PubMed COVID-19 Clinical Care

CONCLUSION: Clinically, it is difficult to distinguish between H1N1 and COVID-19. Thus, a polymerase chain reaction is recommended for all patients suffering from influenza-like symptoms to rule out influenza A subtype H1N1 and/or SARS-CoV2.

There is a paucity of literature on the effect of COVID-19 on hospital processes. We hypothesized that COVID-19 was associated with decreased cancer physiatry referrals in 2020. This is a retrospective cohort study of consecutive patients from April-

The COVID-19 pandemic has resulted in significant worldwide morbidity and mortality. In this review, we examine the intricate relationships between COVID-19 and liver diseases. While respiratory manifestations of COVID-19 are well-known, its impact

Methods of wastewater concentration (electronegative filtration (ENF) versus magnetic bead-based concentration (MBC)) were compared for the analysis of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), beta-2 microglobulin, and human

CONCLUSION: Clinical characteristics and the post-injection endophthalmitis rate were similar during both periods, however, patients presented with worse vision during the pandemic suggesting that the pandemic may have contributed to delayed

Over the last few years, the SARS-CoV-2 pandemic has made the need for rapid, affordable diagnostics more compelling than ever. While traditional laboratory diagnostics like PCR and well-plate ELISA are sensitive and specific, they can be costly and

CONCLUSION: There was relatively increased number of adults reporting with red eye in 2020. Eye injuries were the most common among all years, followed by conjunctivitis and keratitis. Ocular problems, however, might be a primary or secondary COVID

CONCLUSIONS: Our results highlight the need for continuous monitoring of CPE to limit widespread MDR pathogens carrying multiple mechanisms conferring resistance to novel antimicrobial molecules.

CONCLUSION: These data suggest that TeleNP is feasible and highly reliable in MS clinical practice.

CONCLUSIONS: Population shift in the data is able to deteriorate differences of AI models performance. Update of the probability threshold together with the population shift seems to be valuable to preserve AI models performance without retraining