Relationships between motor performance and body composition of school adolescents

Introdução: A coordenação motora é uma interação harmoniosa entre diversos sistemas corporais para produzir ações cinéticas precisas e equilibradas. Diagnosticar níveis de desempenho motor em crianças e adolescentes pode favorecer a prevenção, conservação e melhoria da saúde e qualidade de vida. A composição corporal pode interferir consideravelmente na coordenação motora, principalmente em situações de sobrepeso e obesidade. Objetivo: Analisar relações entre desempenho motor e composição corporal de escolares. Método: Foram avaliados em 105 escolares a coordenação motora através do teste KTK (Körperkoordinationstest für Kinder) considerando o Quociente Motor (QM) e a composição corporal por meio do Percentual de Gordura Corporal (%GC) e Índice de Massa Corporal (IMC). Resultados: Os resultados da composição corporal demonstraram que pelo IMC (38% e 36%) e %GC (28% e 22%) dos meninos e meninas, respectivamente, foram classificados no grupo Acima do Ideal. Com relação ao desempenho motor as meninas apresentaram valores de QM inferiores aos dos meninos (p<0,001). O grupo com %GC Abaixo do Ideal apresentou maiores valores de QM que os grupos Ideal (p<0,05) e Acima do Ideal (p<0,05). Foi observada correlação inversa entre o QM, o %GC e o IMC (r=-0,432 e r=-0,254, respectivamente). Conclusão: existem relações entre composição corporal e coordenação motora de adolescentes entre 11 e 14 anos, específicas ou não ao sexo e a faixa etária.  Introduction: Motor coordination is a result of interactions between many body systems, producing accurate and balanced kinetic actions. The evaluation of motor performance levels in children and teenagers may conserve and improve health and life qualities. Body composition may interfere considerably in motor coordination, particularly in overweight and obese conditions. Objective: To analyse the relationships between motor performance and body composition in children. Methods: Motor coordination was evaluated through the Körperkoordinations test für Kinder (KTK test), considering the motor quotient (MQ) and body composition using the body fat percentage (BF%) and body mass index (BMI). Results: BMI (38% and 36%) and BF% (28% and 22%), from boys and girls respectively, demonstrated that body composition is above the recommended. Girls presented MQ values lower than those observed in boys (p < 0.001). The groups with BFPs below the recommended value showed higher values of MQ than the normal group (p<0.05) and than children above the recommended ideal (p < 0.05). A reverse correlation was observed between MQ with BF% (r = -0.432) or BMI (r = -0.254). Conclusion: There are relationships between body composition and motor coordination in teenagers between 11 and 14 years old, related or not to gender and age. &nbsp

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Clinical characteristics and outcomes of hospital-manifested COVID-19 among Brazilians

ABSTRACT: Objectives: To analyze the clinical characteristics and outcomes of admitted patients with the hospital- versus community-manifested COVID-19 and to evaluate the risk factors related to mortality in the first population. Methods: This retrospective cohort included consecutive adult patients with COVID-19, hospitalized between March and September 2020. The demographic data, clinical characteristics, and outcomes were extracted from medical records. Patients with hospital-manifested COVID-19 (study group) and those with community-manifested COVID-19 (control group) were matched by the propensity score model. Logistic regression models were used to verify the risk factors for mortality in the study group. Results: Among 7,710 hospitalized patients who had COVID-19, 7.2% developed symptoms while admitted for other reasons. Patients with hospital-manifested COVID-19 had a higher prevalence of cancer (19.2% vs 10.8%) and alcoholism (8.8% vs 2.8%) than patients with community-manifested COVID-19 and also had a higher rate of intensive care unit requirement (45.1% vs 35.2%), sepsis (23.8% vs 14.5%), and death (35.8% vs 22.5%) (P <0.05 for all). The factors independently associated with increased mortality in the study group were increasing age, male sex, number of comorbidities, and cancer. Conclusion: Hospital-manifested COVID-19 was associated with increased mortality. Increasing age, male sex, number of comorbidities, and cancer were independent predictors of mortality among those with hospital-manifested COVID-19 disease

Núcleos de Ensino da Unesp: artigos 2013: volume 2: metodologias de ensino e a apropriação de conhecimento pelos alunos

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

Núcleos de Ensino da Unesp: artigos 2013: volume 2: metodologias de ensino e a apropriação de conhecimento pelos alunos

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

Resumos concluídos - Neurociências

Resumos concluídos -  Neurociência

ABC₂-SPH risk score for in-hospital mortality in COVID-19 patients

Objectives: The majority of available scores to assess mortality risk of coronavirus disease 2019 (COVID-19) patients in the emergency department have high risk of bias. Therefore, this cohort aimed to develop and validate a score at hospital admission for predicting in-hospital mortality in COVID-19 patients and to compare this score with other existing ones. Methods: Consecutive patients (≥ 18 years) with confirmed COVID-19 admitted to the participating hospitals were included. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients admitted between March–July, 2020. The model was validated in the 1054 patients admitted during August–September, as well as in an external cohort of 474 Spanish patients. Results: Median (25–75th percentile) age of the model-derivation cohort was 60 (48–72) years, and in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. Seven significant variables were included in the risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO2/FiO2 ratio, platelet count, and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829–0.859), which was confirmed in the Brazilian (0.859 [95% CI 0.833–0.885]) and Spanish (0.894 [95% CI 0.870–0.919]) validation cohorts, and displayed better discrimination ability than other existing scores. It is implemented in a freely available online risk calculator (https://abc2sph.com/). Conclusions: An easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation was designed and validated for early stratification of in-hospital mortality risk of patients with COVID-19.</p