Evidence map›Paper›PMID 41552911›Full record

ArticleCNS neuroscience & therapeutics2026

OCTA-Derived Retinal Biomarkers and Infarct Topography Improve Etiologic Classification of Recent Single Subcortical Infarction: A Nomogram Model.

Shuai Jiang, William Robert Kwapong, Yuying Yan, Tang Yang, Le Cao, Chen Ye, Junfeng Liu, Bo Wu

Abstract read
In one paragraph

Article in CNS neuroscience & therapeutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Shuai JiangDepartment of Neurology, West China Hospital, Sichuan University, Chengdu, China.ORCID 0000-0003-2140-1535
William Robert KwapongDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.ORCID 0000-0001-9633-4694
Yuying YanDepartment of Neurology, West China Hospital, Sichuan University, Chengdu, China.
Tang YangDepartment of Neurology, West China Hospital, Sichuan University, Chengdu, China.
Le CaoDepartment of Neurology, West China Hospital, Sichuan University, Chengdu, China.
Chen YeDepartment of Neurology, West China Hospital, Sichuan University, Chengdu, China.ORCID 0000-0003-2969-5486
Junfeng LiuDepartment of Neurology, West China Hospital, Sichuan University, Chengdu, China.ORCID 0009-0004-7881-0166
Bo WuDepartment of Neurology, West China Hospital, Sichuan University, Chengdu, China.ORCID 0000-0003-2067-9965

Funding

National Natural Science Foundation of China 82271328National Natural Science Foundation of China 82301661National Natural Science Foundation of China 82371322Noncommunicable Chronic Diseases-National Science and Technology Major Project 2023ZD0504900Noncommunicable Chronic Diseases-National Science and Technology Major Project 2023ZD0504903Post Doctor Research Project, West China Hospital, Sichuan University 2023HXBH007Post Doctor Research Project, West China Hospital, Sichuan University 2024HXBH041Sichuan Province Science and Technology Support Program 2024YFFK0314
6 · The paper itself

Abstract

backgroundRecent single subcortical infarction (RSSI) in lenticulostriate artery territories exhibits etiological heterogeneity. Misclassification risks persist due to overlapping neuroimaging features between cerebral small-vessel disease-related lacunar infarction (CSVD-related LI) and branch atheromatous disease (BAD). We developed a nomogram that integrates retinal optical coherence tomography angiography (OCTA) metrics with infarct topography to improve etiological classification.

methodsPatients with RSSI were prospectively enrolled between December 2021 and December 2023. LASSO regression identified predictors for a logistic regression-based nomogram. Performance was evaluated via concordance index (C-index), calibration curves, and decision-curve analysis.

resultsA total of 127 RSSI patients (86 CSVD-related LI, 41 BAD) were included. Three variables-superficial vascular complex density, number of lesion slices, and proximal lesion location-were retained in the final model. The nomogram achieved a C-index of 0.84 (95% CI, 0.80-0.89) versus 0.68 for conventional imaging, with superior net benefit across clinical thresholds (AUC 0.84 vs. 0.68, p < 0.001).

conclusionThe novel nomogram combining OCTA-derived retinal biomarkers with infarct topography improves differentiation of BAD from CSVD-related LI in RSSI patients and may facilitate etiology-driven clinical decision-making. External validation is needed for clinical implementation.

Indexed as

Cerebral InfarctionNomogramsRetinaTomography, Optical CoherenceAgedBiomarkersFemaleHumansMaleMiddle AgedProspective StudiesStroke, LacunarBiomarkersbranch atheromatous diseasecerebral small‐vessel diseasenomogramrecent single subcortical infarctionretinal microvasculature

Identifiers

PMID41552911
PMCPMC12813863

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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 OpenQuestion graph.