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Yao Y, Wang Q, Yang J, Yan Y, Wei W. Associations of retinal microvascular alterations with diabetes mellitus: an OCTA-based cross-sectional study. BMC Ophthalmol 2024; 24:245. [PMID: 38858679 PMCID: PMC11165894 DOI: 10.1186/s12886-024-03492-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 05/23/2024] [Indexed: 06/12/2024] Open
Abstract
BACKGROUND Diabetes, 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. METHODS The 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. RESULTS This 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). CONCLUSIONS In 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.
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Affiliation(s)
- Yao Yao
- Laboratory 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 Wang
- Laboratory 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 Yang
- Laboratory 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 Yan
- Laboratory 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 Wei
- Laboratory 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.
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El Sawy S, Bekhit M, Abdelhamid A, Esmat S, Ashraf H, Naguib M. Assessment of early macular microangiopathy in subjects with prediabetes using optical coherence tomography angiography and fundus photography. Acta Diabetol 2024; 61:69-77. [PMID: 37689606 PMCID: PMC10806077 DOI: 10.1007/s00592-023-02167-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 07/31/2023] [Indexed: 09/11/2023]
Abstract
AIMS Early detection of retinal microangiopathy in patients with prediabetes may reduce diabetic retinopathy complications. The aim of this study was to assess early macular vascular changes in prediabetics before development of over diabetes using OCTA and fundus photography. METHODS In this cross-sectional study, 66 prediabetic individuals and 66 normal controls underwent clinical, laboratory, and fundus photography evaluation followed by OCTA macular imaging to examine for the foveal avascular zone, and area of capillary non-perfusion, thickness, disorganization of vessels, and vessel density perfusion percentage of superficial capillary plexus and deep capillary plexus. RESULTS Retinal microangiopathy was detected in 36.4% of prediabetics by OCTA and only in 10.6% by fundus photography. None of clinical or laboratory parameters had significant association with DR. Area of capillary non-perfusion and disorganization of SCP were detected in 53.8% and 56.8%, respectively, in prediabetics. VDP of SCP and DCP of whole image, parafoveal, and perifoveal areas was significantly lower in prediabetes group compared to normal control. VDP of DCP of perifoveal area (β coefficient: - 0.10, OR: 0.91, 95% CI: 0.86-0.96, P < 0.001) and disorganization of DCP (β coefficient: 1.93, OR: 6.89, 95% CI: 2.5-18.8, P < 0.001) were significant predictors of DR in prediabetics. There was no difference in FAZ in prediabetics with and without retinopathy. CONCLUSIONS OCTA could detect early retinal vascular changes during the prediabetic state before developing diabetes. VDP was significantly reduced in prediabetic patients. Furthermore, VDP of DCP of perifoveal area and disorganization of DCP were the most important predictors of retinopathy in prediabetic patients.
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Affiliation(s)
- Shereen El Sawy
- Internal Medicine Department, Faculty of Medicine, Kasr Al-Ainy Hospital, Cairo University, 41 Manial Street, Cairo, 11451, Egypt
| | - Mirrette Bekhit
- Internal Medicine Department, Faculty of Medicine, Kasr Al-Ainy Hospital, Cairo University, 41 Manial Street, Cairo, 11451, Egypt
| | - Alaa Abdelhamid
- Kasr Al-Ainy Vascular Laboratory, Cairo University, Cairo, Egypt
| | - Sohair Esmat
- Ophthalmology Department, Faculty of Medicine, Kasr Al-Ainy Hospital, Cairo University, Cairo, Egypt
| | - Hala Ashraf
- Clinical and Chemical Pathology Department, Faculty of Medicine, Kasr Al-Ainy Hospital, Cairo University, Cairo, Egypt
| | - Mervat Naguib
- Internal Medicine Department, Faculty of Medicine, Kasr Al-Ainy Hospital, Cairo University, 41 Manial Street, Cairo, 11451, Egypt.
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Yongpeng Z, Yaxing W, Jinqiong Z, Qian W, Yanni Y, Xuan Y, Jingyan Y, Wenjia Z, Ping W, Chang S, Ming Y, Yanan L, Jinyuan W, Shouling W, Shuohua C, Haiwei W, Lijian F, Qianqian W, Jingyuan Z, Zihan N, Yuning C, Ying X, Jonas JB, Wenbin W. The Association Between Diabetic Retinopathy and the Prevalence of Age-Related Macular Degeneration—The Kailuan Eye Study. Front Public Health 2022; 10:922289. [PMID: 35923972 PMCID: PMC9339787 DOI: 10.3389/fpubh.2022.922289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Accepted: 06/10/2022] [Indexed: 11/18/2022] Open
Abstract
This study aimed to investigate the prevalence of age-related macular degeneration (AMD) in patients with diabetes mellitus (DM) and diabetic retinopathy (DR) and analyze whether DR is a risk factor for AMD. This population-based epidemiological study included 14,440 people from the Kailuan Eye Study in 2016, of whom 1,618 were patients with type 2 DM aged over 50 years, and 409 had DM with DR. We analyzed whether there were differences in the prevalence of AMD between DM with DR and DM without DR, and conducted a hierarchical statistical analysis according to different stages of DR. Using variable regression analysis, we explored whether DR constituted a risk factor for AMD. In the DM population, the prevalence of wet AMD in patients with DM with and without DR was 0. 3 and 0.2%, respectively, with no significant difference (P = 0.607). Meanwhile, the prevalence of dry AMD in patients with DM with and without DR was 20.8 and 16.0%, respectively, with a significant difference. In the subgroup analysis of dry AMD, the prevalence of early, middle, and late dry AMD in DM with DR was 14.4, 5.9, and 0.5%, respectively. In DM without DR, the prevalence of early, middle, and late dry AMD was 10.5, 4.8, and 0.7%, respectively (P = 0.031). In the subgroup analysis of DR staging, statistical analysis could not be performed because of the limited number of patients with PDR. In the variable regression analysis of risk factors for dry AMD, after adjusting for age, sex, body mass index, hypertension, and dyslipidemia, DR constituted the risk factor for dry AMD. In conclusion, DM did not constitute a risk factor for AMD, and the prevalence of wet AMD and dry AMD in patients with DM and DR was higher than that in patients with DM without DR (among which dry AMD was statistically significant). Multivariate regression analysis confirmed that DR is an independent risk factor for dry AMD. Reasonable control of DM and slowing down the occurrence and development of DR may effectively reduce the prevalence of AMD in patients with DM.
