| Title: |
Attributes and predictors of long COVID |
| Authors: |
Sudre CH; Murray B; Varsavsky T; Graham MS; Penfold RS; Bowyer RC; Pujol JC; Klaser K; Antonelli M; Canas LS; Molteni E; Modat M; Cardoso MJ; May A; Ganesh S; Davies R; Nguyen LH; Drew DA; Astley CM; Joshi AD; Merino J; Tsereteli N; Fall T; Gomez MF; Duncan EL; Menni C; Williams FMK; Franks PW; Chan AT; Wolf J; Ourselin S; Spector T; Steves CJ |
| Contributors: |
C. Sudre; B. Murray; T. Varsavsky; M. Graham; R. Penfold; R. Bowyer; J. Pujol; K. Klaser; M. Antonelli; L. Cana; E. Molteni; M. Modat; M. Cardoso; A. May; S. Ganesh; R. Davie; L. Nguyen; D. Drew; C. Astley; A. Joshi; J. Merino; N. Tsereteli; T. Fall; M. Gomez; E. Duncan; C. Menni; F. William; P. Frank; A. Chan; J. Wolf; S. Ourselin; T. Spector; C. Steves |
| Publication Year: |
2021 |
| Collection: |
The University of Milan: Archivio Istituzionale della Ricerca (AIR) |
| Subject Terms: |
Settore MEDS-24/A - Statistica medica |
| Description: |
Reports of long-lasting coronavirus disease 2019 (COVID-19) symptoms, the so-called 'long COVID', are rising but little is known about prevalence, risk factors or whether it is possible to predict a protracted course early in the disease. We analyzed data from 4,182 incident cases of COVID-19 in which individuals self-reported their symptoms prospectively in the COVID Symptom Study app(1). A total of 558 (13.3%) participants reported symptoms lasting >= 28 days, 189 (4.5%) for >= 8 weeks and 95 (2.3%) for >= 12 weeks. Long COVID was characterized by symptoms of fatigue, headache, dyspnea and anosmia and was more likely with increasing age and body mass index and female sex. Experiencing more than five symptoms during the first week of illness was associated with long COVID (odds ratio = 3.53 (2.76-4.50)). A simple model to distinguish between short COVID and long COVID at 7 days (total sample size, n = 2,149) showed an area under the curve of the receiver operating characteristic curve of 76%, with replication in an independent sample of 2,472 individuals who were positive for severe acute respiratory syndrome coronavirus 2. This model could be used to identify individuals at risk of long COVID for trials of prevention or treatment and to plan education and rehabilitation services. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
info:eu-repo/semantics/altIdentifier/pmid/33692530; info:eu-repo/semantics/altIdentifier/wos/WOS:000627193300001; volume:27; issue:4; firstpage:626; lastpage:631; numberofpages:6; journal:NATURE MEDICINE; https://hdl.handle.net/2434/1101088 |
| DOI: |
10.1038/s41591-021-01292-y |
| Availability: |
https://hdl.handle.net/2434/1101088; https://doi.org/10.1038/s41591-021-01292-y |
| Rights: |
info:eu-repo/semantics/openAccess |
| Accession Number: |
edsbas.BEE8EDDD |
| Database: |
BASE |