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Trajectories of the Evolution of Post COVID-19 Condition, Up to Two Years after Symptoms Onset

13 Pages Posted: 20 Oct 2022

See all articles by Clemence Servier

Clemence Servier

Center for Research in Epidemiology and Statistics Sorbonne Paris Cité (CRESS- UMR 1153) - METHODS Team

Raphael Porcher

Université Côte d'Azur - INSERM; Universite Paris Descartes - Center for Clinical Epidemiology; Center for Research in Epidemiology and Statistics Sorbonne Paris Cité (CRESS- UMR 1153) - METHODS Team

Isabelle Pane

Center for Research in Epidemiology and Statistics Sorbonne Paris Cité (CRESS- UMR 1153) - METHODS Team

Philippe Ravaud

Center for Research in Epidemiology and Statistics Sorbonne Paris Cité (CRESS- UMR 1153) - METHODS Team

Viet-Thi Tran

Center for Research in Epidemiology and Statistics Sorbonne Paris Cité (CRESS- UMR 1153) - METHODS Team; Universite Paris Descartes; Universite Paris Descartes - Center for Clinical Epidemiology

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Abstract

Background: Post coronavirus-19 (COVID-19) condition is multifaceted with a heterogeneous clinical presentation. We aimed to identify distinct trajectories of the evolution of post COVID-19 condition, up to two years after symptom onset.

Methods: The ComPaRe long COVID e-cohort is a nationwide prospective cohort of adult patients with symptoms lasting at least two months after SARS-CoV2 infection. We used trajectory modelling to identify different trajectories of the evolution of post COVID-19 condition, based on 53 self-reported symptoms collected every 60 days using the long COVID Symptom Tool. We used regression analyses to identify the clinical characteristics associated with each trajectory.

Findings: A total of 2,197 patients were enrolled in the cohort between December 2020 and July 2022 (median age 46 years, interquartile range [IQR] 38–54 years; 79% women and 69% with laboratory- confirmed SARS-CoV-2 infection). Three distinct trajectories of the evolution of post COVID-19 condition were identified: “high persistent symptoms” (4%), “rapidly decreasing symptoms” (5%), and “slowly decreasing symptoms” (91%). Participants with high persistent symptoms were older and more likely to report a history of systemic diseases. They often reported tachycardia, bradycardia, palpitations, and arrhythmia, paraesthesia or hot flushes. Participants with rapidly decreasing symptoms were younger and more likely to report a confirmed infection. They often reported diarrhoea and, neck, back, and/or low back pain. Participants with slowly decreasing symptoms were more likely to have functional diseases.

Interpretation: Most of patients with post COVID-19 condition improve slowly over time, while 5% have rapid improvement in the two years after symptom onset and 4% have a persistent condition. Our results will help to better inform patients about their prognosis and warrant special focus on the response required by the healthcare system.

Funding: The authors received no specific funding for this study.

Declaration of Interest: The authors declare no competing interests or financial associations that may be relevant or seen as relevant to the submitted manuscript

Ethical Approval: The Institutional Review Board of Hôtel-Dieu Hospital, Paris (IRB 0008367) approved the ComPaRe cohort.

Keywords: COVID-19, long COVID, trajectory, prospective cohort, natural history, endotypes

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Suggested Citation

Servier, Clemence and Porcher, Raphael and Pane, Isabelle and Ravaud, Philippe and Tran, Viet-Thi, Trajectories of the Evolution of Post COVID-19 Condition, Up to Two Years after Symptoms Onset. Available at SSRN: https://ssrn.com/abstract=4253730 or http://dx.doi.org/10.2139/ssrn.4253730

Clemence Servier

Center for Research in Epidemiology and Statistics Sorbonne Paris Cité (CRESS- UMR 1153) - METHODS Team ( email )

Raphael Porcher

Université Côte d'Azur - INSERM ( email )

France

Universite Paris Descartes - Center for Clinical Epidemiology ( email )

France

Center for Research in Epidemiology and Statistics Sorbonne Paris Cité (CRESS- UMR 1153) - METHODS Team ( email )

Isabelle Pane

Center for Research in Epidemiology and Statistics Sorbonne Paris Cité (CRESS- UMR 1153) - METHODS Team ( email )

Philippe Ravaud

Center for Research in Epidemiology and Statistics Sorbonne Paris Cité (CRESS- UMR 1153) - METHODS Team

Viet-Thi Tran (Contact Author)

Center for Research in Epidemiology and Statistics Sorbonne Paris Cité (CRESS- UMR 1153) - METHODS Team ( email )

1 Place du Parvis Notre Dame
Paris, 75006
France

Universite Paris Descartes ( email )

12, rue de l'Ecole de Médecine
Cedex 06
Paris, 75270
France

Universite Paris Descartes - Center for Clinical Epidemiology ( email )

France

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