Characterizing Long COVID: Deep Phenotype of a Complex Condition
Autor: | Joel H. Saltz, Tellen D. Bennett, Emily R. Pfaff, George D. Vavougios, Sebastian Köhler, Joel J. Gagnier, Melissa Haendel, Chen Liang, Madeline A Rock, Peter N. Robinson, Anupam A Sule, Farrukh M. Koraishy, Carolyn T. Bramante, Julian Solway, Hongfang Liu, Umit Topaloglu, Heidi Spratt, Douglas S McNair, Tiffany J. Callahan, Teshamae S. Monteith, Wesley Kimble, Lauren E Chan, Julie A. McMurry, James Brian Byrd, Casey S. Greene, Richard A. Moffitt, Alfred J. Anzalone, Ann M. Parker, Ben Coleman, Mallory A Perry, Charisse R. Madlock-Brown, Robert A Schuff, Feifan Liu, Rachel R Deer, Vithal Madhira, Hannah E. Davis, Marc D. Basson, Timothy Bergquist, Halie M. Rando, Ramakanth Kavuluru, Diego R. Mazzotti, Nicole Vasilevsky, Anthony Solomonides, Liwei Wang, Leigh C. Carmody, Nicolas Matentzoglu, Eilis A. Boudreau, Justin T. Reese, Gary S. Stein, William B. Hillegass, Christopher G. Chute, Haitao Chu |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
medicine.medical_specialty
Medicine (General) Medical terminology phenotyping Coronavirus disease 2019 (COVID-19) media_common.quotation_subject Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) General Biochemistry Genetics and Molecular Biology Terminology Presentation Post-Acute COVID-19 Syndrome R5-920 Human Phenotype Ontology medicine Relevance (law) Humans In patient Intensive care medicine long COVID Organ system media_common Original Research business.industry SARS-CoV-2 Foundation (evidence) COVID-19 General Medicine Natural history Layperson of post-acute sequelae of SARS-CoV-2 Medicine business human phenotype ontology |
Zdroj: | EBioMedicine, Vol 74, Iss, Pp 103722-(2021) EBioMedicine |
ISSN: | 2352-3964 |
Popis: | Background Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or "long COVID"), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. Methods The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. Findings We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. Interpretation Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID. Funding U24TR002306; UL1TR001439; P30AG024832; GBMF4552; R01HG010067; UL1TR002535; K23HL128909; UL1TR002389; K99GM145411 . |
Databáze: | OpenAIRE |
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