Society of Thoracic Surgeons Risk Scores Performance in Patients with Left Main Coronary Artery Disease Undergoing Revascularization in the EXCEL trial

Aims: Accurate risk prediction in patients undergoing revascularization is essential. We aimed to assess the predictive performance of Society for Thoracic Surgeons (STS) risk models in patients with left main coronary artery disease (LMCAD) undergoing coronary artery bypass grafting (CABG) or percutaneous coronary intervention with everolimus-eluting stents (PCI-EES). 

Methods and results: The predictive performance of STS risk models for perioperative mortality, stroke and renal failure were evaluated for their discriminative ability (C statistic) and calibration (Hosmer-Lemeshow goodness-of-fit-test; χ2 and p-values) among patients with LMCAD undergoing PCI-EES (n=935) and CABG (n=923) from the randomized EXCEL trial. STS risk scores, in CABG patients, showed good discrimination for 30-day mortality and average discrimination for stroke (C statistics 0.730 and 0.629 respectively) with average calibration. For PCI, STS risk scores had no discrimination for mortality (C statistic 0.507), yet good discrimination (C statistic 0.751) and calibration for stroke. The predictive performance for renal failure was good for CABG (C statistic 0.82), yet poor for PCI (C statistic 0.59). 

Conclusions: In selected patients with LMCAD from the EXCEL trial, STS risk models showed good predictive performance for CABG yet lacked predictive performance for PCI for perioperative mortality and renal failure. The STS stroke risk model was surprisingly more discriminating in PCI compared to CABG EXCEL patients. Improved and procedure-specific risk-prediction instruments are needed to accurately estimate adverse events after LMCAD revascularization by CABG and PCI.