Mean platelet volume (MPV) is an indicator of platelet activation. Platelet activation and aggregation are central processes in the pathophysiology of coronary heart disease. Non-alcoholic fatty liver disease (NAFLD) is present up to one-third of the general population and the majority of patients with cardio-metabolic risk factors such as abdominal obesity, type 2 diabetes and other components of the metabolic syndrome (MS). The aim of the current study was to investigate the MPV in patients who had NAFLD. MPV values of the patients with NAFLD and of the patients without fatty liver disease were compared. NAFLD patients had significantly higher body mass index compared to the control cases. Among biochemical variables, fasting plasma glucose and triglyceride were significantly higher in the NAFLD group. NAFLD cases also had lower platelet count and higher MPV (10.43 +/- 1.14 vs. 9.09 +/- 1.25; p < 0.001, respectively). MPV was positively correlated with AST (r: 0.186, p < 0.042), ALT level (r: 0.279; p 0.002) and the presence of NAFLD (0.492; p < 0.001) but negatively correlated with platelet number (r: -0.26; p 0.004) and creatinine (r: -0.255; p 0.005). In logistic regression analysis (age, gender, NAFLD, body mass index, high-density lipid (HDL) cholesterol, systolic and diastolic blood pressure, triglyceride and fasting plasma glucose were used as covariates) only NAFLD was found to be the independent predictor of MPV (Odds Ratio (OR) 21.98) [95% confidence interval (CI): 2.404-201.048; p: 0.006]. We have shown for the first time in the literature that, patients with NAFLD have higher MPV. It may have prognostic value in NAFLD patients indicating a possible cardiovascular disease (CVD) risk increase.

Backgroud:Branch retinal vein occlusion (BRVO) is the second most common retinal vascular disease after diabetic retinopathy. To date, the studies were unable to elucidate the mechanism of the thrombosis leading to the entity; particularly the relation between thrombocyte aggregation and retinal vein occlusion is still unclear. Mean platelet volume (MPV) is a determinant of rate of platelet production and activation, both of which are indices of function of platelets. The relation between MPV and BRVO has not been studied before. The aim was to evaluate MPV in BRVO.Materials and Methods:Forty patients were included in the study. Forty six age and sex matched hypertensive volunteers were recruited as the control group.Results:MPV values were significantly higher in BRVO patients compared with the control subjects (8.01 ± 0.79vs 7.52 ± 0.32fL, respectively; P < 0.001). Conclusion: MPV is significantly higher in patients hypertensive BRVO patients and further investigations regarding its potentially use as a prognostic biomarker in patients with BRVO are needed.

The metabolic syndrome is closely associated with atherosclerotic risk factors and increased mortality. Mean platelet volume (MPV) is an indicator of platelet activation which also shows a close relationship with cardiovascular risk factors, such as diabetes mellitus, hypertension, hypercholesterolemia, obesity, metabolic syndrome. The aim of this study was to investigate the correlates of metabolic syndrome, its components and MPV adjusted for obesity in a large population study. A total of 2298 individuals with a mean age of 50 (age range 18-92) were interviewed. Nine hundred and twenty obese participants, who had BMI 30 kg/m² or more, further evaluated for the presence of metabolic syndrome. Five hundred and thirteen [396 women (70.2%)] had metabolic syndrome and the rest 407 individuals [324 women (79.6%)] served as the control group. The BMI, SBP, DBP, waist circumference, fasting plasma glucose, visceral fat, total cholesterol, high-density lipoprotein-cholesterol, and triglyceride was higher significantly in metabolic syndrome group (P = 0.002 for BMI and P < 0.001 for the others). No significant difference was observed between groups regarding low-density lipoprotein cholesterol, white blood cells, platelet counts, MPV, hematocrit and hemoglobin (P > 0.05 for all). The presence of metabolic syndrome and its components do not constitute a difference in MPV values in obese patients with a BMI 30 kg/m² or more.

