89 resultados para Probability sample


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PURPOSE: The aim of this study was to analyze the prevalence of urinary incontinence (UI) in a community sample from the city of Sao Paulo. METHODS: This epidemiological survey was conducted at a family health program in Sao Paulo, Brazil, using randomized sampling. Data were collected by interviewing residents and were analyzed by Pearson`s correlation coefficients, chi-square tests, and logistic regression analysis. RESULTS: Seventy (10.7%) of the 657 subjects currently presented UI, including 50.7% with sporadic UI and 74.3% with UI upon moderate efforts. Ninety-three percent woke up during the night, 43.7% maintained continence until the bathroom, 63.4% had a sensation of wetness, and 77.5% reported no use of any continence aids. Female gender, advanced age, gynecologic or urologic surgery, dysuria, and urinary tract infection were correlated with UI (P < .001; r(2) = 0.572). CONCLUSION: The overall prevalence of UI was found to be high and was comparable to results from multiple countries.

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Experiments based on a 2(3) central composite full factorial design were carried out in 200-ml stainless-steel containers to study the pretreatment, with dilute sulfuric acid, of a sugarcane bagasse sample obtained from a local sugar-alcohol mill. The independent variables selected for study were temperature, varied from 112.5A degrees C to 157.5A degrees C, residence time, varied from 5.0 to 35.0 min, and sulfuric acid concentration, varied from 0.0% to 3.0% (w/v). Bagasse loading of 15% (w/w) was used in all experiments. Statistical analysis of the experimental results showed that all three independent variables significantly influenced the response variables, namely the bagasse solubilization, efficiency of xylose recovery in the hemicellulosic hydrolysate, efficiency of cellulose enzymatic saccharification, and percentages of cellulose, hemicellulose, and lignin in the pretreated solids. Temperature was the factor that influenced the response variables the most, followed by acid concentration and residence time, in that order. Although harsher pretreatment conditions promoted almost complete removal of the hemicellulosic fraction, the amount of xylose recovered in the hemicellulosic hydrolysate did not exceed 61.8% of the maximum theoretical value. Cellulose enzymatic saccharification was favored by more efficient removal of hemicellulose during the pretreatment. However, detoxification of the hemicellulosic hydrolysate was necessary for better bioconversion of the sugars to ethanol.

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This study aimed to correlate the efficiency of enzymatic hydrolysis of the cellulose contained in a sugarcane bagasse sample pretreated with dilute H(2)SO(4) with the levels of independent variables such as initial content of solids and loadings of enzymes and surfactant (Tween 20), for two cellulolytic commercial preparations. The preparations, designated cellulase I and cellulase II, were characterized regarding the activities of total cellulases, endoglucanase, cellobiohydrolase, cellobiase, beta-glucosidase, xylanase, and phenoloxidases (laccase, manganese and lignin peroxidases), as well as protein contents. Both extracts showed complete cellulolytic complexes and considerable activities of xylanases, without activities of phenoloxidases. For the enzymatic hydrolyses, two 2(3) central composite full factorial designs were employed to evaluate the effects caused by the initial content of solids (1.19-4.81%, w/w) and loadings of enzymes (1.9-38.1 FPU/g bagasse) and Tween 20 (0.0-0.1 g/g bagasse) on the cellulose digestibility. Within 24 h of enzymatic hydrolysis, all three independent variables influenced the conversion of cellulose by cellulase I. Using cellulase II, only enzyme and surfactant loadings showed significant effects on cellulose conversion. An additional experiment demonstrated the possibility of increasing the initial content of solids to values much higher than 4.81% (w/w) without compromising the efficiency of cellulose conversion, consequently improving the glucose concentration in the hydrolysate.

