Retinal neurovascular characteristics for the diagnosis and staging of nondiabetic chronic kidney disease: a diagnostic study

Retinal neurovascular characteristics for the diagnosis and staging of nondiabetic chronic kidney disease: a diagnostic study

:371-388
 
Aims: To identify the characteristic retinal neurovascular changes in patients in different stages of nondiabetic chronic kidney disease (CKD) and to develop a model for the accurate diagnosis of nondiabetic CKD.
Methods: Peripapillary retinal nerve fiber layer (pRNFL) thickness and average macular ganglion cell-inner plexiform layer (GC-IPL) thickness of nondiabetic CKD patients and healthy controls (HC) were evaluated by spectral-domain optical coherence tomography (OCT). The vessel density (VD) and perfusion density (PD) of the macula were obtained from optical coherence tomography angiography (OCTA). The estimated glomerular filtration rate (eGFR) was obtained to access the kidney function of CKD patients. Multiple linear regression models were used to adjust for confounding factors in statistical analyzes. The diagnostic capabilities of the parameters were evaluated by logistic regression models.
Results: 131 nondiabetic CKD patients and 62 HC 
entered the study. eGFR was found significantly associated with parafoveal VD and PD (average PD: β = 0.000 4, Padjusted < 0.001) in various sectors. Thinning of pRNFL (β = -6.725, Padjusted0.001) and GC-IPL (β = -4.542, Padjusted < 0.001), as well as decreased VD (β = -2.107, P- adjusted0.001) and PD (β = -0.057, Padjusted = 0.0328) were found in CKD patients. Thinning of pRNFL and deteriorated perifoveal vasculature were found in early CKD, and the parafoveal and foveal VD significantly declined in advanced CKD. Logistic regression models were employed, and selected neurovascular parameters showed an AUC of 0.853 (95% Confidence Interval [CI]: 0.795 to 0.910) in distinguishing CKD patients from HC.
Conclusions: Distinctive retinal neurovascular 
characteristics could be observed in nondiabetic CKD patients of different severities. Our results suggest that retinal manifestations could be valuable in the screening, diagnosis, and follow-up evaluation of patients with CKD.
Aims: To identify the characteristic retinal neurovascular changes in patients in different stages of nondiabetic chronic kidney disease (CKD) and to develop a model for the accurate diagnosis of nondiabetic CKD.
Methods: Peripapillary retinal nerve fiber layer (pRNFL) thickness and average macular ganglion cell-inner plexiform layer (GC-IPL) thickness of nondiabetic CKD patients and healthy controls (HC) were evaluated by spectral-domain optical coherence tomography (OCT). The vessel density (VD) and perfusion density (PD) of the macula were obtained from optical coherence tomography angiography (OCTA). The estimated glomerular filtration rate (eGFR) was obtained to access the kidney function of CKD patients. Multiple linear regression models were used to adjust for confounding factors in statistical analyzes. The diagnostic capabilities of the parameters were evaluated by logistic regression models.
Results: 131 nondiabetic CKD patients and 62 HC 
entered the study. eGFR was found significantly associated with parafoveal VD and PD (average PD: β = 0.000 4, Padjusted < 0.001) in various sectors. Thinning of pRNFL (β = -6.725, Padjusted < 0.001) and GC-IPL (β = -4.542, Padjusted < 0.001), as well as decreased VD (β = -2.107, Padjusted < 0.001) and PD (β = -0.057, Padjusted = 0.0328) were found in CKD patients. Thinning of pRNFL and deteriorated perifoveal vasculature were found in early CKD, and the parafoveal and foveal VD significantly declined in advanced CKD. Logistic regression models were employed, and selected neurovascular parameters showed an AUC of 0.853 (95% Confidence Interval [CI]: 0.795 to 0.910) in distinguishing CKD patients from HC.
Conclusions: Distinctive retinal neurovascular 
characteristics could be observed in nondiabetic CKD patients of different severities. Our results suggest that retinal manifestations could be valuable in the screening, diagnosis, and follow-up evaluation of patients with CKD.
Perspective

From barn lanterns to the 5G intelligent ophthalmic cruiser: the perspective of artificial intelligence and digital technologies on the modality and efficiency of blindness prevention in China

From barn lanterns to the 5G intelligent ophthalmic cruiser: the perspective of artificial intelligence and digital technologies on the modality and efficiency of blindness prevention in China

:1-6
 

Blindness prevention has been an important national policy in China. Previous strategies, such as deploying experienced cataract surgeons to rural areas and assisting in building local ophthalmology centers, had successfully decreased the prevalence of visual impairment and blindness. However, new challenges arise with the aging population and the shift of the disease spectrum towards age-related eye diseases and myopia. With the constant technological boom, digital healthcare innovations in ophthalmology could immensely enhance screening and diagnosing capabilities. Artifcial intelligence (AI) and telemedicine have been proven valuable in clinical ophthalmology settings. Moreover, the integration of cutting-edge communication technology and AI in mobile clinics and remote surgeries is on the horizon, potentially revolutionizing blindness prevention and ophthalmic healthcare. The future of blindness prevention in China is poised to undergo signifcant transformation, driven by emerging challenges and new opportunities.

Blindness prevention has been an important national policy in China. Previous strategies, such as deploying experienced cataract surgeons to rural areas and assisting in building local ophthalmology centers, had successfully decreased the prevalence of visual impairment and blindness. However, new challenges arise with the aging population and the shift of the disease spectrum towards age-related eye diseases and myopia. With the constant technological boom, digital healthcare innovations in ophthalmology could immensely enhance screening and diagnosing capabilities. Artifcial intelligence (AI) and telemedicine have been proven valuable in clinical ophthalmology settings. Moreover, the integration of cutting-edge communication technology and AI in mobile clinics and remote surgeries is on the horizon, potentially revolutionizing blindness prevention and ophthalmic healthcare. The future of blindness prevention in China is poised to undergo signifcant transformation, driven by emerging challenges and new opportunities.
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