Evidence map›Paper›PMID 34926208›Full record

ArticleInternational journal of ophthalmology2021

Quantitative analysis of retinal vasculature in normal eyes using ultra-widefield fluorescein angiography.

Jing-Wen Jiang, Zuo-Hui-Zi Yi, Xiao-Ling Wang, Jue-Jun Liu, Gong-Peng Sun, Chang-Zheng Chen

Open access · goldAbstract read
In one paragraph

Article in International journal of ophthalmology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 1 institution in 1 country.

Jing-Wen JiangEye Center, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei Province, China.
Zuo-Hui-Zi YiEye Center, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei Province, China.
Xiao-Ling WangEye Center, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei Province, China.
Jue-Jun LiuEye Center, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei Province, China.
Gong-Peng SunEye Center, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei Province, China.
Chang-Zheng ChenEye Center, Renmin Hospital of Wuhan University, Wuhan 430060, Hubei Province, China.
Wuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo quantify the area and density of retinal vascularity by ultra-widefield fluorescein angiography (UWFA).

methodsIn a retrospective study, UWFA images were obtained using an ultra-widefield imaging device in 42 normal eyes of 42 patients. Central and peripheral steered images were used to define the edge of retinal vasculature by a certified grader. The length from the center of the optic disc to the edge of retinal vascularity (RVL) in each quadrant and the total retinal vascular perfusion area (RVPA) were determined by the grader using OptosAdvance software. The density of retinal vascularity (RVD) was quantified in different zones of central-steered images using Image J software.

resultsAmong 42 healthy eyes, the values for mean RVL in each quadrant were 19.007±0.781 mm (superior), 18.467±0.869 mm (inferior), 17.738±0.622 mm (nasal) and 24.241±1.336 mm (temporal). The mean RVPA was 1140.117±73.825 mm

conclusionThe UWFA device can be a promising tool for analyzing the overall retinal vasculature and may provide a better understanding of retinal vascular morphology in normal eyes. Aging may be related to lower RVD.

Indexed as

imagingretinalultra-widefield fluorescein angiographyvasculature

Identifiers

PMID34926208
PMCPMC8640767
OpenAlexW3216358155

What OpenQuestion holds

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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.