Evidence map›Paper›PMID 31048908›Full record

ArticlePloS one2019

Age-related changes of the retinal microvasculature.

Nikita V Orlov, Cristopher Coletta, Freekje van Asten, Yong Qian, Jun Ding, Majd AlGhatrif, Edward Lakatta, Emily Chew, Wai Wong, Anand Swaroop and 5 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.4field-weighted citation impact, top 8% of its field
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

14 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. The Role of Oxidative Stress in the Aging Eye.Life (Basel, Switzerland) · 2023
    Review
  6. Article
  7. Article
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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

15 authors at 3 institutions in 2 countries.

Nikita V OrlovLaboratory of Genetics & Genomics, National Institute on Aging/National Institutes of Health, Baltimore, Maryland, United States of America.ORCID 0000-0002-3716-5146
Cristopher ColettaLaboratory of Genetics & Genomics, National Institute on Aging/National Institutes of Health, Baltimore, Maryland, United States of America.
Freekje van AstenDivision of Epidemiology and Clinical Applications, National Eye Institute/National Institutes of Health, Baltimore, Maryland, United States of America.
Yong QianLaboratory of Genetics & Genomics, National Institute on Aging/National Institutes of Health, Baltimore, Maryland, United States of America.
Jun DingLaboratory of Genetics & Genomics, National Institute on Aging/National Institutes of Health, Baltimore, Maryland, United States of America.
Majd AlGhatrifLaboratory of Cardiovascular Science, National Institute on Aging/National Institutes of Health, Baltimore, Maryland, United States of America.
Edward LakattaLaboratory of Cardiovascular Science, National Institute on Aging/National Institutes of Health, Baltimore, Maryland, United States of America.
Emily ChewDivision of Epidemiology and Clinical Applications, National Eye Institute/National Institutes of Health, Baltimore, Maryland, United States of America.
Wai WongDivision of Epidemiology and Clinical Applications, National Eye Institute/National Institutes of Health, Baltimore, Maryland, United States of America.
Anand SwaroopNeurobiology, Neurodegeneration and Repair Laboratory, National Eye Institute/National Institutes of Health, Baltimore, Maryland, United States of America.
Edoardo FiorilloIstituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Cagliari, Italy.
Alessandro DelitalaDepartment of Clinical and Experimental Medicine, Azienda Ospedaliero Universitaria di Sassari, Sassari, Italy.
Michele MarongiuIstituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Cagliari, Italy.ORCID 0000-0002-7289-9815
Ilya G GoldbergLaboratory of Genetics & Genomics, National Institute on Aging/National Institutes of Health, Baltimore, Maryland, United States of America.ORCID 0000-0001-8514-6110
David SchlessingerLaboratory of Genetics & Genomics, National Institute on Aging/National Institutes of Health, Baltimore, Maryland, United States of America.
National Institutes of Health · USInstitute of Genetic and Biomedical Research · ITAzienda Ospedaliero Universitaria di Sassari · IT

Funding

Statistical genetics of aging-related genomic and phenotypic changeZIAAG000693 · NIA · NATIONAL INSTITUTE ON AGING · PI DING, JUN · 2011 to 2025
$12.5M
6 · The paper itself

Abstract

purposeBlood vessels of the retina provide an easily-accessible, representative window into the condition of microvasculature. We investigated how retinal vessel structure captured in fundus photographs changes with age, and how this may reflect features related to patient health, including blood pressure.

resultsWe used two approaches. In the first approach, we segmented the retinal vasculature from fundus photographs and then we correlated 25 parameterized aspects ("traits")-comprising 15 measures of tortuosity, 7 fractal ranges of self-similarity, and 3 measures of junction numbers-with participant age and blood pressure. In the second approach, we examined entire fundus photographs with a set of algorithmic CHARM features. We studied 2,280 Sardinians, ages 20-28, and an U.S. based population from the AREDS study in 1,178 participants, ages 59-84. Three traits (relating to tortuosity, vessel bifurcation number, and vessel endpoint number) showed significant changes with age in both cohorts, and one additional trait (relating to fractal number) showed a correlation in the Sardinian cohort only. When using second approach, we found significant correlations of particular CHARM features with age and blood pressure, which were stronger than those detected when using parameterized traits, reflecting a greater signal from the entire photographs than was captured in the segmented microvasculature.

conclusionsThese findings demonstrate that automated quantitative image analysis of fundus images can reveal general measures of patient health status.

Indexed as

AdultAgedAged, 80 and overAgingBlood PressureCohort StudiesFemaleFundus OculiHumansMaleMicrovesselsMiddle AgedPhotographyRetinal VesselsYoung Adult

Identifiers

PMID31048908
PMCPMC6497255
OpenAlexW2942886053

What OpenQuestion holds

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LicenceCC0
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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.