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

IF 4.1 Q1 HEALTH CARE SCIENCES & SERVICES
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, Ruairidh MacLeod, Niall Strang, Baljean Dhillon
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引用次数: 0

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.

SCONe:一个社区获得的视网膜图像库,可以预测眼部、心血管和神经退行性疾病。
目的:将苏格兰社区获得的视网膜图像(彩色眼底照片)保存在安全的中央存储库中,并支持各种研究,包括眼部、神经退行性和全身性疾病预测。设计:在验光实践中捕获的视网膜图像与国家常规收集的纵向医疗保健数据相关。环境:社区验光和苏格兰公共卫生国家安全港。参与者:自2006年以来参加验光师眼科检查并拍摄视网膜图像的成年人(大多数年龄在60岁以上)。主要成果措施:从实际使用的系统中成功检索可链接的彩色眼底照片,并将其交付给安全港进行链接和安全存储。结果:苏格兰合作验光眼科网络电子研究(SCONe)目前包含超过36.7万张视网膜图像,与超过3.6万名患者相匹配。检索具有一张或多张图像的患者的医疗保健数据(住院和门诊、普通眼科、死亡和处方)记录,为95%的队列提供人口统计和医疗保健信息。关联数据允许在特定时间点应用条件标签或表型,促进对血管和神经疾病的视网膜表现的研究。该队列在性别方面代表了苏格兰60岁以上的人口(54%为女性),黑人、亚洲人和少数民族群体(2%对1%)以及生活在较贫困地区的人(30%对最低两类的16%)的代表性略高。早期的研究工作已经开始,重点是眼部和神经退行性疾病的预测。结论:成功建立了SCONe视网膜图像库。我们相信,它为支持疾病早期检测的研究提供了巨大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.10
自引率
4.90%
发文量
40
审稿时长
18 weeks
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