Retinal Information is Independently Associated with Cardiovascular Disease in Patients with Type 2 diabetes

Vivian Yawei Guo, Juliana Chung Ngor Chan, Harriet Chung, Risa Ozaki, Wingyee So, Andrea Luk, Augustine Lam, Jack Lee, Benny Chung-Ying Zee, Vivian Yawei Guo, Juliana Chung Ngor Chan, Harriet Chung, Risa Ozaki, Wingyee So, Andrea Luk, Augustine Lam, Jack Lee, Benny Chung-Ying Zee

Abstract

To evaluate the association between a series of retinal information and cardiovascular disease (CVD) and to evaluate whether this association is independent of traditional CVD risk factors in type 2 diabetes patients, we undertook an age-sex matched case-control study with 79 CVD cases and 150 non-CVD controls. All the participants underwent standardized physical examinations and retinal imaging. Retinal information was extracted from the retinal images using a semi-automatic computer program. Three stepwise logistic regression models were evaluated: model 1 with cardiovascular risk factors only; model 2 with retinal information only and model 3 with both cardiovascular risk factors and retinal information. The areas under the receiver operating characteristic curves (AUCs) were used to compare the performances of different models. Results showed that the AUCs were 0.692 (95%CI: 0.622-0.761) and 0.661 (95%CI: 0.588-0.735) for model 1 and model 2, respectively. In addition, model 3 had an AUC of 0.775 (95%CI: 0.716-0.834). Compared to the previous two models, the AUC of model 3 increased significantly (p < 0.05 in both comparisons). In conclusion, retinal information is independently associated with CVD in type 2 diabetes. Further work is needed to validate the translational value of applying retinal imaging analysis into clinical practice.

Figures

Figure 1. AUC comparison between different models.
Figure 1. AUC comparison between different models.
(Model 1: Inclusion of traditional cardiovascular risk factors only; Model 2: Inclusion of retinal information only; Model 3: Inclusion of traditional cardiovascular risk factors + retinal information).

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