Evidence map›Paper›PMID 38106559›Full record

ArticleEClinicalMedicine2023

Long-term symptom profiles after COVID-19

Giulia Vivaldi, Paul E Pfeffer, Mohammad Talaei, Tariro Jayson Basera, Seif O Shaheen, Adrian R Martineau

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in EClinicalMedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04330599 (Longitudinal Population-based Observational Study of COVID-19 in the UK Population), which is not on this map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
8.0field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04330599 recruitingnot on this map

Longitudinal Population-based Observational Study of COVID-19 in the UK Population

TypeobservationalSponsorQueen Mary University of LondonRan2020 to 2026Enrolled13,000ConditionsCOVID-19
3 · Its place in the literature

Who cites it

27 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.

  1. Guideline
  2. Article
  3. Article
  4. Article
  5. Leveraging Community-Based System Dynamics to Understand Long Covid Disparities in African American Communities: A Model for Health Equity Research.Health expectations : an international journal of public participation in health care and health policy · 2025
    Article
  6. Article
  7. Article
  8. Long COVID-19: A Concept Analysis.Infectious disease reports · 2025
    Article
  9. Article
  10. Observational
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Giulia VivaldiBlizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Paul E PfefferBarts Health NHS Trust, London, UK.
Mohammad TalaeiWolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Tariro Jayson BaseraBlizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Seif O ShaheenWolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Adrian R MartineauBlizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Queen Mary University of London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Long COVID is a well recognised, if heterogeneous, entity. Acute respiratory infections (ARIs) due to other pathogens may cause long-term symptoms, but few studies compare post-acute sequelae between SARS-CoV-2 and other ARIs. We aimed to compare symptom profiles between people with previous SARS-CoV-2 infection, people with previous non-COVID-19 ARIs, and contemporaneous controls, and to identify clusters of long-term symptoms. Methods: COVIDENCE UK is a prospective, population-based UK study of ARIs in adults. We analysed data for 16 potential long COVID symptoms and health-related quality of life (HRQoL), reported between January 21 and February 15, 2021, by participants unvaccinated against SARS-CoV-2. We classified participants as having previous SARS-CoV-2 infection or previous non-COVID-19 ARI (≥4 weeks prior) or no reported ARI. We compared symptoms by infection status using logistic and fractional regression, and identified symptom clusters using latent class analysis (LCA). This study is registered with ClinicalTrials.gov, NCT04330599. Findings: We included 10,171 participants (1311 [12.9%] with SARS-CoV-2 infection, 472 [4.6%] with non-COVID-19 ARI). Both types of infection were associated with increased prevalence/severity of most symptoms and decreased HRQoL compared with no infection. Participants with SARS-CoV-2 infection had increased odds of problems with taste/smell (odds ratio 19.74, 95% CI 10.53-37.00) and lightheadedness or dizziness (1.74, 1.18-2.56) compared with participants with non-COVID-19 ARIs. Separate LCA models identified three symptom severity groups for each infection type. In the most severe groups (representing 22% of participants for both SARS-CoV-2 and non-COVID-19 ARI), SARS-CoV-2 infection presented with a higher probability of problems with taste/smell (probability 0.41 Interpretation: Both SARS-CoV-2 and non-COVID-19 ARIs are associated with a wide range of symptoms more than 4 weeks after the acute infection. Research on post-acute sequelae of ARIs should extend from SARS-CoV-2 to include other pathogens. Funding: Barts Charity.

Indexed as

Acute respiratory infectionsLong COVIDPost-acute sequelaeSARS-CoV-2

Identifiers

PMID38106559
PMCPMC10721552
OpenAlexW4387407220

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.