Identifying trajectories of the evolution of post-COVID-19 condition

NewsGuard 100/100 Score

A recent study published in the International Journal of Infectious Diseases analyzed the evolution of the post-coronavirus disease 2019 (COVID-19) condition for up to two years post-onset.

Study: Trajectories of the evolution of post COVID-19 condition, up to two years after symptoms onset. Image Credit: AriyaJ/Shutterstock.comStudy: Trajectories of the evolution of post COVID-19 condition, up to two years after symptoms onset. Image Credit: AriyaJ/Shutterstock.com

Background

Most individuals with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection recover from the illness. Still, some report symptoms beyond 4-12 weeks post-infection, a condition termed long COVID or post-COVID-19 condition.

Fatigue, dyspnea, altered taste or smell, cognitive disturbances, and chest pain are the most common symptoms.

Most longitudinal studies described the prevalence of patients with symptoms at specific time points post-infection without identifying or defining distinct patient subgroups.

Only a few studies have assessed the heterogeneity of this condition, focusing on the presence of symptom clusters. Specifically, clustering was based on the similarities in symptoms and clinical presentation of patients instead of evolution over time.

About the study

In the present study, researchers evaluated whether distinct evolutionary trajectories of the post-COVID-19 condition could be identified.

They obtained data from an e-cohort of over 50,000 French patients with chronic conditions, followed up through self-reported outcome or experience measurements. A long COVID cohort was established within this e-cohort in December 2020.

The team included all adults in the cohort who had suspected or confirmed COVID-19 and at least one of the 53 symptoms within three months of onset that linger for at least two months.

Individuals lacking the date of symptom onset were excluded. Participants were instructed to complete periodical questionnaires, and they self-reported the symptom onset date.

Patients were considered to be in remission if they reported having no symptoms in three successive questionnaires. The primary outcome was the long COVID-19 symptom tool score, which assessed 53 symptoms.

Latent class mixed modeling was used to identify trajectories in symptom evolution over time. The robustness of the model was examined using the numerical sampling method.

Findings

The study included 2,197 long COVID patients, predominately females (79%), with a median age of 46. Most participants (90%) were enrolled before June 7, 2021, when SARS-CoV-2 Alpha was the predominant variant in France.

Patients were followed up for a median of 291 days. Overall, 10,799 measurements were obtained. Seventy-seven patients reported reinfection; 141 patients were considered to be in remission.

The researchers observed three trajectories – 1) high persistent symptoms, 2) rapidly decreasing symptoms, and 3) slowly decreasing symptoms. Ninety-four patients had high scores at symptom onset with no or little change in symptoms.

These patients with highly persistent symptoms often reported bradycardia, arrhythmia, palpitations, tachycardia, paresthesia, sweating, heat or cold intolerance, phonophobia, and photophobia within the first year of symptom onset.

Daily relapses were reported by half of these patients, which was consistent at 18 months post-onset. Less than weekly relapses were reported by 4% and 10% of these subjects at symptom onset and 18 months post-onset, respectively.

There were 104 patients with moderate scores at symptom onset who exhibited a decrease in symptoms. These subjects were likelier to report back pain, lower back pain, neck pain, and diarrhea in the first year of onset. Less than weekly relapses increased to 75% after 18 months.

Most participants (90.8%) with a low score exhibited a slow improvement in symptoms over time. Less than weekly relapses were reported by 11% and 30% of these patients at symptom onset and after 18 months, respectively. Results were similar for the subgroup of patients with laboratory-confirmed COVID-19.

Older individuals, current smokers, subjects with systemic diseases, and those without functional diseases were likelier to have highly persistent symptoms than those with slowly decreasing symptoms.

Current smokers and those without functional diseases were more likely to have rapidly decreasing symptoms than those with slowly reducing symptoms. Older patients and participants with systemic diseases were less likely to have rapidly reduced symptoms.

Conclusions

Taken together, the researchers identified three trajectories of the evolution of the post-COVID-19 condition. Most patients (nearly 91%) exhibited a much slower symptom improvement over time.

Most subjects were recruited when the wild-type strain and the Alpha variant circulated. Despite the small number of individuals infected during the Omicron wave, none exhibited highly persistent symptoms.

Further studies should explore the association of these trajectories with biological and clinical markers.

Journal reference:
Tarun Sai Lomte

Written by

Tarun Sai Lomte

Tarun is a writer based in Hyderabad, India. He has a Master’s degree in Biotechnology from the University of Hyderabad and is enthusiastic about scientific research. He enjoys reading research papers and literature reviews and is passionate about writing.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Sai Lomte, Tarun. (2023, May 17). Identifying trajectories of the evolution of post-COVID-19 condition. News-Medical. Retrieved on April 26, 2024 from https://www.news-medical.net/news/20230517/Identifying-trajectories-of-the-evolution-of-post-COVID-19-condition.aspx.

  • MLA

    Sai Lomte, Tarun. "Identifying trajectories of the evolution of post-COVID-19 condition". News-Medical. 26 April 2024. <https://www.news-medical.net/news/20230517/Identifying-trajectories-of-the-evolution-of-post-COVID-19-condition.aspx>.

  • Chicago

    Sai Lomte, Tarun. "Identifying trajectories of the evolution of post-COVID-19 condition". News-Medical. https://www.news-medical.net/news/20230517/Identifying-trajectories-of-the-evolution-of-post-COVID-19-condition.aspx. (accessed April 26, 2024).

  • Harvard

    Sai Lomte, Tarun. 2023. Identifying trajectories of the evolution of post-COVID-19 condition. News-Medical, viewed 26 April 2024, https://www.news-medical.net/news/20230517/Identifying-trajectories-of-the-evolution-of-post-COVID-19-condition.aspx.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Does diabetes increase the risk of long COVID?