Physical and pulmonary capacities of individuals with severe coronavirus disease after hospital discharge: A preliminary cross-sectional study based on cluster analysis

OBJECTIVE: This study aimed to analyze the physical and pulmonary capacities of hospitalized patients with severe coronavirus disease and its correlation with the time of hospitalization and complications involved. METHODS: A total of 54 patients, aged ≥18 years of both sexes, were evaluated 2-4 months after hospital discharge in São Paulo, Brazil. The physical characteristics analyzed were muscle strength, balance, flexibility, and pulmonary function. The K-means cluster algorithm was used to identify patients with similar physical and pulmonary capacities, related to the time of hospitalization. RESULTS: Two clusters were derived using the K-means algorithm. Patients allocated in cluster 1 had fewer days of hospitalization, intensive care, and intubation than those in cluster 2, which reflected a better physical performance, strength, balance, and pulmonary condition, even 2-4 months after discharge. Days of hospitalization were inversely related to muscle strength, physical performance, and lung function: hand grip D (r=−0.28, p=0.04), Short Physical Performance Battery score (r=−0.28, p=0.03), and forced vital capacity (r=−0.29, p=0.03). CONCLUSION: Patients with a longer hospitalization time and complications progressed with greater loss of physical and pulmonary capacities

Sociedade Brasileira de Melhoramento de Plantas Crop Breeding and Applied Biotechnology

ABSTRACT The common bean grain color is controlled by a large number of genes, probably distributed in all the chromosomes. Therefore, early selection for this trait is likely to cause an expressive reduction in the variability of other traits such as grain yield, which is the main objective of most breeding programs. This study was carried out to verify the effect of early (F 2 generation) selection for grain type on grain yield in more advanced generations. The F 2 population from the cross between the Ouro Negro (black grains) and Pérola ("carioca" -cream with brown stripes) type grains was used. The harvest seeds were divided into two groups, one with "carioca" grains and another of mixed type, where no selection was applied. The F 3 plants of both sub-populations were individually harvested resulting in 199 families per sub-populations. These 398 F 3:4 families and the parent cultivars were assessed during the year 2000 dry season in Lavras and the F 3:5 families in the winter of 2000 in Lavras and in Patos de Minas. On average, no yield differences among the non-selected and selected for grain type family means were detected. It was also observed that the heritability estimates were high and similar. It is, therefore, inferred that early (F 2 generation) selection for grain type did not reduce the potential of the population for selection of superior inbred lines. Consequently, strong selection for grain color in the F 2 generation, to screen out undesirable types will enable breeders to concentrate their efforts on the selection of other traits in the advanced generations. Only families with commercially acceptable grain type will be submitted to selection, increasing the chances of success

Quality of life and socio-demographic factors associated with nutritional risk in Brazilian community-dwelling individuals aged 80 and over: cluster analysis and ensemble methods

IntroductionThe aim of the present study was to use cluster analysis and ensemble methods to evaluate the association between quality of life, socio-demographic factors to predict nutritional risk in community-dwelling Brazilians aged 80 and over.MethodsThis cross-sectional study included 104 individuals, both sexes, from different community locations. Firstly, the participants answered the sociodemographic questionnaire, and were sampled for anthropometric data. Subsequently, the Mini-Mental State Examination (MMSE) was applied, and Mini Nutritional Assessment Questionnaire (MAN) was used to evaluate their nutritional status. Finally, quality of life (QoL) was assessed by a brief version of World Health Organizations’ Quality of Life (WHOQOL-BREF) questionnaire and its older adults’ version (WHOQOL-OLD).ResultsThe K-means algorithm was used to identify clusters of individuals regarding quality-of-life characteristics. In addition, Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) algorithms were used to predict nutritional risk. Four major clusters were derived. Although there was a higher proportion of individuals aged 80 and over with nutritional risk in cluster 2 and a lower proportion in cluster 3, there was no statistically significant association. Cluster 1 showed the highest scores for psychological, social, and environmental domains, while cluster 4 exhibited the worst scores for the social and environmental domains of WHOQOL-BREF and for autonomy, past, present, and future activities, and intimacy of WHOQOL-OLD.ConclusionHandgrip, household income, and MMSE were the most important predictors of nutritional. On the other hand, sex, self-reported health, and number of teeth showed the lowest levels of influence in the construction of models to evaluate nutritional risk. Taken together, there was no association between clusters based on quality-of-life domains and nutritional risk, however, predictive models can be used as a complementary tool to evaluate nutritional risk in individuals aged 80 and over

Retirement, food and health risk factors in the Longitudinal Study of Adult Health (ELSA-Brazil)

