Machine Learning Predicts Prolonged Acute Hypoxemic Respiratory Failure in Pediatric Severe Influenza

Machine Learning Predicts Prolonged Acute Hypoxemic Respiratory Failure in Pediatric Severe Influenza

Background:. Influenza virus is a major cause of acute hypoxemic respiratory failure. Early identification of patients who will suffer severe complications can help stratify patients for clinical trials and plan for resource use in case of pandemic. Objective:. We aimed to identify which clinical va...

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Auteurs principaux: Michaël S. Sauthier, MD MBI, Philippe A. Jouvet, MD, PhDMBA, Margaret M. Newhams,, MPH, Adrienne G. Randolph, MD, MSc, for the Pediatric Acute Lung Injury and Sepsis Investigators (PALISI) Pediatric Intensive Care Influenza (PICFLU) Network Investigators, Michele Kong, Ronald C. Sanders, Jr, Olivia K. Irby, David Tellez, Katri Typpo, Barry Markovitz, Natalie Cvijanovich, Heidi Flori, Adam Schwarz, Nick Anas, Patrick McQuillen, Peter Mourani, John S. Giuliano, Jr., Gwenn McLaughlin, Matthew Paden, Keiko Tarquinio, Bria M. Coates, Neethi Pinto, Juliane Bubeck Wardenburg, Janice Sullivan, Vicki Montgomery, Adrienne G. Randolph, Anna A. Agan, Tanya Novak, Margaret M. Newhams, Melania Bembea, Sapna R. Kudchadkar, Stephen C. Kurachek, Mary E. Hartman, Edward J. Truemper, Sidharth Mahapatra, Sholeen Nett, Daniel L. Levin, Kate G. Ackerman, Ryan Nofziger, Steven L. Shein, Mark W. Hall, Neal Thomas, Scott L. Weiss, Julie Fitzgerald, Renee Higgerson, Laura L. Loftis, Rainer G. Gedeit
Format: article
Langue:EN
Publié: Wolters Kluwer 2020
Sujets:
Medical emergencies. Critical care. Intensive care. First aid
RC86-88.9
Accès en ligne:https://doaj.org/article/ca6d7df3e8c14e91a9b1f188a01d97ae
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