Evidence map›Paper›PMID 38793083›Full record

ReviewJournal of personalized medicine2024

Non-Invasive Retinal Vessel Analysis as a Predictor for Cardiovascular Disease.

Raluca Eugenia Iorga, Damiana Costin, Răzvana Sorina Munteanu-Dănulescu, Elena Rezuș, Andreea Dana Moraru

Abstract readReview
In one paragraph

Review in Journal of personalized medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

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

  1. Pooled it
  2. Review
  3. Observational
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Vascular medicine in the 21World journal of clinical cases · 2024
    Review
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

5 authors.

Raluca Eugenia IorgaDepartment of Surgery II, Discipline of Ophthalmology, "Grigore T. Popa" University of Medicine and Pharmacy, Strada Universitatii No. 16, 700115 Iași, Romania.
Damiana CostinDoctoral School, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iași, Romania.
Răzvana Sorina Munteanu-DănulescuDepartment of Gastroenterology, "L. Pasteur" Clinical Hospital, 28630 Le Coudray, France.
Elena RezușDepartment of Internal Medicine II, Discipline of Reumathology, "Grigore T. Popa" University of Medicine and Pharmacy, 700115 Iași, Romania.ORCID 0000-0002-8175-2583
Andreea Dana MoraruDepartment of Surgery II, Discipline of Ophthalmology, "Grigore T. Popa" University of Medicine and Pharmacy, Strada Universitatii No. 16, 700115 Iași, Romania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiovascular disease (CVD) is the most frequent cause of death worldwide. The alterations in the microcirculation may predict the cardiovascular mortality. The retinal vasculature can be used as a model to study vascular alterations associated with cardiovascular disease. In order to quantify microvascular changes in a non-invasive way, fundus images can be taken and analysed. The central retinal arteriolar (CRAE), the venular (CRVE) diameter and the arteriolar-to-venular diameter ratio (AVR) can be used as biomarkers to predict the cardiovascular mortality. A narrower CRAE, wider CRVE and a lower AVR have been associated with increased cardiovascular events. Dynamic retinal vessel analysis (DRVA) allows the quantification of retinal changes using digital image sequences in response to visual stimulation with flicker light. This article is not just a review of the current literature, it also aims to discuss the methodological benefits and to identify research gaps. It highlights the potential use of microvascular biomarkers for screening and treatment monitoring of cardiovascular disease. Artificial intelligence (AI), such as Quantitative Analysis of Retinal vessel Topology and size (QUARTZ), and SIVA-deep learning system (SIVA-DLS), seems efficient in extracting information from fundus photographs and has the advantage of increasing diagnosis accuracy and improving patient care by complementing the role of physicians. Retinal vascular imaging using AI may help identify the cardiovascular risk, and is an important tool in primary cardiovascular disease prevention. Further research should explore the potential clinical application of retinal microvascular biomarkers, in order to assess systemic vascular health status, and to predict cardiovascular events.

Indexed as

artificial intelligencecardiovascular diseaseretinal microvascular biomarkersretinal vessel analysis

Identifiers

PMID38793083
PMCPMC11122007

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.