Geriatric urolithiasis in the emergency department: risk factors for hospitalisation and emergency management patterns of acute urolithiasis

Urolithiasis is one of the most common conditions seen in emergency departments (ED) worldwide, with an increasing frequency in geriatric patients (>65 years). Given the high costs of emergency medical urolithiasis treatment, the need to optimise management is obvious. We aimed to determine risk factors for hospitalisation and evaluate diagnostic and emergency treatment patterns by ED physicians in geriatric urolithiasis patients to assist in optimising treatment.

Variation of Patterns of Malocclusion by Site of Pharyngeal Obstruction in Children

Objective: To correlate the type of dental occlusion and the type of pharyngeal lymphoid tissue obstruction in children. Design: Cross-sectional study. Setting: Ambulatory ear, nose, and throat clinic of Faculdade de Medicina da Universidade de Sao Paulo. Patients: One hundred fourteen children aged 3 to 12 years presenting with mouth breathing and snoring due to tonsil and/or adenoid enlargement. Interventions: Oroscopy and nasal fiber pharyngoscopy complemented by lateral head radiography to diagnose the type of obstruction, and clinical examination to evaluate the dental occlusion. Main Outcome Measures: Tonsil and adenoid obstruction (classified from grades 1-4) and sagittal, transverse, and vertical evaluation of dental occlusion. Results: Obstructive enlargement of both tonsils and adenoids was detected in 64.9% of the sample; isolated enlargement of the adenoids, in 21.9%; isolated enlargement of the palatine tonsils, in 7.0%; and nonobstructive tonsils and adenoids, in 6.1%. All types of pharyngeal obstruction were related to a high prevalence of posterior crossbite (36.8%). Statistically significant association was found between sagittal dental occlusion and the site of lymphoid tissue obstruction (P = .02). A higher rate of class II relationship (43.2%) was detected in the group with combined adenoid and tonsil obstructive enlargement. Isolated tonsil obstruction showed a higher rate of class III relationship (37.5%). Conclusions: Different sites of obstruction of the upper airway due to enlarged lymphoid tissue are associated with different types of dental malocclusion. Findings are relevant to orthodontic and surgical decision making in these mouth-breathing patients.

Duality of patterns in hepatitis a epidemiology: A study involving two socioeconomically distinct populations in Campinas, São Paulo state, Brazil

To evaluate the prevalence of antibodies against hepatitis A in two socioeconomically distinct populations, 101 and 82 serum samples from high and low socioeconomic groups, respectively, were analysed for the presence of IgG anti-HAV using a commercial ELISA. The prevalence in low socioeconomic level subjects was 95.0%, whereas in high socioeconomic subjects was only 19.6% (p<0.001). These data show a duality in Brazil: anti-HAV prevalence in low socioeconomic subjects is similar to that of developing countries, while in high socioeconomic subjects, a pattern typical of developed countries is found. The control of this infection in our country is primarily related to the improvement of sanitation, but especially for high socioeconomic level populations, the use of vaccination against hepatitis A is strongly advisable to avoid the occasional appearance of this disease in adults.

Longitudinal analysis of patterns and predictors of changes in self-reported adherence to antiretroviral therapy: Swiss HIV Cohort Study.

BACKGROUND: Adherence to combination antiretroviral therapy (cART) is a dynamic process, however, changes in adherence behavior over time are insufficiently understood. METHODS: Data on self-reported missed doses of cART was collected every 6 months in Swiss HIV Cohort Study participants. We identified behavioral groups associated with specific cART adherence patterns using trajectory analyses. Repeated measures logistic regression identified predictors of changes in adherence between consecutive visits. RESULTS: Six thousand seven hundred nine individuals completed 49,071 adherence questionnaires [median 8 (interquartile range: 5-10)] during a median follow-up time of 4.5 years (interquartile range: 2.4-5.1). Individuals were clustered into 4 adherence groups: good (51.8%), worsening (17.4%), improving (17.6%), and poor adherence (13.2%). Independent predictors of worsening adherence were younger age, basic education, loss of a roommate, starting intravenous drug use, increasing alcohol intake, depression, longer time with HIV, onset of lipodystrophy, and changing care provider. Independent predictors of improvements in adherence were regimen simplification, changing class of cART, less time on cART, and starting comedications. CONCLUSIONS: Treatment, behavioral changes, and life events influence patterns of drug intake in HIV patients. Clinical care providers should routinely monitor factors related to worsening adherence and intervene early to reduce the risk of treatment failure and drug resistance.

