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HbA(1c) Variability as an Independent Risk Factor for Diabetic Retinopathy in Type 1 Diabetes: A German/Austrian Multicenter Analysis on 35,891 Patients

OBJECTIVE: This study aimed to analyze the effect of HbA(1c) variability on the occurrence of diabetic retinopathy in type 1 diabetes patients. PATIENTS AND METHODS: 35,891 patients with childhood, adolescent or adult onset of type 1 diabetes from a large multicentre survey, the German/Austrian pros...

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Detalles Bibliográficos
Autores principales: Hermann, Julia M., Hammes, Hans-Peter, Rami-Merhar, Birgit, Rosenbauer, Joachim, Schütt, Morten, Siegel, Erhard, Holl, Reinhard W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3946653/
https://www.ncbi.nlm.nih.gov/pubmed/24609115
http://dx.doi.org/10.1371/journal.pone.0091137
Descripción
Sumario:OBJECTIVE: This study aimed to analyze the effect of HbA(1c) variability on the occurrence of diabetic retinopathy in type 1 diabetes patients. PATIENTS AND METHODS: 35,891 patients with childhood, adolescent or adult onset of type 1 diabetes from a large multicentre survey, the German/Austrian prospective documentation system (DPV), were analysed. Cox proportional hazard models were used to examine whether intra-individual HbA(1c) variability expressed as variation coefficient is an independent risk factor for the occurrence of diabetic retinopathy. RESULTS: Kaplan-Meier curves stratified by median HbA(1c) and variation coefficient revealed that retinopathy-free survival probability is lower when both median HbA(1c) and HbA(1c) variability are above the 50(th) percentile. Cox regression models confirmed this finding: After adjustment for age at diabetes onset, gender and median HbA(1c), HbA(1c) variability was independently associated with the occurrence of diabetic retinopathy. Time-covariate interactions used to model non-proportionality indicated an effect decreasing with duration of diabetes for both median HbA(1c) and HbA(1c) variability. Predictive accuracy increased significantly when adding HbA(1c) variability to the Cox regression model. CONCLUSIONS: In patients with type 1 diabetes, HbA(1c) variability adds to the risk of diabetic retinopathy independently of average metabolic control.