New body fat prediction equations for severely obese patients

Background & aims: Severe obesity imposes physical limitations to body composition assessment. Our aim was to compare body fat (BF) estimations of severely obese patients obtained by bioelectrical impedance (BIA) and air displacement plethysmography (ADP) for development of new equations for BF prediction. Methods: Severely obese subjects (83 female/36 mate, mean age = 41.6 +/- 11.6 years) had BF estimated by BIA and ADP. The agreement of the data was evaluated using Bland-Altman`s graphic and concordance correlation coefficient (CCC). A multivariate regression analysis was performed to develop and validate new predictive equations. Results: BF estimations from BIA (64.8 +/- 15 kg) and ADP (65.6 +/- 16.4 kg) did not differ (p > 0.05, with good accuracy, precision, and CCC), but the Bland- Altman graphic showed a wide Limit of agreement (- 10.4; 8.8). The standard BIA equation overestimated BF in women (-1.3 kg) and underestimated BF in men (5.6 kg; p < 0.05). Two BF new predictive equations were generated after BIA measurement, which predicted BF with higher accuracy, precision, CCC, and limits of agreement than the standard BIA equation. Conclusions: Standard BIA equations were inadequate for estimating BF in severely obese patients. Equations developed especially for this population provide more accurate BF assessment. (C) 2008 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Effects of biomass burning on nasal mucociliary clearance and mucus properties after sugarcane harvesting

Objective: Biofuel from sugarcane is widely produced in developing countries and is a clean and renewable alternative source of energy. However, sugarcane harvesting is mostly performed after biomass burning. The aim of this study was to evaluate the effects of harvesting after biomass burning on nasal mucociliary clearance and the nasal mucus properties of farm workers. Methods: Twenty seven sugarcane workers (21-45 years old) were evaluated at the end of two successive time-periods: first at the end of a 6-month harvesting period (harvesting), and then at the end of a 3-month period without harvesting (non-harvesting). Nasal mucociliary clearance was evaluated by the saccharine transit test, and mucus properties were analyzed using in vitro mucus contact angle and mucus transportability by sneeze. Arterial blood pressure, heart rate, respiratory rate, pulse oximetry, body temperature, associated illness, and exhaled carbon monoxide were registered. Results: Data are presented as mean values (95% confidence interval). The multivariate model analysis adjusted for age, body-mass index, smoking status and years of working with this agricultural practice showed that harvesting yielded prolonged saccharine transit test in 7.83 min (1.88-13.78), increased mucus contact angle in 8.68 degrees (3.18-14.17) and decreased transportability by sneeze in 32.12 mm (-44.83 to -19.42) compared with the non-harvesting period. No significant differences were detected in any of the clinical parameter at either time-period. Conclusion: Sugarcane harvesting after biomass burning negatively affects the first barrier of the respiratory system in farm workers by impairing nasal mucociliary clearance and inducing abnormal mucus properties. (C) 2011 Elsevier Inc. All rights reserved.

Altered endothelial function following the Fontan procedure

Objective: Thrombosis has been widely described after the Fontan procedure. The vascular endothelium plays a central role in the control of coagulation and fibrinolysis. The aim of this study was to investigate if patients undergoing a modified Fontan procedure have impaired endothelial function and fibrinolysis in the late postoperative course. Patients and methods: We compared 23 patients aged from 7 to 26 years with age-matched healthy volunteers, collecting blood samples prior to and following standardized venous occlusion testing. Plasma levels of von Willebrand factor antigen, tissue-type plasminogen activator antigen, plasminogen activator inhibitor-1, and D-dimer were measured with enzyme-linked immunosorbent assay. Results: We found increased plasma levels of von Willebrand factor antigen in patients when compared to controls (p = 0.003). At the basal condition, concentrations of tissue-type plasminogen activator antigen and plasminogen activator inhibitor-1 antigen in the plasma, as well as their activity, were not significantly different between patients and controls. Following venous occlusion, concentrations of tissue-type plasminogen activator antigen in the plasma were significantly increased both in patients and controls, compared to pre-occlusion values. D-dimer was within the reference range. Multivariate discriminant analysis differentiated patients and their controls on the basis of differences for plasminogen activator inhibitor-1 and von Willebrand factor antigen (p = 0.0016). Conclusions: Our data suggest that patients with the Fontan circulation may have endothelial dysfunction, as indicated by raised levels of von Willebrand factor. Fibrinolysis seems to be relatively preserved, as suggested by appropriate response to venous occlusion.

