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Author Correction: Attributes and predictors of long COVID.
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.
  • Sudre CH; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • Murray B; MRC Unit for Lifelong Health and Ageing, Department of Population Health Sciences, University College London, London, UK.
  • Varsavsky T; Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK.
  • Graham MS; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • Penfold RS; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • Bowyer RC; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • Pujol JC; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Klaser K; Zoe Global, London, UK.
  • Antonelli M; Zoe Global, London, UK.
  • Canas LS; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • Molteni E; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • Modat M; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • Jorge Cardoso M; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • May A; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • Ganesh S; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • Davies R; Zoe Global, London, UK.
  • Nguyen LH; Zoe Global, London, UK.
  • Drew DA; Zoe Global, London, UK.
  • Astley CM; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA.
  • Joshi AD; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA.
  • Merino J; Division of Endocrinology & Computational Epidemiology, Boston Children's Hospital, Boston, MA, USA.
  • Tsereteli N; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA.
  • Fall T; Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
  • Gomez MF; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.
  • Duncan EL; Department of Medicine, Harvard Medical School, Boston, MA, USA.
  • Menni C; Lund University Diabetes Centre, Department of Clinical Sciences, Malmö, Sweden.
  • Williams FMK; Molecular Epidemiology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
  • Franks PW; Lund University Diabetes Centre, Department of Clinical Sciences, Malmö, Sweden.
  • Chan AT; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Wolf J; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Ourselin S; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Spector T; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Steves CJ; Lund University Diabetes Centre, Department of Clinical Sciences, Malmö, Sweden.
Nat Med ; 27(6): 1116, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1260945

Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Long Covid Language: English Journal: Nat Med Journal subject: Molecular Biology / Medicine Year: 2021 Document Type: Article Affiliation country: S41591-021-01361-2

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Topics: Long Covid Language: English Journal: Nat Med Journal subject: Molecular Biology / Medicine Year: 2021 Document Type: Article Affiliation country: S41591-021-01361-2