Evidence map›Paper›PMID 31982390›Full record

ArticleOphthalmology. Retina2020

Ultra-Widefield Protocol Enhances Automated Classification of Diabetic Retinopathy Severity with OCT Angiography.

FuPeng Wang, Steven S Saraf, Qinqin Zhang, Ruikang K Wang, Kasra A Rezaei

Abstract read
In one paragraph

Article in Ophthalmology. Retina, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

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

  1. Pooled it
  2. Article
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  5. Volumetric montaging of optical coherence tomography in human retinas.bioRxiv : the preprint server for biology · 2026
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  10. Review
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  12. Review
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  14. Article
  15. Assessing the Sensitivity of OCT-A Retinal Vasculature Metrics.Translational vision science & technology · 2023
    Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Observational
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.

FuPeng WangDepartment of Bioengineering, University of Washington, Seattle, Washington; College of Information Science and Engineering, Ocean University of China, Qingdao, China.
Steven S SarafDepartment of Ophthalmology, University of Washington, Seattle, Washington.
Qinqin ZhangDepartment of Bioengineering, University of Washington, Seattle, Washington.
Ruikang K WangDepartment of Bioengineering, University of Washington, Seattle, Washington; Department of Ophthalmology, University of Washington, Seattle, Washington.
Kasra A RezaeiDepartment of Ophthalmology, University of Washington, Seattle, Washington. Electronic address: krezaei@uw.edu.

Funding

Ultra-wide field optical coherence tomography based angiography for imaging diabetic retinopathyR01EY028753 · NEI · UNIVERSITY OF WASHINGTON · PI WANG, RUIKANG · 2018 to 2021
$2.2M
NON-INVASIVE REAL-TIME LABEL-FREE 3D IMAGING OF RETINAL MICROCIRCULATIONR01EY024158 · NEI · UNIVERSITY OF WASHINGTON · PI WANG, RUIKANG · 2014 to 2017
$1.7M
NEI NIH HHS R01 EY024158NEI NIH HHS R01 EY028753
6 · The paper itself

Abstract

purposeTo assess the diagnostic usefulness of retinal nonperfusion to classify eyes based on diabetic retinopathy (DR) severity on OCT angiography (OCTA) and determine whether wider field of view (FOV) OCTA protocols enhance the diagnostic usefulness of retinal nonperfusion in the classification of DR severity.

designRetrospective cross-sectional study.

participantsDiabetic patients undergoing ultra-widefield (UWF) OCTA imaging at 1 academic retina practice.

methodsUltra-widefield OCTA images with 100° FOV were obtained from 60 eyes. Eyes were grouped as those with diabetes without retinopathy (DWR), those with nonproliferative diabetic retinopathy (NPDR), or those with proliferative diabetic retinopathy (PDR). The ratio of nonperfusion (RNP) was expressed as the percent area of capillary nonperfusion within the FOV. The RNP was obtained in the FOV 100° image and concentric sectors encompassing 10°, 10° to 30°, 30° to 50°, and 50° to 100°.

main outcome measuresMean RNP among DR groups, mean RNP measured among FOV sectors, and area under the curve (AUC) of the receiver operating characteristics when using RNP as a cutoff value to distinguish between DR groups.

resultsMean RNP from the FOV 50° to 100° sector was different among all groups: DWR, 14.6±5.1%; NPDR, 27.5±7.5%; and PDR, 41.5±19.1% (P < 0.01). Within each DR group, field of view from 50° to 100° measured higher RNP than all other sectors (P < 0.01). Field of view from 50° to 100° showed the highest optimal sensitivity and specificity to distinguish NPDR from DWR with an RNP cutoff value of 21.2% (89.5% and 88.2%; AUC, 0.944) and PDR from NPDR with an RNP cutoff value of 31.6% (79.2% and 78.9%; AUC, 0.752).

conclusionsRatio of nonperfusion on average is higher in more severe DR. The most peripheral sector of the widefield OCTA (FOV 50°-100°) showed on average higher RNP and showed more diagnostic usefulness in determining DR severity compared with more central sectors and the FOV 100 image as a whole.

Indexed as

Visual AcuityAgedCross-Sectional StudiesDiabetic RetinopathyFemaleFluorescein AngiographyFundus OculiHumansMaleMiddle AgedReproducibility of ResultsRetinaRetrospective StudiesSeverity of Illness IndexTomography, Optical Coherence

Identifiers

PMID31982390
PMCPMC7150627

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Registered trials

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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.