PubMed COVID-19 Clinical Care

Red porgy (Pagrus pagrus) is a reef-associated, economically-important, winter-spawning, protogynous Sparidae species that appears to have declined in abundance in recent years along the southeast United States Atlantic coast. We used spatially

CONCLUSIONS: The PRI report provides performance data including ABC and identifies performance gaps in the quality of care for common respiratory illnesses. Future directions include examining health inequities, and understanding and addressing the

CONCLUSIONS: The findings highlight that during a crisis, there is value in rapidly monitoring food insufficiency and investing in government food benefits.

Coronavirus disease 2019 (COVID-19) is an acute respiratory infection caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The uncontrolled systemic inflammatory response, resulting from the release of large amounts of pro

CONCLUSION: We found gaps in and factors associated with care-seeking behaviour of mothers for their sick young infants including fear of COVID-19 and pre-existing health system-level barriers. The findings of the study were used to design and

The outbreak of the COVID-19 epidemic in 2020 has caused unprecedented panic among all mankind, pointing the major importance of effective treatment. Since the emergence of the swine acute diarrhea syndrome coronavirus (SADS-CoV) at the end of 2017

One of the most pressing challenges associated with SARS-CoV-2 treatment is the emergence of new variants that may be more transmissible, cause more severe disease, or be resistant to current treatments and vaccines. The emergence of SARS-CoV-2 has

CONCLUSION: The hormone α1Thy could reduce, through the modulation of DCs, the amount of proinflammatory cytokines produced by T cells. Moreover, α1Thy improve lymphocyte functionality and could become a beneficial therapeutic alternative as an

CONCLUSION: Between the first and second SARS-CoV-2 pandemic waves, demographic, clinical and geographical features of IBD patients were different as were the symptoms and outcomes of infection. These differences are likely due to the different

Predicting clinical deterioration in COVID-19 patients remains a challenging task in the Emergency Department (ED). To address this aim, we developed an artificial neural network using textual (e.g. patient history) and tabular (e.g. laboratory