Evidence map›Paper›PMID 37987832›Full record

ArticleActa diabetologica2024

Retinal age gap as a predictive biomarker for future risk of clinically significant diabetic retinopathy.

Ruiye Chen, Yanping Chen, Junyao Zhang, Wei Wang, Wenyi Hu, Mingguang He, Zhuoting Zhu

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Article in Acta diabetologica, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.9field-weighted citation impact, top 6% 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.

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 17 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

7 authors at 2 institutions in 2 countries.

Ruiye Chen *Centre for Eye Research Australia; Ophthalmology, University of Melbourne, Melbourne, Australia.
Yanping Chen *State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Sun Yat-Sen University, Guangzhou, China.
Junyao ZhangCentre for Eye Research Australia; Ophthalmology, University of Melbourne, Melbourne, Australia.
Wei WangState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Sun Yat-Sen University, Guangzhou, China.
Wenyi HuCentre for Eye Research Australia; Ophthalmology, University of Melbourne, Melbourne, Australia.
Mingguang HeCentre for Eye Research Australia; Ophthalmology, University of Melbourne, Melbourne, Australia. mingguang.he@unimelb.edu.au.
Zhuoting ZhuCentre for Eye Research Australia; Ophthalmology, University of Melbourne, Melbourne, Australia. lisa.zhu@unimelb.edu.au.ORCID http://orcid.org/0000-0002-9897-1192
The University of Melbourne · AUSun Yat-sen University · CN

Funding

Fundamental Research Funds of the State Key Laboratory of Ophthalmology. 303060202400362High-level Talent Flexible Introduction Fund of Guangdong Provincial People's Hospital KJ012019530National Natural Science Foundation of China 82000901National Natural Science Foundation of China 82101173NHMRC Investigator Grants 2010072
6 · The paper itself

Abstract

aimsRetinal age derived from fundus images has been verified as a novel ageing biomarker. We aim to explore the association between retinal age gap (retinal age minus chronological age) and incident diabetic retinopathy (DR).

methodsRetinal age prediction was performed by a deep learning model, trained and validated based on 19,200 fundus images of 11,052 disease-free participants. Retinal age gaps were determined for 2311 patients with diabetes who had no history of diabetic retinopathy at baseline. DR events were ascertained by data linkage to hospital admissions. Cox proportional hazards regression models were performed to evaluate the association between retinal age gaps and incident DR.

resultsDuring the median follow-up period of 11.0 (interquartile range: 10.8-11.1) years, 183 of 2311 participants with diabetes developed incident DR. Each additional year of the retinal age gap was associated with a 7% increase in the risk of incident DR (hazard ratio [HR] = 1.07, 95% confidence interval [CI] 1.02-1.12, P = 0.004), after adjusting for confounding factors. Participants with retinal age gaps in the fourth quartile had a significantly higher DR risk compared to participants with retinal age gaps in the lowest quartile (HR = 2.88, 95% CI 1.61-5.15, P < 0.001).

conclusionsWe found that higher retinal age gap was associated with an increased risk of incident DR. As an easy and non-invasive biomarker, the retinal age gap may serve as an informative tool to facilitate the individualized risk assessment and personalized screening protocol for DR.

Indexed as

Diabetes Mellitus, Type 2Diabetic RetinopathyHumansProspective StudiesRetinaRisk FactorsBiomarkerDiabetic retinopathyPredictionRetinal age

Identifiers

PMID37987832
OpenAlexW4388845253

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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.