PubMed COVID-19 Clinical Care

CONCLUSIONS: A COVID-19 positive diagnosis is associated with significantly higher risk of all-cause mortality following ambulatory surgery. This mortality risk is greatest in patients that undergo ambulatory surgery within 45 days of testing

CONCLUSION: The current findings underscore the need for increased attention on improving the psychological capital of medical interns.

CONCLUSIONS: SARS-CoV-2 RNA was widely distributed on high-touch surfaces and on PPE in the contaminated zone of the Fangcang shelter hospital, implying a potentially high infection risk for healthcare workers. Our findings emphasize the need to

CONCLUSIONS: Saliva sampling for COVID-19 at ECE sites is an acceptable strategy as an additional layer of protection for 4- and 5-year-olds; however, alternate testing strategies may be needed for younger children.

Objectives At the beginning of the COVID-19 pandemic, the number of infected children was lower than that of adults. Most cases were transmitted in the family, asymptomatic, and severe cases were rare. In the sixth wave in Japan the number of

Minimally invasive autopsy (MIA) is an alternative to full autopsy for collection of tissue samples from patient's bodies, using an instrument such as a biopsy needle. MIA has been conducted in many cases of coronavirus disease 2019 (COVID-19) and

Vitamin D deficiency is one of the most common vitamin deficiencies across different populations. It has primarily been implicated in the development of metabolic bone disease in adults and children. However, in recent years its role in

CONCLUSIONS: Vaccination was well-tolerated and associated with a lower risk of COVID-19 infection among HCT survivors and their household contacts. Vaccination and booster doses should be encouraged as part of a multi-faceted approach in this high

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CONCLUSIONS: Regarding the categories of detection methods, evaluating detection methods using homogeneous data across countries and years provides a solid and consistent comparison. An explainability analysis of a tree-based machine-learning model