PubMed COVID-19 Clinical Care

CONCLUSIONS: State and federal legislators use social media to share opinions and thoughts on key topics, including burnout and mental health strain among health care workers. Variations in the volume of posts indicated that a focus on burnout and

African American women breast cancer survivors are among those with the greater burden of cancer. Breast cancer is the second leading cause of death among black women, and this death rate is 40% higher than that of white women. The COVID-19 pandemic

CONCLUSIONS: To our knowledge, this is the first study to address the prevalence and determinants of BHD among MSK researchers. MSK researchers experienced and observed BHD, while many were not comfortable reporting and discussing violations to their

CONCLUSION: Hospitalizations were higher in children with asthma with COVID-19 infection. However, using ICS reduced the risk of COVID-19 infection. As for CF, postlung transplantation and CFRDM were risk factors for severe disease.

Background: Since the outset of the COVID-19 pandemic, substantial public attention has focused on the role of seasonality in impacting transmission. Misconceptions have relied on seasonal mediation of respiratory diseases driven solely by

BACKGROUND: COVID-19 forced healthcare systems to make unprecedented changes in clinical care processes. We hypothesized that the COVID-19 pandemic adversely impacted timely access to care, perioperative processes, and clinical outcomes for pediatric

The COVID-19 pandemic has drawn attention to the strategic responses of Chinese firms on digital transformation and led to a call for enhancing competitive advantage via accelerating digital transformation. Besides the physical health issue, the

CONCLUSIONS: Meagre government-provided formal supports may adversely impact the health and wellbeing of self-employed workers. This study points to ways that statutory social protection programs should be decoupled from benefits provided by

The present study aimed to estimate the infection fatality risk (IFR) and ascertainment bias of SARS-CoV-2 for six epidemic waves in Japan from February 2020 to January 2022. We used two types of datasets: (i) surveillance-based datasets containing

A full understanding of the characteristics of Covid-19 patients with a better chance of experiencing poor vital outcomes is critical for implementing accurate and precise treatments. In this paper, two different advanced data-driven statistical