PubMed COVID-19 Clinical Care

COVID-19 pneumonia presents several particularities in its clinical presentation (cytokine storm, silent hypoxemia, thrombo-embolic risk) and may lead to a number of acute respiratory distress syndrome (ARDS) phenotypes. While the optimal oxygenation

CONCLUSION: Patients were more likely to accept COVID-19 vaccination if they received Tdap or influenza vaccinations. Older age, obesity, Asian race, and private insurance were independent predictors of vaccine uptake. Disparities in COVID-19

No abstract

The demand for rapid and efficient diagnostic point-of-care tests for respiratory infectious diseases has become increasingly critical in the current landscape. The emphasis on accessibility has been underscored over the past year, making it crucial

CONCLUSION: This review provides concrete information about the frequency of various inflammatory markers in patients with COVID-19 infection who required hospitalization. It also provides us some insight into the approach clinicians took in the

CONCLUSIONS: In hospitalized patients with COVID-19, the presence of AP is associated with increased mortality and morbidity. Risk factors for developing AP in this population include Hispanic ethnicity, residence in the southern region, higher

Non-bacterial thrombotic endocarditis is mainly associated with malignancies and rheumatological diseases. We report the case of mildly symptomatic COVID-19 infection with non-bacterial aortic valve vegetation complicated by transient ischemic attack

This study presents a comprehensive comparative analysis of reverse transcription-loop-mediated isothermal amplification (RT-LAMP) and three reverse transcription quantitative polymerase chain reaction (RT-qPCR) assays targeting the N and E genes of

Middle East Respiratory Syndrome (MERS) is a zoonotic disease. Dromedary camel is responsible of its transmission to humans. Accordingly, several human cases have been reported worldwide with a high mortality rate. In Algeria, no data reported on

CONCLUSIONS: The study highlights the effectiveness of computational methods like natural language processing in managing large-scale engagement and misinformation. It underscores the critical role of trust in health authorities for effective risk