Evidence mapPaperPMID 42545069Full record

ArticleInvestigative ophthalmology & visual science2026

Retinal and Choroidal Vascular Metrics Predict Cerebral Atrophy and Cognitive Impairment in Noninfarcted Large Artery Stenosis.

Le Cao, Hang Wang, Yuyin Yan, William Robert Kwapong, Shijia Zhou, Tianxiang Lan, LeiLei Yuan, Ruishan Liu, Chen Ye, Wendan Tao and 3 more

Abstract readMulticenter Study
In one paragraph

Article in Investigative ophthalmology & visual science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Le CaoDepartment of Neurology, West China Hospital, Sichuan University, Chengdu, China.
Hang WangDepartment of Neurology, West China Hospital, Sichuan University, Chengdu, China.
Yuyin YanDepartment of Neurology, West China Hospital, Sichuan University, Chengdu, China.
William Robert KwapongDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.
Shijia ZhouLaboratory of Advanced Theragnostic Materials and Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China.
Tianxiang LanDepartment of Neurology, West China Hospital, Sichuan University, Chengdu, China.
LeiLei YuanLaboratory of Advanced Theragnostic Materials and Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China.
Ruishan LiuDepartment of Neurology, West China Hospital, Sichuan University, Chengdu, China.
Chen YeDepartment of Neurology, West China Hospital, Sichuan University, Chengdu, China.
Wendan TaoDepartment of Neurology, West China Hospital, Sichuan University, Chengdu, China.
Guina LiuDepartment of Ophthalmology, West China Second University Hospital, Sichuan University, Chengdu, China.
Yitian ZhaoLaboratory of Advanced Theragnostic Materials and Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China.
Bo WuDepartment of Neurology, West China Hospital, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Large artery stenosis (LAS) can drive cognitive impairment and neurodegeneration even without overt infarction, yet scalable biomarkers for capturing this silent vascular brain injury are limited. We investigated whether retinal and choroidal microvascular and neurostructural measures reflect cerebral atrophy and cognitive impairment in noninfarcted LAS. Methods: In a multicenter cohort of 1239 participants (1035 patients with noninfarcted LAS and 204 community-based controls), we integrated optical coherence tomography/angiography (OCT/OCTA), brain magnetic resonance imaging volumetry, and cognitive assessments. Machine learning models were trained internally (n = 891) and externally validated (n = 348) to evaluate the predictive value of combined retinal and choroidal features for cerebral atrophy and cognitive impairment. Results: LAS was associated with ganglion cell-inner plexiform layer (GCIPL) thinning and profound retinal and choroidal microvascular rarefaction, which tracked closely with reduced gray matter (GM) and white matter (WM) volumes (all P < 0.001). These retina-brain associations were strongest in bilateral subcortical and medial temporal regions (all P < 0.05). Crucially, integrating OCT/OCTA metrics into machine learning models substantially improved prediction of cerebral atrophy and cognitive impairment beyond the enhanced clinical baseline model: random forest achieved an external test R2 of 0.456 versus 0.254 for GM volume and 0.430 versus 0.251 for WM volume, while the support vector machine achieved the best classification performance for cognitive impairment (area under the curve = 0.794 vs. 0.668). Conclusions: Retinal and choroidal microvascular measures are sensitive, noninvasive biomarkers of silent, vascular-driven neurodegeneration. They offer substantial incremental value for individual risk stratification in vascular contributions to cognitive impairment and dementia.

Indexed as

ChoroidCognitive DysfunctionRetinal VesselsAgedAtrophyConstriction, PathologicFemaleHumansMachine LearningMagnetic Resonance ImagingMaleMiddle AgedTomography, Optical Coherence

Identifiers

PMID42545069
PMCPMC13440623

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.