PubMed COVID-19 Clinical Care

BACKGROUND: The COVID-19 pandemic brought rapid and major changes to research, and those wishing to carry out Patient and Public Involvement (PPI) activities faced challenges, such as restrictions on movement and contact, illness, bereavement and

Infection with SARs-COV-2 results in COVID-19 disease. Between March 2020 and August 2021, 468 COVID-19 patients confirmed by PCR or antigen test, in Yepes, Spain, received early treatment with antihistamines, adding azithromycin in selected cases

This paper applies multiple machine learning (ML) algorithms to a dataset of de-identified COVID-19 patients provided by the COVID-19 Research Database. The dataset consists of 20,878 COVID-positive patients, among which 9,177 patients died in the

CONCLUSION: Being highly suspicious of all patients affected with COVID-19 is highly recommended to avoid the complications of the late diagnosis of mucormycosis. In addition, our knowledge and methods in diagnosing and treating classical

No abstract

The COVID-19 pandemic continues to be widespread, and little is known about mental health impacts from dealing with the disease itself. This retrospective study used a deidentified health information exchange (HIE) dataset of electronic health record

Occupational burnout has become widespread. The syndrome can be especially harmful in health care settings, affecting clinicians, organizational effectiveness, and patient safety. Certain approaches have proven helpful in some cases in combatting the

CONCLUSIONS: Our process evaluation of the SRF, using the BCW approach to describe and theorize its content, provided granular support for the SRF working to change IPC behaviours as anticipated. However, our complementary inductive thematic analysis

Japan's responses to COVID-19 have been conducted based on the Act on the Prevention of Infectious Diseases and Medical Care for Patients with Infectious Diseases (the Infectious Diseases Control Law) and the Act on Special Measures against Novel

CONCLUSION: We developed a deep learning-based clinical decision support system that could become an efficient concurrent reading tool to assist clinicians, utilising a newly created European dataset including more than 2,800 CT scans.