학술논문
Characterization of long COVID temporal sub-phenotypes by distributed representation learning from electronic health record data: a cohort studyResearch in Context
Document Type
article
Author
Arianna Dagliati; Zachary H. Strasser; Zahra Shakeri Hossein Abad; Jeffrey G. Klann; Kavishwar B. Wagholikar; Rebecca Mesa; Shyam Visweswaran; Michele Morris; Yuan Luo; Darren W. Henderson; Malarkodi Jebathilagam Samayamuthu; Bryce W.Q. Tan; Guillame Verdy; Gilbert S. Omenn; Zongqi Xia; Riccardo Bellazzi; Shawn N. Murphy; John H. Holmes; Hossein Estiri; James R. Aaron; Giuseppe Agapito; Adem Albayrak; Giuseppe Albi; Mario Alessiani; Anna Alloni; Danilo F. Amendola; François Angoulvant; Li L.L.J. Anthony; Bruce J. Aronow; Fatima Ashraf; Andrew Atz; Paul Avillach; Paula S. Azevedo; James Balshi; Brett K. Beaulieu-Jones; Douglas S. Bell; Antonio Bellasi; Vincent Benoit; Michele Beraghi; José Luis Bernal-Sobrino; Mélodie Bernaux; Romain Bey; Surbhi Bhatnagar; Alvar Blanco-Martínez; Clara-Lea Bonzel; John Booth; Silvano Bosari; Florence T. Bourgeois; Robert L. Bradford; Gabriel A. Brat; Stéphane Bréant; Nicholas W. Brown; Raffaele Bruno; William A. Bryant; Mauro Bucalo; Emily Bucholz; Anita Burgun; Tianxi Cai; Mario Cannataro; Aldo Carmona; Charlotte Caucheteux; Julien Champ; Jin Chen; Krista Y. Chen; Luca Chiovato; Lorenzo Chiudinelli; Kelly Cho; James J. Cimino; Tiago K. Colicchio; Sylvie Cormont; Sébastien Cossin; Jean B. Craig; Juan Luis Cruz-Bermúdez; Jaime Cruz-Rojo; Mohamad Daniar; Christel Daniel; Priyam Das; Batsal Devkota; Audrey Dionne; Rui Duan; Julien Dubiel; Scott L. DuVall; Loic Esteve; Shirley Fan; Robert W. Follett; Thomas Ganslandt; Noelia García- Barrio; Lana X. Garmire; Nils Gehlenborg; Emily J. Getzen; Alon Geva; Tobias Gradinger; Alexandre Gramfort; Romain Griffier; Nicolas Griffon; Olivier Grisel; Alba Gutiérrez-Sacristán; Larry Han; David A. Hanauer; Christian Haverkamp; Derek Y. Hazard; Bing He; Martin Hilka; Yuk-Lam Ho; Chuan Hong; Kenneth M. Huling; Meghan R. Hutch; Richard W. Issitt; Anne Sophie Jannot; Vianney Jouhet; Ramakanth Kavuluru; Mark S. Keller; Chris J. Kennedy; Daniel A. Key; Katie Kirchoff; Isaac S. Kohane; Ian D. Krantz; Detlef Kraska; Ashok K. Krishnamurthy; Sehi L'Yi; Trang T. Le; Judith Leblanc; Guillaume Lemaitre; Leslie Lenert; Damien Leprovost; Molei Liu; Ne Hooi Will Loh; Qi Long; Sara Lozano-Zahonero; Kristine E. Lynch; Sadiqa Mahmood; Sarah E. Maidlow; Adeline Makoudjou; Alberto Malovini; Kenneth D. Mandl; Chengsheng Mao; Anupama Maram; Patricia Martel; Marcelo R. Martins; Jayson S. Marwaha; Aaron J. Masino; Maria Mazzitelli; Arthur Mensch; Marianna Milano; Marcos F. Minicucci; Bertrand Moal; Taha Mohseni Ahooyi; Jason H. Moore; Cinta Moraleda; Jeffrey S. Morris; Karyn L. Moshal; Sajad Mousavi; Danielle L. Mowery; Douglas A. Murad; Thomas P. Naughton; Carlos Tadeu Breda Neto; Antoine Neuraz; Jane Newburger; Kee Yuan Ngiam; Wanjiku F.M. Njoroge; James B. Norman; Jihad Obeid; Marina P. Okoshi; Karen L. Olson; Nina Orlova; Brian D. Ostasiewski; Nathan P. Palmer; Nicolas Paris; Lav P. Patel; Miguel Pedrera-Jiménez; Emily