Highly sensitive C-reactive protein and male gender are independently related to the severity of coronary disease in patients with metabolic syndrome and an acute coronary event

Patients with metabolic syndrome are at high-risk for development of atherosclerosis and cardiovascular events. The objective of this study was to examine the major determinants of coronary disease severity, including those coronary risk factors associated with metabolic syndrome, during the early period after an acute coronary episode. We tested the hypothesis that inflammatory markers, especially highly sensitive C-reactive protein (hsCRP), are related to coronary atherosclerosis, in addition to traditional coronary risk factors. Subjects of both genders aged 30 to 75 years (N = 116) were prospectively included if they had suffered a recent acute coronary syndrome (acute myocardial infarction or unstable angina pectoris requiring hospitalization) and if they had metabolic syndrome diagnosed according to the National Cholesterol Education Program/Adult Treatment Panel III. Patients were submitted to a coronary angiography and the burden of atherosclerosis was estimated by the Gensini score. The severity of coronary disease was correlated (Spearman’s or Pearson’s coefficient) with gender (r = 0.291, P = 0.008), age (r = 0.218, P = 0.048), hsCRP (r = 0.256, P = 0.020), ApoB/ApoA ratio (r = 0.233, P = 0.041), and carotid intima-media thickness (r = 0.236, P = 0.041). After multiple linear regression, only male gender (P = 0.046) and hsCRP (P = 0.012) remained independently associated with the Gensini score. In this high-risk population, male gender and high levels of hsCRP, two variables that can be easily obtained, were associated with more extensive coronary disease, identifying patients with the highest potential of developing new coronary events.

Body composition measures of obese adolescents by the deuterium oxide dilution method and by bioelectrical impedance

The objectives of the present study were to describe and compare the body composition variables determined by bioelectrical impedance (BIA) and the deuterium dilution method (DDM), to identify possible correlations and agreement between the two methods, and to construct a linear regression model including anthropometric measures. Obese adolescents were evaluated by anthropometric measures, and body composition was assessed by BIA and DDM. Forty obese adolescents were included in the study. Comparison of the mean values for the following variables: fat body mass (FM; kg), fat-free mass (FFM; kg), and total body water (TBW; %) determined by DDM and by BIA revealed significant differences. BIA overestimated FFM and TBW and underestimated FM. When compared with data provided by DDM, the BIA data presented a significant correlation with FFM (r = 0.89; P < 0.001), FM (r = 0.93; P < 0.001) and TBW (r = 0.62; P < 0.001). The Bland-Altman plot showed no agreement for FFM, FM or TBW between data provided by BIA and DDM. The linear regression models proposed in our study with respect to FFM, FM, and TBW were well adjusted. FFM obtained by DDM = 0.842 x FFM obtained by BIA. FM obtained by DDM = 0.855 x FM obtained by BIA + 0.152 x weight (kg). TBW obtained by DDM = 0.813 x TBW obtained by BIA. The body composition results of obese adolescents determined by DDM can be predicted by using the measures provided by BIA through a regression equation.

Caffeine intake by patients with autosomal dominant polycystic kidney disease

Because caffeine may induce cyst and kidney enlargement in autosomal dominant polycystic kidney disease (ADPKD), we evaluated caffeine intake and renal volume using renal ultrasound in ADPKD patients. Caffeine intake was estimated by the average of 24-h dietary recalls obtained on 3 nonconsecutive days in 102 ADPKD patients (68 females, 34 males; 39 ± 12 years) and compared to that of 102 healthy volunteers (74 females, 28 males; 38 ± 14 years). The awareness of the need for caffeine restriction was assessed. Clinical and laboratory data were obtained from the medical records of the patients. Mean caffeine intake was significantly lower in ADPKD patients versus controls (86 vs 134 mg/day), and 63% of the ADPKD patients had been previously aware of caffeine restriction. Caffeine intake did not correlate with renal volume in ADPKD patients. There were no significant differences between the renal volumes of patients in the highest and lowest tertiles of caffeine consumption. Finally, age-adjusted multiple linear regression revealed that renal volume was associated with hypertension, chronic kidney disease stage 3 and the time since diagnosis, but not with caffeine intake. The present small cross-sectional study indicated a low level of caffeine consumption by ADPKD patients when compared to healthy volunteers, which was most likely due to prior awareness of the need for caffeine restriction. Within the range of caffeine intake observed by ADPKD patients in this study (0-471 mg/day), the renal volume was not directly associated with caffeine intake.

Biological significance of miR-126 expression in atrial fibrillation and heart failure

We investigated the biological significance of microRNA-126 (miR-126) expression in patients with atrial fibrillation (AF) and/or heart failure (HF) to examine the possible mechanism of miR-126-dependent AF and development of HF. A total of 103 patients were divided into three groups: AF group (18 men and 17 women, mean age: 65.62±12.72 years), HF group (17 men and 15 women, mean age: 63.95±19.71 years), and HF-AF group (20 men and 16 women, mean age: 66.56±14.37 years). Quantitative real-time PCR was used to measure relative miR-126 expression as calculated by the 2−ΔΔCt method. miR-126 was frequently downregulated in the 3 patient groups compared with controls. This reduction was significantly lower in permanent and persistent AF patients than in those with paroxysmal AF (P<0.05, t-test). Moreover, miR-126 expression was markedly lower in the HF-AF group compared with the AF and HF groups. The 3 patient groups had higher N-terminal prohormone brain natriuretic peptide (NT-proBNP) levels, lower left ventricular ejection fraction (LVEF), larger left atrial diameter, and higher cardiothoracic ratio compared with controls. There were significant differences in NT-proBNP levels and LVEF among the AF, HF, and HF-AF groups. Pearson correlation analysis showed that relative miR-126 expression was positively associated with LVEF, logarithm of NT-proBNP, left atrial diameter, cardiothoracic ratio, and age in HF-AF patients. Multiple linear regression analysis showed that miR-126 expression was positively correlated with LVEF, but negatively correlated with the logarithm of NT-pro BNP and the cardiothoracic ratio (all P<0.05). Serum miR-126 levels could serve as a potential candidate biomarker for evaluating the severity of AF and HF. However, to confirm these results, future studies with a larger and diverse patient population are necessary.