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Affiliation(s)
- Zhang Yongpeng
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and 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, Beijing, China
| | - Wang Yaxing
- Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Zhou Jinqiong
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and 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, Beijing, China
| | - Wang Qian
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and 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, Beijing, China
| | - Yan Yanni
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and 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, Beijing, China
| | - Yang Xuan
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and 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, Beijing, China
| | - Yang Jingyan
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and 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, Beijing, China
| | - Zhou Wenjia
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and 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, Beijing, China
| | - Wang Ping
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and 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, Beijing, China
| | - Shen Chang
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and 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, Beijing, China
| | - Yang Ming
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and 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, Beijing, China
| | - Luan Yanan
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and 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, Beijing, China
| | - Wang Jinyuan
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and 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, Beijing, China
| | - Wu Shouling
- Cardiology Department, Kailuan General Hospital, Tangshan, China
| | - Chen Shuohua
- Health Care Center, Kailuan Group, Tangshan, China
| | - Wang Haiwei
- Department of Ophthalmology, Fuxing Hospital, Capital Medical University, Beijing, China
| | - Fang Lijian
- Department of Ophthalmology, Beijing Liangxiang Hospital, Capital Medical University, Beijing, China
| | - Wan Qianqian
- Department of Ophthalmology, The Second Hospital of Anhui Medical University, Hefei, China
| | - Zhu Jingyuan
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and 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, Beijing, China
| | - Nie Zihan
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and 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, Beijing, China
| | - Chen Yuning
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and 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, Beijing, China
| | - Xie Ying
- Department of Ophthalmology, Shanxi Provincial People's Hospital, Taiyuan, China
| | - Jost B. Jonas
- Department of Ophthalmology, Medical Faculty Mannheim of the Ruprecht-Karls-University of Heidelberg, Heidelberg, Germany
| | - Wei Wenbin
- Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology and 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, Beijing, China
- *Correspondence: Wei Wenbin
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Kushner-Lenhoff S, Li Y, Zhang Q, Wang RK, Jiang X, Kashani AH. OCTA Derived Vessel Skeleton Density Versus Flux and Their Associations With Systemic Determinants of Health. Invest Ophthalmol Vis Sci 2022; 63:19. [PMID: 35142788 PMCID: PMC8842473 DOI: 10.1167/iovs.63.2.19] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
Purpose To examine the associations of optical coherence tomography angiography (OCTA)-derived retinal capillary flux with systemic determinants of health. Methods This is a cross-sectional study of subjects recruited from the African American Eye Disease Study. A commercially available swept-source (SS)-OCTA device was used to image the central 3 × 3 mm macular region. Retinal capillary perfusion was assessed using vessel skeleton density (VSD) and flux. Flux approximates the number of red blood cells moving through vessel segments and is a novel metric, whereas VSD is a previously validated measure commonly used to quantify capillary density. The associations of OCTA derived measures with systemic determinants of health were evaluated using multivariate generalized linear mixed-effects models. Results A total of 154 eyes from 83 participants were enrolled. Mean VSD and flux were 0.148 ± 0.009 and 0.156 ± 0.016, respectively. In a model containing age, systolic blood pressure, diabetes status, hematocrit, and presence of retinopathy as covariates, there was a negative correlation between VSD and age (P < 0.001) and retinopathy (P = 0.02), but not with hematocrit (P = 0.85) or other factors. There was a positive correlation between flux and hematocrit (P = 0.02), as well as a negative correlation for flux with age (P < 0.001), systolic blood pressure (P = 0.04), and diabetes status (P = 0.02). A 1% decrease in hematocrit was associated with the same magnitude change in flux as ∼1.24 years of aging. Signal strength was associated with flux (P < 0.001), but not VSD (P = 0.51). Conclusions SS-OCTA derived flux provides additional information about retinal perfusion distinct from that obtained with skeleton density-based measures. Flux is appropriate for detecting subclinical changes in perfusion in the absence of clinical retinopathy.
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Affiliation(s)
- Sam Kushner-Lenhoff
- Department of Ophthalmology, UW Medicine Eye Institute, University of Washington, Seattle, Washington, United States
| | - Yuandong Li
- Department of Biomedical Therapeutics, University of Washington, Seattle, Washington, United States
| | - Qinqin Zhang
- Department of Biomedical Therapeutics, University of Washington, Seattle, Washington, United States
| | - Ruikang K Wang
- Department of Biomedical Therapeutics, University of Washington, Seattle, Washington, United States
| | - Xuejuan Jiang
- Department of Ophthalmology, Keck School of Medicine of USC, University of Southern California, Los Angeles, California, United States
| | - Amir H Kashani
- Department of Ophthalmology, Wilmer Eye Institute, Johns Hopkins University, Baltimore, Maryland, United States
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