Evidence map›Paper›PMID 34708731›Full record

ReviewIndian journal of ophthalmology2021

Current status and future possibilities of retinal imaging in diabetic retinopathy care applicable to low- and medium-income countries.

Yamini Attiku, Ye He, Muneeswar Gupta Nittala, SriniVas R Sadda

Open access · diamondAbstract readReview
In one paragraph

Review in Indian journal of ophthalmology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

10 citing papers in PubMed, 15 citations in OpenAlex.

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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

4 authors at 2 institutions in 2 countries.

Yamini AttikuDoheny Image Reading Center, Doheny Eye Institute, Los Angeles, California.
Ye HeDoheny Image Reading Center, Doheny Eye Institute, Los Angeles, California; Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, Tianjin, China.
Muneeswar Gupta NittalaDoheny Image Reading Center, Doheny Eye Institute, Los Angeles, California.
SriniVas R SaddaDoheny Image Reading Center, Doheny Eye Institute; Department of Ophthalmology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.
Doheny Eye Institute · USUniversity of California, Los Angeles · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic retinopathy (DR) is a leading cause of blindness among adults and the numbers are projected to rise. There have been dramatic advances in the field of retinal imaging since the first fundus image was captured by Jackman and Webster in 1886. The currently available imaging modalities in the management of DR include fundus photography, fluorescein angiography, autofluorescence imaging, optical coherence tomography, optical coherence tomography angiography, and near-infrared reflectance imaging. These images are obtained using traditional fundus cameras, widefield fundus cameras, handheld fundus cameras, or smartphone-based fundus cameras. Fluorescence lifetime ophthalmoscopy, adaptive optics, multispectral and hyperspectral imaging, and multicolor imaging are the evolving technologies which are being researched for their potential applications in DR. Telemedicine has gained popularity in recent years as remote screening of DR has been made possible. Retinal imaging technologies integrated with artificial intelligence/deep-learning algorithms will likely be the way forward in the screening and grading of DR. We provide an overview of the current and upcoming imaging modalities which are relevant to the management of DR.

Indexed as

Diabetes MellitusDiabetic RetinopathyAdultArtificial IntelligenceFluorescein AngiographyFundus OculiHumansPhotographyRetinaTomography, Optical CoherenceArtificial intelligencediabetic retinopathyfundus camerahandheld fundus camerasoptical coherence tomographyoptical coherence tomography angiographysmartphone-based fundus camerastelemedicinewidefield fundus cameras

Identifiers

PMID34708731
PMCPMC8725126
OpenAlexW3210580091

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.