Coronary artery aneurysms: outcomes following medical, percutaneous interventional and surgical management

BackgroundCoronary artery aneurysms (CAAs) are increasingly diagnosed on coronary angiography; however, controversies persist regarding their optimal management. In the present study, we analysed the long-term outcomes of patients with CAAs following three different management strategies.MethodsWe performed a retrospective review of patient records with documented CAA diagnosis between 2000 and 2005. Patients were divided into three groups: medical management versus percutaneous coronary intervention (PCI) versus coronary artery bypass grafting (CABG). We analysed the rate of major cardiovascular and cerebrovascular events (MACCEs) over a period of 10 years.ResultsWe identified 458 patients with CAAs (mean age 78±10.5 years, 74.5% men) who received medical therapy (N=230) or underwent PCI (N=52) or CABG (N=176). The incidence of CAAs was 0.7% of the total catheterisation reports. The left anterior descending was the most common coronary artery involved (38%). The median follow-up time was 62 months. The total number of MACCE during follow-up was 155 (33.8%); 91 (39.6%) in the medical management group vs 46 (26.1%) in the CABG group vs 18 (34.6%) in the PCI group (p=0.02). Kaplan-Meier survival analysis showed that CABG was associated with better MACCE-free survival (p log-rank=0.03) than medical management. These results were confirmed on univariate Cox regression, but not multivariate regression (OR 0.773 (0.526 to 1.136); p=0.19). Both Kaplan-Meier survival and regression analyses showed that dual antiplatelet therapy (DAPT) and anticoagulation were not associated with significant improvement in MACCE rates.ConclusionOur analysis showed similar long-term MACCE risks in patients with CAA undergoing medical, percutaneous and surgical management. Further, DAPT and anticoagulation were not associated with significant benefits in terms of MACCE rates. These results should be interpreted with caution considering the small size and potential for selection bias and should be confirmed in large, randomised trials.