Validation of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from UK Biobank.

Journal: BMC medicine
PMID: 36691041

Abstract

BACKGROUND: Currently in the United Kingdom, cardiovascular disease (CVD) risk assessment is based on the QRISK3 score, in which 10% 10-year CVD risk indicates clinical intervention. However, this benchmark has limited efficacy in clinical practice and the need for a more simple, non-invasive risk stratification tool is necessary. Retinal photography is becoming increasingly acceptable as a non-invasive imaging tool for CVD. Previously, we developed a novel CVD risk stratification system based on retinal photographs predicting future CVD risk. This study aims to further validate our biomarker, Reti-CVD, (1) to detect risk group of ≥ 10% in 10-year CVD risk and (2) enhance risk assessment in individuals with QRISK3 of 7.5-10% (termed as borderline-QRISK3 group) using the UK Biobank.

Authors

  • Rachel Marjorie Wei Wen Tseng
    Singapore National Eye Centre, Singapore Eye Research Institute, Singapore.
  • Tyler Hyungtaek Rim
    Department of Ocular Epidemiology, Singapore Eye Research Institute, Singapore, Singapore.
  • Eduard Shantsila
    Department of Primary Care and Mental Health, University of Liverpool, Liverpool, UK.
  • Joseph K Yi
    Albert Einstein College of Medicine, New York, NY, USA.
  • Sungha Park
    Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea; Integrated Research Center for Cerebrovascular and Cardiovascular Disease, Yonsei University College of Medicine, Seoul, South Korea.
  • Sung Soo Kim
    The Heart Center of Chonnam National University Hospital, 42 Jaebongro, Dong-gu, Gwangju 501-757, South Korea.
  • Chan Joo Lee
    Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea.
  • Sahil Thakur
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
  • Simon Nusinovici
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
  • Qingsheng Peng
    Department of Ophthalmology, Guangdong Eye Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China.
  • Hyeonmin Kim
    Mediwhale Inc., Seoul, South Korea.
  • Geunyoung Lee
    MediWhale, Seoul, South Korea.
  • Marco Yu
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
  • Yih-Chung Tham
    Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore.
  • Ameet Bakhai
    Department of Cardiology, Royal Free Hospital, London, United Kingdom.
  • Paul Leeson
    Ultromics Ltd, Oxford, United Kingdom.
  • Gregory Y H Lip
    Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool John Moores University and Liverpool Heart & Chest Hospital, L69 3BX Liverpool, UK.
  • Tien Yin Wong
    Singapore National Eye Center, Duke-National University of Singapore Medical School, Singapore 168751, Singapore; National Institutes of Health Research Biomedical Research Centre Biomedical Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK.
  • Ching-Yu Cheng
    Singapore National Eye Centre, Singapore Eye Research Institute, Singapore, Singapore.

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