Analysis of patterns in mining time series using Qlucore

Raw measurement data does not always immediately convey useful information, but applying mathematical statistical analysis tools into measurement data can improve the situation. Data analysis can offer benefits like acquiring meaningful insight from the dataset, basing critical decisions on the findings, and ruling out human bias through proper statistical treatment. In this thesis we analyze data from an industrial mineral processing plant with the aim of studying the possibility of forecasting the quality of the final product, given by one variable, with a model based on the other variables. For the study mathematical tools like Qlucore Omics Explorer (QOE) and Sparse Bayesian regression (SB) are used. Later on, linear regression is used to build a model based on a subset of variables that seem to have most significant weights in the SB model. The results obtained from QOE show that the variable representing the desired final product does not correlate with other variables. For SB and linear regression, the results show that both SB and linear regression models built on 1-day averaged data seriously underestimate the variance of true data, whereas the two models built on 1-month averaged data are reliable and able to explain a larger proportion of variability in the available data, making them suitable for prediction purposes. However, it is concluded that no single model can fit well the whole available dataset and therefore, it is proposed for future work to make piecewise non linear regression models if the same available dataset is used, or the plant to provide another dataset that should be collected in a more systematic fashion than the present data for further analysis.

Analysis of Patterns in Electricity Spot Market Time Series

Due to its non-storability, electricity must be produced at the same time that it is consumed, as a result prices are determined on an hourly basis and thus analysis becomes more challenging. Moreover, the seasonal fluctuations in demand and supply lead to a seasonal behavior of electricity spot prices. The purpose of this thesis is to seek and remove all causal effects from electricity spot prices and remain with pure prices for modeling purposes. To achieve this we use Qlucore Omics Explorer (QOE) for the visualization and the exploration of the data set and Time Series Decomposition method to estimate and extract the deterministic components from the series. To obtain the target series we use regression based on the background variables (water reservoir and temperature). The result obtained is three price series (for Sweden, Norway and System prices) with no apparent pattern.

Typographic meaning: readers’ impressions of patterns of typographic differentiation

This research explores whether patterns of typographic differentiation influence readers’ impressions of documents. It develops a systematic approach to typographic investigation that considers relationships between different kinds of typographic attributes, rather than testing the influence of isolated variables. An exploratory study using multiple sort tasks and semantic differential scales identifies that readers form a variety of impressions in relation to how typographic elements are differentiated in document design. Building on the findings of the exploratory study and analysis of a sample of magazines, the research describes three patterns of typographic differentiation: high, moderate, and low. Each pattern comprises clusters of typographic attributes and organisational principles that are articulated in relation to a specified level of typographic differentiation (amplified, medium, or subtle). The patterns are applied to two sets of controlled test material. Using this purposely-designed material, the influence of patterns of typographic differentiation on readers’ impressions of documents is explored in a repertory grid analysis and a paired comparison procedure. The results of these studies indicate that patterns of typographic differentiation consistently shape readers’ impressions of documents, influencing judgments of credibility, document address, and intended readership; and suggesting particular kinds of engagement and genre associations. For example, high differentiation documents are likely to be considered casual, sensationalist, and young; moderate differentiation documents are most likely to be seen as formal and serious; and low differentiation examples are considered calm. Typographic meaning is shown to be created through complex, yet systematic, interrelationships rather than reduced to a linear model of increasing or decreasing variation. The research provides a way of describing typographic articulation that has application across a variety of disciplines and design practice. In particular, it illuminates the ways in which typographic presentation is meaningful to readers, providing knowledge that document producers can use to communicate more effectively.