IntroductionIn the present study, we investigated the effects of breast-feeding time on bone mineral density (BMD) later in life.Material and methodsThe current study was based on a retrospective analysis of 586 postmenopausal women with a mean age of 60.8 years, who were screened for osteoporosis by dual energy X-ray absorptiometry (DXA).They were classified into 4 groups with respect to the duration of their breast-feeding as never (group 1), 1-24 months (group 2), 25-60 months (group 3), or > 60 months (group 4). Bone mineral density results for the femur neck and lumbar spine were classified into 3 groups according to WHO criteria as normal (T score > –1.0 SD), osteopenia (T score –1.0 to –2.5 SD), and osteoporosis (T score < –2.5 SD). Patients with osteopenia or osteoporosis (T score < –1.0 SD) were considered as having low bone mass (LBM).ResultsWe found a correlation between duration of lactation and femur BMD or spine BMD in the study population (r = 0.116, p < 0.005; r = –0.151, p = 0.001, respectively). Significant differences were found between femur BMD and spine BMD of groups in one-way ANOVA analysis (p = 0.025, p = 0.005, respectively). Additionally, when compared with the other three groups, group 4 was older and had longer duration of menopause (p < 0.01). In logistic regression analysis, age and body mass index were found as independent risk factors of LBM [odds ratio: 1.084 (95% CI 1.031-1.141); odds ratio: 0.896 (95% CI 0.859-0.935)], while duration of lactation was not found as an independent predictor of LBM.ConclusionsIn this study, we have found that changes of bone metabolism during lactation had no effect on postmenopausal BMD measured by DXA. Consequently, it can be suggested that long breast-feeding duration is not a risk factor for low bone mass later in life.

PSYCHIATRIST.COM Method. The data derived from a retrospective study investigating demographic characteristics, diagnosis, and medication of all inpatients between August 1, 2002, and August 31, 2004, who were admitted to the Department of Child and Adolescent Psychiatry of Innsbruck Medical University. Seventy inpatients were prescribed drugs for the time after discharge. Data about further drug intake, consultations (psychiatrist or general practitioner), and weight gain were evaluated by follow-up interviews. Twenty-two of the 70 could not be contacted or were not willing to give any further information, and 48 patients were included in the study. Their mean ± SD age was 15.8 ± 1.7 years (range, 10-18 years), 23 (48%) were male, and 25 (52%) were female. According to DSM-IV criteria, 8 (17%) were diagnosed with schizophrenia, 22 (46%) with mood disorders (including adjustment disorders), 11 (23%) with disruptive behavior disorders, and 7 (15%) had other diagnoses (misuse of psychoactive substances, mental retardation, personality disorders, and development disorders). They were treated with antipsychotics (48%, N = 23; risperidone, olanzapine, clozapine, quetiapine, amisulpride, and ziprasidone) and antidepressants (52%, N = 25; citalopram, mirtazapine, fluoxetine, sertraline, escitalopram, trazodone, and venlafaxine).The effects of age, gender, time since discharge (≤ 6 months, 46%; > 6 months, 54%), weight gain (< 5 kg versus ≥ 5 kg), and pharmacologic treatment (antidepressant versus antipsychotic) on adherence were investigated by means of logistic regression with backward variable selection. The same method was applied to analyze the effects of the above-mentioned variables on weight gain. Odds ratios were calculated to quantify the effect of the potential risk factors. The logistic regression was supplemented by bivariate analyses of the associations between adherence and the individual potential risk factors using Fisher exact test.Results. Forty-six of 48 patients took part in follow-up consultations. Twenty-two patients continued the drug intake at the point of the interview, 12 had discontinued the drug intake after consulting their psychiatrist or general practitioner, and 12 had discontinued without consulting. These 12 patients were classified as noncompliant.When considering the effects of age, gender, time since discharge, weight gain, and pharmacologic treatment on adherence one by one, 2 variables were found to significantly increase the probability of nonadherence, namely, antidepressive treatment (p = .017) and diagnostic group (mood disorders versus all other diagnoses, p < .001). However, when investigating the potential risk factors jointly by logistic regression, only the effect of the diagnostic group remained significant (odds ratio = 26.4, p = .003, logistic regression), whereas the significance of antidepressive treatment disappeared (odds ratio = 4.33, p = .122, logistic regression). Obviously, the difference in adherence rate between patients with and without antidepressive treatm...