PubMed COVID-19 Clinical Care

Leadership is vital to a well-functioning and effective health system. This importance was underscored during the COVID-19 pandemic. As disparities in infection and mortality rates became pronounced, greater calls for equity-informed healthcare

This paper examines whether school COVID-19 policies influenced enrollment differently by student age and race/ethnicity. Unlike much prior research, we i) analyze enrollments for virtually the entire U.S. public school population for both the 2020

CONCLUSIONS: Although mean discharge rate of motor units in TA was similar during foot adduction and ankle dorsiflexion, discharge variability was less during dorsiflexion resulting in less accurate performance of the steady adduction contractions

Digitalization has emerged as a new hope for low-carbon sustainable economic growth after its successful trial during the COVID-19 measures. Therefore, both developed and developing economies focus on digitalization to cope with carbon neutrality

The COVID-19 pandemic and the ensuing widespread lockdown measures have had a negative impact on the mental health of children and adolescents. We thus conducted a meta-analysis of the worldwide prevalence of sleep disturbances in children and

CONCLUSION: Implementation of CC and centralized management systems has the potential to improve quality of care by supporting early identification and real-time management of patients at risk of harm and clinical deterioration, including COVID-19

CONCLUSIONS: We found no evidence that periods of healthcare disruption from the COVID-19 pandemic resulted in more avoidable hospitalisations. Falling avoidable hospital admissions has coincided with declining inequalities most strongly by level of

Halofuginone hydrobromide has shown potent antiviral efficacy against a variety of viruses such as SARS-CoV-2, dengue, or chikungunya virus, and has, therefore, been hypothesized to have broad-spectrum antiviral activity. In this paper, we tested

No abstract

CONCLUSIONS: We developed and internally validated an ML model to predict delirium in COVID-19 inpatients. The model identified modifiable factors associated with the development of delirium and could be clinically useful for the prediction and