Attributes and predictors of long COVID

Author: Sudre, Carole H.; Murray, Benjamin; Varsavsky, Thomas; Graham, Mark S.; Penfold, Rose S.; Bowyer, Ruth C.; Pujol, Joan Capdevila; Klaser, Kerstin; Antonelli, Michela; Canas, Liane S.; Molteni, Erika; Modat, Marc; Jorge Cardoso, M.; May, Anna; Ganesh, Sajaysurya; Davies, Richard; Nguyen, Long H.; Drew, David A.; Astley, Christina M.; Joshi, Amit D.; Merino, Jordi; Tsereteli, Neli; Fall, Tove; Gomez, Maria F.; Duncan, Emma L.; Menni, Cristina; Williams, Frances M. K.; Franks, Paul W.; Chan, Andrew T.; Wolf, Jonathan; Ourselin, Sebastien; Spector, Tim; Steves, Claire J.

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. 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.

Subject headings: Adult; Age Factors; Aged; COVID-19; Female; Humans; Male; Middle Aged; Prospective Studies; Risk Factors; SARS-CoV-2; Time Factors; Long covid

Publication year: 2021

Journal or book title: Nature Medicine

Volume: 27

Issue: 4

Pages: 626-631

Find the full text: https://www.nature.com/articles/s41591-021-01292-y.pdf

Find more like this one (cited by): https://scholar.google.com/scholar?cites=8434619110205895761&as_sdt=1000005&sciodt=0,16&hl=en

Serial number: 3558

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