Association of Epicardial Fat Volume With Increased Risk of Obstructive Coronary Artery Disease in Chinese Patients With Suspected Coronary Artery Disease

Epicardial fat modifies the relationship between coronary calcium score and all-cause mortality: The St. Francis Heart Study

Objective

Epicardial fat is associated with cardiovascular risk factors and adverse outcomes. However, it is not clear if epicardial fat remains to be a mortality risk when coronary calcium score (CAC) is taken into account.

Methods

We studied the 1005 participants from the St. Francis Heart Study who were apparently healthy with CAC scores at 80th percentile or higher for age and gender, randomly assigned to placebo or statin therapy. At baseline, lipid profiles and non-contrast CT images were obtained where the epicardial fat volume was analyzed. Likelihood ratio testing was used to assess the additional prognostic value of epicardial fat to CAC for the risk of all-cause mortality.

Results

Increased epicardial fat volume was associated with higher CAC. For each unit increase in lnCAC, the average epicardial fat volume increased by 3.34 mL/m2. After a mean follow-up period of 17 years, 179 (18%) participants died. Increased epicardial fat volume was associated with an adjusted hazard ratio of 1.11 (95% CI: 1.02 to 1.20) predicting all-cause mortality. In the stratified analysis testing strata of epicardial fat and CAC, those with increased epicardial fat and increased CAC had the highest risk of death. Compared with a model containing lnCAC and traditional risk factors, a model additionally containing epicardial fat volume yielded a better model fit (likelihood ratio test p < 0.001).

Conclusion

Increased epicardial fat volume is associated with increased all-cause mortality risk. In addition, it portends incremental prognostic value to CAC score in mortality prediction.

Epicardial adipose tissue as an independent predictor of long-term outcome in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement

BACKGROUND

Accurate risk stratification is important to improve patient selection and outcome of patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). As epicardial adipose tissue (EAT) is discussed to be involved in cardiovascular disease, it could be useful as a marker of poor prognosis in patients with severe AS undergoing TAVR.

METHODS

A total of 416 patients diagnosed with severe AS by transthoracic echocardiography were assigned for TAVR and enrolled for systematic assessment. Patients underwent clinical surveys and 5-year long-term follow-up, with all-cause mortality as the primary endpoint. EAT volume was quantified on pre-TAVR planning CTs. Patients were retrospectively dichotomized at the median of 74 cm3 of EAT into groups with low EAT and high EAT volumes. Mortality rates were compared using Kaplan-Meyer plots and uni- and multivariable cox regression analyses.

RESULTS

A total number of 341 of 416 patients (median age 80.9 years, 45% female) were included in the final analysis. Patients with high EAT volumes had similar short-term outcome (p = 0.794) but significantly worse long-term prognosis (p = 0.023) compared to patients with low EAT volumes. Increased EAT volumes were associated with worse long-term outcome (HR1.59; p = 0.031) independently from concomitant cardiovascular risk factors, general type of AS, and functional echocardiography parameters of AS severity (HR1.69; p = 0.013).

CONCLUSION

Increased EAT volume is an independent predictor of all-cause mortality in patients with severe AS undergoing TAVR. It can be easily obtained from pre-TAVR planning CTs and may thus qualify as a novel marker to improve prognostication and management of patient with severe AS.

TRIAL REGISTRATION

DRKS, DRKS00024479.

Machine learning to predict hemodynamically significant CAD based on traditional risk factors, coronary artery calcium and epicardial fat volume

