Hyperplane navigation: A method to set individual scores in fMRI group datasets

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.

A Bayesian approach to fuzzy hypotheses testing for the estimation of optimal age for vaccination against measles

Fuzzy Bayesian tests were performed to evaluate whether the mother`s seroprevalence and children`s seroconversion to measles vaccine could be considered as ""high"" or ""low"". The results of the tests were aggregated into a fuzzy rule-based model structure, which would allow an expert to influence the model results. The linguistic model was developed considering four input variables. As the model output, we obtain the recommended age-specific vaccine coverage. The inputs of the fuzzy rules are fuzzy sets and the outputs are constant functions, performing the simplest Takagi-Sugeno-Kang model. This fuzzy approach is compared to a classical one, where the classical Bayes test was performed. Although the fuzzy and classical performances were similar, the fuzzy approach was more detailed and revealed important differences. In addition to taking into account subjective information in the form of fuzzy hypotheses it can be intuitively grasped by the decision maker. Finally, we show that the Bayesian test of fuzzy hypotheses is an interesting approach from the theoretical point of view, in the sense that it combines two complementary areas of investigation, normally seen as competitive. (C) 2007 IMACS. Published by Elsevier B.V. All rights reserved.

Error in body weight estimation leads to inadequate parenteral anticoagulation

Parenteral anticoagulation is a cornerstone in the management of venous and arterial thrombosis. Unfractionated heparin has a wide dose/response relationship, requiring frequent and troublesome laboratorial follow-up. Because of all these factors, low-molecular-weight heparin use has been increasing. Inadequate dosage has been pointed out as a potential problem because the use of subjectively estimated weight instead of real measured weight is common practice in the emergency department (ED). To evaluate the impact of inadequate weight estimation on enoxaparin dosage, we investigated the adequacy of anticoagulation of patients in a tertiary ED where subjective weight estimation is common practice. We obtained the estimated, informed, and measured weight of 28 patients in need of parenteral anticoagulation. Basal and steady-state (after the second subcutaneous shot of enoxaparin) anti-Xa activity was obtained as a measure of adequate anticoagulation. The patients were divided into 2 groups according the anticoagulation adequacy. From the 28 patients enrolled, 75% (group 1, n = 21) received at least 0.9 mg/kg per dose BID and 25% (group 2, n = 7) received less than 0.9 mg/kg per dose BID of enoxaparin. Only 4 (14.3%) of all patients had anti-Xa activity less than the inferior limit of the therapeutic range (<0.5 UI/mL), all of them from group 2. In conclusion, when weight estimation was used to determine the enoxaparin dosage, 25% of the patients were inadequately anticoagulated (anti-Xa activity <0.5 UI/mL) during the initial crucial phase of treatment. (C) 2011 Elsevier Inc. All rights reserved.

Food energy content influences food portion size estimation by nutrition students

Background: Food portion size estimation involves a complex mental process that may influence food consumption evaluation. Knowing the variables that influence this process can improve the accuracy of dietary assessment. The present study aimed to evaluate the ability of nutrition students to estimate food portions in usual meals and relate food energy content with errors in food portion size estimation. Methods: Seventy-eight nutrition students, who had already studied food energy content, participated in this cross-sectional study on the estimation of food portions, organised into four meals. The participants estimated the quantity of each food, in grams or millilitres, with the food in view. Estimation errors were quantified, and their magnitude were evaluated. Estimated quantities (EQ) lower than 90% and higher than 110% of the weighed quantity (WQ) were considered to represent underestimation and overestimation, respectively. Correlation between food energy content and error on estimation was analysed by the Spearman correlation, and comparison between the mean EQ and WQ was accomplished by means of the Wilcoxon signed rank test (P < 0.05). Results: A low percentage of estimates (18.5%) were considered accurate (+/- 10% of the actual weight). The most frequently underestimated food items were cauliflower, lettuce, apple and papaya; the most often overestimated items were milk, margarine and sugar. A significant positive correlation between food energy density and estimation was found (r = 0.8166; P = 0.0002). Conclusions: The results obtained in the present study revealed a low percentage of acceptable estimations of food portion size by nutrition students, with trends toward overestimation of high-energy food items and underestimation of low-energy items.

A general hazard model for lifetime data in the presence of cure rate

Historically, the cure rate model has been used for modeling time-to-event data within which a significant proportion of patients are assumed to be cured of illnesses, including breast cancer, non-Hodgkin lymphoma, leukemia, prostate cancer, melanoma, and head and neck cancer. Perhaps the most popular type of cure rate model is the mixture model introduced by Berkson and Gage [1]. In this model, it is assumed that a certain proportion of the patients are cured, in the sense that they do not present the event of interest during a long period of time and can found to be immune to the cause of failure under study. In this paper, we propose a general hazard model which accommodates comprehensive families of cure rate models as particular cases, including the model proposed by Berkson and Gage. The maximum-likelihood-estimation procedure is discussed. A simulation study analyzes the coverage probabilities of the asymptotic confidence intervals for the parameters. A real data set on children exposed to HIV by vertical transmission illustrates the methodology.

The Provisional Paediatric Rheumatology International Trials Organisation/American College of Rheumatology/European League Against Rheumatism disease activity core set for the evaluation of response to therapy in juvenile dermatomyositis: A prospective validation study

Objective. To validate a core set of outcome measures for the evaluation of response to treatment in patients with juvenile dermatomyositis (DM). Methods. In 2001, a preliminary consensus-derived core set for evaluating response to therapy in juvenile DM was established. In the present study, the core set was validated through an evidence-based, large-scale data collection that led to the enrollment of 294 patients from 36 countries. Consecutive patients with active disease were assessed at baseline and after 6 months. The validation procedures included assessment of feasibility, responsiveness, discriminant and construct ability, concordce in the evaluation of response to therapy between physicians and parents, redundancy, internal consistency, and ability to predict a therapeutic response. Results. The following clinical measures were found to be feasible, and to have good construct validity, discriminative ability, and internal consistency; furthermore, they were not redundant, proved responsive to clinically important changes in disease activity, and were associated strongly with treatment outcome and thus were included in the final core set: 1) physician`s global assessment of disease activity, 2) muscle strength, 3) global disease activity measure, 4) parent`s global assessment of patient`s well-being, 5) functional ability, and 6) health-related quality of life. Conclusion. The members of the Paediatric Rheumatology International Trials Organisation, with the endorsement of the American College of Rheumatology and the European Leauge Against Rheumatism, propose a core set of criteria for the evaluation of response of therapy that is scientifically and clinically relevant and statistically validated. The core set will help standardize the conduct and reporting of clinical trials and assist practitioners in deciding whether a child with juvenile DM has responded adequately to therapy.

Estimation of R(0) from the initial phase of an outbreak of a vector-borne infection

The magnitude of the basic reproduction ratio R(0) of an epidemic can be estimated in several ways, namely, from the final size of the epidemic, from the average age at first infection, or from the initial growth phase of the outbreak. In this paper, we discuss this last method for estimating R(0) for vector-borne infections. Implicit in these models is the assumption that there is an exponential phase of the outbreaks, which implies that in all cases R(0) > 1. We demonstrate that an outbreak is possible, even in cases where R(0) is less than one, provided that the vector-to-human component of R(0) is greater than one and that a certain number of infected vectors are introduced into the affected population. This theory is applied to two real epidemiological dengue situations in the southeastern part of Brazil, one where R(0) is less than one, and other one where R(0) is greater than one. In both cases, the model mirrors the real situations with reasonable accuracy.