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Purpose Adverse drug events (ADEs) are harmful and occur with alarming frequency in critically ill patients. Complex pharmacotherapy with multiple medications increases the probability of a drug interaction (DI) and ADEs in patients in intensive care units (ICUs). The objective of the study is to determine the frequency of ADEs among patients in the ICU of a university hospital and the drugs implicated. Also, factors associated with ADEs are investigated. Methods This cross-sectional study investigated 299 medical records of patients hospitalized for 5 or more days in an ICU. ADEs were identified through intensive monitoring adopted in hospital pharmacovigilance and also ADE triggers. Adverse drug reactions (ADR) causality was classified using the Naranjo algorithm. Data were analyzed through descriptive analysis, and through univariate and multiple logistic regression. Results The most frequent ADEs were ADRs type A, of possible causality and moderate severity. The most frequent ADR was drug-induced acute kidney injury. Patients with ADEs related to DIs corresponded to 7% of the sample. The multiple logistic regression showed that length of hospitalization (OR = 1.06) and administration of cardiovascular drugs (OR = 2.2) were associated with the occurrence of ADEs. Conclusion Adverse drug reactions of clinical significance were the most frequent ADEs in the ICU studied, which reduces patient safety. The number of ADEs related to drug interactions was small, suggesting that clinical manifestations of drug interactions that harm patients are not frequent in ICUs.

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In this paper, we compare three residuals to assess departures from the error assumptions as well as to detect outlying observations in log-Burr XII regression models with censored observations. These residuals can also be used for the log-logistic regression model, which is a special case of the log-Burr XII regression model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is 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 the modified martingale-type residual in log-Burr XII regression models with censored data.

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In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model.

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This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is 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 for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

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In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

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We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap 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. Further, for different parameter settings, sample sizes, and censoring percentages, several 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 extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.

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A three-phase hollow-fiber liquid-phase microextraction method for the analysis of rosiglitazone and its metabolites N-desmethyl rosiglitazone and p-hydroxy rosiglitazone in microsomal preparations is described for the first time. The drug and metabolites HPLC determination was carried out using an X-Terra RP-18 column, at 22 degrees C. The mobile phase was composed of water, acetonitrile and acetic acid (85:15:0.5, v/v/v) and the detection was performed at 245 nm. The hollow-fiber liquid-phase microextraction procedure was optimized using multifactorial experiments and the following optimal condition was established: sample agitation at 1750 rpm, extraction for 30 min, hydrochloric acid 0.01 mol/L as acceptor phase, 1-octanol as organic phase, and donor phase pH adjustment to 8.0. The recovery rates, obtained by using 1 mL of microsomal preparation, were 47-70%. The method presented LOQs of 50 ng/mL and it was linear over the concentration range of 50-6000 ng/mL, with correlation coefficients (r) higher than 0.9960, for all analytes. The validated method was employed to study the in vitro biotransformation of rosiglitazone using rat liver microsomal fraction.

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Despite the necessity to differentiate chemical species of mercury in clinical specimens, there area limited number of methods for this purpose. Then, this paper describes a simple method for the determination of methylmercury and inorganic mercury in blood by using liquid chromatography with inductively coupled mass spectrometry (LC-ICP-MS) and a fast sample preparation procedure. Prior to analysis, blood (250 mu L) is accurately weighed into 15-mL conical tubes. Then, an extractant solution containing mercaptoethanol, L-cysteine and HCI was added to the samples following sonication for 15 min. Quantitative mercury extraction was achieved with the proposed procedure. Separation of mercury species was accomplished in less than 5 min on a C18 reverse-phase column with a mobile phase containing 0.05% (v/v) mercaptoethanol, 0.4% (m/v) L-cysteine, 0.06 mol L(-1) ammonium acetate and 5% (v/v) methanol. The method detection limits were found to be 0.25 mu g L(-1) and 0.1 mu Lg L(-1) for inorganic mercury and methylmercury, respectively. Method accuracy is traceable to Standard Reference Material (SRM) 966 Toxic Metals in Bovine Blood from the National Institute of Standards and Technology (NIST). The proposed method was also applied to the speciation of mercury in blood samples collected from fish-eating communities and from rats exposed to thimerosal. With the proposed method there is a considerable reduction of the time of sample preparation prior to speciation of Hg by LC-ICP-MS. Finally, after the application of the proposed method, we demonstrated an interesting in vivo ethylmercury conversion to inorganic mercury. (C) 2009 Elsevier B.V. All rights reserved.

