An unprecedented global pandemic caused by a novel coronavirus, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has quickly overwhelmed the health care systems worldwide. While there is an absence of consensus among the community in how to manage solid organ transplant recipients and donors, a platform provided by the American Society of Transplantation online community "Outstanding Questions in Transplantation," hosted a collaborative multicenter, multinational discussions to share knowledge in a rapidly evolving global situation. Here, we present a summary of the discussion in addition to the latest published literature.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435543 | PMC |
| http://dx.doi.org/10.1111/ctr.14059 | DOI Listing |
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Severity and Long-Term Mortality of COVID-19, Influenza, and Respiratory Syncytial Virus.
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Research and Development, Veterans Affairs Puget Sound Health Care System, Seattle, Washington.
Importance: SARS-CoV-2, influenza, and respiratory syncytial virus (RSV) contribute to many hospitalizations and deaths each year. Understanding relative disease severity can help to inform vaccination guidance.
Objective: To compare disease severity of COVID-19, influenza, and RSV among US veterans.
Firearm-Related Injury Hospital Admissions During the COVID-19 Pandemic.
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Division of Acute Care Surgery, Department of Surgery, University of Michigan, Ann Arbor.
Comparative Analysis of Machine Learning Algorithms Used for Translating Aptamer-Antigen Binding Kinetic Profiles to Diagnostic Decisions.
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Department of Engineering Physics, McMaster University, 1280 Main Street West, L8S 4L8 Hamilton, Ontario, Canada.
Current approaches for classifying biosensor data in diagnostics rely on fixed decision thresholds based on receiver operating characteristic (ROC) curves, which can be limited in accuracy for complex and variable signals. To address these limitations, we developed a framework that facilitates the application of machine learning (ML) to diagnostic data for the binary classification of clinical samples, when using real-time electrochemical measurements. The framework was applied to a real-time multimeric aptamer assay (RT-MAp) that captures single-frequency (12.
View Article and Find Full Text PDFDecreases in frequency-dependent intrinsic activity of the default mode network are associated with depression and cognition in patients with postacute sequelae of SARS-CoV-2 infection.
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Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China.
A significant proportion of patients who have recovered from COVID-19 suffer from persistent symptoms, referred to as "post-acute sequelae of SARS-CoV-2 infection (PASC)". Abnormal brain intrinsic activity has been observed in PASC patients, but the patterns of frequency-dependent intrinsic activity in the PASC and non-PASC (recovered COVID-19 patients without persistent symptoms) groups and their association with neuropsychiatric sequelae remain unclear in PASC. Twenty-nine PASC patients, 27 non-PASC subjects, and 31 healthy controls (HCs) were recruited.
View Article and Find Full Text PDFOccurrence and clinical correlates of SARS-CoV-2 viremia in two German patient cohorts.
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Institute for Medical Virology, Goethe University, University Hospital Frankfurt, Frankfurt am Main, Germany.
Viremia defined as detectable SARS-CoV-2 RNA in the blood is a potential marker of disease severity and prognosis in COVID-19 patients. Here, we determined the frequency of viremia in serum of two independent COVID-19 patient cohorts within the German National Pandemic Cohort Network (German: tionales andemie horten etzwerk, NAPKON) with diagnostic RT-PCR against SARS-CoV-2. A cross-sectional cohort with 1,122 COVID-19 patients (German: , SUEP) and 299 patients recruited in a high-resolution platform with patients at high risk to develop severe courses (German: , HAP) were tested for viremia.
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