Comparison between the reliability levels of manual palpation and pressure pain threshold in children who reported orofacial pain

The aim of this study was to compare the intra-and inter-rater reliability of pressure pain threshold (PPT) and manual palpation (MP) of orofacial structures in symptomatic and symptom-free children for temporomandibular disorders (TMD). Fourteen children reporting pain in masticatory muscles or the temporomandibular joint and 16 symptom-free children were randomly assessed on three different occasions: by rater-1 in the first and third session and by rater-2 in the second session. The trained raters applied algometry and MP as recommended by the Research Diagnostic Criteria for TMD. Intraclass correlation coefficients and the Kappa statistic were used to assess the levels of reliability of PPT and MP, respectively. Excellent intra-and inter-rater reliability levels were observed for PPT values at most of the examined sites for symptom-free children and excellent and moderate reliability levels for children reporting pain. For MP, moderate and poor intra-rater and inter-rater reliability levels were observed for most sites in both groups. Algometry showed higher reliability levels for both groups of children and is recommended for pain assessment in children in association with MP. (C) 2010 Elsevier Ltd. All rights reserved.

Tactile threshold detection in leprosy patients with an electronic algometer

Objective: To propose an electronic method for sensitivity evaluation in leprosy and to compare it to the Semmes-Weinstein monofilaments. Methods:Thirty patients attending the Dermatology outpatient clinic of HCFMRP-USP were consecutively evaluated by both the electronic aesthesiometer and Semmes-Weinstein monofilaments on hand and foot test points. The intraclass correlation coefficient (ICC) was calculated to determine the variability of the electronic measures and the Kappa coefficient was calculated to determine the agreement between methods according to their categories (altered and non-altered tactile sensitivity). Results: The ICC was approximately 1, demonstrating repeatability. The Kappa coefficient showed more than 75 and 63% agreement on the hand and foot points, respectively. The mean agreement between the 2 methods for the 7 points of the right and left hand was 77.14 and 75.71%, respectively. The mean agreement for all 10 points was 74.33 and 63.66% on the right and left foot, respectively. In cases of disagreement the detection of altered tactile sensitivity by the electronic esthesiometer on the right and left foot was 90.91 and 84.25%, respectively, with no detection by the monofilaments. Conclusion: The results suggest that the electronic esthesiometer is a reliable and easy application, capable of evaluating alterations of tactile sensitivity in leprosy patients. (C) 2009 Elsevier B.V. All rights reserved.

Expression of fibroblast growth factor receptors during development and regression of the bovine corpus luteum

There is evidence that fibroblast growth factors (FGFs) are involved in the regulation of growth and regression of the corpus luteum (CL). However, the expression pattern of most FGF receptors (FGFRs) during CL lifespan is still unknown. The objective of the present study was to determine the pattern of expression of `B` and `C` splice variants of FGFRs in the bovine CL. Bovine CL were collected from an abattoir and classed as corpora hemorrhagica (Stage I), developing (Stage II), developed (Stage III) or regressed (Stage IV) CL. Expression of FGFR mRNA was measured by semiquantitative reverse transcription-polymerase chain reaction and FGFR protein was localised by immunohistochemistry. Expression of mRNA encoding the `B` and `C` spliced forms of FGFR1 and FGFR2 was readily detectable in the bovine CL and was accompanied by protein localisation. FGFR1C and FGFR2C mRNA expression did not vary throughout CL lifespan, whereas FGFR1B was upregulated in the developed (Stage III) CL. FGFR3B, FGFR3C and FGFR4 expression was inconsistent in the bovine CL. The present data indicate that FGFR1 and FGFR2 splice variants are the main receptors for FGF action in the bovine CL.

Stress intensity factor threshold in dental porcelains

The stress intensity factor threshold (K(IO)) is related to the stress level at which cracks start to grow stably, causing the weakening of porcelain prostheses during their use. The values of K(IO) of seven dental porcelains (with and without reinforcing leucite crystal, KAlSi(2)O(6)) stored in air (22 degrees C, 60% relative humidity) and artificial saliva (37 degrees C) were determined by measuring the crack growth velocity of radial cracks generated at the corner of Vickers indentations. The results of K(IO) were correlated with the leucite content, fracture toughness (K(Ic)), and chemical composition of the porcelains. It was observed that K(IO) increased with the increase of leucite content (only for the leucite-based porcelains) and with the increase of K(Ic). The increase in Al(2)O(3) content or the decrease in the alkali oxide (K(2)O and Na(2)O) content of the material`s glassy matrix tended to increase the K(IO) values. Storage media (air and saliva) did not significantly affect the K(IO) of porcelains tested, indicating that the control parameter of K(IO) value was not the water content of the storage media.

