PubMed COVID-19 Clinical Care

CONCLUSIONS: This study, albeit with the limitations of a cross-sectional experimental design with self-evaluation tools in a general population sample, showed a vulnerability to COVID-19 pandemic stress due to high levels of hyper-arousal in

PURPOSE: A number of factors may contribute to disparities in mental health and suicidality for lesbian, gay, bisexual, and questioning (LGBQ) students, including parental abuse.

CONCLUSION: Higher anti-RBD antibodies in patients were associated with protection against symptomatic COVID-19 during emergence of SARS-CoV-2 Delta and Omicron variants.

CONCLUSIONS: Mothers with a mild or asymptomatic COVID-19 infection at the time of the delivery were less likely to have exclusively breastfed during their hospital stay than other mothers in these BFHI-accredited hospitals. However, there were no

There is now a need more than ever to streamline services. A one-stop shoulder clinic was introduced during the COVID-19 pandemic. A total of 861 patients were seen, saving 794 future appointments. 111 patients had an ultrasound scan and 285 patients

CONCLUSION: The RR/SpO(2) relationship before oxygen administration does not differ between patients with COVID-19 and those without COVID-19, except in elderly patients.

In the era of living with COVID-19, the risk of localised SARS-CoV-2 outbreaks remains. Here, we develop a multiscale modelling framework for estimating the local outbreak risk for a viral disease (the probability that a major outbreak results from a

CONCLUSION: Our project bidirectionally engaged Spanish-monolingual Latino community members and culturally/linguistically concordant cancer experts during the COVID-19 pandemic. Strengths included developing community partnerships and collaborations

COVID-19, caused by infection with the SARS-CoV-2 has become a global health problem due to significant mortality rates; the exact pathophysiological mechanism remains uncertain. Articles reporting patient data are quite heterogeneous and have

This paper proposes an optimized Long Short-Term Memory (LSTM+) model for predicting cumulative confirmed cases of COVID-19 in Germany, the UK, Italy, and Japan. The LSTM+ model incorporates two key optimizations: (1) fine-adjustment of parameters