Abstract

Objective: To identify predictors of incident diabetes during follow-up of non-diabetic patients with chronic heart failure (CHF) in the CHARM program.

Research Design and Methods: 1620 non-diabetic patients had full baseline datasets. We compared baseline demographic, medication and laboratory data for patients who did or did not develop diabetes and conducted logistic regression and receiver operator characteristic curve analyses.

Results: 126 of the 1620 patients (7.8%) developed diabetes over a median period of 2.8 years. In multiple logistic regression analysis, the following baseline characteristics were independently associated with incident diabetes in decreasing order of significance by stepwise selection: higher HbA1c (odds ratio [OR] 1.78 per 1 standard deviation (SD) increase; p<0.0001), higher BMI (OR 1.64 per 1SD increase; p<0.0001), lipid-lowering therapy (OR 2.05; p=0.0005), lower serum creatinine concentration (OR 0.68 per 1SD increase; p=0.0018), diuretic therapy (OR 4.81; p=0.003), digoxin therapy (OR 1.65; p=0.022), higher serum ALT concentration (OR 1.15 per 1SD increase; p=0.027) and lower age (OR 0.81 per 1SD increase; p=0.048). Using receiver operating characteristic curve analysis, HbA1c and BMI yielded areas under the curve of 0.723 and 0.712 respectively, increasing to 0.788 when combined. Addition of other variables independently associated with diabetes risk minimally improved prediction of diabetes.

Conclusions: In non-diabetic CHF patients in CHARM, HbA1c and BMI were the strongest predictors of the development of diabetes. Other minor predictors in part reflected CHF severity or drug-associated diabetes risk. Identifying CHF patients at risk of diabetes through simple criteria appears possible and could enable targeted preventative measures.