Gustavo Pasquali Moretti

Incidence of congenital syphilis in the South Region of Brazil

INTRODUCTION The aim of this study was to establish the incidence rates of congenital syphilis in the South Region of Brazil from 2001 to 2009. METHODS Temporal ecological and descriptive study based on the cases recorded by the System of Information of Notifiable Diseases. RESULTS The incidence of congenital syphilis has been increasing in the South Region of Brazil since 2004; the highest incidence rates were in women who received prenatal care (113.5 new cases per 100,000 births, p<0.001), who were diagnosed with syphilis at pregnancy (69.8 new cases per 100,000 births, p=0.001), and whose partner did not undergo treatment for syphilis (53.1 new cases per 100,000 births, p=0.001). CONCLUSIONS The population of the present study mostly consisted of adult black women with low educational levels who attended prenatal care, who were diagnosed with syphilis during pregnancy, and whose partners were not treated for syphilis. Based on these results, actions are recommended to reduce the incidence of this disease, which is preventable by early diagnosis and appropriate treatment. The present was merely an ecological study; therefore, further investigations are necessary to elucidate the causes of these findings.

Metanálise do uso de redes bayesianas no diagnóstico de câncer de mama

The aim of this study was to determine the accuracy of Bayesian networks in supporting breast cancer diagnoses. Systematic review and meta-analysis were carried out, including articles and papers published between January 1990 and March 2013. We included prospective and retrospective cross-sectional studies of the accuracy of diagnoses of breast lesions (target conditions) made using Bayesian networks (index test). Four primary studies that included 1,223 breast lesions were analyzed, 89.52% (444/496) of the breast cancer cases and 6.33% (46/727) of the benign lesions were positive based on the Bayesian network analysis. The area under the curve (AUC) for the summary receiver operating characteristic curve (SROC) was 0.97, with a Q* value of 0.92. Using Bayesian networks to diagnose malignant lesions increased the pretest probability of a true positive from 40.03% to 90.05% and decreased the probability of a false negative to 6.44%. Therefore, our results demonstrated that Bayesian networks provide an accurate and non-invasive method to support breast cancer diagnosis.O objetivo deste estudo foi avaliar a acuracia das redes bayesianas no apoio ao diagnostico de câncer de mama. Foram realizadas revisao sistematica e metanalise, que incluiram artigos e relatorios publicados entre Janeiro de 1990 e Marco de 2013. Foram incluidos estudos transversais prospectivos e retrospectivos que avaliaram a acuracia do diagnostico de lesoes de mama (condicao alvo) usando as redes bayesianas (teste em avaliacao). Quatro estudos primarios que incluiram 1.223 lesoes de mama foram analisados, 89,52% (444/496) dos casos de câncer de mama e 6,33% (46/727) das lesoes benignas foram positivas tendo-se como base a analise das redes bayesianas. A area dentro da curva SROC (caracteristica de operacao do receptor sumaria) foi 0,97, com um valor Q* de 0,92. O uso de redes bayesianas no diagnostico de lesoes malignas aumentou a probabilidade pre-teste para um verdadeiro positivo de 40,03% para 90,05% e diminuiu a probabilidade de um falso negativo para 6,44%. Portanto, nossos resultados demonstraram que as redes bayesianas oferecem um metodo acurado e nao invasivo no apoio ao diagnostico de câncer de mama.

Classification of images acquired with colposcopy using artificial neural networks.

Objective To explore the advantages of using artificial neural networks (ANNs) to recognize patterns in colposcopy to classify images in colposcopy. PURPOSE: Transversal, descriptive, and analytical study of a quantitative approach with an emphasis on diagnosis. The training test e validation set was composed of images collected from patients who underwent colposcopy. These images were provided by a gynecology clinic located in the city of Criciúma (Brazil). The image database (n = 170) was divided; 48 images were used for the training process, 58 images were used for the tests, and 64 images were used for the validation. A hybrid neural network based on Kohonen self-organizing maps and multilayer perceptron (MLP) networks was used. Results After 126 cycles, the validation was performed. The best results reached an accuracy of 72.15%, a sensibility of 69.78%, and a specificity of 68%. Conclusion Although the preliminary results still exhibit an average efficiency, the present approach is an innovative and promising technique that should be deeply explored in the context of the present study.

Epidemiological profile of suicide in the Santa Catarina Coal Mining Region from 1980 to 2007.

BACKGROUND Suicide is a public health problem worldwide. Estimates have indicated that over 1 million people commit suicide every year all over the world. Brazil has a moderate suicide death rate (4.1 per 100,000 inhabitants), but the fact that it is a large country leads to the coexistence of diverse characteristics and levels of development across the different Brazilian regions. In this sense, the South region has been shown to present suicide rates above the national average. OBJECTIVE To estimate the profile of suicide in municipalities comprising the Santa Catarina Coal Mining Region from 1980 to 2007. METHODS This ecological, time-series, descriptive study sought to characterize epidemiological aspects related to suicide method, marital status, sex, age, and occupation in the municipalities of the region in the years 1980 to 2007. RESULTS A total of 474 suicides occurred in the period, yielding a mean death rate of 10.83 per 100,000 inhabitants. There was a predominance of males, at a 5:1 ratio, and a peak rate in the 55-64-year age group (11.31 per 100,000 inhabitants). The suicide method most commonly used was hanging (72%) and the most frequent occupation was hard labor work (11.60%); in relation to marital status, married subjects (48%) were the ones with the highest rates of suicide. CONCLUSIONS The Santa Catarina Coal Mining Region has suicide mortality rates above the national average. This study highlights specific characteristics of suicide in the region and may contribute to the development of preventive measures.