Evidence map›Paper›PMID 31358386›Full record

ArticleOphthalmology2019

OCT Angiography Metrics Predict Progression of Diabetic Retinopathy and Development of Diabetic Macular Edema: A Prospective Study.

Zihan Sun, Fangyao Tang, Raymond Wong, Jerry Lok, Simon K H Szeto, Jason C K Chan, Carmen K M Chan, Clement C Tham, Danny S Ng, Carol Y Cheung

Erratum issuedAbstract read
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In one paragraph

Article in Ophthalmology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 177 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
177citing papers in PubMed, 3 pooled it
31.6field-weighted citation impact, top 1% 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

177 citing papers in PubMed, 3 syntheses or guidelines pooled it, 297 citations in OpenAlex.

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  5. Citicoline and Vitamin BAdvances in therapy · 2020
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117 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Zihan SunDepartment of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
Fangyao TangDepartment of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
Raymond WongDepartment of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Eye Hospital, Hong Kong Special Administrative Region, China.
Jerry LokDepartment of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Eye Hospital, Hong Kong Special Administrative Region, China.
Simon K H SzetoDepartment of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Eye Hospital, Hong Kong Special Administrative Region, China.
Jason C K ChanDepartment of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Eye Hospital, Hong Kong Special Administrative Region, China.
Carmen K M ChanDepartment of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Hong Kong Eye Hospital, Hong Kong Special Administrative Region, China.
Clement C ThamDepartment of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
Danny S NgDepartment of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China.
Carol Y CheungDepartment of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China. Electronic address: carolcheung@cuhk.edu.hk.
Chinese University of Hong Kong · CNHong Kong Eye Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo prospectively determine the relationship of OCT angiography (OCTA) metrics to diabetic retinopathy (DR) progression and development of diabetic macular edema (DME).

designProspective, observational study.

participantsA total of 205 eyes from 129 patients with diabetes mellitus followed up for at least 2 years.

methodsAll participants underwent OCTA with a swept-source OCT device (DRI-OCT Triton, Topcon, Inc, Tokyo, Japan). Individual OCTA images of superficial capillary plexus (SCP) and deep capillary plexus (DCP) were generated by IMAGEnet6 (Basic License 10). After a quality check, automated measurements of foveal avascular zone (FAZ) area, FAZ circularity, vessel density (VD), and fractal dimension (FD) of both SCP and DCP were then obtained.

main outcome measuresProgression of DR and development of DME.

resultsOver a median follow-up of 27.14 months (interquartile range, 24.16-30.41 months), 28 of the 205 eyes (13.66%) developed DR progression. Of the 194 eyes without DME at baseline, 17 (8.76%) developed DME. Larger FAZ area (hazard ratio [HR], 1.829 per SD increase; 95% confidence interval [CI], 1.332-2.512), lower VD (HR, 1.908 per SD decrease; 95% CI, 1.303-2.793), and lower FD (HR, 4.464 per SD decrease; 95% CI, 1.337-14.903) of DCP were significantly associated with DR progression after adjusting for established risk factors (DR severity, glycated hemoglobin, duration of diabetes, age, and mean arterial blood pressure at baseline). Lower VD of SCP (HR, 1.789 per SD decrease; 95% CI, 1.027-4.512) was associated with DME development. Compared with the model with established risk factors alone, the addition of OCTA metrics improved the predictive discrimination of DR progression (FAZ area of DCP, C-statistics 0.723 vs. 0.677, P < 0.001; VD of DCP, C-statistics 0.727 vs. 0.677, P = 0.001; FD of DCP, C-statistics 0.738 vs. 0.677, P < 0.001) and DME development (VD of SCP, C-statistics 0.904 vs. 0.875, P = 0.036).

conclusionsThe FAZ area, VD, and FD of DCP predict DR progression, whereas VD of SCP predicts DME development. Our findings provide evidence to support that OCTA metrics improve the evaluation of risk of DR progression and DME development beyond traditional risk factors.

Indexed as

AgedBiometryDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2Diabetic RetinopathyDisease ProgressionFemaleFluorescein AngiographyFollow-Up StudiesHumansMacular EdemaMaleMiddle AgedProportional Hazards ModelsProspective StudiesRetinal Vessels

Identifiers

PMID31358386
OpenAlexW2954946691

What OpenQuestion holds

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Read underepoch 390

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.