Risk of Potential Drug-Drug Interactions among Brazilian Elderly A Population-Based, Cross-Sectional Study

Background: Drug-drug interactions (DDIs) are one of the main causes of adverse reactions related to medications, being responsible for up to 23% of hospital admissions. However, only a few studies have evaluated this problem in elderly Brazilians. Objectives: To determine the prevalence of potential DDIs (PDDIs) in community-dwelling elderly people in Brazil, analyse these interactions with regard to severity and clinical implications, and identify associated factors. Methods: A population-based cross-sectional study was carried out involving 2143 elderly (aged 60 years) residents of the metropolitan area of Sao Paulo, Brazil. Data were obtained from the SABE (Saude, Bem estar e Envelhecimento [Health, Well-Being, and Aging]) survey, which is a multicentre study carried out in seven countries of Latin America and the Caribbean, coordinated by the Pan-American Health Organization. PDDIs were analysed using a computerized program and categorized according to level of severity, onset, mechanism and documentation in the literature. The STATA software statistical package was used for data analysis, and logistic regression was conducted to determine whether variables were associated with PDDIs. Results: Analysis revealed that 568 (26.5%) of the elderly population included in the study were taking medications that could lead to a DDI. Almost two-thirds (64.4%) of the elderly population exposed to PDDIs were women, 50.7% were aged >= 75 years, 71.7% reported having fair or poor health and 65.8% took 2-5 medications. A total of 125 different PDDIs were identified; the treatment combination of an ACE inhibitor with a thiazide or loop diuretic (associated with hypotension) was the most frequent cause of PDDIs (n=322 patients; 56.7% of individuals with PDDIs). Analysis of the PDDIs revealed that 70.4% were of moderate severity, 64.8% were supported by good quality evidence and 56.8% were considered of delayed onset. The multivariate analysis showed that the risk of a PDDI was significantly increased among elderly individuals using six or more medications (odds ratio [OR] 3.37) and in patients with hypertension (OR 2.56), diabetes mellitus (OR 1.73) or heart problems (OR 3.36). Conclusions: Approximately one-quarter of the elderly population living in Sao Paulo could be taking two or more potentially interacting medicines. Polypharmacy predisposes elderly individuals to PDDIs. More than half of these drug combinations (57.6%, n = 72) were part of commonly employed treatment regimens and may be responsible for adverse reactions that compromise the safety of elderly individuals, especially at home. Educational initiatives are needed to avoid unnecessary risks.

Age and gender influence on maximal bite force and masticatory muscles thickness

The present study aimed investigate the age and gender influence on maximal molar bite force and at outlining the criteria for normal masticatory muscle development in a sample of 177 Brazilian Caucasian dentate individuals aged 7-80 years divided into five age groups: I(7-12 years), II (13-20 years), III (21-40 years), IV (41-60 years), and V (61-80 years). Except for Group V, which comprised nine women and eight men, all groups were equally divided in respect to gender (20 M/20 F). Bite force was recorded with a mouth-adapted 1000 N dynamometer and the highest out of three records was regarded as the maximal bite force. The data were submitted to multivariate statistical analysis (SPSS 17.0 p < 0.05). Effects of group and gender were found, but no interactions between them. The ANOVA showed significant differences between groups bilaterally. Bonferroni`s test showed that group I had significantly lower bite force means at both sides as compared to all groups, except group V. No differences were found between the left and right sides. In all the groups, gender was found to be a significant factor associated with maximal bite force. A global comparison including all the subjects and measures showed that the means of men were approximately 30% higher than those of women, within-group comparisons yielded similar results in all groups. Muscle thickness was measured with a SonoSite Titan ultrasound tool using a high-resolution real-time 56 mm/10 MHz linear-array transducer. Three ultrasound images were obtained from the bilateral masseter and temporal muscles at rest and at maximal voluntary contraction. The means of the three measures in each clinical condition were analyzed with multivariate statistical analysis (SPSS 17.0 p < 0.05). A gradual increase in thickness of the masseter and temporal muscles was found both at rest and maximal voluntary contraction for groups I to IV, whereas a decrease in muscle thickness was observed in group V. Multivariate analysis showed that in both conditions there was an effect of group and gender. The study of the development of the stomatognathic system in relation to age and gender can provide useful data for the identification of normal and impaired functioning patterns. The results of this study indicate that age and gender are associated with structural and functional alterations in the muscles of the stomatognathic system. (C) 2010 Elsevier Ltd. All rights reserved.

