1 did not seem to have any impact on renal dysfunction.

Crosstalk of Various Biomarkers That Might Provide Prompt Identification of Acute or Chronic Cardiorenal Syndromes

Introduction: Pathophysiological interaction between the heart and kidneys represents the basis for clinical entities called cardiorenal syndromes. The purpose of the study was to assess the relations between acute and chronic cardiorenal syndromes and biomarkers [advanced oxidation protein products, brain natriuretic peptide, malondialdehyde, xanthine oxidoreductase (XOD), xanthine oxidase, xanthine dehydrogenase, interleukin 8, cystatin C, plasminogen activator inhibitor-1, high-sensitive troponin T, C-reactive protein and glomerular filtration rate, measured by the Modification of Diet in Renal Disease (MDRD) formula], to hypothesize biomarkers that might provide a prompt identification of acute or chronic cardiorenal syndromes, and to distinguish acute versus chronic types of these syndromes. Methods: A total of 114 participants were enrolled in this study, i.e. 79 patients divided into subgroups of acute and chronic cardiorenal syndromes and 35 volunteers. Results: Nonadjusted odds ratio (OR) showed that there was a significant risk for acute cardiorenal syndrome with increased XOD activity (p = 0.037), elevated cystatin C concentration (p = 0.038) and MDRD (p = 0.028). Multivariable adjusted OR, on the other hand, revealed that only glomerular filtration rate measured by the MDRD formula had a significance for acute cardiorenal syndrome (p = 0.046). Nonadjusted OR showed a significant risk for chronic cardiorenal syndrome only in elderly (p = 0.002). Multivariable adjusted OR exhibited that age was the only risk factor for chronic cardiorenal syndrome (p = 0.012). Conclusion: Cystatin C, glomerular filtration rate measured by the MDRD equation and XOD were independent risk factors for acute cardiorenal syndrome, while age remained an independent risk factor for chronic cardiorenal syndrome. When comparing ORs of evaluated parameters, the highest significance for acute cardiorenal syndrome was plasma concentration of cystatin C.

Relationship between the Manner of Mobile Phone Use and Depression, Anxiety, and Stress in University Students

Objectives: There is insufficient evidence regarding the potential risk of mobile phone use on mental health. Therefore, the aim of this research was to examine the relationship between mobile phone use and mental health by measuring the levels of depression, anxiety, and stress among university students in Serbia and Italy. Methods: This cross-sectional study was carried out at two distinguished universities in Serbia and Italy from March to May of the 2015/2016 academic year and included 785 students of both genders. The questionnaire was compiled and developed from different published sources regarding the manner and intensity of mobile phone use, along with the Depression Anxiety Stress Scale (DASS 42) for measuring psychological health. The statistical analysis of the data included the application of binary logistic regression and correlation tests. Results: Statistical analysis indicates that anxiety symptoms are somewhat more present in younger students (odds ratio (OR) = 0.86, 95% confidence interval (CI): 0.76–0.96), in those who send more text messages (SMSs) (OR = 1.15, 95% CI: 1.11–1.31), and in those who browse the internet less frequently (OR = 0.84, 95% CI: 0.73–0.95). Stress is more common in students who make fewer calls a day (OR = 0.79, 95% CI: 0.64–0.97), as well in those who spend more time talking on the mobile phone per day (OR = 1.28, 95% CI: 1.12–1.56). The strongest predictor of high stress levels was keeping the mobile phone less than 1 m away during sleeping (OR = 1.48, 95% CI: 1.12–2.08). Conclusions: The results indicated that the intensity and modality of mobile phone use could be a factor that can influence causal pathways leading to mental health problems in the university student population.

Renalase Assessment With Regard to Kidney Function, Lipid Disturbances, and Endothelial Dysfunction Parameters in Stable Renal Transplant Recipients

Background: Renal transplant dysfunction has been shown to be independent predictor for premature cardiovascular disease and mortality. Renalase, a flavoprotein secreted by several tissues, including the kidney, has been found to regulate sympathetic tone and blood pressure. The purpose of this secondary analysis was to explore relationships among parameters of endothelial dysfunction, lipids, glomerular filtration rate, and renalase in 2 groups: renal transplant patients with controlled hypertension and healthy volunteers. Methods: In the parent study, 73 renal transplant recipients and 32 age- and gender-matched controls were enrolled. A fasting sample for endothelial, lipid, and renalase values, along with other clinical parameters, was obtained. Results: We found statistically significant inverse correlation between renalase and estimated glomerular filtration rate (r = −0.552, P < .001), positive correlation between renalase and creatinine (r = 0.364, P = .003), total cholesterol (r = 0.578, P < .001), low-density lipoprotein cholesterol (r = 0.261, P = .046), and non-high-density lipoprotein cholesterol (r = 0.327, P = .01). Renalase inversely correlated with hemoglobin (r = −0.232, P = .032) and positively with white blood cells (r = 0.233, P = .032). There was a significant difference in plasma renalase with regard to chronic kidney disease stages (F = 13.346, P < .001) but did not correlate with C-reactive protein. Renalase did not correlate with any of parameters of endothelial dysfunction, C-reactive protein, neither with some demographic data (gender, age, time or type of transplantation, risk factors). There were no differences in renalase concentration with regard to antihypertensive therapy. Conclusion: Renalase strongly and inversely correlated with kidney function, positively with creatinine and lipid disturbances. Due to that it is very likely that renalase levels are determined mostly by renal function.

