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2 results on '"Gwenn E McLaughlin"'

1. Data-driven clustering identifies features distinguishing multisystem inflammatory syndrome from acute COVID-19 in children and adolescents

Author

Alon Geva, Manish M. Patel, Margaret M. Newhams, Cameron C. Young, Mary Beth F. Son, Michele Kong, Aline B. Maddux, Mark W. Hall, Becky J. Riggs, Aalok R. Singh, John S. Giuliano, Charlotte V. Hobbs, Laura L. Loftis, Gwenn E. McLaughlin, Stephanie P. Schwartz, Jennifer E. Schuster, Christopher J. Babbitt, Natasha B. Halasa, Shira J. Gertz, Sule Doymaz, Janet R. Hume, Tamara T. Bradford, Katherine Irby, Christopher L. Carroll, John K. McGuire, Keiko M. Tarquinio, Courtney M. Rowan, Elizabeth H. Mack, Natalie Z. Cvijanovich, Julie C. Fitzgerald, Philip C. Spinella, Mary A. Staat, Katharine N. Clouser, Vijaya L. Soma, Heda Dapul, Mia Maamari, Cindy Bowens, Kevin M. Havlin, Peter M. Mourani, Sabrina M. Heidemann, Steven M. Horwitz, Leora R. Feldstein, Mark W. Tenforde, Jane W. Newburger, Kenneth D. Mandl, and Adrienne G. Randolph

Subjects
COVID-19, Multisystem inflammatory syndrome, Pediatrics, Critical care medicine, Clustering, Medicine (General), R5-920
Abstract

Background: Multisystem inflammatory syndrome in children (MIS-C) consensus criteria were designed for maximal sensitivity and therefore capture patients with acute COVID-19 pneumonia. Methods: We performed unsupervised clustering on data from 1,526 patients (684 labeled MIS-C by clinicians)

Published
2021
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2. Data-driven clustering identifies features distinguishing multisystem inflammatory syndrome from acute COVID-19 in children and adolescents

Author

Shira J. Gertz, Vijaya L. Soma, Margaret M. Newhams, Courtney M. Rowan, Aline B Maddux, Aalok R. Singh, Tamara T. Bradford, Mark W. Hall, Mary Beth F. Son, Manish M. Patel, Michele Kong, Natalie Z. Cvijanovich, John K. McGuire, Gwenn E. McLaughlin, Laura Loftis, Overcoming Covid Investigators, Philip C. Spinella, Julie C. Fitzgerald, Steven M. Horwitz, Elizabeth H. Mack, Alon Geva, Katharine N. Clouser, Heda Dapul, Cindy Bowens, Sule Doymaz, Becky J. Riggs, Stephanie P Schwartz, Jennifer E. Schuster, Leora R. Feldstein, Keiko M. Tarquinio, Sabrina M. Heidemann, Cameron C. Young, Katherine Irby, Christopher L. Carroll, Jane W. Newburger, Mary Allen Staat, Kenneth D. Mandl, John S. Giuliano, Mark W Tenforde, Peter M. Mourani, Christopher J. Babbitt, Charlotte V. Hobbs, Janet R. Hume, Mia Maamari, Kevin M Havlin, Adrienne G. Randolph, and Natasha B. Halasa

Subjects
medicine.medical_specialty, Medicine (General), medicine.diagnostic_test, Coronavirus disease 2019 (COVID-19), business.industry, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Mucocutaneous zone, Pulmonary disease, COVID-19, Multisystem inflammatory syndrome, General Medicine, medicine.disease, Pediatrics, Article, Clustering, Pneumonia, R5-920, Internal medicine, Medicine, High likelihood, Critical care medicine, business, Chest radiograph, Cluster analysis
Abstract

Background: Multisystem inflammatory syndrome in children (MIS-C) consensus criteria were designed for maximal sensitivity and therefore capture patients with acute COVID-19 pneumonia. Methods: We performed unsupervised clustering on data from 1,526 patients (684 labeled MIS-C by clinicians)

Published
2021

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