PubMed COVID-19 Clinical Care

CONCLUSIONS: Neighborhood socioeconomic and educational disadvantage amplified racial-ethnic disparities in STI screening during the pandemic. Future interventions should focus on improving primary care utilization of non-Hispanic-Black adolescents

SARS-CoV-2 must bind its principal receptor, ACE2, on the target cell to initiate infection. This interaction is largely driven by the receptor binding domain (RBD) of the viral Spike (S) protein. Accordingly, antiviral compounds that can block RBD

The coronavirus (COVID-19) pandemic has impacted breast cancer screening with concerns that this may lead to increased overall breast cancer mortality and worsened racial and ethnic disparities in breast cancer survival. As pandemic recovery efforts

CONCLUSION: PoD has shifted from hospital to home during the COVID-19 pandemic in Japan. The majority of whom were older population with cancer or old age.

Background: Withdrawal of life-sustaining treatment (WLST) is a process with unique pressure for all involved. The use of an electronic order set can facilitate best care. Objective: To assess utilization of a WLST order set and time to inpatient

This study aims to apply machine learning models to identify new biomarkers associated with the early diagnosis and prognosis of SARS-CoV-2 infection.Plasma and serum samples from COVID-19 patients (mild, moderate, and severe), patients with other

CONCLUSIONS: Chronic conditions after infection with COVID-19 or vaccination remain relatively rare and self-limited, yet reinforce the importance of comprehensive history taking involving COVID-19 to differentiate potential etiologic factors for

The global COVID-19 pandemic has caused more than 1 billion infections, and numerous SARS-CoV-2 vaccines developed rapidly have been administered over 10 billion doses. The world is continuously concerned about the cytokine storms induced by the

CONCLUSION: The lessons to be observed from this COVID-19 crisis are that in the early days of increasing calls heralding a strain on the healthcare system, support by medical students must be considered.

We proposed a self-supervised machine learning method to automatically rate the severity of pulmonary edema in the frontal chest X-ray radiographs (CXR) which could be potentially related to COVID-19 viral pneumonia. For this we use the modified