Identification of asymptomatic type 2 diabetes mellitus patients with a low, intermediate and high risk of ischaemic heart disease: is there an algorithm?

The leading cause of death in type 2 diabetes is cardiovascular disease (CVD). We examined the prevalence of myocardial ischaemia in type 2 diabetes patients and tried to establish an algorithm to identify patients with a high risk of ischaemic heart disease. Type 2 diabetes patients who had no known or suspected CVD, and had been referred consecutively to a diabetes clinic for the first time (n = 305; age 58.6 +/- 11.3 years; diabetes duration 4.5 +/- 5.3 years) were screened for myocardial ischaemia using myocardial perfusion scintigraphy (MPS). The univariate predictors of myocardial ischaemia were: atypical or typical angina pectoris, two or more traditional risk factors for CVD, BMI > 32 kg/m(2), systolic blood pressure > 140 mmHg, HbA(1c) > 8.5%, high-sensitivity C-reactive protein > 4.0 mg/l, N-terminal pro-brain natriuretic peptide > 300 pg/ml, left atrial volume index > 32 ml/m(2), left ventricular ejection fraction < 50%, and carotid and peripheral arterial disease. The algorithm identified low (n = 96), intermediate (n = 65) and high risk groups (n = 115), in which the prevalence of myocardial ischaemia was 15%, 23% and 43%, respectively. Overall the algorithm reduced the number of patients referred to MPS from 305 to 144. However, the sensitivity and specificity of the algorithm was just 68% and 62%, respectively. Our algorithm was able to stratify which patients had a low, intermediate or high risk of myocardial ischaemia based on MPS. However, the algorithm had low sensitivity and specificity, combined with high cost and time requirements. clinicaltrials.gov NCT00298844 The study was funded by the Danish Cardiovascular Research Academy (DaCRA), The Danish Diabetes Association and The Danish Heart Foundation.