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Endocrine Abstracts (2016) 44 P98 | DOI: 10.1530/endoabs.44.P98

SFEBES2016 Poster Presentations Diabetes and Cardiovascular (30 abstracts)

Predictors and generation of risk equations for albuminuria progression in type 2 diabetes

Miriam Giordano Imbroll 1, , Daniele Agius Lauretta 1 , Trevor Tabone 1 & Stephen Fava 1,


1Diabetes and Endocrine Centre, Mater Dei Hospital, Malta, Malta; 2University of Malta, Malta, Malta.


Background: Diabetes is the commonest cause of end-stage renal disease in the western world. However not all type 2 diabetic subjects develop renal disease, and of those who do, not all progress. At present it is not possible to identify patients who will progress.

Aim: The aim of the study was to identify baseline risk factors for the development and progression of renal disease in a cohort with type 2 diabetes and use this data to generate risk equations.

Patients and methods: Type 2 diabetic patients who had albumin:creatinine ratio (ACR) measurement in 2007–2008 were recruited, baseline characteristics were recorded and followed up for 8 years.

Results: Two hundred and sixty patients were included in the study. Of all the normo and microalbuminuric patients, 24.3% progressed and of all the micro and macroalbuminuric patients 22.1% regressed.

Baseline HbA1c, white cell count (WCC), smoking and duration of diabetes were associated with progression of renal disease in univariate analysis. Smoking (P=0.064) and duration of diabetes (P=0.034) were independently associated with progression in binary logistic regression.

Spearman correlation showed baseline HbA1c (P=0.0016), age (P=0.0064), serum creatinine (P=0.0178), serum potassium (P=0.0414), WCC (P=0.0226), serum triglycerides (P=0.0156), systolic blood pressure (P=0.0164) and duration of diabetes (P=0.003) to be positively correlated with % change in ACR, whilst baseline eGFR (P=0.0278), serum sodium (P=0.039), haemoglobin (P=0.0006) and haematocrit (P=0.0002) were negatively correlated. Duration of diabetes (P=0.025) and baseline HbA1c (P=0.018) was independently associated with % change in ACR in multivariate analysis.

Based on these results risk equations were generated.

Conclusions: We have identified baseline characteristics associated with progression of renal disease in type 2 diabetic subjects and generated equations to estimate risk of progression. If validated in other populations, these equations might be useful in predicting risk of progression in clinical practice.

Volume 44

Society for Endocrinology BES 2016

Brighton, UK
07 Nov 2016 - 09 Nov 2016

Society for Endocrinology 

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