Inequalities in dental services utilization among Brazilian low-income children: the role of individual determinants

Objectives: To assess the role of the individual determinants on the inequalities of dental services utilization among low-income children living in the working area of Brazilian`s federal Primary Health Care program, which is called Family Health Program (FHP), in a big city in Southern Brazil. Methods: A cross-sectional population-based study was performed. The sample included 350 children, ages 0 to 14 years, whose parents answered a questionnaire about their socioeconomic conditions, perceived needs, oral hygiene habits, and access to dental services. The data analysis was performed according to a conceptual framework based on Andersen`s behavioral model of health services use. Multivariate models of logistic regression analysis instructed the hypothesis on covariates for never having had a dental visit. Results: Thirty one percent of the surveyed children had never had a dental visit. In the bivariate analysis, higher proportion of children who had never had a dental visit was found among the very young, those with inadequate oral hygiene habits, those without perceived need of dental care, and those whose family homes were under absent ownership. The mechanisms of social support showed to be important enabling factors: children attending schools/kindergartens and being regularly monitored by the FHP teams had higher odds of having gone to the dentist, even after adjusting for socioeconomic, demographic, and need variables. Conclusions: The conceptual framework has confirmed the presence of social and psychosocial inequalities on the utilization pattern of dental services for low-income children. The individual determinants seem to be important predictors of access.

Drizzle and Fog Analysis in the Sao Paulo Metropolitan Area: Changes 1933-2005 and Correlations with other Climate Factors

In order to improve our understanding of climate change, the aim of this research project was to study the climatology and the time trends of drizzle and fog events in the Sao Paulo Metropolitan Area, and the possible connections of this variability with the sea surface temperature (SST) of the Atlantic and Pacific Oceans. The climatology of both phenomena presents differences and similarities. Fog shows a marked maximum frequency in winter and a minimum frequency in summer, while the seasonal differences of drizzle occurrence are less pronounced, there is a maximum in spring, whereas the other seasons present smaller and similar numbers of events. Both phenomena present a negative trend from 1933 to 2005 which is stronger for fog events. A multivariate statistical analysis indicates that the South Atlantic SST could increase warm temperature advection to the continent. This could be one of the responsible factors for the negative tendency in the number of both fog and drizzle events.

PCA Tomography: how to extract information from data cubes

Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector`s orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge.

Investigation of a new GRASP-based clustering algorithm applied to biological data

A large amount of biological data has been produced in the last years. Important knowledge can be extracted from these data by the use of data analysis techniques. Clustering plays an important role in data analysis, by organizing similar objects from a dataset into meaningful groups. Several clustering algorithms have been proposed in the literature. However, each algorithm has its bias, being more adequate for particular datasets. This paper presents a mathematical formulation to support the creation of consistent clusters for biological data. Moreover. it shows a clustering algorithm to solve this formulation that uses GRASP (Greedy Randomized Adaptive Search Procedure). We compared the proposed algorithm with three known other algorithms. The proposed algorithm presented the best clustering results confirmed statistically. (C) 2009 Elsevier Ltd. All rights reserved.

Two-Phase Mapping for Projecting Massive Data Sets

Most multidimensional projection techniques rely on distance (dissimilarity) information between data instances to embed high-dimensional data into a visual space. When data are endowed with Cartesian coordinates, an extra computational effort is necessary to compute the needed distances, making multidimensional projection prohibitive in applications dealing with interactivity and massive data. The novel multidimensional projection technique proposed in this work, called Part-Linear Multidimensional Projection (PLMP), has been tailored to handle multivariate data represented in Cartesian high-dimensional spaces, requiring only distance information between pairs of representative samples. This characteristic renders PLMP faster than previous methods when processing large data sets while still being competitive in terms of precision. Moreover, knowing the range of variation for data instances in the high-dimensional space, we can make PLMP a truly streaming data projection technique, a trait absent in previous methods.