Association between tooth loss and obesity in Brazilian adults: a population-based study

OBJECTIVE: To examine the association between tooth loss and general and central obesity among adults. METHODS: Population-based cross-sectional study with 1,720 adults aged 20 to 59 years from Florianópolis, Southern Brazil. Home interviews were performed and anthropometric measures were taken. Information on sociodemographic data, self-reported diabetes, self-reported number of teeth, central obesity (waist circumference [WC] > 88 cm in women and > 102 cm in men) and general obesity (body mass index [BMI] ≥ 30 kg/m²) was collected. We used multivariable Poisson regression models to assess the association between general and central obesity and tooth loss after controlling for confounders. We also performed simple and multiple linear regressions by using BMI and WC as continuous variables. Interaction between age and tooth loss was also assessed. RESULTS: The mean BMI was 25.9 kg/m² (95%CI 25.6;26.2) in men and 25.4 kg/m2 (95%CI 25.0;25.7) in women. The mean WC was 79.3 cm (95%CI 78.4;80.1) in men and 88.4 cm (95%CI 87.6;89.2) in women. A positive association was found between the presence of less than 10 teeth in at least one arch and increased mean BMI and WC after adjusting for education level, self-reported diabetes, gender and monthly per capita income. However, this association was lost when the variable age was included in the model. The prevalence of general obesity was 50% higher in those with less than 10 teeth in at least one arch when compared with those with 10 or more teeth in both arches after adjusting for education level, self-reported diabetes and monthly per capita family income. However, the statistical significance was lost after controlling for age. CONCLUSIONS: Obesity was associated with number of teeth, though it depended on the participants' age groups.

Limited-sampling strategy models for estimating the pharmacokinetic parameters of 4-methylaminoantipyrine, an active metabolite of dipyrone

Bioanalytical data from a bioequivalence study were used to develop limited-sampling strategy (LSS) models for estimating the area under the plasma concentration versus time curve (AUC) and the peak plasma concentration (Cmax) of 4-methylaminoantipyrine (MAA), an active metabolite of dipyrone. Twelve healthy adult male volunteers received single 600 mg oral doses of dipyrone in two formulations at a 7-day interval in a randomized, crossover protocol. Plasma concentrations of MAA (N = 336), measured by HPLC, were used to develop LSS models. Linear regression analysis and a "jack-knife" validation procedure revealed that the AUC0-¥ and the Cmax of MAA can be accurately predicted (R²>0.95, bias <1.5%, precision between 3.1 and 8.3%) by LSS models based on two sampling times. Validation tests indicate that the most informative 2-point LSS models developed for one formulation provide good estimates (R²>0.85) of the AUC0-¥ or Cmax for the other formulation. LSS models based on three sampling points (1.5, 4 and 24 h), but using different coefficients for AUC0-¥ and Cmax, predicted the individual values of both parameters for the enrolled volunteers (R²>0.88, bias = -0.65 and -0.37%, precision = 4.3 and 7.4%) as well as for plasma concentration data sets generated by simulation (R²>0.88, bias = -1.9 and 8.5%, precision = 5.2 and 8.7%). Bioequivalence assessment of the dipyrone formulations based on the 90% confidence interval of log-transformed AUC0-¥ and Cmax provided similar results when either the best-estimated or the LSS-derived metrics were used.

Artificial neural network models for predicting 1-year mortality in elderly patients with intertrochanteric fractures in China

The mortality rate of older patients with intertrochanteric fractures has been increasing with the aging of populations in China. The purpose of this study was: 1) to develop an artificial neural network (ANN) using clinical information to predict the 1-year mortality of elderly patients with intertrochanteric fractures, and 2) to compare the ANN's predictive ability with that of logistic regression models. The ANN model was tested against actual outcomes of an intertrochanteric femoral fracture database in China. The ANN model was generated with eight clinical inputs and a single output. ANN's performance was compared with a logistic regression model created with the same inputs in terms of accuracy, sensitivity, specificity, and discriminability. The study population was composed of 2150 patients (679 males and 1471 females): 1432 in the training group and 718 new patients in the testing group. The ANN model that had eight neurons in the hidden layer had the highest accuracies among the four ANN models: 92.46 and 85.79% in both training and testing datasets, respectively. The areas under the receiver operating characteristic curves of the automatically selected ANN model for both datasets were 0.901 (95%CI=0.814-0.988) and 0.869 (95%CI=0.748-0.990), higher than the 0.745 (95%CI=0.612-0.879) and 0.728 (95%CI=0.595-0.862) of the logistic regression model. The ANN model can be used for predicting 1-year mortality in elderly patients with intertrochanteric fractures. It outperformed a logistic regression on multiple performance measures when given the same variables.