Prognostic value of a novel index: computational pressure-flow dynamics derived fractional flow reserve in patients with stable coronary artery disease treated with optimal medical therapy alone

Abstract

Abstract Background The use of fractional flow reserve (FFR) is limited due to the need of invasive pressure wire and hyperaemic stimulus. Computational pressure-flow dynamics derived fractional flow reserve (caFFR) is a novel non-invasive index to determine the FFR in patients with stable coronary artery disease (CAD). Purpose The clinical value of caFFR remains uncertain. The aim of the study is to evaluate the prognostic role of caFFR in patients with stable CAD who were treated by optimal medical therapy alone. Methods A total of 558 stable CAD patients (mean age=64.5±11.2, 59.0% male) with ≥1 coronary lesion detected during conventional coronary angiogram were included. All of them did not undergo percutaneous coronary intervention and were treated with optimal medical therapy alone. Patients were then classified into 4 groups according to their caFFR value; caFFR ≤0.70 (n=40), caFFR = 0.71–0.80 (n=28), caFFR = 0.81–0.90 (n=292), caFFR = 0.91–1.00 (n=198), with a lower caFFR indicating a greater magnitude of myocardial ischemia. The primary endpoint was 3-year major adverse cardiac events (MACE), defined as a composite of all-cause mortality, myocardial infarction or any unplanned revascularization. Results During a median follow-up of 36 months, a total of 49 composite events occurred, including 27 all-cause mortality, 4 myocardial infarction and 18 unplanned revascularization. After multivariate adjustment, caFFR was an independent predictor of MACE (adjusted hazard ratio [HR] = 0.97 per 0.01 increase in caFFR; 95% confidence interval [Cl], 0.95–0.99; P<0.01), all-cause mortality (adjusted HR = 0.96 per 0.01 increase in caFFR; 95% Cl, 0.94–0.99; P<0.01), and stroke (adjusted HR = 0.95 per 0.01 increase in caFFR; 95% Cl, 0.90–0.99; P=0.03). The area under the curve (AUC) by receiver-operating characteristic curve analysis (ROC) is 0.70 (95% Cl, 0.62–0.78; P<0.01). The optimal cut-off of caFFR defined by ROC analysis for predicting MACE is 0.80, concluding that patients with caFFR ≤0.80 have significantly higher adverse event rate, which is consistent with the cut-off from wire-based FFR. Using caFFR = 0.91–1.00 as reference, the risk of MACE was highest in patients with caFFR ≤0.70 (adjusted HR = 4.65; 95% Cl, 1.81–11.94; P<0.01), followed by caFFR = 0.71–0.80 (adjusted HR = 3.67; 95% Cl, 1.12–11.33; P=0.02). The risk of MACE was nonetheless similar among patients with caFFR >0.8 (adjusted HR = 1.39; 95% Cl, 0.61–3.19, P=0.44). Conclusion In patients with stable CAD who were treated with optimal medical therapy alone, those with more significant myocardial ischemia, indicated by lower caFFR, had higher risks of adverse outcomes. The finding thus supports the use of this non invasive index to quantify the severity of myocardial ischemia, improve risk-stratification, and predict adverse outcomes in patients with stable CAD. Funding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): The University of Hong Kong, Queen Mary Hospital