R. Pfaff; Ashley C. Pfaff; Danielle Pillion; Sara Pizzimenti; Hans U. Prokosch; Robson A. Prudente; Andrea Prunotto; Víctor Quirós-González; Rachel B. Ramoni; Maryna Raskin; Siegbert Rieg; Gustavo Roig-Domínguez; Pablo Rojo; Paula Rubio-Mayo; Paolo Sacchi; Carlos Sáez; Elisa Salamanca; L. Nelson Sanchez-Pinto; Arnaud Sandrin; Nandhini Santhanam; Janaina C.C. Santos; Fernando J. Sanz Vidorreta; Maria Savino; Emily R. Schriver; Petra Schubert; Juergen Schuettler; Luigia Scudeller; Neil J. Sebire; Pablo Serrano-Balazote; Patricia Serre; Arnaud Serret-Larmande; Mohsin Shah; Domenick Silvio; Piotr Sliz; Jiyeon Son; Charles Sonday; Andrew M. South; Anastasia Spiridou; Amelia L.M. Tan; Byorn W.L. Tan; Suzana E. Tanni; Deanne M. Taylor; Ana I. Terriza-Torres; Valentina Tibollo; Patric Tippmann; Emma M.S. Toh; Carlo Torti; Enrico M. Trecarichi; Yi-Ju Tseng; Andrew K. Vallejos; Gael Varoquaux; Margaret E. Vella; Guillaume Verdy; Jill-Jênn Vie; Michele Vitacca; Lemuel R. Waitman; Xuan Wang; Demian Wassermann; Griffin M. Weber; Martin Wolkewitz; Scott Wong; Xin Xiong; Ye Ye; Nadir Yehya; William Yuan; Alberto Zambelli; Harrison G. Zhang; Daniela Zo¨ller; Valentina Zuccaro; Chiara Zucco
Source
EClinicalMedicine, Vol 64, Iss , Pp 102210- (2023)
Subject
Language
English
ISSN
2589-5370
Abstract
Summary: Background: Characterizing Post-Acute Sequelae of COVID (SARS-CoV-2 Infection), or PASC has been challenging due to the multitude of sub-phenotypes, temporal attributes, and definitions. Scalable characterization of PASC sub-phenotypes can enhance screening capacities, disease management, and treatment planning. Methods: We conducted a retrospective multi-centre observational cohort study, leveraging longitudinal electronic health record (EHR) data of 30,422 patients from three healthcare systems in the Consortium for the Clinical Characterization of COVID-19 by EHR (4CE). From the total cohort, we applied a deductive approach on 12,424 individuals with follow-up data and developed a distributed representation learning process for providing augmented definitions for PASC sub-phenotypes. Findings: Our framework characterized seven PASC sub-phenotypes. We estimated that on average 15.7% of the hospitalized COVID-19 patients were likely to suffer from at least one PASC symptom and almost 5.98%, on average, had multiple symptoms. Joint pain and dyspnea had the highest prevalence, with an average prevalence of 5.45% and 4.53%, respectively. Interpretation: We provided a scalable framework to every participating healthcare system for estimating PASC sub-phenotypes prevalence and temporal attributes, thus developing a unified model that characterizes augmented sub-phenotypes across the different systems. Funding: Authors are supported by National Institute of Allergy and Infectious Diseases, National Institute on Aging, National Center for Advancing Translational Sciences, National Medical Research Council, National Institute of Neurological Disorders and Stroke, European Union, National Institutes of Health, National Center for Advancing Translational Sciences.