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Original research
Development, validation and comparison of multivariable risk scores for prediction of total stroke and stroke types in Chinese adults: a prospective study of 0.5 million adults

Authors

  • Matthew Chun Clinical Trial Service Unit and Epidemiological Studies, Nuffield Department of Population Health, University of Oxford, Oxford, UK Department of Engineering Science, University of Oxford, Oxford, UK PubMed articlesGoogle scholar articles
  • Robert Clarke Clinical Trial Service Unit and Epidemiological Studies, Nuffield Department of Population Health, University of Oxford, Oxford, UK PubMed articlesGoogle scholar articles
  • Tingting Zhu Department of Engineering Science, University of Oxford, Oxford, UK PubMed articlesGoogle scholar articles
  • David Clifton Department of Engineering Science, University of Oxford, Oxford, UK Department of Biomedical Engineering, Oxford-Suzhou Centre for Advanced Research, Suzhou, China PubMed articlesGoogle scholar articles
  • Derrick A Bennett Clinical Trial Service Unit and Epidemiological Studies, Nuffield Department of Population Health, University of Oxford, Oxford, UK PubMed articlesGoogle scholar articles
  • Yiping Chen Clinical Trial Service Unit and Epidemiological Studies, Nuffield Department of Population Health, University of Oxford, Oxford, UK Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK PubMed articlesGoogle scholar articles
  • Yu Guo CKB Project Department, Fuwai Hospital Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Beijing, China PubMed articlesGoogle scholar articles
  • Pei Pei CKB Project Department, Chinese Academy of Medical Sciences, Beijing, China PubMed articlesGoogle scholar articles
  • Jun Lv Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China Department of Epidemiology, Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China PubMed articlesGoogle scholar articles
  • Canqing Yu Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China Department of Epidemiology, Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China PubMed articlesGoogle scholar articles
  • Ling Yang Clinical Trial Service Unit and Epidemiological Studies, Nuffield Department of Population Health, University of Oxford, Oxford, UK PubMed articlesGoogle scholar articles
  • Liming Li Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China Department of Epidemiology, Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China PubMed articlesGoogle scholar articles
  • Zhengming Chen Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK PubMed articlesGoogle scholar articles
  • Benjamin J Cairns Clinical Trial Service Unit and Epidemiological Studies, Nuffield Department of Population Health, University of Oxford, Oxford, UK PubMed articlesGoogle scholar articles
  • On behalf of the China Kadoorie Biobank Collaborative Group
    Google scholar articles
  1. Correspondence to Professor Robert Clarke; robert.clarke{at}ndph.ox.ac.uk
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Citation

Chun M, Clarke R, Zhu T On behalf of the China Kadoorie Biobank Collaborative Group, et al
Development, validation and comparison of multivariable risk scores for prediction of total stroke and stroke types in Chinese adults: a prospective study of 0.5 million adults
Stroke and Vascular Neurology 2022;7:doi: 10.1136/svn-2021-001251

Publication history

  • Received July 29, 2021
  • Accepted January 11, 2022
  • First published March 15, 2022.
Online issue publication 
September 02, 2022

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© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.