A sociedade brasileira tem passado nas últimas décadas por um intenso processo de envelhecimento. Entretanto, o número de estudos sobre a influência da aposentadoria na alimentação e outros possíveis fatores de risco ainda é baixo. Esta dissertação foi dividida em duas partes. Na primeira, foi analisado o papel da aposentadoria na alimentação, e na segunda, a sua associação com o tabagismo, a prática de atividade física e o consumo excessivo de álcool. A amostra foi composta por 6.529 servidores públicos de 50 a 69 anos de idade, sendo 2.854 homens e 3.675 mulheres, provenientes do Estudo Longitudinal de Saúde do Adulto (ELSA-Brasil), um estudo de coorte realizado em seis centros de ensino superior no Brasil. O Índice de Qualidade da Dieta-Revisado (IQD-R) foi utilizado para a avaliação do consumo a partir do Questionário de Frequência Alimentar aplicado na primeira onda de avaliações, que ocorreu entre agosto de 2008 e dezembro de 2010. Nas duas análises, foram utilizados modelos de regressão logística com efeitos fixos por centro de investigação e ajuste por variáveis sociodemográficas e de saúde. Os resultados mostraram que a aposentadoria esteve associada com uma dieta de melhor qualidade apenas entre os homens (OR 1,70; IC95 por cento : 1,04-2,76). Foi encontrada também uma associação positiva para homens com cônjuge também aposentado (OR 2,24; IC95 por cento : 1,01-4,95). Quanto aos demais fatores analisados, entre os homens foi encontrada uma associação da aposentadoria com maior prática de atividade física (OR 1,73; IC95 por cento : 1,08-2,78) e neutra com tabagismo e consumo de álcool. Entre as mulheres, foi encontrada associação da aposentadoria com maior prática de atividade física apenas quando o cônjuge não estava aposentado (OR 2,35; IC95 por cento : 1,20-4,64). Este estudo apresenta análises e resultados novos sobre a relação entre aposentadoria e fatores de risco como alimentação e atividade física, essenciais para a preservação da saúde e da qualidade de vida durante o processo de envelhecimentoBrazil has undergone an intense aging process in recent decades. However, the number of studies on the influence of retirement on individual diet and other possible risk factors is still low. This dissertation was divided in two parts. In the first, we analyzed the role of retirement in diet, and in the second, its association with smoking, physical activity and excessive alcohol consumption. The sample consisted of 6,529 public servants from 50 to 69 years old, of which 2,854 were men and 3,675 women. Data was obtained from the Longitudinal Study of Adult Health (ELSA-Brazil), a cohort study with civil servants from six Brazilian higher education centers. The Diet-Revised Quality Index (IQD-R) was used to evaluate the intake from the Food Frequency Questionnaire applied in the first wave, which occurred between 2008 and 2010. We used logistic regression with fixed effects per research center, adjusted for sociodemographic and health variables. Retirement was associated with a better quality diet only among men (OR 1,70; CI95 per cent : 1,04-2,76). There was also a positive association for men with a retired spouse (OR 2,24; CI95 per cent : 1,01-4,95). Regarding the other factors analyzed, for men we found an association of retirement with greater physical activity practice (OR 1,73; CI95 per cent : 1,08-2,78) and neutral with smoking and alcohol consumption. Among women, we found an association of retirement with greater physical activity when spouse was not retired (OR 2,35; CI95 per cent : 1,20-4,64). The study presents new results on the relationship between retirement and risk factors such as diet and physical activity, which are essential for the preservation of health and quality of life during the aging proces

Application of machine learning algorithms in the assessment of food consumption: baseline results from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

