Symptom clusters in COVID-19: A potential clinical prediction tool from the COVID Symptom Study app

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Symptom clusters in COVID-19 : A potential clinical prediction tool from the COVID Symptom Study app

Sudre, C. H. (author): School of Biomedical Engineering & Imaging Sciences, King's College London, Westminster Bridge Road, London SE17EH, UK; MRC Unit for Lifelong Health and Ageing at UCL, University College London, London WC1E 7BH, UK; Centre for Medical Image Computing, Department of Computer Science, University College London, London UK

Lee, K. A. (author): Department of Twin Research and Genetic Epidemiology King's College London, Westminster Bridge Road, London SE17EH, UK

Lochlainn, M. N. (author): Department of Twin Research and Genetic Epidemiology King's College London, Westminster Bridge Road, London SE17EH, UK

Varsavsky, T. (author): School of Biomedical Engineering & Imaging Sciences, King’s College London, Westminster Bridge Road, London SE17EH, UK

Murray, B. (author): School of Biomedical Engineering & Imaging Sciences, King’s College London, Westminster Bridge Road, London SE17EH, UK

Graham, M. S. (author): School of Biomedical Engineering & Imaging Sciences, King’s College London, Westminster Bridge Road, London SE17EH, UK

Menni, C. (author): Department of Twin Research and Genetic Epidemiology King’s College London, Westminster Bridge Road, London SE17EH, UK

Modat, M. (author): School of Biomedical Engineering & Imaging Sciences, King’s College London, Westminster Bridge Road, London SE17EH, UK

Bowyer, R. C. E. (author): Department of Twin Research and Genetic Epidemiology King’s College London, Westminster Bridge Road, London SE17EH, UK

Nguyen, L. H. (author): Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, MA, USA

Drew, D. A. (author): Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, MA, USA

Joshi, A. D. (author): Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, MA, USA

Ma, W. (author): Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, MA, USA

Guo, C. G. (author): Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, MA, USA

Lo, C. H. (author): Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, MA, USA

Ganesh, S. (author): Zoe Global Limited, 164 Westminster Bridge Road, London SE1 7RW, UK

Buwe, A. (author): Zoe Global Limited, 164 Westminster Bridge Road, London SE1 7RW, UK

Pujol, J. C. (author): Zoe Global Limited, 164 Westminster Bridge Road, London SE1 7RW, UK

du Cadet, J. L. (author): Zoe Global Limited, 164 Westminster Bridge Road, London SE1 7RW, UK

Visconti, A. (author): Department of Twin Research and Genetic Epidemiology King’s College London, Westminster Bridge Road, London SE17EH, UK

Freidin, M. B. (author): Department of Twin Research and Genetic Epidemiology King’s College London, Westminster Bridge Road, London SE17EH, UK

El-Sayed Moustafa, J. S. (author): Department of Twin Research and Genetic Epidemiology King’s College London, Westminster Bridge Road, London SE17EH, UK

Gomez, Maria F. (author): Lund University,Lunds universitet,Diabetiska komplikationer,Forskargrupper vid Lunds universitet,Diabetic Complications,Lund University Research Groups

Davies, R. (author): Zoe Global Limited, 164 Westminster Bridge Road, London SE1 7RW, UK

Gomez, M. F. (author): Department of Clinical Sciences, Lund University Diabetes Centre, Malmö, Sweden

Fall, Tove, 1979- (author): Lund University,Lunds universitet,Genomik, diabetes och endokrinologi,Forskargrupper vid Lunds universitet,Genomics, Diabetes and Endocrinology,Lund University Research Groups

Cardoso, M. J. (author): School of Biomedical Engineering & Imaging Sciences, King’s College London, Westminster Bridge Road, London SE17EH, UK

Wolf, J. (author): Zoe Global Limited, 164 Westminster Bridge Road, London SE1 7RW, UK

Franks, Paul W. (author): Lund University,Lunds universitet,Genetisk och molekylär epidemiologi,Forskargrupper vid Lunds universitet,Genetic and Molecular Epidemiology,Lund University Research Groups,King's College London

Chan, A. T. (author): Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, MA, USA

Spector, T. D. (author): Department of Twin Research and Genetic Epidemiology King’s College London, Westminster Bridge Road, London SE17EH, UK

Steves, C. J. (author): Department of Twin Research and Genetic Epidemiology King’s College London, Westminster Bridge Road, London SE17EH, UK

Ourselin, S. (author): School of Biomedical Engineering & Imaging Sciences, King’s College London, Westminster Bridge Road, London SE17EH, UK

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American Association for the Advancement of Science (AAAS), 2021
2021
English.
In: Science Advances. - : American Association for the Advancement of Science (AAAS). - 2375-2548. ; 7:12

Related links:: https://doi.org/10.1...; show more...; https://uu.diva-port... (primary) (Raw object); https://www.science....; http://dx.doi.org/10... (free); https://urn.kb.se/re...; https://doi.org/10.1...; https://lup.lub.lu.s...; show less...

Journal article (peer-reviewed)

Abstract Subject headings

As no one symptom can predict disease severity or the need for dedicated medical support in coronavirus disease 2019 (COVID-19), we asked whether documenting symptom time series over the first few days informs outcome. Unsupervised time series clustering over symptom presentation was performed on data collected from a training dataset of completed cases enlisted early from the COVID Symptom Study Smartphone application, yielding six distinct symptom presenta- tions. Clustering was validated on an independent replication dataset between 1 and 28 May 2020. Using the first 5 days of symptom logging, the ROC-AUC (receiver operating characteristic – area under the curve) of need for respiratory sup- port was 78.8%, substantially outperforming personal characteristics alone (ROC-AUC 69.5%). Such an approach could be used to monitor at-risk patients and predict medical resource requirements days before they are required.

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MEDICAL AND HEALTH SCIENCES: MEDICAL AND HEAL ...; and Health Sciences; and Public Health Gl ...

MEDICAL AND HEALTH SCIENCES: MEDICAL AND HEAL ...; and Clinical Medicin ...; and Infectious Medic ...

Articles in the publication: Science Advances

By the university: Uppsala University; Lund University

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Symptom clusters in COVID-19 : A potential clinical prediction tool from the COVID Symptom Study app

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