SCONe: a community-acquired retinal image repository enabling ocular, cardiovascular and neurodegenerative disease prediction
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 t...
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| Format: | Article |
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BMJ Publishing Group
2025-05-01
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| Series: | BMJ Health & Care Informatics |
| Online Access: | https://informatics.bmj.com/content/32/1/e101236.full |
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| author | Tom Macgillivray Andrew J Tatham Niall Strang Baljean Dhillon Robert Wallace Heather Anderson Miguel O Bernabeu Claire Tochel Alice McTrusty Emma Pead Fiona Buckmaster Jonathan Penny Malihe Javidi Ana Paula Rubio Jamie B R Kidd Ruairidh MacLeod |
| author_facet | Tom Macgillivray Andrew J Tatham Niall Strang Baljean Dhillon Robert Wallace Heather Anderson Miguel O Bernabeu Claire Tochel Alice McTrusty Emma Pead Fiona Buckmaster Jonathan Penny Malihe Javidi Ana Paula Rubio Jamie B R Kidd Ruairidh MacLeod |
| author_sort | Tom Macgillivray |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-a97ca2c163a8406bbfb36e1a70c80581 |
| institution | OA Journals |
| issn | 2632-1009 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Health & Care Informatics |
| spelling | doaj-art-a97ca2c163a8406bbfb36e1a70c805812025-08-20T02:30:50ZengBMJ Publishing GroupBMJ Health & Care Informatics2632-10092025-05-0132110.1136/bmjhci-2024-101236SCONe: a community-acquired retinal image repository enabling ocular, cardiovascular and neurodegenerative disease predictionTom Macgillivray0Andrew J Tatham1Niall Strang2Baljean Dhillon3Robert Wallace4Heather Anderson5Miguel O Bernabeu6Claire Tochel7Alice McTrusty8Emma Pead9Fiona Buckmaster10Jonathan Penny11Malihe Javidi12Ana Paula Rubio13Jamie B R Kidd14Ruairidh MacLeod15The University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UKDepartment of Ophthalmology, Princess Alexandra Eye Pavilion, Edinburgh, UK3 Department of Vision Sciences, Glasgow Caledonian University, Glasgow, UKThe University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK2 Epidemiology, The University of Iowa College of Public Health, Iowa City, Iowa, USABarts Health NHS Trust, London, UKUsher Institute,College of Medicine and Veterinary Medicine, The University of Edinburgh, Edinburgh, Scotland, UKCentre for Medical Informatics, The University of Edinburgh Usher Institute, Edinburgh, UKThe University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UKThe University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UKThe University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UKRoyal College of Surgeons of Edinburgh, Edinburgh, UKCentre for Medical Informatics, The University of Edinburgh Usher Institute, Edinburgh, UKCentre for Medical Informatics, The University of Edinburgh Usher Institute, Edinburgh, UKPublic Health Scotland, Edinburgh, UKEPCC, The University of Edinburgh, Edinburgh, UKObjectives 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.https://informatics.bmj.com/content/32/1/e101236.full |
| spellingShingle | Tom Macgillivray Andrew J Tatham Niall Strang Baljean Dhillon Robert Wallace Heather Anderson Miguel O Bernabeu Claire Tochel Alice McTrusty Emma Pead Fiona Buckmaster Jonathan Penny Malihe Javidi Ana Paula Rubio Jamie B R Kidd Ruairidh MacLeod SCONe: a community-acquired retinal image repository enabling ocular, cardiovascular and neurodegenerative disease prediction BMJ Health & Care Informatics |
| title | SCONe: a community-acquired retinal image repository enabling ocular, cardiovascular and neurodegenerative disease prediction |
| title_full | SCONe: a community-acquired retinal image repository enabling ocular, cardiovascular and neurodegenerative disease prediction |
| title_fullStr | SCONe: a community-acquired retinal image repository enabling ocular, cardiovascular and neurodegenerative disease prediction |
| title_full_unstemmed | SCONe: a community-acquired retinal image repository enabling ocular, cardiovascular and neurodegenerative disease prediction |
| title_short | SCONe: a community-acquired retinal image repository enabling ocular, cardiovascular and neurodegenerative disease prediction |
| title_sort | scone a community acquired retinal image repository enabling ocular cardiovascular and neurodegenerative disease prediction |
| url | https://informatics.bmj.com/content/32/1/e101236.full |
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