Introdução: A avaliação do consumo alimentar permite gerar conhecimento sobre a alimentação de indivíduos e populações, além de identificar os determinantes e tendências no consumo. Com ela é possível planejar ações, orientar serviços e implementar políticas públicas de saúde adequadas as necessidades da população. Com o apoio da tecnologia é possível automatizar algumas etapas do processo de análise de dados, com redução do tempo e recursos necessários, especialmente em grandes grupos. Entretanto, em países como o Brasil, ainda são escassas as aplicações de algoritmos de machine learning na avaliação da dieta. Objetivo: Aplicar algoritmos de machine learning na avaliação do consumo alimentar de servidores públicos em um grande estudo brasileiro. Métodos: Este estudo analisou transversalmente os dados da linha de base do Estudo Longitudinal de Saúde do Adulto (ELSA-Brasil). A partir destes dados, para explorar e classificar padrões alimentares, foi utilizado o algoritmo de cluster - K-Means. Na sequência, quatro algoritmos preditivos - Support Vector Machines (SVM), Decision Trees (DT), Naïve Bayes (NB), K-Nearest Neighbours (Knn) - foram aplicados incluindo variáveis demográficas, socioeconômicas e clínicas para predizer padrões alimentares. Adicionalmente, Sistemas de Recomendações foram construídos com algoritmos de Filtragem Colaborativa Baseada em Usuário e Itens (UBCF / IBCF) para o aconselhamento personalizado de dieta. As análises foram realizadas com a utilização do ambiente R. Resultados: Dois padrões alimentares foram derivados na amostra. O primeiro padrão, rotulado como \"Padrão Ocidental\", no qual os participantes apresentaram ingestões médias superiores para cereais refinados, feijões, carnes vermelhas e processadas, leite e produtos lácteos com alto teor de gorduras e bebidas adoçadas, quando comparados aqueles incluídos no outro padrão. O segundo padrão, rotulado como \"Padrão Prudente\", os participantes apresentaram consumo superior de frutas, vegetais, cereais integrais, aves, peixes, leite e produtos lácteos com redução de gorduras. Para a construção dos Sistemas de Recomendações foi fixado o limite de cinco itens, por participante, para evitar recomendações extensas e inespecíficas sobre a dieta (precisão entre 90% [IBCF] e 91% [UBCF]). Conclusão: Através da aplicação de algoritmos de machine learning foi possível realizar a análise de dados sobre o consumo, predizer padrões e personalizar recomendações sobre a dieta. Com o apoio das técnicas utilizadas, é possível subsidiar profissionais na gestão e no planejamento de ações de educação alimentar e nutricional personalizadas.Introduction: The evaluation of food consumption allows generating knowledge about the diet of individuals and populations, in addition to identifying the determinants and trends in consumption. With it is possible to plan actions, guide services and implement public health policies appropriate to the needs of the population. With the support of technology, it is possible to automate some stages of the data analysis process, reducing the time and resources needed, especially in large groups. However, in countries like Brazil, the applications of machine learning algorithms in diet assessment are still scarce. Objective: Apply machine learning algorithms in the evaluation of food consumption by public servants in a large Brazilian study. Methods: This study cross-sectionally analyzed the baseline data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). From these data, to explore and classify dietary patterns, the cluster algorithm K-Means was used. Next, four predictive algorithms - Support Vector Machines (SVM), Decision Trees (DT), Naïve Bayes (NB), K-Nearest Neighbors (Knn) - were applied including demographic, socioeconomic and clinical variables to predict dietary patterns. Additionally, Recommendation Systems were built with User- and Items-Based Collaborative Filtering algorithms (UBCF / IBCF) for personalized diet advice. The analyzes were performed using the environment R. Results: Two dietary patterns were derived in the sample. The first pattern, labeled as \"Western Pattern\", in which the participants had higher average intakes for refined cereals, beans, red and processed meats, milk and dairy products with a high fat content and sweetened drinks, when compared to those included in the other pattern. The second pattern, labeled \"Prudent Pattern\", participants showed a higher consumption of fruits, vegetables, whole grains, poultry, fish, milk and dairy products with reduced fats. For the construction of the Recommender Systems, a limit of five items was set, per participant, to avoid extensive and unspecific recommendations on the diet (accuracy between 90% [IBCF] and 91% [UBCF]). Conclusion: Through the application of machine learning algorithms, it was possible to perform data analysis on consumption, predict patterns and personalize diet recommendations. With the support of the techniques used, it is possible to subsidize professionals in the management and planning of personalized food and nutrition education actions

Arthur Neiva e a 'questão nacional' nos anos 1910 e 1920 Arthur Neiva and the 'national question' in the 1910s and 1920s

Com o objetivo de analisar as interpretações e os diagnósticos sobre o Brasil elaborados pelo cientista e escritor Arthur Neiva entre as décadas de 1910 e 1920, especialmente a partir de suas crônicas literárias e do relatório da expedição científica realizada ao interior do Brasil em 1912, destaco suas críticas contra a mentalidade das elites dirigentes e dos homens de letras, sobretudo pela falta de ação política, pelo apego à imitação das ideias e ao uso exagerado da retórica bacharelesca - considerados por ele os principais responsáveis pelo atraso cultural e político do país. Analiso também a maneira como Arthur Neiva lidou com a questão racial e os dilemas da formação nacional, tema considerado, no início do século XX, de fundamental importância para a compreensão da realidade e do destino do Brasil no chamado 'concerto das nações'.<br>The article analyzes the interpretations and diagnoses of Brazil developed by scientist and writer Arthur Neiva in the 1910s and 1920s, focusing especially on his literary crônicas and his report on the 1912 scientific expedition to the interior of Brazil. I highlight the author's criticisms of the mentality of the governing elite and men of letters, especially their failure to take political initiative, their penchant for imitating ideas, and their exaggerated use of pretentious rhetoric, which Neiva believed to be the main culprits behind Brazil's cultural and political backwardness. I also analyze how Neiva addressed the race issue and the dilemma of nation building, which in the early twentieth century was considered a theme of prime importance in understanding Brazil's reality and destiny within the so-called concert of nations