The log-exponentiated Weibull regression model for interval-censored data

In interval-censored survival data, the event of interest is not observed exactly but is only known to occur within some time interval. Such data appear very frequently. In this paper, we are concerned only with parametric forms, and so a location-scale regression model based on the exponentiated Weibull distribution is proposed for modeling interval-censored data. We show that the proposed log-exponentiated Weibull regression model for interval-censored data represents a parametric family of models that include other regression models that are broadly used in lifetime data analysis. Assuming the use of interval-censored data, we employ a frequentist analysis, a jackknife estimator, a parametric bootstrap and a Bayesian analysis for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Furthermore, for different parameter settings, sample sizes and censoring percentages, various simulations are performed; in addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to a modified deviance residual in log-exponentiated Weibull regression models for interval-censored data. (C) 2009 Elsevier B.V. All rights reserved.

Statistical analysis of proficiency testing results under elliptical distributions

The use of inter-laboratory test comparisons to determine the performance of individual laboratories for specific tests (or for calibration) [ISO/IEC Guide 43-1, 1997. Proficiency testing by interlaboratory comparisons - Part 1: Development and operation of proficiency testing schemes] is called Proficiency Testing (PT). In this paper we propose the use of the generalized likelihood ratio test to compare the performance of the group of laboratories for specific tests relative to the assigned value and illustrate the procedure considering an actual data from the PT program in the area of volume. The proposed test extends the test criteria in use allowing to test for the consistency of the group of laboratories. Moreover, the class of elliptical distributions are considered for the obtained measurements. (C) 2008 Elsevier B.V. All rights reserved.

Log-Burr XII regression models with censored data

In survival analysis applications, the failure rate function may frequently present a unimodal shape. In such case, the log-normal or log-logistic distributions are used. In this paper, we shall be concerned only with parametric forms, so a location-scale regression model based on the Burr XII distribution is proposed for modeling data with a unimodal failure rate function as an alternative to the log-logistic regression model. Assuming censored data, we consider a classic analysis, a Bayesian analysis and a jackknife estimator for the parameters of the proposed model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the log-logistic and log-Burr XII regression models. Besides, we use sensitivity analysis to detect influential or outlying observations, and residual analysis is used to check the assumptions in the model. Finally, we analyze a real data set under log-Buff XII regression models. (C) 2008 Published by Elsevier B.V.

Gamma transition intensity determination using multidetector coincidence data

This work describes two similar methods for calculating gamma transition intensities from multidetector coincidence measurements. In the first one, applicable to experiments where the angular correlation function is explicitly fitted, the normalization parameter from this fit is used to determine the gamma transition intensities. In the second, that can be used both in angular correlation or DCO measurements, the spectra obtained for all the detector pairs are summed up, in order to get the best detection statistics possible, and the analysis of the resulting bidimensional spectrum is used to calculate the transition intensities; in this method, the summation of data corresponding to different angles minimizes the influence of the angular correlation coefficient. Both methods are then tested in the calculation of intensities for well-known transitions from a (152)Eu standard source, as well as in the calculation of intensities obtained in beta-decay experiments with (193)Os and (155)Sm sources, yielding excellent results in all these cases. (C) 2009 Elsevier B.V. All rights reserved.

Comparing diagnostic tests with missing data

When missing data occur in studies designed to compare the accuracy of diagnostic tests, a common, though naive, practice is to base the comparison of sensitivity, specificity, as well as of positive and negative predictive values on some subset of the data that fits into methods implemented in standard statistical packages. Such methods are usually valid only under the strong missing completely at random (MCAR) assumption and may generate biased and less precise estimates. We review some models that use the dependence structure of the completely observed cases to incorporate the information of the partially categorized observations into the analysis and show how they may be fitted via a two-stage hybrid process involving maximum likelihood in the first stage and weighted least squares in the second. We indicate how computational subroutines written in R may be used to fit the proposed models and illustrate the different analysis strategies with observational data collected to compare the accuracy of three distinct non-invasive diagnostic methods for endometriosis. The results indicate that even when the MCAR assumption is plausible, the naive partial analyses should be avoided.