Pedro Romero-Aroca1, Raul Navarro-Gil1, Albert Feliu2, Aida Valls3, Antonio Moreno3, Marc Baget-Bernaldiz1. 1. Ophthalmology Service, University Hospital Sant Joan, Institut de Investigacio Sanitaria Pere Virgili (IISPV), Universitat Rovira & Virgili, 43204 Reus, Spain. 2. Pediatric Service, University Hospital Sant Joan, Institut de Investigacio Sanitaria Pere Virgili (IISPV), Universitat Rovira & Virgili, 43204 Reus, Spain. 3. Departament d'Enginyeria Informàtica I Matemàtiques, Escola Tècnica Superior d'Enginyeria, Universitat Rovira & Virgili, ITAKA-Intelligent Technologies for Advanced Knowledge Acquisition, 43204 Tarragona, Spain.
Abstract
BACKGROUND: To measure the relationship between variability in HbA1c and microalbuminuria (MA) and diabetic retinopathy (DR) in the long term. METHODS: A prospective case-series study, was conducted on 366 Type 1 Diabetes Mellitus patients with normoalbuminuria and without diabetic retinopathy at inclusion. The cohort was followed for a period of 12 years. The Cox survival analysis was used for the multivariate statistical study. The effect of variability in microangiopathy (retinopathy and nephropathy) was evaluated by calculating the standard deviation of HbA1c (SD-HbA1c), the coefficient of variation of HbA1c (CV-HbA1c), average real variability (ARV-HbA1c) and variability irrespective of the mean (VIM-HbA1c) adjusted for the other known variables. RESULTS: A total of 106 patients developed diabetic retinopathy (29%) and 73 microalbuminuria (19.9%). Overt diabetic nephropathy, by our definition, affected only five patients (1.36%). Statistical results show that the current age, mean HbA1c, SD-HbA1c and ARV-HbA1c are significant in the development of diabetic retinopathy. Microalbuminuria was significant for current age, mean HbA1c, CV-HbA1c and ARV-HbA1c. CONCLUSIONS: By measuring the variability in HbA1c, we can use SD-HbA1c and ARV-HbA1c as possible targets for judging which patients are at risk of developing DR and MA, and CV-HbA1c as the target for severe DR.
BACKGROUND: To measure the relationship between variability in HbA1c and microalbuminuria (MA) and diabetic retinopathy (DR) in the long term. METHODS: A prospective case-series study, was conducted on 366 Type 1 Diabetes Mellituspatients with normoalbuminuria and without diabetic retinopathy at inclusion. The cohort was followed for a period of 12 years. The Cox survival analysis was used for the multivariate statistical study. The effect of variability in microangiopathy (retinopathy and nephropathy) was evaluated by calculating the standard deviation of HbA1c (SD-HbA1c), the coefficient of variation of HbA1c (CV-HbA1c), average real variability (ARV-HbA1c) and variability irrespective of the mean (VIM-HbA1c) adjusted for the other known variables. RESULTS: A total of 106 patients developed diabetic retinopathy (29%) and 73 microalbuminuria (19.9%). Overt diabetic nephropathy, by our definition, affected only five patients (1.36%). Statistical results show that the current age, mean HbA1c, SD-HbA1c and ARV-HbA1c are significant in the development of diabetic retinopathy. Microalbuminuria was significant for current age, mean HbA1c, CV-HbA1c and ARV-HbA1c. CONCLUSIONS: By measuring the variability in HbA1c, we can use SD-HbA1c and ARV-HbA1c as possible targets for judging which patients are at risk of developing DR and MA, and CV-HbA1c as the target for severe DR.
Entities:
Keywords:
HbA1c variability; coefficient of variation of HbA1c; diabetic retinopathy; severity of diabetic retinopathy
Authors: Luis Mena; Salvador Pintos; Nestor V Queipo; José A Aizpúrua; Gladys Maestre; Tulio Sulbarán Journal: J Hypertens Date: 2005-03 Impact factor: 4.844
Authors: Peter M Rothwell; Sally C Howard; Eamon Dolan; Eoin O'Brien; Joanna E Dobson; Bjorn Dahlöf; Neil R Poulter; Peter S Sever Journal: Lancet Neurol Date: 2010-03-11 Impact factor: 44.182
Authors: C P Wilkinson; Frederick L Ferris; Ronald E Klein; Paul P Lee; Carl David Agardh; Matthew Davis; Diana Dills; Anselm Kampik; R Pararajasegaram; Juan T Verdaguer Journal: Ophthalmology Date: 2003-09 Impact factor: 12.079
Authors: Julia M Hermann; Hans-Peter Hammes; Birgit Rami-Merhar; Joachim Rosenbauer; Morten Schütt; Erhard Siegel; Reinhard W Holl Journal: PLoS One Date: 2014-03-07 Impact factor: 3.240
Authors: John M Lachin; Neil H White; Dean P Hainsworth; Wanjie Sun; Patricia A Cleary; David M Nathan Journal: Diabetes Date: 2014-09-09 Impact factor: 9.461
Authors: Pedro Romero-Aroca; Sofia de la Riva-Fernandez; Aida Valls-Mateu; Ramon Sagarra-Alamo; Antonio Moreno-Ribas; Nuria Soler Journal: Br J Ophthalmol Date: 2016-01-14 Impact factor: 4.638
Authors: Vivian Schreur; Freekje van Asten; Heijan Ng; Jack Weeda; Joannes M M Groenewoud; Cees J Tack; Carel B Hoyng; Eiko K de Jong; Caroline C W Klaver; B Jeroen Klevering Journal: Acta Ophthalmol Date: 2018-08 Impact factor: 3.761