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DETERMINANTS OF NEW-ONSET DIABETES AMONG 19,257 HYPERTENSIVE PATIENTS RANDOMISED IN THE ASCOT-BPLA TRIAL AND THE RELATIVE INFLUENCE OF ANTIHYPERTENSIVE MEDICATION

¹ International Centre for Circulatory Health, National Heart & Lung Institute, Imperial College London
² Sahlgrenska University Hospital/Ostra, Goteborg, Sweden
³ Nordic School of Public Health, Goteborg, Sweden

n.poulter{at}imperial.ac.uk

ABSTRACT

Objectives: To determine the baseline predictors of new-onset diabetes (NOD) in hypertensive patients, and to develop a risk score to identify those at high risk of NOD.

Research Design and Methods: Among 19257 hypertensive patients in ASCOT-BPLA that were randomised to receive one of two antihypertensive regimens: atenolol ± thiazide or amlodipine ± perindopril, 14120 were ‘at risk’ of developing diabetes at baseline. Of these, 1366 (9.7%) subsequently developed NOD during median follow-up of 5.5 years. A multivariate Cox model was developed to identify the independent predictors of NOD, and individual risk scores

Results: NOD was significantly associated with increase in baseline fasting plasma glucose (FPG), BMI, serum triglyceride and systolic blood-pressure (SBP). In contrast, amlodipine ± perindopril in comparison with atenolol ± thiazide treatment (HR 0.66 95%CI 0.59 to 0.74), high HDLc, alcohol use and age >55 years were found to be significantly protective factors. FPG was the most powerful predictor with risk increasing by 5.8 times (95%CI 5.23 to 6.43) for each mmol/l rise above 5 mmol/l. Risk of NOD increased steadily with increasing quartile of risk score, with a nineteen-fold increase (95% CI 14.3 to 25.4) among those in the highest compared with those in the lowest quartile. The model showed excellent internal validity and discriminative ability.

Conclusions: Baseline FPG >5mmol/l, BMI and use of an atenolol ± diuretic regimen were among the major determinants of NOD in hypertensive patients. The model developed from these data allows accurate prediction of NOD among hypertensive subjects

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