Association of age at diagnosis of diabetes with subsequent risk of age-related ocular diseases and vision acuity

BACKGROUND The importance of age on the development of ocular conditions has been reported by numerous studies.Diabetes may have different associations with different stages of ocular conditions,and the duration of diabetes may affect the development of diabetic eye disease.While there is a dose-response relationship between the age at diagnosis of diabetes and the risk of cardiovascular disease and mortality,whether the age at diagnosis of diabetes is associated with incident ocular conditions remains to be explored.It is unclear which types of diabetes are more predictive of ocular conditions.AIM To examine associations between the age of diabetes diagnosis and the incidence of cataract,glaucoma,age-related macular degeneration(AMD),and vision acuity.METHODS Our analysis was using the UK Biobank.The cohort included 8709 diabetic participants and 17418 controls for ocular condition analysis,and 6689 diabetic participants and 13378 controls for vision analysis.Ocular diseases were identified using inpatient records until January 2021.Vision acuity was assessed using a chart.RESULTS During a median follow-up of 11.0 years,3874,665,and 616 new cases of cataract,glaucoma,and AMD,respectively,were identified.A stronger association between diabetes and incident ocular conditions was observed where diabetes was diagnosed at a younger age.Individuals with type 2 diabetes(T2D)diagnosed at<45 years[HR(95%CI):2.71(1.49-4.93)],45-49 years[2.57(1.17-5.65)],50-54 years[1.85(1.13-3.04)],or 50-59 years of age[1.53(1.00-2.34)]had a higher risk of AMD independent of glycated haemoglobin.T2D diagnosed<45 years[HR(95%CI):2.18(1.71-2.79)],45-49 years[1.54(1.19-2.01)],50-54 years[1.60(1.31-1.96)],or 55-59 years of age[1.21(1.02-1.43)]was associated with an increased cataract risk.T2D diagnosed<45 years of age only was associated with an increased risk of glaucoma[HR(95%CI):1.76(1.00-3.12)].HRs(95%CIs)for AMD,cataract,and glaucoma associated with type 1 diabetes(T1D)were 4.12(1.99-8.53),2.95(2.17-4.02),and 2.40(1.09-5.31),respectively.In multivariable-adjusted analysis,individuals with T2D diagnosed<45 years of age[β95%CI:0.025(0.009,0.040)]had a larger increase in LogMAR.Theβ(95%CI)for LogMAR associated with T1D was 0.044(0.014,0.073).CONCLUSION The younger age at the diagnosis of diabetes is associated with a larger relative risk of incident ocular diseases and greater vision loss.

A new measure of nystagmus acuity

AIM: To construct a new visual acuity measuring function for congenital nystagmus(CN) patients by studying the relationships between acuity,velocities and positions of the eye. ·METHODS: After assessing the relationship between acuity,movement velocities and positions of the eye separately,a new function,which we call the automated nystagmus acuity function(ANAF),was constructed to measure the visual acuity of CN patients. Using a high-speed digital video system working at 500 frames per second,each eye was calibrated during monocular fixation. Twenty-six recorded nystagmus data were selected randomly. Using nystagmus waveforms,the best vision position(foveation period) and visual acuity were analyzed in three groups of subjects,and then all outputs were compared with the well-known expanded nystagmus acuity function(NAFX) and ANAF. Standard descriptive statistics were used to summarize the outputs of the two programs. ·RESULTS: Foveation periods were brief intervals in the CN waveform when the image was on or near the fovea and eye velocity was relatively slow. Results showed good visual acuity happened during the period when velocity was low and the eye position was near the zero position,which fitted the foveation periods. The data analyzed with NAFX and ANAF had a correlation coefficient of 0.934276,with an average error of-0.00973. · CONCLUSION: The results from ANAF and NAFX analyses showed no significant difference. The NAFX manually identifies foveation eye positions and produces accurate measurements. The ANAF,however,can be calculated simply using the factors eye position andvelocity,and it automatically calculates the ANAF without the need to manually identify foveation eye positions.