No model has been developed to predict significant coronary artery disease (CAD) on coronary computed tomographic angiography (CCTA) in asymptomatic type 2 diabetes. Therefore, we sought to develop a model for the prediction of significant CAD on CCTA in these patients.
We analyzed 607 asymptomatic patients with type 2 diabetes who underwent CCTA. The cardiac event was defined as a composite of cardiac death, nonfatal myocardial infarction, acute coronary syndrome, and coronary revascularization.
Significant CAD (diameter stenosis ≥50%) in at least one coronary artery on CCTA was observed in 188 (31.0%). During the follow-up period (median 4.3 [interquartile range, 3.7–4.8] years), 71 patients had 83 cardiac events. Clinical risk factors for significant CAD were age, male gender, duration of diabetes, hypertension, current smoking, family history of premature CAD, previous history of stroke, ratio of total cholesterol to high-density lipoprotein cholesterol, and neuropathy. Using these variables, we formulated a risk score model, and the scores ranged from 0 to 17 (area under the curve = 0.727, 95% confidence interval = 0.714–0.739, P < 0.001). Patients were categorized into low (≤3), intermediate (4–6), or high (≥7) risk group. There were significant differences between the risk groups in the probability of significant CAD (12.6% vs 29.4% vs 57.7%, P for all < 0.001) and 5-year cardiac event-free survival rate (96.6% ± 1.5% vs 88.9% ± 1.8% vs 73.8% ± 4.1%, log-rank P for trend < 0.001).
This model predicts significant CAD on CCTA and has the potential to identify asymptomatic type 2 diabetes with high risk.