We sought to establish an explainable machine learning (ML) model to screen for hemodynamically significant coronary artery disease (CAD) based on traditional risk factors, coronary artery calcium (CAC) and epicardial fat volume (EFV) measured from non-contrast CT scans. 184 symptomatic inpatients who underwent Single Photon Emission Computed Tomography/Myocardial Perfusion Imaging (SPECT/MPI) and Invasive Coronary Angiography (ICA) were enrolled. Clinical and imaging features (CAC and EFV) were collected. Hemodynamically significant CAD was defined when coronary stenosis severity ≥ 50% with a matched reversible perfusion defect in SPECT/MPI. Data was randomly split into a training cohort (70%) on which five-fold cross-validation was done and a test cohort (30%). The normalized training phase was preceded by the selection of features using recursive feature elimination (RFE). Three ML classifiers (LR, SVM, and XGBoost) were used to construct and choose the best predictive model for hemodynamically significant CAD. An explainable approach based on ML and the SHapley Additive exPlanations (SHAP) method was deployed to generate individual explanation of the model's decision. In the training cohort, hemodynamically significant CAD patients had significantly higher age, BMI and EFV, higher proportions of hypertension and CAC comparing with controls (P all < .05). In the test cohorts, hemodynamically significant CAD had significantly higher EFV and higher proportion of CAC. EFV, CAC, diabetes mellitus (DM), hypertension, and hyperlipidemia were the highest ranking features by RFE. XGBoost produced better performance (AUC of 0.88) compared with traditional LR model (AUC of 0.82) and SVM (AUC of 0.82) in the training cohort. Decision Curve Analysis (DCA) demonstrated that XGBoost model had the highest Net Benefit index. Validation of the model also yielded a favorable discriminatory ability with the AUC, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of 0.89, 68.0%, 96.8%, 94.4%, 79.0% and 83.9% in the XGBoost model. A XGBoost model based on EFV, CAC, hypertension, DM and hyperlipidemia to assess hemodynamically significant CAD was constructed and validated, which showed favorable predictive value. ML combined with SHAP can offer a transparent explanation of personalized risk prediction, enabling physicians to gain an intuitive understanding of the impact of key features in the model.

Impact of epicardial adipose tissue volume on hemodynamically significant coronary artery disease in Chinese patients with known or suspected coronary artery disease

Background

Epicardial adipose tissue (EAT) is directly related to coronary artery disease (CAD), but little is known about its role in hemodynamically significant CAD. Therefore, our goal is to explore the impact of EAT volume on hemodynamically significant CAD.

Methods

Patients who underwent coronary computed tomography angiography (CCTA) and received coronary angiography within 30 days were retrospectively included. Measurements of EAT volume and coronary artery calcium score (CACs) were performed on a semi-automatic software based on CCTA images, while quantitative flow ratio (QFR) was automatically calculated by the AngioPlus system according to coronary angiographic images.

Results

This study included 277 patients, 112 of whom had hemodynamically significant CAD and showed higher EAT volume. In multivariate analysis, EAT volume was independently and positively correlated with hemodynamically significant CAD [per standard deviation (SD) cm³; odds ratio (OR), 2.78; 95% confidence interval (CI), 1.86-4.15; P < 0.001], but negatively associated with QFR_min (per SD cm³; β coefficient, -0.068; 95% CI, -0.109 to -0.027; P = 0.001) after adjustment for traditional risk factors and CACs. Receiver operating characteristics curve analysis demonstrated a significant improvement in predictive value for hemodynamically significant CAD with the addition of EAT volume to obstructive CAD alone (area under the curve, 0.950 vs. 0.891; P < 0.001).

Conclusion

In this study, we found that EAT volume correlated substantially and positively with the existence and severity of hemodynamically significant CAD in Chinese patients with known or suspected CAD, which was independent of traditional risk factors and CACs. In combination with obstructive CAD, EAT volume significantly improved diagnostic performance for hemodynamically significant CAD, suggesting that EAT could be a reliable noninvasive indicator of hemodynamically significant CAD.

The correlation of pericoronary adipose tissue with coronary artery disease and left ventricular function

Objective

We sought to investigate the correlation of pericoronary adipose tissue with coronary artery disease and left ventricular (LV) function.

Methods

Participants with clinically suspected coronary artery disease were enrolled. All participants underwent coronary computed tomography angiography (CCTA) and echocardiography followed by invasive coronary angiography (ICA) within 6 months. Pericoronary adipose tissue (PCAT) was extracted to analyze the correlation with the Gensini score and LV function parameters, including IVS, LVPW, LVEDD, LVESD, LVEDV, LVESV, FS, LVEF, LVM, and LVMI. The correlation between PCAT and the Gensini score was assessed using Spearman’s correlation analysis, and that between the PCAT volume or FAI and LV function parameters was determined using partial correlation analysis.

