PubMed COVID-19 Clinical Care

No abstract

CONCLUSION: The mortality rate among COVID-19 patients admitted to ICU is generally high. Dyspnea, as the initial presentation and comorbidity, especially hypertension, diabetes, and cardiovascular diseases, may be associated with a higher risk of

CONCLUSION: Families of youth of color with type 1 diabetes mostly had positive perceptions of telehealth but also identified issues with feasibility and quality of care. Our findings highlight a need for interventions promoting equal access to

CONCLUSION: The Hi5 protocol was noninferior to standard single-session protocols and improved brow heights and submental lifting.

CONCLUSIONS: The trend of nonmedical use of methylphenidate has changed significantly due to the COVID-19 pandemic. Among the machine learning models using SNS data to analyze the adverse effects and nonmedical use of methylphenidate, the random

COVID-19, first detected in Wuhan, China, in December 2019, was declared a global pandemic by the WHO following the rapid spread of cases worldwide. The pandemic resulted in governments enforcing nationwide lockdowns, halting economic activities

Coronavirus disease 19 has been predominant in China then transmitted to different countries. The study aimed to evaluate the recent evidences from published papers of potential risks of COVID-19 contagion through gestation and if vertical

Noroviruses (NoVs) are a global concern, causing widespread outbreaks and sporadic acute gastroenteritis (AGE) cases across all age groups. Recent research has shed light on the emergence of novel recombinant strains of NoV in various countries. To

COVID-19 survivors often endorse persistent physical and neuropsychiatric problems following disease recovery, a phenomenon described as "long COVID." Research exploring long-COVID continues to evolve in large-scale studies but remains limited among

This paper investigates the impact of COVID-19 on mental health in the US using a large CDC dataset and a new method with generative AI for automatically generating Python code. The generated code was used to investigate and visualize the time-series