Longitudinal Study of Growth of Children With Unilateral Cleft-Lip Palate From Birth to Two Years of Age

Objective: To study the growth of children with complete unilateral cleft lip and palate (UCLP) from birth to 2 years of age and to construct specific UCLP growth curves. Design: Physical growth was a secondary outcome measure of a National Institutes of Health-sponsored longitudinal, prospective clinical trial involving the University of Florida (United States) and the University of Sao Paulo (Brazil). Patients: Six hundred twenty-seven children with UCLP, nonsyndromic, both genders. Methods: Length, weight, and head circumference were prospectively measured for a group of children enrolled in a clinical trial. Median growth curves for the three parameters (length, weight, head circumference) were performed and compared with the median for the National Center for Health Statistics (NCHS) curves. The median values for length, weight, and head circumference at birth and 6, 12, 18, and 24 months of age were plotted against NCHS median values and statistically compared at birth and 24 months. Setting: Hospital de Reabilitacao de Anomalias Craniofaciais, Universidade de Sao Paulo, Bauru, Brazil (HRAC-USP). Results: At birth, children of both genders with UCLP presented with smaller body dimensions in relation to NCHS median values, but the results suggest a catch-up growth for length, weight, and head circumference for girls and for weight (to some degree) and head circumference for boys. Conclusions: Weight was the most compromised parameter for both genders, followed by length and then head circumference. There was no evidence of short stature. This study established growth curves for children with UCLP.

In vitro sensitivity of Leishmania (Viannia) braziliensis and Leishmania (Leishmania) amazonensis Brazilian isolates to meglumine antimoniate and amphotericin B

Resistance of Leishmania parasites to specific chemotherapy has become a well-documented problem in the Indian subcontinent in recent years but only a few studies have focused on the susceptibility of American Leishmania isolates. Our susceptibility assays to meglumine antimoniate were performed against intracellular amastigotes after standardizing an in vitro model of macrophage infection appropriate for Leishmania (Viannia) braziliensis isolates. For the determination of promastigote susceptibility to amphotericin B, we developed a simplified MTT-test. The sensitivity in vitro to meglumine antimoniate and amphotericin B of 13 isolates obtained from Brazilian patients was determined. L. (V.) braziliensis isolates were more susceptible to meglumine antimoniate than Leishmania (Leishmania) amazonensis. EC(50), EC(90) and activity indexes (calculated over the sensitivity of reference strains), suggested that all isolates tested were susceptible in vitro to meglumine antimoniate, and did not show association with the clinical outcomes. Isolates were also uniformly susceptible in vitro to amphotericin B.

Bayesian analysis for a skew extension of the multivariate null intercept measurement error model

Skew-normal distribution is a class of distributions that includes the normal distributions as a special case. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis in a multivariate, null intercept, measurement error model [R. Aoki, H. Bolfarine, J.A. Achcar, and D. Leao Pinto Jr, Bayesian analysis of a multivariate null intercept error-in -variables regression model, J. Biopharm. Stat. 13(4) (2003b), pp. 763-771] where the unobserved value of the covariate (latent variable) follows a skew-normal distribution. The results and methods are applied to a real dental clinical trial presented in [A. Hadgu and G. Koch, Application of generalized estimating equations to a dental randomized clinical trial, J. Biopharm. Stat. 9 (1999), pp. 161-178].

Inference and local influence assessment in skew-normal null intercept measurement error model

In this article, we discuss inferential aspects of the measurement error regression models with null intercepts when the unknown quantity x (latent variable) follows a skew normal distribution. We examine first the maximum-likelihood approach to estimation via the EM algorithm by exploring statistical properties of the model considered. Then, the marginal likelihood, the score function and the observed information matrix of the observed quantities are presented allowing direct inference implementation. In order to discuss some diagnostics techniques in this type of models, we derive the appropriate matrices to assessing the local influence on the parameter estimates under different perturbation schemes. The results and methods developed in this paper are illustrated considering part of a real data set used by Hadgu and Koch [1999, Application of generalized estimating equations to a dental randomized clinical trial. Journal of Biopharmaceutical Statistics, 9, 161-178].

A robust Bayesian approach to null intercept measurement error model with application to dental data

Measurement error models often arise in epidemiological and clinical research. Usually, in this set up it is assumed that the latent variable has a normal distribution. However, the normality assumption may not be always correct. Skew-normal/independent distribution is a class of asymmetric thick-tailed distributions which includes the Skew-normal distribution as a special case. In this paper, we explore the use of skew-normal/independent distribution as a robust alternative to null intercept measurement error model under a Bayesian paradigm. We assume that the random errors and the unobserved value of the covariate (latent variable) follows jointly a skew-normal/independent distribution, providing an appealing robust alternative to the routine use of symmetric normal distribution in this type of model. Specific distributions examined include univariate and multivariate versions of the skew-normal distribution, the skew-t distributions, the skew-slash distributions and the skew contaminated normal distributions. The methods developed is illustrated using a real data set from a dental clinical trial. (C) 2008 Elsevier B.V. All rights reserved.

A web application for follow-up of results from a mobile device test battery for parkinson’s disease patients

Background: A test battery consisting of self-assessments and motor tests (tapping and spiral drawing) was developed for a hand computer with touch screen in a telemedicine setting. Objectives: To develop and evaluate a web-based system that delivers decision support information to the treating clinical staff for assessing PD symptoms in their patients based on the test battery data. Methods: The test battery is currently being used in a clinical trial (DAPHNE, EudraCT No. 2005-002654-21) by sixty five patients with advanced Parkinson’s disease (PD) on 9991 test occasions (four tests per day during in all 362 week-long test periods) at nine clinics around Sweden. Test results are sent continuously from the hand unit over a mobile net to a central computer and processed with statistical methods. They are summarized into scores for different dimensions of the symptom state and an ‘overall test score’ reflecting the overall condition of the patient during a test period. The information in the web application is organized and presented graphically in a way that the general overview of the patient performance per test period is emphasized. Focus is on the overall test score, symptom dimensions and daily summaries. In a recent preliminary user evaluation, the web application was demonstrated to the fifteen study nurses who had used the test battery in the clinical trial. At least one patient per clinic was shown. Results: In general, the responses from nurses were positive. They claimed that the test results shown in the system were consistent with their own clinical observations. They could follow complications, changes and trends within their patients. Discussion: In conclusion, the system is able to summarise the various time series of motor test results and self-assessments during test periods and present them in a useful manner. Its main contribution is a novel and reliable way to capture and easily access symptom information from patients’ home environment. The convenient access to current symptom profile as well as symptom history provides a basis for individualized evaluation and adjustment of treatments.