Progress of statistical analysis in biomedical research through the historical review of the development of the Framingham score

BackgroundThe interest in developing risk models in medicine not only is appealing, but also associated with many obstacles in different aspects of predictive model development. Initially, the association of biomarkers or the association of more markers with the specific outcome was proven by statistical significance, but novel and demanding questions required the development of new and more complex statistical techniques.MethodsProgress of statistical analysis in biomedical research can be observed the best through the history of the Framingham study and development of the Framingham score.ResultsEvaluation of predictive models comes from a combination of the facts which are results of several metrics. Using logistic regression and Cox proportional hazards regression analysis, the calibration test, and the ROC curve analysis should be mandatory and eliminatory, and the central place should be taken by some new statistical techniques. In order to obtain complete information related to the new marker in the model, recently, there is a recommendation to use the reclassification tables by calculating the net reclassification index and the integrated discrimination improvement. Decision curve analysis is a novel method for evaluating the clinical usefulness of a predictive model. It may be noted that customizing and fine-tuning of the Framingham risk score initiated the development of statistical analysis.ConclusionClinically applicable predictive model should be a trade-off between all abovementioned statistical metrics, a trade-off between calibration and discrimination, accuracy and decision-making, costs and benefits, and quality and quantity of patient’s life.

Impact of socio-demographic characteristics and long-term complications on quality of life in patients with diabetes mellitus

OBJECTIVE Diabetes mellitus (DM) has been one of the leading chronic diseases worldwide over past decades. The objective of the study was to identify predictors associated with health-related quality of life (HRQOL) in diabetic patients. METHODS A cross-sectional questionnaire-based study was conducted at the General Hospital of the city of Leskovac, between June and November 2015. The Short Form-36 (SF-36) questionnaire, EuroQol-5D (EQ-5D) and EuroQol-VAS (EQ-VAS) questionnaires were used. Univariate and multivariate linear regression analyses were performed. RESULTS The total number of patients was 285, 112 men (39.3%) and 173 women (60.7%), average age 63.92 ± 1.07 years. The results of multiple linear regression of socio-demographic characteristics in relation to dimensions of the quality of life measured by SF-36 and EQ-VAS showed that age, country (rural) life, low level of education, retirement, and poor economic status are predictors of lower quality of life. Our results showed that employment has a significant association with higher Physical Component Score (PCS), Mental Component Score (MCS) and EQ-VAS score, which can be explained with higher incomes, improved economic status and less possibility for the occurrence of depressive mood. Patients without formal education have lower QOL. Univariate multiple regression analysis of the presence of micro- and macrovascular complications of DM showed that angina pectoris, heart failure, diabetic retinopathy, and diabetic nephropathy are the most important factors affecting the quality of life in our population. After including the multivariate model, all tested complications remained statistically significant. CONCLUSION Our results showed that both socioeconomic and chronic complications are relevant factors of HRQOL in type 1 and 2 diabetes mellitus patients. Age, rural lifestyle, retirement, lower level of education and low socioeconomic status, as well as DM complications (angina pectoris, hearth failure, diabetes nephropathy, and diabetes retinopathy) were found to be independent risk factors for the component scores of SF-36 and EQ-VAS score. Taking into consideration the results obtained, health practitioners should be aware not only of the clinical parameters of patients with DM, but also of their educational level and working status.

Green Function of the Point Source Inside/Outside Spherical Domain - Approximate Solution

A brief review of derivation of two groups of approximate closed form expressions for the electrical scalar potential (ESP) Green functions that originates from the current of the point ground electrode (PGE) in the presence of a spherical ground inhomogeneity are presented in this paper. The PGE is fed by a very low frequency periodic current through a thin isolated conductor. One of approximate solutions is proposed in this paper. Known exact solutions that have parts in a form of infinite series sums are also given in this paper. In this paper, the exact solution is solely reorganized in order to facilitate comparison to the closed form solutions, and to estimate the error introduced by the approximate solutions. Finally, error estimation is performed comparing the results for the electrical scalar potential obtained applying the approximate expressions and the accurate calculations. This is illustrated by a number of numerical experiments.

The grounding system of the pillar on the road

The lightning pillars on the highway need to be grounded in accordance with the corresponding standards. A procedure for characterization of the grounding systems placed inside the road is presented in the paper. The road is treated as a ground inhomogeneity. Using the estimation method, the road is approximated by a domain having semi-circular cross-section. The analysis includes application of the quasi-stationary image theory and the Greens function for the point source placed inside the cylinder of the semi-circular cross-section. Leakage current distributions are obtained applying the Method of Moments. Afterwards, the grounding system characteristics are determined.