Results

One hundred and fifty-nine participants (mean age, 64.55 ± 10.64 years; men, 65.4% [104/159]) were included in the final analysis. Risk factors for coronary artery disease, such as hypertension, diabetes, dyslipidemia, and a history of smoking or drinking, had no significant association with PCAT (P > 0.05), and there was also no correlation between PCAT and the Gensini score. However, the LAD-FAI was positively correlated with the IVS (r = 0.203, P = 0.013), LVPW (r = 0.218, P = 0.008), LVEDD (r = 0.317, P < 0.001), LVESD (r = 0.298, P < 0.001), LVEDV (r = 0.317, P < 0.001), LVESV (r = 0.301, P < 0.001), LVM (r = 0.371, P < 0.001), and LVMI (r = 0.304, P < 0.001). Also, the LCX-FAI was positively correlated with the LVEDD (r = 0.199, P = 0.015), LVESD (r = 0.190, P = 0.021), LVEDV (r = 0.203, P = 0.013), LVESV (r = 0.197, P = 0.016), LVM (r = 0.220, P = 0.007), and LVMI (r = 0.172, P = 0.036), and the RCA-FAI was positively correlated with the LVEDD (r = 0.258, P = 0.002), LVESD (r = 0.238, P = 0.004), LVEDV (r = 0.266, P = 0.001), LVESV (r = 0.249, P = 0.002), LVM (r = 0.237, P = 0.004), and LVMI (r = 0.218, P = 0.008), respectively. Finally, the total volume was positively correlated with FS (r = 0.167, P = 0.042).

Conclusion

The FAI was positively correlated with the LV function but was not associated with the severity of coronary artery disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-022-02843-y.

A significant correlation exists between the fat attenuation index (FAI) and left ventricular function parameters.

Our results suggest that cardiac mortality caused by an increased FAI may be due to changes in the left ventricular function.

Pericoronary adipose tissue did not correlate with the body mass index or risk factors of coronary heart disease.

The Role and Implications of Epicardial Fat in Coronary Atherosclerotic Disease

The current minireview aims to assess the implications of epicardial fat secretory function in the development of coronary artery disease. The epicardial adipose tissue (EAT) is a visceral fat depot that has been described as a cardiovascular risk factor. In addition to its mechanical protection role and physiological secretory function, it seems that various secretion products of the epicardial fat are responsible for metabolic disturbances at the level of the cardiac muscle when in association with pre-existing pathological conditions, such as metabolic syndrome. There is a pathological reduction in sarcomere shortening, abnormal cytosolic Ca²⁺ fluxes, reduced expression of sarcoplasmic endoplasmic reticulum ATPase 2a and decreased insulin-mediated Akt-Ser473-phosphorylation in association with abnormal levels of epicardial fat tissue. Activin A, angiopoietin-2, and CD14-positive monocytes selectively accumulate in the diseased myocardium, resulting in reduced cardiomyocyte contractile function. At the same time, it is believed that these alterations in secretory products directly decrease the myocyte function via molecular changes, thus contributing to the development of coronary disease when certain comorbidities are associated.

Quantification of Cardiac Adipose Tissue in Failing and Nonfailing Human Myocardium

Background

Because body mass index (BMI) is generally used clinically to define obesity and to estimate body adiposity, BMI likely is positively correlated with epicardial adipose tissue (EAT) level. Based on echocardiography, previous outcomes on this matter have varied from almost absent to rather strong correlations between BMI and EAT. The purpose of our study was to unambiguously examine EAT content and determine if correlations exist between EAT content and BMI, cause of heart failure, or contractile force.

Methods and Results

We qualitatively scored 150 human hearts ex vivo on EAT distribution. From each heart, multiple photographs of the heart were taken, and both atrial and ventricular adipose tissue levels were semiquantitatively scored. Main findings include a generally higher EAT content on nonfailing hearts compared with end‐stage failing hearts (atrial adipose tissue level 5.70±0.13 vs. 5.00±0.12, P<0.001; ventricular adipose tissue level 5.14±0.16 vs. 4.57±0.12, P=0.0048). The results also suggest that EAT quantity is not strongly correlated with BMI in nonfailing (atrial adipose tissue level r=0.069, ventricular adipose tissue level r=0.14) or failing (atrial adipose tissue level r=−0.022, ventricular adipose tissue level r=0.051) hearts. Atrial EAT is closely correlated with ventricular EAT in both nonfailing (r=0.92, P<0.001) and failing (r=0.87, P<0.001) hearts.

Conclusions

EAT volume appears to be inversely proportional to severity of or length of time with heart failure based on our findings. Based on a lack of correlation with BMI, it is incorrect to assume high EAT volume given high body fat percentage.

