Literature DB >> 28472211

Progressive Retinal Vasodilation in Patients With Type 1 Diabetes: A Longitudinal Study of Retinal Vascular Geometry.

Gerald Liew1, Paul Benitez-Aguirre2, Maria E Craig2, Alicia J Jenkins3, Lauren A B Hodgson4, Annette Kifley1, Paul Mitchell1, Tien Y Wong5, Kim Donaghue2.   

Abstract

Purpose: Retinal vessels can be used to noninvasively monitor changes in microvasculature. These changes in retinal vascular geometry (RVG) may predict chronic diabetes complications. We evaluated longitudinal RVG changes in adolescents with type 1 diabetes.
Methods: We followed 102 adolescents (baseline: 47.1% male, mean [SD] age 14.4 [1.6] years, diabetes duration 7.2 [3.1] years, HbA1c 8.1% [1.3%] [65 (9.3) mmol/mol]) over three visits, with a mean follow-up of 2.6 years. Retinal vascular geometry was measured using a standardized computer-assisted protocol from retinal photographs at each visit. Multivariable linear mixed-models and logistic regression were used to examine predictors of RVG and diabetic retinopathy.
Results: During follow-up, mean arteriolar caliber, venular caliber, and venular tortuosity increased, from 156.0 (SD, 14.5) to 164.9 (14.0) μm, 215.9 (22.5) to 230.3 (20.6) μm, and 1.096 (0.014) to 1.099 (0.016), respectively (all P < 0.005). Other RVG measurements (fractal dimension, branching angle, length to diameter ratio) remained stable. Higher than baseline HbA1c and longer diabetes duration were associated with greater venular vasodilation. Retinopathy developed at any time-point in 24% of subjects, and the highest tertile arteriolar fractal dimension was associated with cumulative incidence of retinopathy (multivariable odds ratio 3.2, 95% confidence interval 1.0-9.6; P = 0.04). Conclusions: Higher HbA1c and longer diabetes duration in early adolescence predicts greater venular vasodilation over time. Arteriolar fractal dimension predicts subsequent retinopathy development, suggesting value as a potential biomarker for diabetic complications.

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Year:  2017        PMID: 28472211     DOI: 10.1167/iovs.16-21015

Source DB:  PubMed          Journal:  Invest Ophthalmol Vis Sci        ISSN: 0146-0404            Impact factor:   4.799


  6 in total

1.  Towards Accurate Segmentation of Retinal Vessels and the Optic Disc in Fundoscopic Images with Generative Adversarial Networks.

Authors:  Jaemin Son; Sang Jun Park; Kyu-Hwan Jung
Journal:  J Digit Imaging       Date:  2019-06       Impact factor: 4.056

2.  Computational investigation of blood cell transport in retinal microaneurysms.

Authors:  He Li; Yixiang Deng; Konstantina Sampani; Shengze Cai; Zhen Li; Jennifer K Sun; George E Karniadakis
Journal:  PLoS Comput Biol       Date:  2022-01-05       Impact factor: 4.475

3.  Predicting High Coronary Artery Calcium Score From Retinal Fundus Images With Deep Learning Algorithms.

Authors:  Jaemin Son; Joo Young Shin; Eun Ju Chun; Kyu-Hwan Jung; Kyu Hyung Park; Sang Jun Park
Journal:  Transl Vis Sci Technol       Date:  2020-11-11       Impact factor: 3.283

4.  Macular Vascular Geometry Changes With Sex and Age in Healthy Subjects: A Fundus Photography Study.

Authors:  Ziqing Feng; Gengyuan Wang; Honghui Xia; Meng Li; Guoxia Liang; Tingting Dong; Peng Xiao; Jin Yuan
Journal:  Front Med (Lausanne)       Date:  2021-12-15

5.  The Longitudinal Assessment of Vascular Parameters of the Retina and Their Correlations with Systemic Characteristics in Type 2 Diabetes-A Pilot Study.

Authors:  Rehana Khan; Sajib K Saha; Shaun Frost; Yogesan Kanagasingam; Rajiv Raman
Journal:  Vision (Basel)       Date:  2022-07-20

6.  Predictive modelling of thrombus formation in diabetic retinal microaneurysms.

Authors:  He Li; Konstantina Sampani; Xiaoning Zheng; Dimitrios P Papageorgiou; Alireza Yazdani; Miguel O Bernabeu; George E Karniadakis; Jennifer K Sun
Journal:  R Soc Open Sci       Date:  2020-08-26       Impact factor: 2.963

  6 in total

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