Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences
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Zhong Nan Da Xue Xue Bao Yi Xue Ban · May 2020
Nursing standard of internet-based rehabilitation for patients with coronavirus disease 2019.
Coronavirus disease 2019 (COVID-19) is an acute respiratory infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Patients with COVID-19 may have respiratory dysfunction, physical dysfunction, and psychological dysfunction. Rehabilitation and long-term follow-up management are particularly important for these patients. ⋯ While online rehabilitation nursing mode will be more feasible by using mobile internet technology. Based on literature review and focus group discussion, we standardize the internet-based nursing assessment, plan formulation, implementation, and effectiveness evaluation on discharged patients with COVID-19. We hope it can give guidance for nurses to provide better care for patients.
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Zhong Nan Da Xue Xue Bao Yi Xue Ban · May 2020
Relation between blood glucose and the prognosis of severe coronavirus disease 2019.
To describe the clinical characteristics and outcomes of severely ill patients with coronavirus disease 2019, and to investigate the relationship between plasma glucose level and the prognosis of severely ill patients with coronavirus disease 2019. ⋯ Fasting hyperglycemia at admission is a significant predictor for the prognosis of severely ill patients with coronavirus disease 2019. Closely monitoring and the optimal management of hyperglycemia may improve the prognosis of patients with coronavirus disease 2019.
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Zhong Nan Da Xue Xue Bao Yi Xue Ban · May 2020
Clinical characteristics and the risk factors for severe events of elderly coronavirus disease 2019 patients.
To investigate the clinical characteristics and risk factors for severe events of coronavirus disease 2019 (COVID-19) in elderly patients. ⋯ The proportion of severe cases in elderly COVID-19 patients is higher than that in young and middle-aged patients. CRP level has a good predictive value for the possibility of severe events in elderly COVID-19 patients.