PubMed COVID-19 Clinical Care

CONCLUSIONS: There is a need to improve ED mental health care delivery, with a focus on timely access to ED mental health providers. Access to outpatient/community-based mental health care is needed to complement care received in the ED and to

Chemokine production by epithelial cells is crucial for neutrophil recruitment to sites of inflammation during viral infection. However, the effect of chemokine on epithelia and how chemokine is involved in coronavirus infection remains to be fully

Since the global pandemic of SARS-CoV-2, people's health and the economic support of their countries have been seriously affected. It was necessary to develop a low-cost and faster diagnostic tool that allows the evaluation of symptomatic patients

CONCLUSION: COVID-19 vaccination can influence the menstrual cycle. Age, body mass index, level of education, underlying comorbidities, and use of chronic medications are significantly associated with changes in menstrual length, flow, and symptoms

CONCLUSIONS: The reduced chance of experiencing an adverse event with some COVID-19 vaccines may help to overcome vaccine hesitancy in population groups with concerns about the side effects of vaccines.

The number of pancreas transplants in the United States was largely unchanged in 2021 at 963 transplants compared with 962 in 2020, showing that recovery from the COVID-19 pandemic was not as pronounced in pancreas transplantation as in other organs

The number of lung transplants has continued to decline since 2020, a period that coincides with the onset of the COVID-19 pandemic. Lung allocation policy continues to undergo considerable change in preparation for adoption of the Composite

Since late December 2019, coronavirus disease 2019 (COVID-19) outbreak caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been rapidly spread across the globe. The early, safe, sensitive, and accurate diagnosis of viral

Artificial intelligence (AI) speeds up the drug development process and reduces its time, as well as the cost which is of enormous importance in outbreaks such as COVID-19. It uses a set of machine learning algorithms that collects the available data

By using a large international firm-level data set this paper aims to make a contribution in better understanding how COVID-19 related stringency and economic support measures actually affected the corporate sector. Our most important findings can be