Improved cardiac risk assessment with noninvasive measures of coronary flow reserve

Abstract

Background: Impaired vasodilator function is an early manifestation of coronary artery disease and may precede angiographic stenosis. It is unknown whether noninvasive assessment of coronary vasodilator function in patients with suspected or known coronary artery disease carries incremental prognostic significance.

Methods and results: A total of 2783 consecutive patients referred for rest/stress positron emission tomography were followed up for a median of 1.4 years (interquartile range, 0.7-3.2 years). The extent and severity of perfusion abnormalities were quantified by visual evaluation of myocardial perfusion images. Rest and stress myocardial blood flows were calculated with factor analysis and a 2-compartment kinetic model and were used to compute coronary flow reserve (coronary flow reserve equals stress divided by rest myocardial blood flow). The primary end point was cardiac death. Overall 3-year cardiac mortality was 8.0%. The lowest tertile of coronary flow reserve (<1.5) was associated with a 5.6-fold increase in the risk of cardiac death (95% confidence interval, 2.5-12.4; P<0.0001) compared with the highest tertile. Incorporation of coronary flow reserve into cardiac death risk assessment models resulted in an increase in the c index from 0.82 (95% confidence interval, 0.78-0.86) to 0.84 (95% confidence interval, 0.80-0.87; P=0.02) and in a net reclassification improvement of 0.098 (95% confidence interval, 0.025-0.180). Addition of coronary flow reserve resulted in correct reclassification of 34.8% of intermediate-risk patients (net reclassification improvement=0.487; 95% confidence interval, 0.262-0.731). Corresponding improvements in risk assessment for mortality from any cause were also demonstrated.

Conclusion: Noninvasive quantitative assessment of coronary vasodilator function with positron emission tomography is a powerful, independent predictor of cardiac mortality in patients with known or suspected coronary artery disease and provides meaningful incremental risk stratification over clinical and gated myocardial perfusion imaging variables.

Figure 1. Myocardial Blood Flow by CFRTertile

Box plots of rest and stress blood flow distributions of the population divided into tertiles by coronary flow reserve (CFR). Overall median blood flow for rest and stress are indicated by the dashed horizontal lines. Although the blood flows significantly vary across tertiles at both rest and stress, the differences are more pronounced at stress and are small in magnitude at rest.

Figure 2. Unadjusted Cardiac Mortality

Unadjusted annualized cardiac mortality by tertiles of CFR and categories of myocardial ischemia and scar (panel A); by categories of myocardial ischemia (panel B); and by tertiles of CFR and categories of left ventricular ejection fraction (panel C). The annual rate of cardiac death increased with increasing summed stress score, decreasing LVEF and CFR. Importantly, lower CFR consistently identified higher risk patients at every level of myocardial scar/ischemia and LVEF, including among those with visually normal PET scans and normal LV function.

Figure 2. Unadjusted Cardiac Mortality

Unadjusted annualized cardiac mortality by tertiles of CFR and categories of myocardial ischemia and scar (panel A); by categories of myocardial ischemia (panel B); and by tertiles of CFR and categories of left ventricular ejection fraction (panel C). The annual rate of cardiac death increased with increasing summed stress score, decreasing LVEF and CFR. Importantly, lower CFR consistently identified higher risk patients at every level of myocardial scar/ischemia and LVEF, including among those with visually normal PET scans and normal LV function.

Figure 2. Unadjusted Cardiac Mortality

Unadjusted annualized cardiac mortality by tertiles of CFR and categories of myocardial ischemia and scar (panel A); by categories of myocardial ischemia (panel B); and by tertiles of CFR and categories of left ventricular ejection fraction (panel C). The annual rate of cardiac death increased with increasing summed stress score, decreasing LVEF and CFR. Importantly, lower CFR consistently identified higher risk patients at every level of myocardial scar/ischemia and LVEF, including among those with visually normal PET scans and normal LV function.

Figure 3. Univariate Predictors of Cardiac Death

Univariate predictors of cardiac mortality are shown. Hazard ratios are presented for a one unit increase except for age (increase of 10 years), left ventricular ejection fraction (LVEF; decrease of 10%), extent of myocardial ischemia and scar combined and each separately (increase of 10%). CAD indicates patient reported coronary artery disease, known angiographic coronary stenosis, prior myocardial infarction or history of coronary revascularization. Hx = history of. ASA = aspirin. BMI = body mass index.

Figure 4. Cardiac Mortality

Cumulative incidence of cardiac mortality for tertiles of coronary flow reserve presented in Kaplan-Meier format (panel A) and after adjustment (18) for age, sex, body mass index, hypertension, dyslipidemia, diabetes mellitus, family history of coronary artery disease (CAD), tobacco use, prior CAD, chest pain, dyspnea, early revascularization, rest left ventricular ejection fraction (LVEF), summed stress score and LVEF reserve (panel B) showing a significant association between CFR and cardiac mortality. HR = hazard ratio.

Figure 4. Cardiac Mortality

Cumulative incidence of cardiac mortality for tertiles of coronary flow reserve presented in Kaplan-Meier format (panel A) and after adjustment (18) for age, sex, body mass index, hypertension, dyslipidemia, diabetes mellitus, family history of coronary artery disease (CAD), tobacco use, prior CAD, chest pain, dyspnea, early revascularization, rest left ventricular ejection fraction (LVEF), summed stress score and LVEF reserve (panel B) showing a significant association between CFR and cardiac mortality. HR = hazard ratio.

Figure 5. Risk Reclassification

Illustration of risk reclassification by addition of coronary flow reserve (CFR) to a model containing clinical risk factors, left ventricular ejection fraction (LVEF), LVEF reserve and combined extent of myocardial scar and ischemia. The upper horizontal bar graph represents the distribution of risk across categories of <1 (green), 1–3 (blue) and >3% (red) per year risk of cardiac death as estimated by a model containing clinical risk factors, rest LVEF, LVEF reserve and the combination of myocardial scar and ischemia (Model 4, Table 3). The pie graphs represent the proportions of patients in each pre-CFR category reassigned to each risk category after the addition of CFR to the risk model(Model 5, Table 3). The vertical bar charts at the bottom represent the annualized rates of cardiac mortality in each of the post-CFR risk categories.

Figure 6. Subgroup Analysis

Analysis of the hazard ratio for cardiac death across patient subgroups between the upper and lower tertiles of coronary flow reserve (CFR). The graph demonstrates the consistent effect of impaired CFR on cardiac mortality. Hazard ratios were computed without adjustment for other covariates. The left vertical dashed line indicates unity. The right vertical dashed line corresponds to the point estimate for the hazard ratio in the entire population with the grey bar indicating the 95% confidence interval for this estimate. In three subgroups, each containing 20% or fewer of patients in the study (i.e. normotensive individuals, those without stress-induced left ventricular ejection fraction (LVEF) augmentation and those who underwent early revascularization), the Cox model did not generate meaningful estimates for the hazard ratios (indicated by ★). Hx = history of. CAD = coronary artery disease. LVEF = left ventricular ejection fraction.