Epicardial fat volume is associated with preexisting atrioventricular conduction abnormalities and increased pacemaker implantation rate in patients undergoing transcatheter aortic valve implantation

Epicardial fat tissue (EFT) is a highly metabolically active fat depot surrounding the heart and coronary arteries that is related to early atherosclerosis and adverse cardiac events. We aimed to investigate the relationship between the amount of EFT and preexisting cardiac conduction abnormalities (CCAs) and the need for new postinterventional pacemaker in patients with severe aortic stenosis planned for transcatheter aortic valve implantation (TAVI). A total of 560 consecutive patients (54% female) scheduled for TAVI were included in this retrospective study. EFT volume was measured via a fully automated artificial intelligence software (QFAT) using computed tomography (CT) performed before TAVI. Baseline CCAs [first-degree atrioventricular (AV) block, right bundle branch block (RBBB), and left bundle branch block (LBBB)] were diagnosed according to 12-lead ECG before TAVI. Aortic valve calcification was determined by the Agatston score assessed in the pre-TAVI CT. The median EFT volume was 129.5 ml [IQR 94-170]. Baseline first-degree AV block was present in 17%, RBBB in 10.4%, and LBBB in 10.2% of the overall cohort. In adjusted logistic regression analysis, higher EFT volume was associated with first-degree AV block (OR 1.006 [95% CI 1.002-1.010]; p = 0.006) and the need for new pacemaker implantation after TAVI (OR 1.005 [95% CI 1.0-1.01]; p = 0.035) but not with the presence of RBBB or LBBB. EFT volume did not correlate with the Agatston score of the aortic valve. Greater EFT volume is associated independently with preexisting first-degree AV block and new pacemaker implantation in patients undergoing TAVI. It may play a causative role in degenerative processes and the susceptibility of the AV conduction system.

Profiling of Non-Coding Regulators and Their Targets in Epicardial Fat from Patients with Coronary Artery Disease

Epicardial fat is a continuously growing target of investigation in cardiovascular diseases due to both its anatomical proximity to the heart and coronary circulation and its unique physiology among adipose depots. Previous reports have demonstrated that epicardial fat plays key roles in coronary artery disease, but the non-coding RNA and transcriptomic alterations of epicardial fat in coronary artery disease have not been investigated thoroughly. Micro- and lncRNA microarrays followed by GO-KEGG functional enrichment analysis demonstrated sex-dependent unique mi/lncRNAs altered in human epicardial fat in comparison to subcutaneous fat in both patients with and without coronary artery disease (IRB approved). Among the 14 differentially expressed microRNAs in epicardial fat between patients with and without coronary artery disease, the hsa-miR-320 family was the most highly represented. IPW lncRNA interacted with three of these differentially expressed miRNAs. Next-generation sequencing and pathway enrichment analysis identified six unique mRNAs–miRNA pairs. Pathway enrichment identified inflammation, adipogenesis, and cardiomyocyte apoptosis as the most represented functions altered by the mi/lncRNAs and atherosclerosis and myocardial infarction among the highest cardiovascular pathologies associated with them. Overall, the epicardial fat in patients with coronary artery disease has a unique mi/lncRNA profile which is sex-dependent and has potential implications for regulating cardiac function.

Cellular interplay between cardiomyocytes and non-myocytes in diabetic cardiomyopathy

Patients with Type 2 diabetes mellitus (T2DM) frequently exhibit a distinctive cardiac phenotype known as diabetic cardiomyopathy. Cardiac complications associated with T2DM include cardiac inflammation, hypertrophy, fibrosis and diastolic dysfunction in the early stages of the disease, which can progress to systolic dysfunction and heart failure. Effective therapeutic options for diabetic cardiomyopathy are limited and often have conflicting results. The lack of effective treatments for diabetic cardiomyopathy is due in part, to our poor understanding of the disease development and progression, as well as a lack of robust and valid preclinical human models that can accurately recapitulate the pathophysiology of the human heart. In addition to cardiomyocytes, the heart contains a heterogeneous population of non-myocytes including fibroblasts, vascular cells, autonomic neurons and immune cells. These cardiac non-myocytes play important roles in cardiac homeostasis and disease, yet the effect of hyperglycaemia and hyperlipidaemia on these cell types are often overlooked in preclinical models of diabetic cardiomyopathy. The advent of human induced pluripotent stem cells provides a new paradigm in which to model diabetic cardiomyopathy as they can be differentiated into all cell types in the human heart. This review will discuss the roles of cardiac non-myocytes and their dynamic intercellular interactions in the pathogenesis of diabetic cardiomyopathy. We will also discuss the use of sodium-glucose cotransporter 2 inhibitors as a therapy for diabetic cardiomyopathy and their known impacts on non-myocytes. These developments will no doubt facilitate the discovery of novel treatment targets for preventing the onset and progression of diabetic cardiomyopathy.

