ArticleOphthalmology science
Population-Based Normative Reference for Retinal Microvascular Atlas.
Article in Ophthalmology science. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Ethnicity-Stratified Normative Retinal Vascular Features from the UK Biobank Using Deep Learning.Ophthalmology science · 2026Article
- Retinomics as a Tool for Glaucoma Prediction.Ophthalmology science · 2026Article
- The retina-body axis: proteomic mechanisms linking oculomics and clinical traits in a female aging cohort.npj aging · 2026Article
- Retinomics: a window to multidisease prediction using retinal biomarkers from routine eye imaging.BMC medicine · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Objective: To establish the normative range of a comprehensive set of retinal vascular measurements to better understand their value as biomarkers for assessing ocular and systemic health. Design: Cross-sectional study. Participants: The study included 10 151 healthy participants from the UK Biobank. Methods: Retina-based Microvascular Health Assessment System software was used to extract retinal vascular measurements, including caliber, complexity, density, branching angle, and tortuosity, differentiating between arteries and veins and between the macula and retinal periphery. In addition, we explored relationships between those measurements and health metrics, including age, systolic blood pressure (SBP), body mass index, glycated hemoglobin, and intraocular pressure. Main Outcome Measures: We reported the population normative range for 114 retinal vascular measurements, further stratified by sex and age. Results: The mean values of central retinal artery equivalent and central retinal vein equivalent (CRVE) were 152 (standard deviation = 14.9) μm and 233 (21.5) μm, respectively. The mean value of fractal dimension (FD) was 1.77 (0.032), with arterial FD 1.53 (0.039) and venular FD 1.56 (0.025). Age and SBP showed the strongest associations with most retinal parameters among health metrics. Central retinal artery equivalent, CRVE, density, and complexity decreased with increasing age and SBP. Changes in arterial measurements with age and SBP were generally greater than those in venous measurements. Generalized additive models further revealed that observed associations were mainly linear. Conclusions: By establishing population normative data for a comprehensive set of retinal vascular measurements, our study enables quantifiable approaches to better understand retinal vascular changes. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.