PubMed COVID-19 Clinical Care

CONCLUSION: Remdesivir, molnupiravir, and NRV/r may reduce HCU during the COVID-19 pandemic. However, due to limited study details and significant heterogeneity in effect estimates, further precise evidence is crucial, especially concerning emerging

CONCLUSIONS: COVID-19 was associated with long-term depression risk in older adults with overweight/obesity and metabolic syndrome, particularly in women. Thus, long-term evaluations of the impact of COVID-19 on mental health and preventive public

CONCLUSIONS: Using quantitative data, we were able to reveal how counterrumors influence the vaccination status of the COVID-19 vaccine. We think that our findings would be a foundation for considering countermeasures of vaccination.

CONCLUSION: Although a rare event, awareness regarding potential demyelinating episodes post-COVID-19 vaccination can help in early diagnosis. The presence of increased MOG-IgG antibodies with temporal association in post-COVID vaccine patients

Employing the Molecular Electron Density Theory, [3 + 2] cycloaddition processes between 4-chlorobenzenenitrileoxide and linalool, have been applied using the DFT/B3LYP/6-311(d,p) method, activation, reaction energies and the reactivity indices are

CONCLUSION: Faecal immunochemical testing demonstrated clinical value for Lynch syndrome patients requiring colorectal cancer surveillance during the pandemic in this descriptive report of an emergency COVID-19 response service. Further longitudinal

Conspiracy beliefs have been related to aversive emotional experiences often accompanying major world events and have also been linked to maladaptive ways of coping with stress. In this research, we examined how different coping strategies (i.e. self

In this study, a deep quantum neural network (DQNN) based on the Lion-based Coot algorithm (LBCA-based Deep QNN) is employed to predict COVID-19. Here, the genome sequences are subjected to feature extraction. The fusion of features is performed

The COVID-19 pandemic has amplified mental health problems and highlighted inequitable gaps in care worldwide. In response there has been an explosion of digital interventions such as smartphone applications ("apps") to extend care. The objective of

MOTIVATION: Automated extraction of participants, intervention, comparison/control, and outcome (PICO) from the randomized controlled trial (RCT) abstracts is important for evidence synthesis. Previous studies have demonstrated the feasibility of