Thromboinflammatory Processes at the Nexus of Metabolic Dysfunction and Prostate Cancer: The Emerging Role of Periprostatic Adipose Tissue

Simple Summary

As overweight and obesity increase among the population worldwide, a parallel increase in the number of individuals diagnosed with prostate cancer was observed. There appears to be a relationship between both diseases where the increase in the mass of fat tissue can lead to inflammation. Such a state of inflammation could produce many factors that increase the aggressiveness of prostate cancer, especially if this inflammation occurred in the fat stores adjacent to the prostate. Another important observation that links obesity, fat tissue inflammation, and prostate cancer is the increased production of blood clotting factors. In this article, we attempt to explain the role of these latter factors in the effect of increased body weight on the progression of prostate cancer and propose new ways of treatment that act by affecting how these clotting factors work.

Abstract

The increased global prevalence of metabolic disorders including obesity, insulin resistance, metabolic syndrome and diabetes is mirrored by an increased incidence of prostate cancer (PCa). Ample evidence suggests that these metabolic disorders, being characterized by adipose tissue (AT) expansion and inflammation, not only present as risk factors for the development of PCa, but also drive its increased aggressiveness, enhanced progression, and metastasis. Despite the emerging molecular mechanisms linking AT dysfunction to the various hallmarks of PCa, thromboinflammatory processes implicated in the crosstalk between these diseases have not been thoroughly investigated. This is of particular importance as both diseases present states of hypercoagulability. Accumulating evidence implicates tissue factor, thrombin, and active factor X as well as other players of the coagulation cascade in the pathophysiological processes driving cancer development and progression. In this regard, it becomes pivotal to elucidate the thromboinflammatory processes occurring in the periprostatic adipose tissue (PPAT), a fundamental microenvironmental niche of the prostate. Here, we highlight key findings linking thromboinflammation and the pleiotropic effects of coagulation factors and their inhibitors in metabolic diseases, PCa, and their crosstalk. We also propose several novel therapeutic targets and therapeutic interventions possibly modulating the interaction between these pathological states.

Relationship between epicardial fat volume on cardiac CT and atherosclerosis severity in three-vessel coronary artery disease: a single-center cross-sectional study

Background

The ideal treatment strategy for stable three-vessel coronary artery disease (CAD) patients are difficult to determine and for patients undergoing conservative treatment, imaging evidence of coronary atherosclerotic severity progression remains limited. Epicardial fat volume (EFV) on coronary CT angiography (CCTA) has been considered to be associated with coronary atherosclerosis. Therefore, this study aims to evaluate the relationship between EFV level and coronary atherosclerosis severity in three-vessel CAD.

Methods

This retrospective study enrolled 252 consecutive patients with three-vessel CAD and 252 normal control group participants who underwent CCTA between January 2018 and December 2019. A semi-automatic method was developed for EFV quantification on CCTA images, standardized by body surface area. Coronary atherosclerosis severity was evaluated and scored by the number of coronary arteries with ≥ 50% stenosis on coronary angiography. Patients were subdivided into groups on the basis of lesion severity: mild (score = 3 vessels, n = 85), moderate (3.5 vessels ≤ score < 4 vessels, n = 82), and severe (4 vessels ≤ score ≤ 7 vessels, n = 85). The independent sample t-test, analysis of variance, and logistic regression analysis were used to evaluate the associations between EFV level and severity of coronary atherosclerosis.

Results

Compared with normal controls, three-vessel CAD patients had significantly higher EFV level (65 ± 22 mL/m² vs. 48 ± 19 mL/m²; P < 0.001). In patients with three-vessel CAD, there was a progressive decline in EFV level as the score of coronary atherosclerosis severity increased, especially in those patients with a body mass index (BMI) ≥ 25 kg/m² (75 ± 21 mL/m² vs. 72 ± 22 mL/m² vs. 62 ± 17 mL/m²; P < 0.05). Multivariable regression analysis showed that both BMI (OR 3.40, 95% CI 2.00–5.78, P < 0.001) and the score of coronary atherosclerosis severity (OR 0.49, 95% CI 0.26–0.93, P < 0.05) were independently related to the change of EFV level.