The impact of stress and anxiety on the pressure pain threshold of myofascial pain patients

The purpose of this study was to evaluate the influence of stress and anxiety on the pressure pain threshold (PPT) of masticatory muscles and on the subjective pain report. Forty-five women, students, with mean age of 19.75 years, were divided into two groups: group 1:29 presenting with masticatory myofascial pain (MFP), according to the Research Diagnostic Criteria for Temporomandibular Disorders and group 2: 16 asymptomatic controls. An electronic algometer registered the pain thresholds on four different occasions throughout the academic year. To measure levels of stress, anxiety and pain, the Beck Anxiety Inventory, Lipp Stress Symptoms Inventory and Visual Analog Scale (VAS) were used. Three-way anova and Tukey`s tests were used to verify differences in PPT between groups, times and sites. Levels of anxiety and VAS were compared using Mann-Whitney test, while Friedman`s test was used for the within-groups comparison at different times (T1 to T4). The chi-squared and Cochran tests were performed to compare groups for the proportion of subjects with stress (alpha = 0.05). Differences in PPT recordings between time (P = 0.001) and sites (P < 0.001) were detected. Higher levels of anxiety and lower PPT figures were detected at T2 (academic examination) (P = 0.001). There was no difference between groups for anxiety and stress at any time (P > 0.05). The MFP group also has shown significant increase of VAS at the time of academic examination (P < 0.001). External stressors such as academic examinations have a potential impact on masticatory muscle tenderness, regardless of the presence of a previous condition such as masticatory myofascial pain.

Influence of the menstrual cycle on the pressure pain threshold of masticatory muscles in patients with masticatory myofascial pain

Objective. The aim of this study was to investigate the influence of the menstrual cycle and oral contraceptive (OC) intake on the pressure pain threshold (PPT) of masticatory muscles in patients with masticatory myofascial pain (MFP). Study design. The sample was composed of 36 women, divided into 4 groups, according to the presence of MFP and the intake of OC (15 patients had MFP [7 taking OC] and 21 were pain-free controls [8 taking OC]). The algometer-based PPT of masseter and temporalis, and the record of subjective pain by visual analog scale (VAS) were determined during 2 consecutives menstrual cycles at 4 phases (menstrual, follicular, periovulatory, and luteal). A 3-way ANOVA for repeated measurements, Kruskal-Wallis, Friedman, and Dunn tests, with a 5% significant level analyzed the data. Results. PPT was significantly lower in MFP patients when compared with controls throughout the experiment (P < .001). The menstrual phases did not influence PPT (P > .05), while the intake of OC seems to raise PPT levels for the left temporalis (P = .01) and right masseter (P = .04). VAS was, in general, higher at the menstrual phase Conclusions. Different phases of the menstrual cycle have no influence on PPT values, regardless of the presence of a previous condition, as masticatory myofascial pain, while the intake of OC is associated with decreased levels of reported pain.

Non-stationary frequency analysis of extreme daily rainfall in Sao Paulo, Brazil

This work is an assessment of frequency of extreme values (EVs) of daily rainfall in the city of Sao Paulo. Brazil, over the period 1933-2005, based on the peaks-over-threshold (POT) and Generalized Pareto Distribution (GPD) approach. Usually. a GPD model is fitted to a sample of POT Values Selected With a constant threshold. However. in this work we use time-dependent thresholds, composed of relatively large p quantities (for example p of 0.97) of daily rainfall amounts computed from all available data. Samples of POT values were extracted with several Values of p. Four different GPD models (GPD-1, GPD-2, GPD-3. and GDP-4) were fitted to each one of these samples by the maximum likelihood (ML) method. The shape parameter was assumed constant for the four models, but time-varying covariates were incorporated into scale parameter of GPD-2. GPD-3, and GPD-4, describing annual cycle in GPD-2. linear trend in GPD-3, and both annual cycle and linear trend in GPD-4. The GPD-1 with constant scale and shape parameters is the simplest model. For identification of the best model among the four models WC used rescaled Akaike Information Criterion (AIC) with second-order bias correction. This criterion isolates GPD-3 as the best model, i.e. the one with positive linear trend in the scale parameter. The slope of this trend is significant compared to the null hypothesis of no trend, for about 98% confidence level. The non-parametric Mann-Kendall test also showed presence of positive trend in the annual frequency of excess over high thresholds. with p-value being virtually zero. Therefore. there is strong evidence that high quantiles of daily rainfall in the city of Sao Paulo have been increasing in magnitude and frequency over time. For example. 0.99 quantiles of daily rainfall amount have increased by about 40 mm between 1933 and 2005. Copyright (C) 2008 Royal Meteorological Society

