Aims/hypothesis: 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.
Methods: 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).
Results: The univariate predictors of myocardial ischaemia were: atypical or typical angina pectoris, two or more traditional risk factors for CVD, BMI >32 kg/m2, systolic blood pressure >140 mmHg, HbA1c >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/m2, 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.
Conclusions/interpretation: 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.
Trial registration: clinicaltrials.gov NCT00298844 FUNDING: The study was funded by the Danish Cardio vascular Research Academy (DaCRA), The Danish Diabetes Association and The Danish Heart Foundation.