Choroidal Thickness in Diabetic Patients Without Diabetic Retinopathy: A Meta-analysis

Endo, Hiroaki; Kase, Satoru; Saito, Michiyuki; Yokoi, Masahiko; Takahashi, Mitsuo; Ishida, Susumu; Kase, Manabu

doi:10.1016/j.ajo.2020.05.036

Cited by 46 publications

(31 citation statements)

References 50 publications

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“…Using these machines, many studies have shown a significant difference in choroidal thickness (CT) of diabetic eyes compared to healthy eyes [ 13 – 16 ]. However, the findings of these studies were mostly controversial and inconsistent, especially in patients without DR [ 17 – 19 ].…”

Section: Introductionmentioning

confidence: 99%

Choroidal thickness in relation to urinary albumin excretion rate in type 2 diabetes mellitus without retinopathy

et al. 2021

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Background To evaluate choroidal thickness (CT) in diabetic patients without diabetic retinopathy (DR) in relation to the urinary albumin excretion rate (UAER). Methods This is a prospective case-control study that included a consecutive sample of 120 patients with type 2 diabetes without clinically evident DR and a group of 60 matched healthy controls. Diabetic patients were included in two groups according to their UAER (normoalbuminuria and microalbuminuria). Complete ophthalmological examination was performed followed by optical coherence tomography (SD-OCT) for retinal and choroidal assessment. Twenty-four-hour urine samples were collected for UAER and blood samples for HbA1c and serum creatinine were obtained. Results The study included 180 eyes from 180 subjects in three groups. Patients with higher levels of albuminuria had a thinner choroid than normal controls, with decremental thinning as albuminuria progressed. Diabetics with normoalbuminuria showed no significant differences from controls. Choroidal thickness showed a significant moderate negative correlation with UAER (r = − 0.58, p < 0.001). Multiple regression analyses for diabetic patients with microalbuminuria demonstrated that UAER is the most important determinant of subfoveal choroidal thickness (SFCT) (p < 0.001). Conclusions Decreased CT was significantly correlated with UAER in diabetic patients without retinopathy and otherwise normal kidney functions. This decrease in thickness might be a predictor of DR.

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Section: Introductionmentioning

confidence: 99%

Choroidal thickness in relation to urinary albumin excretion rate in type 2 diabetes mellitus without retinopathy

et al. 2021

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“…The SFChT changes in eyes with DR or diabetic eyes without DR have been intensely investigated by several studies [ 15 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ]. However, the relationship between DR severity and SFChT is controversial.…”

Section: Discussionmentioning

confidence: 99%

“…Recently, Wang et al reported an increase in SFChT in the early stage of DR, but this decreased with DR progression [ 45 ]. Moreover, Endo et al showed that the SFChT of eyes with severe NPDR was thicker than that of normal controls only in the DM treatment group [ 37 ]. Changes in choroidal vasculature have also been seen in patients with diabetes [ 10 ], and studies have demonstrated that CVI is significantly decreased with a worsened DR [ 10 , 14 , 15 ].…”

Section: Discussionmentioning

confidence: 99%

Correlation of Renal Profiles with Choroidal Vascularity Index in Eyes with Diabetic Retinopathy

Kim

Lee²

2021

JCM

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The vascular system is affected by systemic conditions, including diabetes, hypertension, and cardiovascular disease. The choroid is an important vascular tissue surrounding the sensory retina. However, the relationship between the choroid and systemic factors in patients with diabetes has rarely been investigated. Here, we assessed the correlation of renal profiles with choroidal vasculature in eyes with diabetic retinopathy (DR) using a retrospective study design. The study included 131 patients with diabetes who underwent swept-source optical coherence tomography and routine medical work-up within a 4-week period between 1 February 2016 and 30 October 2018. Consecutive patients with treatment-naïve DR who did not receive any subsequent treatment were included. The distribution of patients according to the DR stage was as follows: no DR, 32 patients; mild-to-moderate non-proliferative DR (NPDR), 33 patients; severe NPDR, 34 patients; and treatment-naïve proliferative DR, 32 patients. Multivariate regression analyses showed that the choroidal vascularity index (CVI) of naïve eyes with DR was negatively correlated with age (p = 0.013) and the serum levels of phosphorus (p = 0.002) and positively correlated with subfoveal choroidal thickness (p < 0.001). Taken together, our findings suggest that a lower CVI is associated with phosphorus retention in patients with chronic kidney disease.

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“…In diabetic patients with diabetic retinopathy, the regular growth-based prognosis is a crucial and critical element of patient therapy. e cost of therapy is heavily influenced by the accuracy and timeliness of this care [11]. If discovered early, compensatory therapy for diabetic retinopathy is available, and it is a vital step.…”

Section: Introductionmentioning

confidence: 99%

Presentation of a Segmentation Method for a Diabetic Retinopathy Patient’s Fundus Region Detection Using a Convolutional Neural Network

Valizadeh

Ghoushchi

Ranjbarzadeh

et al. 2021

Computational Intelligence and Neuroscience

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Diabetic retinopathy is characteristic of a local distribution that involves early-stage risk factors and can forecast the evolution of the illness or morphological lesions related to the abnormality of retinal blood flows. Regional variations in retinal blood flow and modulation of retinal capillary width in the macular area and the retinal environment are also linked to the course of diabetic retinopathy. Despite the fact that diabetic retinopathy is frequent nowadays, it is hard to avoid. An ophthalmologist generally determines the seriousness of the retinopathy of the eye by directly examining color photos and evaluating them by visually inspecting the fundus. It is an expensive process because of the vast number of diabetic patients around the globe. We used the IDRiD data set that contains both typical diabetic retinopathic lesions and normal retinal structures. We provided a CNN architecture for the detection of the target region of 80 patients’ fundus imagery. Results demonstrate that the approach described here can nearly detect 83.84% of target locations. This result can potentially be utilized to monitor and regulate patients.

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Choroidal Thickness in Diabetic Patients Without Diabetic Retinopathy: A Meta-analysis

Cited by 46 publications

References 50 publications

Choroidal thickness in relation to urinary albumin excretion rate in type 2 diabetes mellitus without retinopathy

Choroidal thickness in relation to urinary albumin excretion rate in type 2 diabetes mellitus without retinopathy

Correlation of Renal Profiles with Choroidal Vascularity Index in Eyes with Diabetic Retinopathy

Presentation of a Segmentation Method for a Diabetic Retinopathy Patient’s Fundus Region Detection Using a Convolutional Neural Network

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