Longitudinal analysis of patterns and predictors of changes in self-reported adherence to antiretroviral therapy: Swiss HIV Cohort Study

Adherence to combination antiretroviral therapy (cART) is a dynamic process, however, changes in adherence behavior over time are insufficiently understood.

Multiple imputation for missing continuous and dichotomous data: The effects of patterns of missingness and variable correlations on type I error with small samples

The purpose of this study is to investigate the effects of predictor variable correlations and patterns of missingness with dichotomous and/or continuous data in small samples when missing data is multiply imputed. Missing data of predictor variables is multiply imputed under three different multivariate models: the multivariate normal model for continuous data, the multinomial model for dichotomous data and the general location model for mixed dichotomous and continuous data. Subsequent to the multiple imputation process, Type I error rates of the regression coefficients obtained with logistic regression analysis are estimated under various conditions of correlation structure, sample size, type of data and patterns of missing data. The distributional properties of average mean, variance and correlations among the predictor variables are assessed after the multiple imputation process. ^ For continuous predictor data under the multivariate normal model, Type I error rates are generally within the nominal values with samples of size n = 100. Smaller samples of size n = 50 resulted in more conservative estimates (i.e., lower than the nominal value). Correlation and variance estimates of the original data are retained after multiple imputation with less than 50% missing continuous predictor data. For dichotomous predictor data under the multinomial model, Type I error rates are generally conservative, which in part is due to the sparseness of the data. The correlation structure for the predictor variables is not well retained on multiply-imputed data from small samples with more than 50% missing data with this model. For mixed continuous and dichotomous predictor data, the results are similar to those found under the multivariate normal model for continuous data and under the multinomial model for dichotomous data. With all data types, a fully-observed variable included with variables subject to missingness in the multiple imputation process and subsequent statistical analysis provided liberal (larger than nominal values) Type I error rates under a specific pattern of missing data. It is suggested that future studies focus on the effects of multiple imputation in multivariate settings with more realistic data characteristics and a variety of multivariate analyses, assessing both Type I error and power. ^

First steps in the discovery of patterns in the academic results of telecommunication engineering students in the subjects Analysis of Circuits and Mathematics

In this paper, the results of six years of research in engineering education, in the application of the European Higher Education Area (EHEA) to improve the performance of the students in the subject Analysis of Circuits of Telecommunication Engineering, are analysed taking into consideration the fact that there would be hidden variables that both separate students into subgroups and show the connection among several basic subjects such as Analysis of Circuits (AC) and Mathematics (Math). The discovery of these variables would help us to explain the characteristics of the students through the teaching and learning methodology, and would show that there are some characteristics that instructors do not take into account but that are of paramount importance

Multiscale assessment of patterns of avian species richness

The search for a common cause of species richness gradients has spawned more than 100 explanatory hypotheses in just the past two decades. Despite recent conceptual advances, further refinement of the most plausible models has been stifled by the difficulty of compiling high-resolution databases at continental scales. We used a database of the geographic ranges of 2,869 species of birds breeding in South America (nearly a third of the world's living avian species) to explore the influence of climate, quadrat area, ecosystem diversity, and topography on species richness gradients at 10 spatial scales (quadrat area, ≈12,300 to ≈1,225,000 km2). Topography, precipitation, topography × latitude, ecosystem diversity, and cloud cover emerged as the most important predictors of regional variability of species richness in regression models incorporating 16 independent variables, although ranking of variables depended on spatial scale. Direct measures of ambient energy such as mean and maximum temperature were of ancillary importance. Species richness values for 1° × 1° latitude-longitude quadrats in the Andes (peaking at 845 species) were ≈30–250% greater than those recorded at equivalent latitudes in the central Amazon basin. These findings reflect the extraordinary abundance of species associated with humid montane regions at equatorial latitudes and the importance of orography in avian speciation. In a broader context, our data reinforce the hypothesis that terrestrial species richness from the equator to the poles is ultimately governed by a synergism between climate and coarse-scale topographic heterogeneity.