Age-Related Macular Degeneration, Cardiovascular Disease and Stroke
Authors: Ledesma-Gil Gerardo , Otero-Marquez Oscar , Alauddin Sharmina , Tong Yuehong , Wei Wei , Tai Katy , Lloyd Harriet , Koci Micaela , Ye Catherine , Pillai Cinthi , Scolaro Maria , Govindaiah Arun , Bhuiyan Alauddin , Deobhakta Avnish , Rosen Richard B. , Yannuzzi Lawrence A. , Freund K. Bailey , Smith R. Theodore 
Published: September 2021

Importance

High-risk vascular diseases (HRVs) may remain undetected until catastrophe ensues. Detection from non-invasive retinal imaging would be highly significant.

Objective

To demonstrate that certain lesions of Age-Related Macular Degeneration (AMD) found on retinal imaging correlate with co-existing HRVs.

Design

Cross-sectional cohort study. Two years. Retinal image graders blinded to HRV status.

Setting

2 retina referral clinics.

Participants

151 consecutive AMD patients, ages 50-90, 97 females, 54 males, with lesions of soft drusen and/or subretinal drusenoid deposits (SDD). 12 others approached, 10 refused, 2 excluded.

Methods

Patients were classified by retinal imaging into SDD (SDD present, +/- drusen) or nonSDD (soft drusen only), and by history into HRV (cardiac pump defect (myocardial infarction (MI), coronary artery bypass grafting (CABG), congestive heart failure (CHF)), valve defect, and carotid stroke) or nonHRV, with serum risk factors and medical histories.

Main Outcome Measures

Correlations of HRV with SDD and other covariates (Univariate chi-square and multivariate regression). Performance of Machine Learning predicting HRV.

Results

75 SDD subjects; 76 nonSDD subjects; HRV prevalence 19.2% (29/151).

High density lipoprotein (HDL) < 62 mg/Dl was found in 24/29 HRV, 42/122 nonHRV, OR 12.40, 95% Confidence Interval (CI) 5.125-30.014; p= 0.0002.

15 Pump defects, 14/15 SDD, 8 Valve defects, 6/8 SDD (4 severe aortic stenosis), 6 carotid strokes, 5/6 SDD. Total HRVs 29, 25/29 SDD, OR 9.0, 95% CI 2.95-27.46; p= 0.000012.

Adjusted multivariate correlations. HRV with SDD (p= 0.000333). SDD and HDL < 62 with HRV (p= 0.000098 and 0.021).

Machine Learning prediction of HRVs from SDD status and HDL level: specificity 87.4%, sensitivity 77.4%, accuracy 84.9%; 95% CIs(%) 79.0-93.3, 58.0-90.4, 77.5-90.7, respectively.

Conclusions and Relevance

High-risk vascular diseases were accurately identified in a cohort of AMD patients from the presence of characteristic deposits (SDDs) on imaging and HDL levels. The SDDs are directly consequent to inadequate ocular perfusion resulting from the systemic vasculopathies. Further validation in larger cohorts of both vasculopathic and AMD subjects could bring this system into widespread medical practice, to reduce mortality and morbidity from vascular disease, particularly in women, where undiagnosed cardiac disease remains a serious issue.

Key Points

Question

What is the relationship and driving mechanism between High Risk Vascular Diseases (HRVs) and Age-Related Macular Degeneration (AMD)?

Findings

The specific AMD lesions of Subretinal Drusenoid Deposits (SDDs) were found to be highly correlated with and directly consequent to the inadequate ocular perfusion resulting from the HRVs of severe cardiac pump insufficiency or valve defect, and carotid occlusion, These vasculopathies could be predicted from the presence of SDDs on spectral domain optical coherence tomography (SD-OCT) imaging and serum HDL.

Meaning

Screening for SDDs with SD-OCT imaging could reduce mortality and morbidity from severe vascular disease, particularly in women, where undiagnosed cardiac disease remains a serious issue.