Fatores de risco associados à hipertensão em gestantes

Most of the problems related to women’s health, which are responsible for the higher incidence of diseases and mortality rates, occur during the reproductive period, especially during pregnancy, childbirth and puerperium due to the intense changes that occur during this period, especially in the gestation. Among the most frequent complications in pregnancy, hypertensive syndromes are identified, being the first cause of maternal mortality in Brazil and main responsible for the high rate of perinatal deaths, in addition to the growing number of sequelae neonates. Maternal mortality is an indicator of health and economic impact that impacts the lives of the people who are in their environment. Since hypertension is the first cause of maternal death, absolutely avoidable, this study aimed to study the risk factors associated with hypertension in pregnant women. This is a cross-sectional, quantitative approach. The sample consisted of 254 pregnant women in prenatal care at the Family Health Units (USF) and at the High Risk Outpatient Clinic of the Cândida Vargas Institute (ICV), a reference in Health Care in High Risk Pregnancy, both services located in the municipality of João Pessoa-PB. The data were collected during the months of October to December 2018. Data were analyzed by means of descriptive statistics through SPSS software and the construction of the Decision Tree model was done through WEKA software (WaikatoEnvironmentforKnowledgeAnalysis).The results showed that the risk factors are involved in the development of arterial hypertension in pregnant women, as well as the identification of the explanatory power of the factors in relation to the outcome by calculating the Information Value (IV). The factors present in the decision tree were: chronic hypertension, history of hypertensive syndrome in gestation, gestational diabetes, low income, black race, low socioeconomic level and overweight or obesity. On the other hand, the significant risk factors according to Odds Ratio with force majeure according to IV were: history of hypertensive syndrome in pregnancy and chronic hypertension; mean degree: gestational diabetes, overweight or obesity, family history of HAC, number of prenatal consultations <6, and history of gestational diabetes; family history of diabetes mellitus reached a weak degree. It was concluded that numerous risk factors contribute to the occurrence of hypertensive syndromes during pregnancy. The factors that most influence the appearance of hypertensive syndromes should be better evaluated and diagnosed by the health professionals as soon as possible in order to contribute to the reduction of maternal morbidity and mortality due to hypertensive causes, offering better assistance during prenatal care, resulting in a favorable postpartum outcome for both mother and child.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESGrande parte dos problemas relacionados à saúde da mulher, os quais são responsáveis pela maior incidência de doenças e taxas de mortalidade, se apresentam durante o período reprodutivo, sobretudo durante a gravidez, parto e puerpério devido às intensas modificações que ocorrem nesse período, principalmente na gestação. Dentre as complicações mais frequentes na gravidez, identificam-se as Síndromes hipertensivas, sendo esta a primeira causa da mortalidade materna no Brasil e principal responsável pela alta taxa de óbitos perinatais, além do crescente número de neonatos sequelados. A mortalidade materna se configura como um indicador de saúde e econômico que traz impacto pra vida das pessoas que estão em seu entorno. Sendo a hipertensão a primeira causa de morte materna, absolutamente evitável, este estudo teve por objetivo estudar os fatores de risco associados à hipertensão em gestantes. Trata-se de um estudo do tipo transversal, de abordagem quantitativa. A amostra foi composta por 254 gestantes em acompanhamento do pré-natal nas Unidades Saúde da Família (USF) e no Ambulatório de Alto Risco do Instituto CândidaVargas (ICV), referência na Atenção à Saúde na Gestação de Alto Risco, ambos serviços localizados no município de JoãoPessoa-PB. A coleta dos dados foi realizada durante os meses de outubro à dezembro de 2018. Os dados foram analisados por meio de estatística descritiva através do software SPSS e a construção do modelo de Árvore de Decisão se deu através do software WEKA (Waikato Environment for Knowledge Analysis). Os resultados mostraram através da construção do modelo decisório quais os fatores de risco estão envolvidos no desenvolvimento da hipertensão arterial em gestantes, além da identificação da força explicativa dos fatores em relação ao desfecho através do cálculo do Information Value (IV). Os fatores presentes na árvore de decisão foram: hipertensão arterial crônica, histórico de síndrome hipertensiva na gestação, diabetes gestacional, baixa renda, raça negra, baixo nível socioeconômico e sobrepeso ou obesidade. Já os fatores de risco significativos segundo Odds Ratio (OR) com grau de força maior de acordo com o IV foram: histórico de síndrome hipertensiva na gestação e hipertensão arterial crônica; grau médio: diabetes gestacional, sobrepeso ou obesidade, histórico familiar de HAC, número de consultas pré-natal < 6 e histórico de diabetes gestacional; histórico familiar de diabetes mellitus atingiu grau fraco. Concluiu-se que inúmeros fatores de risco contribuem para a ocorrência das síndromes hipertensivas na gestação. Os fatores que mais influenciam no aparecimento das síndromes hipertensivas devem ser melhor avaliados e diagnosticados pelos profissionais de saúde mais precocemente possível a fim de conseguir contribuir com a redução da morbimortalidade materna por causas hipertensivas, ofertando uma melhor assistência durante o acompanhamento do pré-natal, resultando em um desfecho favorável no pós-parto para mãe e filho

Data Mining As A Tool To Evaluate Thermal Comfort Of Horses

Thermal comfort is of great importance to preserve body temperature homeostasis during thermal stress conditions. Although thermal comfort of horses has been widely studied, research has not reported its relationship to surface temperature (TS). The aim of this study was to investigate the potential of data mining techniques as a tool to associate surface temperature with thermal comfort of horses. TS was measured using infrared thermographic image processing. Physiological and environmental variables were used to define the predicted class, which classified thermal comfort as "comfort" and "discomfort". The TS variables for the armpit, croup, breast and groin of horses and the predicted class were then submitted to a machine learning process. All dataset variables were considered relevant to the classification problem and the decision-tree model yielded an accuracy rate of 74.0%. The feature selection methods used to reduce computational cost and simplify predictive learning reduced the model accuracy to 70.1%; however the model became simpler with representative rules. For these selection methods and for the classification using all attributes, TS of armpit and breast had a higher rating power for predicting thermal comfort. 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