PubMed COVID-19 Clinical Care

No abstract

CONCLUSIONS: During the COVID-19 pandemic, a significant proportion (>50%) of patients self-cancelled their appointments and nearly a quarter of patients discontinued their medications. Providing a documentation of the problems experienced by

CONCLUSIONS: Preventive measures and early detection of nosocomial outbreaks of COVID-19 should be prioritized to minimize the negative impact of this infection.

CONCLUSION: In our cohort, patients with lower health literacy scores, older and male patients, or who have poor internet access showed a lower level of technological comfort. At risk patients can be identified and provided additional support in

Internet gaming disorder (IGD) and problematic internet use (PIU) are becoming increasingly detrimental to modern society, with serious consequences for daily functioning. IGD and PIU may be exacerbated by lifestyle changes imposed by the coronavirus

CONCLUSION: La pandémie de la COVID-19 amplifie les iniquités structurelles. Les réfugiés et les nouveaux arrivants nécessitent et méritent des soins de santé et du soutien efficaces durant ces moments éprouvants. Cet article présente des approches

CONCLUSIONS: SARS-CoV-2 infection risks to vaccinators, vaccinees, and caregivers during vaccination campaigns can be greatly reduced by adequate PPE, symptomatic screening, and appropriate campaign timing. Our results support the use of adequate

CONCLUSIONS: In summary, we identify that the HCQ/CQ administration is not related to less mortality cases at later phase of COVID-19. More studies are needed to explore whether HCQ/CQ treatment would lead to SARS-Cov-2 RNA clearance delay or not.

CONCLUSIONS: Cardiac adipose tissue index and IL-6 determination at admission could help physicians to better identify diabetic patients with a potentially severe and lethal short term course irrespective of obesity. Diabetic patients with high CATi

This study tested the utility of the Risk Information Seeking and Processing (RISP) model in understanding why people seek or avoid online information about COVID-19. Data collected at three different time points (i.e., February, April, and May 2020)