To support the global restart of elective surgery, data from an international prospective cohort study of 8492 patients (69 countries) was analysed using artificial intelligence (machine learning techniques) to develop a predictive score for mortality in surgical patients with SARS-CoV-2. We found that patient rather than operation factors were the best predictors and used these to create the COVIDsurg Mortality Score (https://covidsurgrisk.app). Our data demonstrates that it is safe to restart a wide range of surgical services for selected patients.
SUMMARY:This study assessed the differences in body composition after 6 months of training in pubertal boys and girl swimmers and in pubertal boys and girls without sport practice. The swimming group was composed of 20 pubertal swimmers: 10 boys (SB) (age: 13.5±1.5 years; Tanner stage: 3.6±0.5) and 10 girls (SG) (age: 11.3±0.7 years; Tanner stage: 3.4±0.5), with an average training experience of 4±1.3 and 3±0.5 years, respectively. The control group was composed of 20 pubertal participants without sport practice: 10 boys (CB) (age: 13.6±1.2 years; Tanner stage: 3.5±0.5) and 10 girls (CG) (age: 11.2±0.8 years; Tanner stage: 3.5±0.5). The following anthropometric measurements were carried out in two assessment periods (pre-and post-test): height, weight and skinfold thickness (biceps, triceps, subscapular and suprailiac). The sum of 4 skinfolds allowed calculating the percentage of fat mass according to sex and maturational status equations. The Pared-Samples T test was used to analyze the differences between the two assessment periods (preand post-test). Between the pre-and post-test, the percentage of fat mass was significantly lower in SB (p= 0.014) and SG (p= 0.016), and significantly higher in CG (p= 0.007). In conclusion, a decrease in the percentage of fat mass was observed in pubertal boys and girls swimmers after 6 months of training compared with the control group, and those results seem to be associated with the swimming training, specifically the high training volume.
http://dx.doi.org/10.5007/2175-7941.2016v33n3p1079O uso de imagens estroboscópicas é antigo e sua aplicabilidade no ensino de física se torna cada vez mais útil com o desenvolvimento de novos aplicativos e softwares. Imagens estroboscópicas digitais se apresentam como promissoras em diversas áreas da ciência, em especial para o ensino de cinemática, pois são baratas e simples. No entanto, estes experimentos têm suas limitações, tais como, contraste com o fundo, iluminação, taxa de frames da câmera, velocidade do corpo e distorção das imagens pelas lentes. No presente artigo demonstra-se quantitativamente e qualitativamente algumas limitações desta técnica a fim de ajudar no planejamento de experimentos.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.