Ferring Pharmaceuticals: Ferring and Rebiotix to Present Landmark Data for Investigational Microbiota-based Live Biotherapeutic RBX2660 at Digestive Disease Week (DDW) 2021
Clostridioides difficile Infection With and Without Sepsis
Presenting Author: Alpesh Amin, MD, MBA, Thomas Mary Cesario Chairman, Department of Medicine, Executive Director, Hospitalist Program, University of California Irvine
EMBARGOED UNTIL PRESENTATION TIME: FRIDAY, MAY 21 AT 12:15 PM ET
DDW has made abstracts available on their website.
About RBX2660
RBX2660 is a potential first-in-class microbiota-based live biotherapeutic being studied to deliver a broad consortium of diverse microbes to the gut to reduce recurrent
C. difficile infection. RBX2660 has been granted Fast Track, Orphan, and Breakthrough Therapy designations from the U.S. Food and Drug Administration (FDA). The pivotal Phase 3 program builds on nearly a decade of research with robust clinical and microbiome data collected over six con
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Irvine, Calif., Feb. 9, 2021 Monoclonal antibodies are showing promise for improving outcomes for COVID-19 patients, but when a hospital is already beyond capacity, administering them can be a challenge. As hospitalizations soared across California, clinicians with UCI Health created a system for delivering monoclonal antibodies that is keeping hospital beds available for patients with the greatest need. The hospital bed is one of the most valuable resources that we have, which has been stretched thin by the COVID-19 pandemic, said Dr. Daniel S. Chow, an assistant professor in residence in radiological sciences and co-director for the Center for Artificial Intelligence in Diagnostic Medicine as well as the project s co-principal investigator. Every effort to expand the number of beds available counts, and that includes being proactive about preventing hospitalizations.
AI, Machine Learning Tools Help Predict COVID-19 Outcomes healthitanalytics.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from healthitanalytics.com Daily Mail and Mail on Sunday newspapers.
A machine-learning model created to calculate COVID-19 health outcomes
University of California, Irvine health sciences researchers have created a machine-learning model to predict the probability that a COVID-19 patient will need a ventilator or ICU care. The tool is free and available online for any healthcare organization to use. The goal is to give an earlier alert to clinicians to identify patients who may be vulnerable at the onset, said Daniel S. Chow, an assistant professor in residence in radiological sciences and first author of the study, published in
PLOS ONE. The tool predicts whether a patient s condition will worsen within 72 hours.
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Irvine, Calif., Dec. 17, 2020 University of California, Irvine health sciences researchers have created a machine-learning model to predict the probability that a COVID-19 patient will need a ventilator or ICU care. The tool is free and available online for any healthcare organization to use. The goal is to give an earlier alert to clinicians to identify patients who may be vulnerable at the onset, said Daniel S. Chow, an assistant professor in residence in radiological sciences and first author of the study, published in
PLOS ONE. The tool predicts whether a patient s condition will worsen within 72 hours.
Coupled with decision-making specific to the healthcare setting in which the tool is used, the model uses a patient s medical history to determine who can be sent home and who will need critical care. The study found that at UCI Health, the tool s predictions were accurate about 95 percent of the time.