Long COVID Characteristics and Experience: A Descriptive Study From the Yale LISTEN Research Cohort - 31/07/24
Abstract |
Background |
The experience of people with long COVID needs further amplification, especially with a comprehensive focus on symptomatology, treatments, and the impact on daily life and finances. Our intent is to describe the experience of people with long COVID symptomatology and characterize the psychological, social, and financial challenges they experience.
Methods |
We collected data from individuals aged 18 and older reporting long COVID as participants in the Yale Listen to Immune, Symptom and Treatment Experiences Now study. The sample population included 441 participants surveyed between May 2022 and July 2023. We evaluated their demographic characteristics, socioeconomic and psychological status, index infection period, health status, quality of life, symptoms, treatments, prepandemic comorbidities, and new-onset conditions.
Results |
Overall, the median age of the participants with long COVID was 46 years (interquartile range [IQR]: 38-57 years); 74% were women, 86% were non-Hispanic White, and 93% were from the United States. Participants reported a low health status measured by the Euro-QoL visual analog scale, with a median score of 49 (IQR: 32-61). Participants documented a diverse range of symptoms, with all 96 possible symptom choices being reported. Additionally, participants had tried many treatments (median number of treatments: 19, IQR: 12-28). They were also experiencing psychological distress, social isolation, and financial stress.
Conclusions |
Despite having tried numerous treatments, participants with long COVID continued to experience an array of health and financial challenges—findings that underscore the failure of the healthcare system to address the medical needs of people with long COVID. These insights highlight the need for crucial medical, mental health, financial, and community support services, as well as further scientific investigation to address the complex impact of long COVID.
Le texte complet de cet article est disponible en PDF.Keywords : COVID-19, Long COVID
Plan
Funding: This project was in part supported by the Howard Hughes Medical Institute Collaborative COVID-19 Initiative, in part supported by funds from Fred Cohen and Carolyn Klebanoff, and in part supported by CTSA Grant Number UL1 TR001863 from the National Center for Advancing Translational Science, a component of the National Institutes of Health. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health. |
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Conflicts of Interest: In the past 3 years, Harlan Krumholz received options for Element Science and Identifeye and payments from F-Prime for advisory roles. He and his spouse are co-founders of and have equity in Hugo Health, the personalized health data platform company that developed the Hugo Kindred platform. His spouse is an officer with Hugo Health. The Yale Conflict of Interest Committee oversees his involvement in this study. He is a co-founder of and holds equity in Refactor Health and Ensight-AI. He is associated with research contracts through Yale University from Janssen, Kenvue, Novartis, and Pfizer. Akiko Iwasaki co-founded RIGImmune, Xanadu Bio, and PanV, and is a member of the Board of Directors of Roche Holding Ltd and Genentech. Yuan Lu received research grants from the United States National Institutes of Health, the Patient-Centered Outcomes Research Institute, and the Sentara Research Foundation outside of the submitted work. Jeph Herrin receives funding from multiple institutes of the National Institutes of Health, from the Patient-Centered Outcomes Research Institute, the American Heart Association, and the Agency for Healthcare Research and Quality for research projects; from the Centers for Medicare & Medicaid Services for the development of quality measures; and from Pfizer. Chenxi Huang receives K12 funding from the National Center for Advancing Translational Science of the National Institutes of Health (UL1TR001863). Bornali Bhattacharjee is supported by, and César Caraballo was supported by, a grant from the Yale-Mayo Clinic Center of Excellence in Regulatory Science and Innovation (CERSI) (U01FD005938). The other authors have no financial relationships to disclose. |
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Authorship: All authors had access to the data in this study, and all had a role in writing and/or reviewing and editing the submitted manuscript for important intellectual content. MS: Writing – review & editing, Writing – original draft, Project administration, Investigation, Conceptualization. YW: Writing – review & editing, Writing – original draft, Formal analysis, Data curation. RMS: Writing – review & editing, Writing – original draft, Formal analysis, Data curation. TZ: Writing – review & editing, Supervision, Project administration, Methodology. ASA: Writing – review & editing, Writing – original draft, Methodology, Formal analysis. PK: Writing – review & editing, Writing – original draft, Methodology, Formal analysis. SK: Writing – review & editing, Writing – original draft, Methodology, Formal analysis. AV: Writing – review & editing, Writing – original draft, Formal analysis, Data curation. BB: Writing – review & editing, Project administration, Investigation. QD: Writing – review & editing, Resources. YL: Writing – review & editing, Supervision. CC: Writing – review & editing, Supervision, Project administration. FW: Writing – review & editing, Validation, Methodology. CH: Writing – review & editing, Validation, Methodology. JH: Writing – review & editing, Validation, Methodology. DP: Writing – review & editing, Supervision. TM: Writing – review & editing, Supervision. LF: Writing – review & editing, Supervision. CA: Writing – review & editing, Supervision. AI: Writing – review & editing, Supervision, Project administration, Investigation, Funding acquisition. HMK: Writing – review & editing, Conceptualization. |
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