Evidence map›Paper›PMID 42733099›Full record

ArticleGeroScience2026

Optical coherence tomography angiography (OCTA) assessing microvascular and macrovascular health in healthy octogenarians.

Aloysius Niko, Pi-Shan Hsu, Wei-Wen Lin, Yi-Min Wang, Liang-Kung Chen, Chia-Wei Sun

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Article in GeroScience, 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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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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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

6 authors.

Aloysius NikoBiomedical Optical Intelligent Lab, Department of Photonics, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
Pi-Shan HsuDepartment of Family Medicine, Taichung Veterans General Hospital, Taichung, Taiwan.
Wei-Wen LinDepartment of Cardiovascular Center, Taichung Veterans General Hospital, Taichung, Taiwan.
Yi-Min WangBiomedical Optical Intelligent Lab, Department of Photonics, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
Liang-Kung ChenDepartment of Medicine, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
Chia-Wei SunBiomedical Optical Intelligent Lab, Department of Photonics, National Yang Ming Chiao Tung University, Hsinchu, Taiwan. chiaweisun@nycu.edu.tw.ORCID http://orcid.org/0000-0001-9769-8019

Funding

National Science and Technology Council 114-2221-E-A49-084-MY3
6 · The paper itself

Abstract

Subclinical cardiovascular abnormalities are recognized as primary risk factors for cardiovascular disease (CVD). Most studies explore microcirculation, while the associations of peripheral microvascular structures and abnormalities have been understudied. This study aimed to use OCTA to gauge the microvascular structure in the proximal nailfold and estimate cardiovascular health via echocardiography, arterial tonometry, and blood tests in samples of healthy octogenarians. We employ unsupervised machine learning methodologies, and vascular patterns are clustered to identify possible microcirculatory characteristics for assessing cardiovascular conditions. We conducted a cross-sectional analysis on 104 participants aged over 80 years to investigate the association between peripheral microvascular structures and subclinical cardiovascular changes. We extracted 12 vascular features from processed three-dimensional nailfold microvasculature obtained from optical coherence tomography angiography (OCTA). Subjects with different microvascular patterns were assigned to one of two clusters using hierarchical clustering analysis based on feature similarity. The cardiovascular parameters of the subjects between these two clusters were statistically compared. As a result, the cluster with denser, smaller, and less tortuous microvascular structure exhibits better cardiovascular conditions regarding resting heartbeats, systolic function, left ventricular sizes, and arterial stiffness. Our study highlights the potential of estimating cardiovascular health in the elderly from nailfold microvascular structure.

Indexed as

Cardiovascular diseaseMachine learningMedical image processingNailfold microvascularOptical coherence tomography angiography (OCTA)

Identifiers

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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.