Articles: pandemics.
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Background: Breastfeeding is a characteristic process of mammals that ensures delivery of an adequate nutritional supply to infants. It is the gold standard food source during an infant's first months of life. Since the onset of the COVID-19 pandemic in 2020, people in quarantine have experienced a wide range of feelings, which may make isolation challenging in terms of maternal health. ⋯ A higher percentage of mothers practiced SSC breastfed (66.9%) and used EBF (150, 79.4%) (p = 0.012 and 0.001, respectively). Conclusions: Results suggest that the pandemic emergency and restrictions imposed on the population significantly affected the well-being of mothers after birth, and that these effects may have posed risks to the mental health and emotional stability of postpartum mothers. Therefore, encouraging BF or EBF and SSC may improve or limit depressive symptoms in postpartum mothers.
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Global coronavirus disease 2019 pandemic leads to the soaring demand for medical statistical applications, bringing a great challenge to medical education at universities worldwide. The purpose of our study is to investigate medical students and teachers attitudes and demands on statistical software education. A multi-city cross-sectional study was conducted in 2021 at medical universities in eastern China. ⋯ Notably, very few students and teachers thought "Statistical software met needs" (from 21.8% of undergraduates to 8.8% of teachers). There were 75.4% of post-graduates and 96.5% of teachers who thought it was necessary for a university to offer an advanced statistical software curriculum such as the R package in the preferred teaching format of offline class as well as the combination of theory and software practice teaching. This study for the first time demonstrated that most medical undergraduates, post-graduates, and teachers in Anhui Province of eastern China were not satisfied with statistical software usage experience, calling for prompt adjustments to statistical software education in medical universities.
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Chest-computer tomography (CT) is a crucial factor in the clinical course and evaluation of patients with COVID-pneumonia. In the initial phase of the COVID-19 pandemic little information was known on the prognostic value of the initially taken thoracic CTs. The purpose of this study was to determine predictive values for clinical outcome based on CT classification of the pulmonary pathologies in patients with COVID-pneumonia. ⋯ A classification system used in this study is helpful for classifying imaging features and is recommended as a standardized CT reporting tool. It could also help in triaging of the therapy of patients with COVID-19 pneumonia. Especially the comorbidities, diabetes and arterial hypertonia triggered a negative outcome in our study population.