PubMed COVID-19 Clinical Care

BACKGROUND AND OBJECTIVES: Strategies to manage the COVID-19 pandemic included widespread use of physical distancing measures. These well intended strategies adversely affected long-term care (LTC) residents' socialization and their caregiving

CONCLUSIONS: The analysed socio-demographic factors, primarily age, gender and place of residence, determined some of the scales concerning patient satisfaction with cancer care during the COVID-19 pandemic. The results of this and other studies of a

Racial and ethnic disparities in COVID-19 incidence are pronounced in underserved U.S./Mexico border communities. Working and living environments in these communities can lead to increased risk of COVID-19 infection and transmission, and this

No abstract

The direction the evolution of virulence takes in connection with any pathogen is a long-standing question. Formerly, it was theorized that pathogens should always evolve to be less virulent. As observations were not in line with this theoretical

Viral and host factors can shape SARS-CoV-2 evolution. However, little is known about lineage-specific and vaccination-specific mutations that occur within individuals. Here, we analysed deep sequencing data from 2,820 SARS-CoV-2 respiratory samples

The viral diseases encouraged scientific community to evaluate the natural antiviral bioactive components rather than protease inhibitors, harmful organic molecules or nucleic acid analogues. For this purpose, medicinal plants have been gaining

The ancestral SARS-CoV-2 strain that initiated the Covid-19 pandemic at the end of 2019 has rapidly mutated into multiple variants of concern with variable pathogenicity and increasing immune escape strategies. However, differences in host cellular

Hematopoietic stem cell transplant (HSCT) recipients may be at high risk of mortality from coronavirus disease 2019 (COVID-19). However, specific data on COVID-19 after treatment with HSCT in patients affected by autoimmune diseases (ADs) are still

CONCLUSION: Machine learning algorithms trained using routinely collected data outperformed traditional statistical models when predicting 90-day ACU. The XGBT algorithm has the potential to identify high-ACU risk patients and enable preventive