The Danish registry of diabetic retinopathy

AIM OF DATABASE: To monitor the development of diabetic eye disease in Denmark and to evaluate the accessibility and effectiveness of diabetic eye screening programs with focus on interregional variations. TARGET POPULATION: The target population includes all patients diagnosed with diabetes. Denmark (5.5 million inhabitants) has ~320,000 diabetes patients with an annual increase of 27,000 newly diagnosed patients. The Danish Registry of Diabetic Retinopathy (DiaBase) collects data on all diabetes patients aged ≥18 years who attend screening for diabetic eye disease in hospital eye departments and in private ophthalmological practice. In 2014–2015, DiaBase included data collected from 77,968 diabetes patients. MAIN VARIABLES: The main variables provide data for calculation of performance indicators to monitor the quality of diabetic eye screening and development of diabetic retinopathy. Data with respect to age, sex, best corrected visual acuity, screening frequency, grading of diabetic retinopathy and maculopathy at each visit, progression/regression of diabetic eye disease, and prevalence of blindness were obtained. Data analysis from DiaBase’s latest annual report (2014–2015) indicates that the prevalence of no diabetic retinopathy, nonproliferative diabetic retinopathy, and proliferative diabetic retinopathy is 78%, 18%, and 4%, respectively. The percentage of patients without diabetic maculopathy is 97%. The proportion of patients with regression of diabetic retinopathy (20%) is greater than the proportion of patients with progression of diabetic retinopathy (10%). CONCLUSION: The collection of data from diabetic eye screening is still expanding in Denmark. Analysis of the data collected during the period 2014–2015 reveals an overall decrease of diabetic retinopathy compared to the previous year, although the number of patients newly diagnosed with diabetes has been increasing in Denmark. DiaBase is a useful tool to observe the quality of screening, prevalence, and progression/regression of diabetic eye disease

Investigation of the correlation between diabetic retinopathy and prevalent and incident migraine in a national cohort study

Migraine is a disease characterized by cerebral vasodilation. While diabetes has previously been associated with a lower risk of migraine, it is not known if diabetic retinopathy (DR), a retinal peripheral vascular occlusive disease, is a potential biomarker of protection against migraine. Therefore, we aimed to examine diabetic retinopathy as a marker of prevalent and 5-year incident migraine. In a national cohort, we compared patients with diabetes attending DR screening from The Danish National Registry of Diabetic Retinopathy (cases, n = 205,970) to an age- and gender-matched group of patients without diabetes (controls, n = 1,003,170). In the cross-sectional study, a multivariable model demonstrated a lower prevalence of migraine among cases compared with controls (OR 0.83, 95% CI 0.81–0.85), with a lower risk in cases with DR than in those without (OR 0.69, 95% CI 0.65–0.72). In the prospective study, a lower risk of incident migraine was found in a multivariable model in cases (HR 0.76, 95% CI 0.70–0.82), but this did not depend upon the presence of DR. To conclude, in a national study of more than 1.2 million people, patients screened for DR had a lower risk of present migraine, but DR was not a protective marker of incident migraine

Constructing pairs of dual bandlimited frame wavelets in L2(Rn)L^2(\mathbb{R}^n)

Given a real, expansive dilation matrix we prove that any bandlimited function $\psi \in L^2(\mathbb{R}^n)$, for which the dilations of its Fourier transform form a partition of unity, generates a wavelet frame for certain translation lattices. Moreover, there exists a dual wavelet frame generated by a finite linear combination of dilations of $\psi$ with explicitly given coefficients. The result allows a simple construction procedure for pairs of dual wavelet frames whose generators have compact support in the Fourier domain and desired time localization. The construction relies on a technical condition on $\psi$, and we exhibit a general class of function satisfying this condition.Comment: 21 pages, 6 figure

Diabetic retinopathy as a potential marker of Parkinson's disease:a register-based cohort study

Neurodegeneration is an early event in the pathogenesis of diabetic retinopathy, and an association between diabetic retinopathy and Parkinson’s disease has been proposed. In this nationwide register-based cohort study, we investigated the prevalence and incidence of Parkinson’s disease among patients screened for diabetic retinopathy in a Danish population-based cohort. Cases (n = 173 568) above 50 years of age with diabetes included in the Danish Registry of Diabetic Retinopathy between 2013 and 2018 were matched 1:5 by gender and birth year with a control population without diabetes (n = 843 781). At index date, the prevalence of Parkinson’s disease was compared between cases and controls. To assess the longitudinal relationship between diabetic retinopathy and Parkinson’s disease, a multivariable Cox proportional hazard model was estimated. The prevalence of Parkinson’s disease was 0.28% and 0.44% among cases and controls, respectively. While diabetic retinopathy was not associated with present (adjusted odds ratio 0.93, 95% confidence interval 0.72–1.21) or incident Parkinson’s disease (adjusted hazard ratio 0.77, 95% confidence interval 0.56–1.05), cases with diabetes were in general less likely to have or to develop Parkinson’s disease compared to controls without diabetes (adjusted odds ratio 0.79, 95% confidence interval 0.71–0.87 and adjusted hazard ratio 0.88, 95% confidence interval 0.78–1.00). In a national cohort of more than 1 million persons, patients with diabetes were 21% and 12% were less likely to have prevalent and develop incident Parkinson’s disease, respectively, compared to an age- and gender-matched control population without diabetes. We found no indication for diabetic retinopathy as an independent risk factor for incident Parkinson’s disease