ArticleAnnals of medicine2026
Retinal vascular parameters as AI-driven biomarkers for pulse wave velocity assessment: a telemedicine strategy for cardiovascular risk assessment.
Article in Annals of medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPulse wave velocity (PWV), known as the gold standard for evaluating arterial stiffness, is limited by device dependence. This study aims to explore the feasibility of retinal parameters to assess PWV based on artificial intelligence (AI), providing a new approach for remote and convenient cardiovascular risk assessment.
methodsThis retrospective study leveraged both cross-sectional and longitudinal data, enrolling patients from Peking University Third Hospital who underwent fundus photography and PWV testing simultaneously over five consecutive years. An optimised AI system automatically quantified retinal vascular parameters, optic morphological features, and lesion counts. Correlation analyses and multivariate linear regression models were employed using the training set to assess associations between retinal features and brachial-ankle PWV (baPWV) or ankle-brachial index (ABI), with validation performed in the test set.
resultsIn the training set of 3,088 visits, baPWV and ABI showed significant correlations with retinal vascular morphology (including mean vessel density, arteriolar-to-venular ratio, regional curvature, fractal dimension), optic disk/cup parameters (disk area, circularity), and lesion counts (exudative and drusen) (all
conclusionThis large-scale study demonstrates significant associations between AI-derived retinal features and baPWV/ABI, identifying robust predictive markers. The proposed AI-based retinal analysis offers a non-invasive, scalable, and remote screening paradigm for arterial stiffness and cardiovascular risk assessment.
Indexed as
Identifiers
What OpenQuestion holds
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.