| Title: |
Profiling post-COVID-19 condition across different variants of SARS-CoV-2: a prospective longitudinal study in unvaccinated wild-type, unvaccinated alpha-variant, and vaccinated delta-variant populations |
| Authors: |
Canas, LS; Molteni, E; Deng, J; Sudre, CH; Murray, B; Kerfoot, E; Antonelli, M; Rjoob, K; Capdevila Pujol, J; Polidori, L; May, A; Österdahl, MF; Whiston, R; Cheetham, NJ; Bowyer, V; Spector, TD; Hammers, A; Duncan, EL; Ourselin, S; Steves, CJ; Modat, M |
| Source: |
The Lancet Digital Health , 5 (7) e421-e434. (2023) |
| Publisher Information: |
Elsevier BV |
| Publication Year: |
2023 |
| Collection: |
University College London: UCL Discovery |
| Subject Terms: |
Humans; SARS-CoV-2; COVID-19; Longitudinal Studies; Artificial Intelligence; Pandemics; Post-Acute COVID-19 Syndrome; Prospective Studies |
| Description: |
BACKGROUND: Self-reported symptom studies rapidly increased understanding of SARS-CoV-2 during the COVID-19 pandemic and enabled monitoring of long-term effects of COVID-19 outside hospital settings. Post-COVID-19 condition presents as heterogeneous profiles, which need characterisation to enable personalised patient care. We aimed to describe post-COVID-19 condition profiles by viral variant and vaccination status. METHODS: In this prospective longitudinal cohort study, we analysed data from UK-based adults (aged 18–100 years) who regularly provided health reports via the Covid Symptom Study smartphone app between March 24, 2020, and Dec 8, 2021. We included participants who reported feeling physically normal for at least 30 days before testing positive for SARS-CoV-2 who subsequently developed long COVID (ie, symptoms lasting longer than 28 days from the date of the initial positive test). We separately defined post-COVID-19 condition as symptoms that persisted for at least 84 days after the initial positive test. We did unsupervised clustering analysis of time-series data to identify distinct symptom profiles for vaccinated and unvaccinated people with post-COVID-19 condition after infection with the wild-type, alpha (B.1.1.7), or delta (B.1.617.2 and AY.x) variants of SARS-CoV-2. Clusters were then characterised on the basis of symptom prevalence, duration, demography, and previous comorbidities. We also used an additional testing sample with additional data from the Covid Symptom Study Biobank (collected between October, 2020, and April, 2021) to investigate the effects of the identified symptom clusters of post-COVID-19 condition on the lives of affected people. FINDINGS: We included 9804 people from the COVID Symptom Study with long COVID, 1513 (15%) of whom developed post-COVID-19 condition. Sample sizes were sufficient only for analyses of the unvaccinated wild-type, unvaccinated alpha variant, and vaccinated delta variant groups. We identified distinct profiles of symptoms for post-COVID-19 condition ... |
| Document Type: |
article in journal/newspaper |
| File Description: |
text |
| Language: |
English |
| Relation: |
https://discovery.ucl.ac.uk/id/eprint/10174197/ |
| Availability: |
https://discovery.ucl.ac.uk/id/eprint/10174197/1/Sudre_Profiling%20post-COVID-19%20condition%20across%20different%20variants%20of%20SARS-CoV-2_VoR.pdf; https://discovery.ucl.ac.uk/id/eprint/10174197/ |
| Rights: |
open |
| Accession Number: |
edsbas.E6A76B94 |
| Database: |
BASE |