ArticleBMJ health & care informatics2025
SCONe: a community-acquired retinal image repository enabling ocular, cardiovascular and neurodegenerative disease prediction.
Article in BMJ health & care informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Oculomics and the NHS: A UK opportunity to translate eye-derived biomarkers into population health.Eye (London, England) · 2026Article
- Cohort Profile: The North East London Diabetes Study (NELDS).International journal of epidemiology · 2026Article
- A large dataset of brain imaging linked to health systems data: curation and access to a whole system national cohort from NHS Scotland.GigaScience · 2026Article
- Beyond the dataset: integrating public voices in data science.Research involvement and engagement · 2026Article
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo 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.
designRetinal images captured in optometry practices linked to national, routinely collected, longitudinal healthcare data.
settingCommunity optometry and the Public Health Scotland National Safe Haven.
participantsAdults (mostly aged 60+) who have attended their optometrist since 2006 for an eye examination during which a retinal image was captured.
main outcome measuresSuccessful retrieval of linkable colour fundus photographs from systems in use in practice and delivery to the Safe Haven for linkage and secure storage.
resultsScottish 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.
conclusionsThe SCONe retinal image repository has been successfully established. We believe it offers enormous potential to support research into earlier detection of disease.
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