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A simple method for mercury speciation in hair samples with a fast sample preparation procedure using high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry is proposed. Prior to analysis, 50 mg of hair samples were accurately weighed into 15 mL conical tubes. Then, an extractant solution containing mercaptoethanol, L-cysteine and HCl was added to the samples following sonication for 10 min. Quantitative mercury extraction was achieved with the proposed procedure. Separation of inorganic mercury (Ino-Hg), methylmercury (Met-Hg) and ethylmercury (Et-Hg) was accomplished in less than 8 min on a C18 reverse phase column with a mobile phase containing 0.05% v/v mercaptoethanol, 0.4% m/v L-cysteine, 0.06 mol L(-1) ammonium acetate and 5% v/v methanol. The method detection limits were found to be 15 ng g(-1), 10 ng g(-1) and 38 ng g(-1), for inorganic mercury, methylmercury and ethylmercury, respectively. Sample throughput is 4 samples h(-1) (duplicate). A considerable improvement in the time of analysis was achieved when compared to other published methods. Method accuracy is traceable to Certified Reference Materials (CRMs) 85 and 86 human hair from the International Atomic Energy Agency (IAEA). Finally, the proposed method was successfully applied to the speciation of mercury in hair samples collected from fish-eating communities of the Brazilian Amazon.

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A simple method with a fast sample preparation procedure for total and inorganic mercury determinations in blood samples is proposed based on flow injection cold vapor inductively coupled plasma mass spectrometry (FI-CVICP-MS). Aliquots of whole blood (500 mL) are diluted 1 + 1 v/v with 10.0% v/v tetramethylammonium hydroxide (TMAH) solution, incubated for 3 h at room temperature and then further diluted 1 + 4 v/v with 2.0% v/v HCl. The inorganic Hg was released by online addition of L-cysteine and then reduced to elemental Hg by SnCl(2). On the other hand, total mercury was determined by on-line addition of KMnO(4) and then reduced to elemental Hg by NaBH(4). Samples were calibrated against matrix-matching. The method detection limit was found to be 0.80 mu g L(-1) and 0.08 mu g L(-1) for inorganic and total mercury, respectively. Sample throughput is 20 samples h(-1). The method accuracy is traceable to Standard Reference Material (SRM) 966 Toxic Metals in Bovine Blood from the National Institute of Standards and Technology (NIST). For additional validation purposes, human whole blood samples were analyzed by the proposed method and by an established CV AAS method, with no statistical difference between the two techniques at 95% confidence level on applying the t-test.

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A simple and fast method is described for simultaneous determination of methylmercury (MeHg), ethylmercury (Et-Hg) and inorganic mercury (Ino-Hg) in blood samples by using capillary gas chromatography-inductively coupled plasma mass spectrometry (GC-ICP-MS) after derivatization and alkaline digestion. Closed-vessel microwave assisted digestion conditions with tetramethylammonium hydroxide (TMAH) have been optimized. Derivatization by using ethylation and propylation procedures have also been evaluated and compared. The absolute detection limits (using a 1 mu L injection) obtained by GC-ICP-MS with ethylation were 40 fg for MeHg and Ino-Hg, respectively, and with propylation were 50, 20 and 50 fg for MeHg, Et-Hg and Ino-Hg, respectively. Method accuracy is traceable to Standard Reference Material (SRM) 966 Toxic Metals in Bovine Blood from the National Institute of Standards and Technology (NIST). Additional validation is provided based on the comparison of results obtained for mercury speciation in blood samples with the proposed procedure and with a previously reported LC-ICP-MS method. With the new proposed procedure no tedious clean-up steps are required and a considerable improvement of the time of analysis was achieved compared to other methods using GC separation.

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Aims: To estimate dementia prevalence and describe the etiology of dementia in a community sample from the city of Sao Paulo, Brazil. Methods: A sample of subjects older than 60 years was screened for dementia in the first phase. During the second phase, the diagnostic workup included a structured interview, physical and neurological examination, laboratory exams, a brain scan, and DSM-IV criteria diagnosis. Results: Mean age was 71.5 years (n = 1,563) and 58.3% had up to 4 years of schooling (68.7% female). Dementia was diagnosed in 107 subjects with an observed prevalence of 6.8%. The estimate of dementia prevalence was 12.9%, considering design effect, nonresponse during the community phase, and positive and negative predictive values. Alzheimer`s disease was the most frequent cause of dementia (59.8%), followed by vascular dementia (15.9%). Older age and illiteracy were significantly associated with dementia. Conclusions: The estimate of dementia prevalence was higher than previously reported in Brazil, with Alzheimer`s disease and vascular dementia being the most frequent causes of dementia. Dementia prevalence in Brazil and in other Latin American countries should be addressed by additional studies to confirm these higher dementia rates which might have a sizable impact on countries` health services. Copyright (C) 2008 S. Karger AG, Basel