Eye Complications and Markers of Morbidity and Mortality in Long‐term Type 1 Diabetes

Abstract

The incidence of type 1 diabetes is rising all over the world. Furthermore, the increased life-expectancy of type 1 diabetic patients is likely to cause a higher number of diabetes-related micro- and macrovascular complications in the years to come. In order to examine the level of long-term complications in type 1 diabetes as well as potential markers of micro- and macroangiopathy, a population-based cohort of Danish type 1 diabetic patients was examined in order to achieve the following aims: 1. To evaluate diabetic retinopathy as a long-term marker of all-cause mortality in type 1 diabetes (Paper I). 2. To estimate the long-term incidence and associated risk factors of blindness (Paper II) and cataract surgery (Paper III) in type 1 diabetes. 3 To use retinal vascular analyses in order to investigate the associations of long-term micro- and macrovascular complications and retinal vascular diameters (Paper IV) and retinal fractals (Paper V) in type 1 diabetes. 4. To examine N-terminal pro brain natriuretic peptide (Paper VI) and osteoprotegerin (Paper VII) as non-invasive markers of micro- and macrovascular complications in type 1 diabetes. In Paper I it was a major finding that, despite a mean age of only 38.3 years at baseline, 44.7% of the patients died during the 25-year follow-up. Patients who had proliferative retinopathy as well as proteinuria at the baseline examination had a significantly higher mortality. For these, the 10-year survival was only 22.2%. As demonstrated in Paper II, blindness is an important issue in type 1 diabetes. The 25-year cumulative incidence of blindness was 7.5%. Glycaemic regulation and maculopathy at baseline were both identified as risk factors of blindness. Finally, mortality was higher in patients who went blind during the follow-up. Cataract surgery is quite common in type 1 diabetes. In Paper III a 25-year cumulative incidence of 20.8% was found. Adjusted for mortality, this was even higher (29.4%). As compared to patients without diabetes, cataract surgery takes place approximately 20 years earlier in type 1 diabetic patients. Age and maculopathy at baseline were both identified as predictors of cataract surgery. In Paper IV it was demonstrated that patients with retinal arteriolar narrowing were 2.17 and 3.17 times more likely to have nephropathy and macrovascular disease, respectively. This was an important finding that suggests that retinal fundus photos may be used in order to predict the risk of non-ophthalmological complications in type 1 diabetes. Retinal fractal analysis is another way to evaluate the vascular system of the retina. In Paper V we found associations between retinal fractal and microvascular - but not macrovascular--disease. For instance, patients with lower fractal dimensions were more likely to have proliferative retinopathy (OR 1.45, 95% CI 1.04-2.03) and neuropathy (OR 1.42, 95% CI 1.01-2.01). NT-proBNP is likely to be a future predictor of diabetes-related complications. In Paper VI higher levels of NT-proBNP were related to nephropathy (OR 5.03, 95% CI 1.77-14.25), neuropathy (OR 4.08, 95% CI 1.52-10.97) and macrovascular disease (OR 5.84, 95% CI 1.65-20.74). These associations should be confirmed in future prospective studies. As opposed to NT-proBNP, osteoprotegerin is less likely to be a predictor of either micro- or macrovascular disease in type 1 diabetes. As demonstrated in Paper VII, even though association between higher levels of OPG and nephropathy were found in an age- and sex-adjusted model (OR 2.54, 95% CI 1.09-5.90), this was no longer statistically significant when other factors were taken into account. Overall, it was demonstrated that various complications such as mortality, blindness and cataract surgery were high in type 1 diabetes. Furthermore, retinal arteriolar narrowing, decreased retinal fractals and plasma NT-proBNP were associated with various micro- and macrovascular complications. If confirmed by prospective studies, these modalities may be used in order to identify patients at risk of diabetes-related complications. This could, ultimately, lead to decreased mortality and morbidity in type 1 diabetic patients.