Evidence map›Paper›PMID 38858679›Full record

ArticleBMC ophthalmology2024

Associations of retinal microvascular alterations with diabetes mellitus: an OCTA-based cross-sectional study.

Yao Yao, Qian Wang, Jingyan Yang, Yanni Yan, Wenbin Wei

Abstract read
In one paragraph

Article in BMC ophthalmology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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

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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

8 citing papers in PubMed.

  1. Observational
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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

5 authors.

Yao YaoLaboratory of Intraocular Tumor Diagnosis and Treatment, Ophthalmology&Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijingkey, 100730, China.
Qian WangLaboratory of Intraocular Tumor Diagnosis and Treatment, Ophthalmology&Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijingkey, 100730, China.
Jingyan YangLaboratory of Intraocular Tumor Diagnosis and Treatment, Ophthalmology&Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijingkey, 100730, China.
Yanni YanLaboratory of Intraocular Tumor Diagnosis and Treatment, Ophthalmology&Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijingkey, 100730, China.
Wenbin WeiLaboratory of Intraocular Tumor Diagnosis and Treatment, Ophthalmology&Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijingkey, 100730, China. weiwenbintr@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiabetes, a health crisis afflicting millions worldwide, is increasing rapidly in prevalence. The microvascular complications triggered by diabetes have emerged as the principal cause of renal disease and blindness. The retinal microvascular network may be sensitive to early systemic vascular structural and functional changes. Therefore, this research endeavored to discern the systemic determinants influencing the retinal microvascular network in patients with and without diabetes.

methodsThe Kailuan Eye Study is a cross-sectional study based on the community-based cohort Kailuan Study. Participants underwent optical coherence tomography angiography (OCTA) (Zeiss Cirrus 5000; Carl Zeiss Meditec) and comprehensive systemic examination. Metrics such as perfusion density (PD), vascular density (VD), foveal avascular zone (FAZ) parameters of the superficial capillary plexus (SCP) in the macula were assessed.

resultsThis study included 860 eligible participants (average age = 62.75 ± 6.52 years; 21.9% female), of which 449 were diabetics. People with diabetes had diminished PD and VD in the entire macular and parafoveal regions compared to people without diabetes. Reduced PD in the whole macular region was correlated with higher fasting plasma glucose (FPG, mmol/L) concentration (Beta = -0.19, 95% CI = -0.42 to -0.36, P < 0.001), longer axial length (AL, mm) (Beta = -0.13, 95%CI = -0.48 to -0.25, P = 0.002), and elevated heart rate (Beta = -0.10, 95%CI = -0.14 to -0.19, P = 0.014), after adjusting for younger age (Beta = -0.18, 95%CI = -0.24 to -0.35, P < 0.001), consistent with VD of the whole macular region. A higher FPG level was significantly correlated with lower SCP density of both PD and VD in the macular and parafoveal region (P < 0.05 for all), as well as increased systolic blood pressure and low-density lipoprotein cholesterol concentration (P < 0.01 for all).

conclusionsIn this large-sample cross-sectional study, OCTA evaluation revealed that high prevalence of diabetes and elevated FPG levels were correlated with reduced retinal VD and PD. Hypertension and hyperlipidemia are important risk factors for the development of atherosclerotic cardiovascular disease but have no significant effect on retinal microvascular abnormalities.

Indexed as

Diabetic RetinopathyFluorescein AngiographyRetinal VesselsTomography, Optical CoherenceAgedBlood GlucoseCross-Sectional StudiesDiabetes MellitusFemaleHumansMaleMiddle AgedBlood GlucoseCapillary densityDiabetes mellitusHypertensionOptical coherence tomography angiography (OCTA)Retinal microvasculature

Identifiers

PMID38858679
PMCPMC11165894

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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.