PubMed COVID-19 Clinical Care

PURPOSE OF REVIEW: The COVID-19 pandemic has accelerated the pace of technological development relating to pulmonary diseases. The advent of newer technologies, such as Artificial Intelligence (AI), continues to be adapted for diagnostic purposes. AI

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CONCLUSIONS: The COVID-19 pandemic has severely impacted on health research projects. The main challenge is now to mitigate negative effects and to improve long-term resilience in health research. The pandemic has also acted as a driver of innovation

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CONCLUSIONS: After rigorous adjustment for factors influencing exposure to SARS-CoV-2, Asian/Asian British ethnicity and raised BMI were associated with increased odds of developing COVID-19, while atopic disease was associated with decreased odds.

Background: The coronavirus disease 2019 (COVID-19) pandemic compelled rapid transition to work from home for the University of Texas MD Anderson Cancer Center Palliative, Rehabilitation, and Integrative Medicine (PRIM) department to ensure social

A high-performing interpretable model is proposed to predict the risk of deterioration in coronavirus disease 2019 (COVID-19) patients. The model was developed using a cohort of 3028 patients diagnosed with COVID-19 and exhibiting common clinical

CONCLUSION: Among 147 highly trained athletes after SARS-CoV-2 infection, cardiac involvement on CMR showed a modest frequency (4.7%), with definite signs of myocarditis present in only 1.4%. Comparing athletes after SARS-CoV-2 infection and healthy

CONCLUSIONS: Patients undergoing surgery for a proximal femoral fracture with a perioperative infection of SARS-CoV-2 have a high rate of mortality. This study would support the need for providing these patients with individualised medical and