PubMed COVID-19 Clinical Care

CONCLUSION: Vaccine hesitancy was associated with mistrust of the medical system. Psychological distress was highly prevalent in this study. Efforts should be made to improve patient trust and provide psychological support for fertility patients.

CONCLUSION: The incidence of COVID-19 is higher among patients with RA who receive DMARDs and glucocorticoids simultaneously or who have diabetes mellitus than among patients with RA not receiving these drug combinations, which should guide treatment

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CONCLUSION: Brain injury biomarkers were frequently elevated in COVID-19 ICU patients, in the absence of clinical evidence of brain injury. S100B was significantly correlated with IL-6, low lymphocyte count, hypoperfusion indices, illness severity

CONCLUSIONS: Findings suggest that public health campaigns can focus on improving trust in science and medical providers. Efforts to improve vaccination rates can only be achieved when individuals trust science, view the work of scientists as

The COVID-19 pandemic had brought changes to individuals, especially in consumer behavior. As the government of different countries has been implementing safety protocols to mitigate the spread of the virus, people became apprehensive about traveling

The introduction of the COVID-19 pandemic has placed additional strain on healthcare workers, inducing immense levels of stress and workplace burnout. Health care professionals are acutely susceptible to COVID-19 exposure, ultimately leading to

Post the coronavirus disease 2019 (COVID-19) pandemic, there arises the concern of a new epidemic as cases of monkeypox are being confirmed, globally. With the initial clinical manifestation of monkeypox resembling that of the common cold or seasonal

Glucocorticoids (GCs) are widely used in the treatment of the coronavirus disease of 2019 (COVID-19), and the toxicity of GCs to aquatic organisms has aroused widespread concern. Powdered activated carbon (PAC) has proven effective in removing

This paper examines the diffusion of COVID-19 news on social media using a large sample of approximately 45 million tweets. Using textual analysis, I identify tweets containing COVID-19 news, and construct an index representing the intensity of