Background: Although the COVID-19 pandemic has persisted for over 3 years, reinfections with SARS-CoV-2 are not well understood. We aim to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection.
Methods: We use an electronic health record study cohort of over 3 million patients from the National COVID Cohort Collaborative as part of the NIH Researching COVID to Enhance Recovery Initiative.
Mucormycosis is a rare and devastating angioinvasive infection that can be challenging to diagnose due to the low sensitivity of current noninvasive diagnostics and the lack of a "gold standard" reference test. We describe a retrospective case series of children with suspected mucormycosis where plasma microbial cell-free DNA testing was utilized in the diagnostic evaluation to illustrate the ways in which microbial cell-free DNA testing can noninvasively contribute to the evaluation and management of at-risk, immunosuppressed patients suspected of mucormycosis.
View Article and Find Full Text PDFIntroduction: There is an urgent need to determine the safety, effectiveness and cost-effectiveness of novel antiviral treatments for COVID-19 in vaccinated patients in the community at increased risk of morbidity and mortality from COVID-19.
Methods And Analysis: PANORAMIC is a UK-wide, open-label, prospective, adaptive, multiarm platform, randomised clinical trial that evaluates antiviral treatments for COVID-19 in the community. A master protocol governs the addition of new antiviral treatments as they become available, and the introduction and cessation of existing interventions via interim analyses.
Background: Many US hospitals are classified as nonprofits and receive tax-exempt status partially in exchange for providing benefits to the community. Proof of compliance is collected with the Schedule H form submitted as part of the annual Internal Revenue Service Form 990 (F990H), including a free-response text section that is known for being ambiguous and difficult to audit. This research is among the first to use natural language processing approaches to evaluate this text section with a focus on health equity and disparities.
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