SCONe: a community-acquired retinal image repository enabling ocular, cardiovascular and neurodegenerative disease prediction

Claire Tochel, Miguel O Bernabeu, Alice McTrusty, Andrew J Tatham, Emma Pead, Fiona Buckmaster, Jonathan Penny, Tom MacGillivray, Malihe Javidi, Heather Anderson, Ana Paula Rubio, Robert Wallace, Jamie B R Kidd, Ruairdh McLeod, Niall Strang, Baljean Dhillon

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Abstract

Objectives To safeguard Scotland’s community-acquired retinal images (colour fundus photographs) in a secure, centrally held repository and support a variety of research including ocular, neurodegenerative and systemic disease prediction.

Design Retinal images captured in optometry practices linked to national, routinely collected, longitudinal healthcare data.

Setting Community optometry and the Public Health Scotland National Safe Haven.

Participants Adults (mostly aged 60+) who have attended their optometrist since 2006 for an eye examination during which a retinal image was captured.

Main outcome measures Successful retrieval of linkable colour fundus photographs from systems in use in practice and delivery to the Safe Haven for linkage and secure storage.

Results Scottish Collaborative Optometry-Ophthalmology Network e-research (SCONe) currently contains over 367 000 retinal images matched to over 36 000 patients. Healthcare data (hospital inpatient and outpatient, general ophthalmic, death and prescribing) records were retrieved for patients with one or more images, providing demographic and healthcare information for 95% of the cohort. The linked data allow the application of condition labels or phenotypes at specific points in time, facilitating research into retinal manifestations of vascular and neural diseases. The cohort is representative of the Scottish 60+ population in terms of sex (54% female), and there is a slight over-representation of people of black, Asian and minority ethnic groups (2% vs 1%) and those living in areas of lower deprivation (30% vs 16% in lowest two categories). Early research work has begun and is focusing on ocular and neurodegenerative disease prediction.

Conclusions The SCONe retinal image repository has been successfully established. We believe it offers enormous potential to support research into earlier detection of disease.
Original languageEnglish
Article numbere101236
Number of pages9
JournalBMJ Health & Care Informatics
Volume32
Issue number1
DOIs
Publication statusPublished - 14 May 2025

Keywords

  • Data Science
  • Medical Informatics
  • Medical Record Linkage
  • Electronic Health Records
  • Health Services Research

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics
  • Health Information Management

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