PubMed COVID-19 Clinical Care

CONCLUSIONS: Overall, students were critical of Zoom's impact on dyadic factors with standardized patients. However, they did acknowledge some positive aspects regarding the technology. These findings provide a foundation to consider when teaching

The COVID-19 outbreak led higher education institutions to shift to distance learning. This article describes data on the self-regulation of undergraduate students in online and blended learning environments during the pandemic situation. A total of

CONCLUSIONS: Results of this study provide evidence for the clinical utility of sample-based and demographically adjusted normative standards for cognitive dispersion on the UDS 3.0. These standards can be used to guide interpretation of

CONCLUSION: Both husband and wife, who had completed high school and were aware of the vaccination, were fearful of the COVID-19 vaccine. Concerns about the side effects and undesirable effects of vaccination on their newborns were the main reasons

Variations in the literature support the benefit of contact precautions for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE) infections in the hospital setting. During personal protective equipment

CONCLUSION: The revised HOME-CoV score, which does not require laboratory testing, may allow accurate risk stratification and safely qualify a significant proportion of patients with probable or proven COVID-19 for home treatment.

Major efforts were deployed to study the antibody response against SARS-CoV-2. Antibodies neutralizing SARS-CoV-2 have been extensively studied in the context of infections, vaccinations, and breakthrough infections. Antibodies, however, are

Generation of a stable long-lived plasma cell (LLPC) population is the sine qua non of durable antibody responses after vaccination or infection. We studied 20 individuals with a prior coronavirus disease 2019 infection and characterized the antibody

CONCLUSIONS: We propose 2 predictive algorithms based on routine clinical data that differentiate primary COVID-19 from incidental SARS-CoV-2 infection. These algorithms can provide a precise surveillance tool that can contribute to pandemic

CONCLUSIONS: We propose 2 predictive algorithms based on routine clinical data that differentiate primary COVID-19 from incidental SARS-CoV-2 infection. These algorithms can provide a precise surveillance tool that can contribute to pandemic