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Previous issue date: 2014-12-18 / Introduction: The metabolic syndrome (MetS) is characterized by a complex disorder represented by a cluster of cardiovascular risk factors associated with central fat distribution and insulin resistance. Interleukin-6 (IL-6) is a adipokine produced in the visceral adipose tissue and have been proposed as an inflammatory marker of MetS and may also be related to the development of cardiovascular disease (CVD). The Artificial Neural Networks (ANN) comprise a processing structure composed of interconnected units, known as artificial neurons, seeking solutions to complex problems through learning. Objective: To evaluate the serum levels of the inflammatory cytokine interleukin-6 in patients with Metabolic Syndrome, with and without Cardiovascular Disease through clinical, biochemical and anthropometric parameters of these patients, to develop and to facilitate a pilot study to aid the propensity of Cardiovascular Disease using models in Artificial Neural Networks. Methods: Serum IL-6 levels were assessed in 80 patients with metabolic syndrome, 40 with CVD and 40 without CVD. Adding to this, clinical, biochemical and anthropometric parameters were selected from the registry database of Cardiometabolic Risk Clinic in a controlled cross-sectional study consisting of a historical sample. From this, parameters were selected relevant to CVD and presented two proposals for training models in ANN. ANN templates were used type Multilayer Perceptrom (MLP) and the setup process, training and validation was performed with the aid of MATLAB computational tool version 6.5, the Mathworks, with Neural Networks Toolbox packages specific to ANN and implemented with Backpropagation algorithm. Results: Among the variables we found that patients without CVD had baseline DBP (p = 0.008) and LDL- cholesterol (p = 0.026) higher than patients with CVD. It was also in the group of patients with CVD, statin use was significantly higher (82.8% vs. 27.5%; p = 0.001) compared to those without CVD group. Serum IL-6 levels were higher in patients with established CVD, 23.52 + 10.39 + 59.78 x 3,50pg/mL; p = 0.036, compared to patients without CVD. ANN was tested two topologies: with IL-6 and without IL-6. The network topology MLP with best result of classification, was considering all parameters relevant to CVD. This topology presented a mean absolute error of 2.41% and a configuration with one hidden layer and 80 internal neurons. Conclusion: Patients with MetS and with established CVD, showed serum levels of inflammatory cytokine IL-6 higher, which are associated with persistent inflammation. The ANN proved to be a complementary instrument at diagnosis, potentially useful for situations that demonstrate the complexity of characterizing the risk of cardiovascular events in patients with MetS / Introdu??o: A S?ndrome Metab?lica (SM) ? caracterizada por um transtorno complexo representado por um conjunto de fatores de risco cardiovascular, relacionados ? deposi??o central de gordura e a resist?ncia ? insulina. A Interleucina-6 (IL-6) ? uma adipocina produzida no tecido adiposo visceral e t?m sido caracterizada como um marcador inflamat?rio da SM, podendo tamb?m estar relacionada ao desenvolvimento de doen?a cardiovascular (DCV). As Redes Neurais Artificiais (RNA) compreendem uma estrutura de processamento, composta por unidades interconectadas, conhecidas como neur?nios artificiais que buscam solu??es de problemas complexos por meio da aprendizagem. Objetivo: Avaliar os n?veis s?ricos da citocina inflamat?ria Interleucina-6 em pacientes com S?ndrome Metab?lica, com e sem Doen?a Cardiovascular e por meio dos par?metros cl?nicos, bioqu?micos e antropom?tricos desses pacientes, desenvolver e viabilizar um estudo piloto para aux?lio na identifica??o ? propens?o de DCV utilizando modelos em RNA. M?todos: N?veis s?ricos de IL-6 foram avaliados em 80 pacientes com S?ndrome Metab?lica, 40 com DCV e 40 sem DCV. Par?metros cl?nicos, bioqu?micos e antropom?tricos foram selecionados entre os registros do banco de dados do Ambulat?rio de Risco Cardiometab?lico, em um estudo transversal controlado, composto por uma amostra hist?rica. A partir desses par?metros foram apresentadas duas propostas para o treinamento de uma RNA. Foi utilizada uma RNA do tipo MultiLayer Perceptron (MLP) e o processo de configura??o, treinamento e valida??o foi realizado com aux?lio da ferramenta computacional MatLab vers?o 6.5, da Mathworks, com pacotes Neural Networks Toolbox espec?ficos para RNA e implementadas com o algoritmo do tipo Backpropagation. Resultados: Entre as vari?veis analisadas verificamos que os pacientes sem DCV apresentaram valores basais PAD (p=0,008) e LDL- Colesterol (p=0,026) maiores que os pacientes com DCV. Constatou-se, tamb?m, que no grupo de pacientes com DCV, o uso de estatina foi significativamente maior (82,8% x 27,5%; p=0,001), comparado ao grupo sem DCV. Os n?veis s?ricos de IL-6 foram maiores em pacientes com DCV estabelecida, 23,52+59,78 x 10,39+3,50pg/mL; p=0,036, comparado aos pacientes sem DCV. Foram testadas duas topologias de RNA: com IL-6 e sem IL-6. A topologia de rede MLP com melhor resultado de classifica??o, foi considerando todos os par?metros relevantes ? DCV. Essa topologia apresentou um erro m?dio absoluto de 2,41% e uma configura??o com 1 camada oculta e 80 neur?nios internos. Conclus?o: Pacientes com SM e com DCV estabelecida, apresentaram n?veis s?ricos da citocina inflamat?ria IL-6 mais elevados, que se associam ao processo inflamat?rio persistente. As RNA mostraram-se um instrumento complementar no aux?lio ao diagn?stico, potencialmente ?teis para situa??es que demonstram complexidade de caracteriza??o do risco de eventos cardiovasculares em pacientes com SM
| Identifer | oai:union.ndltd.org:IBICT/oai:tede2.pucrs.br:tede/1795 |
| Date | 18 December 2014 |
| Creators | Helegda, Lara Colognese |
| Contributors | Bodanese, Luiz Carlos |
| Publisher | Pontif?cia Universidade Cat?lica do Rio Grande do Sul, Programa de P?s-Gradua??o em Medicina e Ci?ncias da Sa?de, PUCRS, BR, Faculdade de Medicina |
| Source Sets | IBICT Brazilian ETDs |
| Language | Portuguese |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/doctoralThesis |
| Format | application/pdf |
| Source | reponame:Biblioteca Digital de Teses e Dissertações da PUC_RS, instname:Pontifícia Universidade Católica do Rio Grande do Sul, instacron:PUC_RS |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 7620745074616285884, 500, 600, -8624664729441623247 |
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