Análise da qualidade de uso e interface com o usuário de softwares brasileiros de apoio à nutrição clínica

O objetivo deste artigo é apresentar um comparativo de qualidade de uso e interface com o usuário de dois softwares nacionais utilizados para avaliação do estado nutricional e prescrição dietética de pacientes com alimentação via oralThe objective of this article is to show a comparative of using and interface quality between two Brazilian softwares used to nutritional state and dietetic prescription assessment on patients with oral alimentationRed de Universidades con Carreras en Informática (RedUNCI

Conception of a computational tool for planning of personalized menus, considering preferences and nutrient requirements.

Ferramentas computacionais têm sido utilizadas na área de nutrição desde os anos de 1960 e buscam auxiliar o nutricionista no cálculo de nutrientes e no planejamento de cardápios, visando o apoio na tomada de decisão. Assim, a utilização da informática na execução dessas tarefas disponibiliza ao nutricionista tempo necessário para que desenvolva outras atividades específicas voltadas ao atendimento dos pacientes/clientes. Entre as ferramentas computacionais, destacam-se os sistemas especialistas (SE) que resolvem problemas de forma parecida com o especialista humano, sobre determinados campos do conhecimento. Nesse contexto, o objetivo deste trabalho foi conceber uma ferramenta computacional utilizando a base de dados de Avaliação de Ingestão de Nutrientes da Tabela Brasileira de Composição de Alimentos (TBCA BD-AIN) para gerar planos alimentares personalizados, considerando as preferências alimentares e necessidades nutricionais do paciente/cliente. Os passos para o desenvolvimento desse trabalho incluíram: (i) diferenciação entre as ferramentas computacionais disponíveis; (ii) caracterização da consulta em nutrição; (iii) definição do protocolo de atendimento clínico para a consulta em nutrição; (iv) adequação da TBCA BD-AIN a ser utilizada na ferramenta computacional; (v) definição das preferências; (vi) implementação da ferramenta computacional; (vii) avaliação dos resultados gerados pela ferramenta computacional. A ferramenta computacional desenvolvida, chamada Nutri - Soluções inteligentes em nutrição, uma web application, caracterizada como SE, utilizou a técnica de máquina de estados finito (MEF), para representar a expertise do nutricionista, na elaboração dos planos alimentares. Os planos alimentares gerados foram avaliados por nutricionistas (n=18) com experiência em atendimento clínico (10,83±7,02 anos). A avaliação de 105 planos alimentares diários (7 planos alimentares para 15 casos fictícios) apresentou adequação quanto às recomendações nutricionais e preferências propostas, além de selecionar alimentos/preparações dos diferentes grupos (conforme a refeição), e considerar características sensoriais, mostrando 89,2% de concordância para os itens avaliados. Dessa forma, a ferramenta proposta contribuirá com: (i) otimização do atendimento clínico, pois auxiliando na redução dos cálculos realizados, o nutricionista disponibilizará mais tempo da consulta em nutrição para atenção ao paciente/cliente; (ii) apoio à decisão, uma vez que os planos alimentares apresentarão maior probabilidade de estarem adequados quanto às recomendações nutricionais; (iii) adesão à prescrição dietética, pois os planos alimentares serão elaborados com base nas escolhas/preferências do paciente/cliente.Computational tools have been used in the area of nutrition since the 1960s and seek to assist the nutritionist in calculating nutrients and planning menus, aiming at support in decision making. Thus, the use of information technology in the execution of these tasks provides the nutritionist with the time needed to develop other specific activities aimed at patient/client care. Among the computational tools, stand out the expert systems (ES) that solve problems in a similar way with the human expert, on certain fields of knowledge. In this context, the objective of this work was to design a computational tool using the Nutrient Intake Assessment database of the Brazilian Food Composition Table (TBCA BD-AIN, acronym in Portuguese) to generate personalized menu, considering the food preferences and nutrient requirements of the patient/client. The steps for the development of this work included: (i) differentiation between the available computational tools; (ii) characterization of the nutrition consultation; (iii) definition of the protocol of clinical care for the consultation in nutrition; (iv) adequacy of TBCA BD-AIN to be used in the computational tool; (v) definition of preferences; (vi) implementation of the computational tool; (vii) evaluation of the results generated by the computational tool. The computational tool developed, called Nutri - Intelligent Solutions in Nutrition, a web application, characterized as ES, used the Finite State Machine (FSM) technique to represent the nutritionist\'s expertise in the elaboration of menu. The menu generated were evaluated by nutritionists (n= 18) with experience in clinical care (10.83±7.02 years). The evaluation of 105 daily menus (7 food plans for 15 fictitious cases) was adequate for the nutritional recommendations and preferences proposed, besides selecting foods/preparations of the different groups (according to the meal), besides considering sensorial characteristics, showing 89.7% agreement for the evaluated items. Thus, the proposed tool will contribute to: (i) optimization of clinical care, because by helping to reduce the calculations performed, the nutritionist will provide more consultation time in nutrition for patient/client care; (ii) decision support, since menu are more likely to be adequate for nutritional recommendations; (iii) adherence to the dietary prescription, since the menus will be elaborated based on the patient/client\'s choices/preferences

A randomized trial of planned cesarean or vaginal delivery for twin pregnancy

Background: Twin birth is associated with a higher risk of adverse perinatal outcomes than singleton birth. It is unclear whether planned cesarean section results in a lower risk of adverse outcomes than planned vaginal delivery in twin pregnancy.\ud \ud Methods: We randomly assigned women between 32 weeks 0 days and 38 weeks 6 days of gestation with twin pregnancy and with the first twin in the cephalic presentation to planned cesarean section or planned vaginal delivery with cesarean only if indicated. Elective delivery was planned between 37 weeks 5 days and 38 weeks 6 days of gestation. The primary outcome was a composite of fetal or neonatal death or serious neonatal morbidity, with the fetus or infant as the unit of analysis for the statistical comparison.\ud \ud Results: A total of 1398 women (2795 fetuses) were randomly assigned to planned cesarean delivery and 1406 women (2812 fetuses) to planned vaginal delivery. The rate of cesarean delivery was 90.7% in the planned-cesarean-delivery group and 43.8% in the planned-vaginal-delivery group. Women in the planned-cesarean-delivery group delivered earlier than did those in the planned-vaginal-delivery group (mean number of days from randomization to delivery, 12.4 vs. 13.3; P = 0.04). There was no significant difference in the composite primary outcome between the planned-cesarean-delivery group and the planned-vaginal-delivery group (2.2% and 1.9%, respectively; odds ratio with planned cesarean delivery, 1.16; 95% confidence interval, 0.77 to 1.74; P = 0.49).\ud \ud Conclusion: In twin pregnancy between 32 weeks 0 days and 38 weeks 6 days of gestation, with the first twin in the cephalic presentation, planned cesarean delivery did not significantly decrease or increase the risk of fetal or neonatal death or serious neonatal morbidity, as compared with planned vaginal delivery