Why the study?
The study was conducted to investigate potential associations between optical coherence tomography angiography (OCTA) parameters and diabetic kidney disease (DKD) categories in patients with type 1 diabetes mellitus and controls.
Do optical coherence tomography angiography (OCTA) parameters correlate with diabetic kidney disease severity in patients with type 1 diabetes mellitus?
Do optical coherence tomography angiography (OCTA) parameters correlate with diabetic kidney disease severity in patients with type 1 diabetes mellitus?
OCTA parameters such as vessel density and foveal avascular zone circularity can non-invasively detect and discriminate diabetic kidney disease severity and progression risk in type 1 diabetes patients.
The purpose of this study is to investigate potential associations between optical coherence tomography angiography (OCTA) parameters and diabetic kidney disease (DKD) categories in type 1 diabetes mellitus (T1DM) patients and controls. A complete ocular and systemic examination, including OCTA imaging tests and bloods, was performed. OCTA parameters included vessel density (VD), perfusion density (PD), foveal avascular zone area (FAZa), perimeter (FAZp) and circularity (FAZc) in the superficial vascular plexus, and DKD categories were defined according to glomerular filtration rate (GFR), albumin-creatinine ratio (ACR) and KDIGO prognosis risk classifications. A total of 425 individuals (1 eye/1 patient) were included. Reduced VD and FAZc were associated with greater categories of GFR (p = 0.002, p = 0.04), ACR (p = 0.003, p = 0.005) and KDIGO risk prognosis classifications (p = 0.002, p = 0.005). FAZc was significantly reduced in greater KDIGO prognosis risk categories (low risk vs. moderate risk, 0.65 ± 0.09 vs. 0.60 ± 0.07, p < 0.05). VD and FAZc presented the best diagnostic performance in ROCs. In conclusion, OCTA parameters, such as VD and FAZc, are able to detect different GFR, ACR, and KDIGO categories in T1DM patients and controls in a non-invasive, objective quantitative way. FAZc is able to discriminate within T1DM patients those with greater DKD categories and greater risk of DKD progression.
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Alé-Chilet et al. (2021) studied this question.
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