Heteroscedastic Nonlinear Regression Models

In this article, we present a generalization of the Bayesian methodology introduced by Cepeda and Gamerman (2001) for modeling variance heterogeneity in normal regression models where we have orthogonality between mean and variance parameters to the general case considering both linear and highly nonlinear regression models. Under the Bayesian paradigm, we use MCMC methods to simulate samples for the joint posterior distribution. We illustrate this algorithm considering a simulated data set and also considering a real data set related to school attendance rate for children in Colombia. Finally, we present some extensions of the proposed MCMC algorithm.

Regression Models with Heteroscedasticity using Bayesian Approach

In this paper, we compare the performance of two statistical approaches for the analysis of data obtained from the social research area. In the first approach, we use normal models with joint regression modelling for the mean and for the variance heterogeneity. In the second approach, we use hierarchical models. In the first case, individual and social variables are included in the regression modelling for the mean and for the variance, as explanatory variables, while in the second case, the variance at level 1 of the hierarchical model depends on the individuals (age of the individuals), and in the level 2 of the hierarchical model, the variance is assumed to change according to socioeconomic stratum. Applying these methodologies, we analyze a Colombian tallness data set to find differences that can be explained by socioeconomic conditions. We also present some theoretical and empirical results concerning the two models. From this comparative study, we conclude that it is better to jointly modelling the mean and variance heterogeneity in all cases. We also observe that the convergence of the Gibbs sampling chain used in the Markov Chain Monte Carlo method for the jointly modeling the mean and variance heterogeneity is quickly achieved.

Methods of Estimation in Multiple Linear Regression: Application to Clinical Data

Nesse artigo, tem-se o interesse em avaliar diferentes estratégias de estimação de parâmetros para um modelo de regressão linear múltipla. Para a estimação dos parâmetros do modelo foram utilizados dados de um ensaio clínico em que o interesse foi verificar se o ensaio mecânico da propriedade de força máxima (EM-FM) está associada com a massa femoral, com o diâmetro femoral e com o grupo experimental de ratas ovariectomizadas da raça Rattus norvegicus albinus, variedade Wistar. Para a estimação dos parâmetros do modelo serão comparadas três metodologias: a metodologia clássica, baseada no método dos mínimos quadrados; a metodologia Bayesiana, baseada no teorema de Bayes; e o método Bootstrap, baseado em processos de reamostragem.

Bayesian nonlinear regression models with scale mixtures of skew-normal distributions: Estimation and case influence diagnostics

The purpose of this paper is to develop a Bayesian analysis for nonlinear regression models under scale mixtures of skew-normal distributions. This novel class of models provides a useful generalization of the symmetrical nonlinear regression models since the error distributions cover both skewness and heavy-tailed distributions such as the skew-t, skew-slash and the skew-contaminated normal distributions. The main advantage of these class of distributions is that they have a nice hierarchical representation that allows the implementation of Markov chain Monte Carlo (MCMC) methods to simulate samples from the joint posterior distribution. In order to examine the robust aspects of this flexible class, against outlying and influential observations, we present a Bayesian case deletion influence diagnostics based on the Kullback-Leibler divergence. Further, some discussions on the model selection criteria are given. The newly developed procedures are illustrated considering two simulations study, and a real data previously analyzed under normal and skew-normal nonlinear regression models. (C) 2010 Elsevier B.V. All rights reserved.

A bivariate regression model for matched paired survival data: local influence and residual analysis

The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.

A nonlinear regression model with skew-normal errors

In this paper we have discussed inference aspects of the skew-normal nonlinear regression models following both, a classical and Bayesian approach, extending the usual normal nonlinear regression models. The univariate skew-normal distribution that will be used in this work was introduced by Sahu et al. (Can J Stat 29:129-150, 2003), which is attractive because estimation of the skewness parameter does not present the same degree of difficulty as in the case with Azzalini (Scand J Stat 12:171-178, 1985) one and, moreover, it allows easy implementation of the EM-algorithm. As illustration of the proposed methodology, we consider a data set previously analyzed in the literature under normality.

On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.

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.