| Literature DB >> 34837589 |
Lilla István1, Cecilia Czakó1, Fruzsina Benyó1, Ágnes Élő1, Zsuzsa Mihály2, Péter Sótonyi2, Andrea Varga2, Zoltán Zsolt Nagy1, Illés Kovács3,4,5.
Abstract
Carotid artery stenosis (CAS) is among the leading causes of mortality and permanent disabilities in the Western world. CAS is a consequence of systemic atherosclerotic disease affecting the majority of the aging population. Optical coherence tomography angiography (OCTA) is a novel imaging technique for visualizing retinal blood flow. It is a noninvasive, fast method for qualitative and quantitative assessment of the microcirculation. Cerebral and retinal circulation share similar anatomy, physiology, and embryology; thus, retinal microvasculature provides a unique opportunity to study the pathogenesis of cerebral small vessel disease in vivo. In this study, we aimed to analyze the effect of systemic risk factors on retinal blood flow in the eyes of patients with significant carotid artery stenosis using OCT angiography. A total of 112 eyes of 56 patients with significant carotid stenosis were included in the study. We found that several systemic factors, such as decreased estimated glomerular filtration rate (eGFR), hypertension, and carotid occlusion have a significant negative effect on retinal blood flow, while statin use and carotid surgery substantially improve ocular microcirculation. Neither diabetes, clopidogrel or acetylsalicylic acid use, BMI, serum lipid level, nor thrombocyte count showed a significant effect on ocular blood flow. Our results demonstrate that a systematic connection does exist between certain systemic risk factors and retinal blood flow in this patient population. OCTA could help in the assessment of cerebral circulation of patients with CAS due to its ability to detect subtle changes in retinal microcirculation that is considered to represent changes in intracranial blood flow.Entities:
Keywords: Carotid artery stenosis; OCT angiography; Retinal biomarkers; Retinal imaging
Mesh:
Year: 2021 PMID: 34837589 PMCID: PMC8810958 DOI: 10.1007/s11357-021-00492-1
Source DB: PubMed Journal: Geroscience ISSN: 2509-2723 Impact factor: 7.713
Fig. 1Color-coded images of macular vessel density (VD) from both eyes of a patient with left unilateral carotid artery stenosis show preserved retinal blood flow (VD: 44.7%) on the contralateral right eye (a) and areas of non-perfusion (arrows) and decreased overall perfusion (VD:41.9%) in the ipsilateral left eye (b)
Baseline characteristics of the study group
| Mean ± SD | Min–max | |
|---|---|---|
| Age (years) | 69.89 ± 7.07 | 53–84 |
| Gender (F/M) | 22/34 | - |
| Carotid stenosis (%) | 79.80 ± 8.96 | 70–99 |
| Hpertension (Y/N) | 52/4 | - |
| Diabetes (Y/N) | 21/35 | - |
| Acetyl salicylic acid use (Y/N) | 33/23 | - |
| Clopidogrel use (Y/N) | 21/35 | - |
| Statin use (Y/N) | 33/23 | - |
| BMI | 28.48 ± 5.64 | 18.31–42.24 |
| ThCT (g/l) | 244.02 ± 60.78 | 77.00–434.00 |
| Creatinin (umol/l) | 92.43 ± 40.31 | 46–257 |
| eGFR (ml/min/1.73 m2) | 69.82 ± 18.61 | 22–90 |
| Cholesterol (mmol/l) | 4.57 ± 1.49 | 2.20–9.70 |
| HDL (mmol/l) | 1.16 ± 0.26 | 0.61–2.08 |
| LDL (mmol/l) | 2.65 ± 1.07 | 0.81–6.30 |
| Triglyceride (mmol/l) | 1.98 ± 1.14 | 0.60–6.88 |
Significant predictors of macular vessel density in patients with CAS
| Superficial capillary layer | ||||||
|---|---|---|---|---|---|---|
| Bivariable analysis | Multivariable analysis | |||||
| Beta | 95% CI | Beta | 95% CI | |||
| Scan quality (unit) | 2.52 | 2.33–2.73 | < 0.001 | 2.16 | 1.96–2.37 | < 0.001 |
| Carotid stenosis (10%) | − 0.11 | − 0.05 to − 0.17 | 0.001 | − 0.10 | − 0.04 to − 0.16 | 0.001 |
| Hypertension (Y/N) | − 1.56 | − 0.77 to − 2.34 | < 0.001 | − 1.46 | − 0.68 to − 2.23 | < 0.001 |
| eGFR (10 units) | 0.34 | 0.23–0.45 | < 0.001 | 0.35 | 0.24–0.46 | < 0.001 |
| Statin use (Y/N) | 0.95 | 0.53–1.37 | < 0.001 | 1.02 | 0.60–1.44 | < 0.001 |
| Surgery | 0.54 | 0.12–0.96 | 0.01 | 0.55 | 0.14–0.95 | 0.01 |
| Age (years) | − 0.12 | − 0.09 to − 0.15 | < 0.001 | − 0.08 | − 0.06 to − 0.12 | < 0.001 |
Bivariable models included scan quality and one predictor. Multivariable models included all listed predictors
Fig. 2Forest plot demonstrates the effect estimates of systemic predictors and carotid surgery on retinal blood flow after adjustment for scan quality