Conclusion

Three-vessel CAD patients do have higher EFV level than the normal controls. While, there may be an inverse relationship between EFV level and the severity of coronary atherosclerosis in patients with three-vessel CAD.

Additive value of epicardial adipose tissue quantification to coronary CT angiography-derived plaque characterization and CT fractional flow reserve for the prediction of lesion-specific ischemia

OBJECTIVES

Epicardial adipose tissue (EAT) from coronary CT angiography (CCTA) is strongly associated with coronary artery disease (CAD). We investigated the additive value of EAT volume to coronary plaque quantification and CT-derived fractional flow reserve (CT-FFR) to predict lesion-specific ischemia.

METHODS

Patients (n = 128, 60.6 ± 10.5 years, 61% male) with suspected CAD who had undergone invasive coronary angiography (ICA) and CCTA were retrospectively analyzed. EAT volume and plaque measures were derived from CCTA using a semi-automatic software approach, while CT-FFR was calculated using a machine learning algorithm. The predictive value and discriminatory power of EAT volume, plaque measures, and CT-FFR to identify ischemic CAD were assessed using invasive FFR as the reference standard.

RESULTS

Fifty-five of 152 lesions showed ischemic CAD by invasive FFR. EAT volume, CCTA ≥ 50% stenosis, and CT-FFR were significantly different in lesions with and without hemodynamic significance (all p < 0.05). Multivariate analysis revealed predictive value for lesion-specific ischemia of these parameters: EAT volume (OR 2.93, p = 0.021), CCTA ≥ 50% (OR 4.56, p = 0.002), and CT-FFR (OR 6.74, p < 0.001). ROC analysis demonstrated incremental discriminatory value with the addition of EAT volume to plaque measures alone (AUC 0.84 vs. 0.62, p < 0.05). CT-FFR (AUC 0.89) showed slightly superior performance over EAT volume with plaque measures (AUC 0.84), however without significant difference (p > 0.05).

CONCLUSIONS

EAT volume is significantly associated with ischemic CAD. The combination of EAT volume with plaque quantification demonstrates a predictive value for lesion-specific ischemia similar to that of CT-FFR. Thus, EAT may aid in the identification of hemodynamically significant coronary stenosis.

KEY POINTS

• CT-derived EAT volume quantification demonstrates high discriminatory power to identify lesion-specific ischemia. • EAT volume shows incremental diagnostic performance over CCTA-derived plaque measures in detecting lesion-specific ischemia. • A combination of plaque measures with EAT volume provides a similar discriminatory value for detecting lesion-specific ischemia compared to CT-FFR.

Association of Epicardial Fat Volume With Increased Risk of Obstructive Coronary Artery Disease in Chinese Patients With Suspected Coronary Artery Disease

Background Epicardial adipose tissue may be associated with the pathogenesis of coronary artery disease (CAD), but its effect on obstructive CAD risk is uncertain. Therefore, we aimed to examine the relationship between epicardial adipose tissue and obstructive CAD in Chinese patients with suspected CAD. Methods and Results The present study enrolled 194 consecutive inpatients with suspected CAD who underwent both noncontrast computed tomography and coronary angiography. We measured epicardial fat volume (EFV) and evaluated its association with obstructive CAD, which was defined as coronary stenosis severity ≥70%. Overall, 44.3% patients had obstructive CAD and tend to have higher EFV. Age, body mass index, triglycerides, incidence of hypertension, and hyperlipidemia were higher across tertiles of EFV (P for trend <0.05). In univariate regression analysis, a per-SD increase in EFV was independently associated with obstructive CAD (odds ratio [OR], 2.31; 95% CI, 1.61-3.32; P<0.001). Consistent with these findings, EFV was still significantly related to obstructive CAD as continuous variable after adjustment for all traditional risk factors and coronary artery calcium (OR per SD, 2.82; 95% CI, 1.68-4.74; P<0.001). Generalized additive model indicated that EFV was linearly associated with risk of obstructive CAD. E-value analysis suggested robustness to unmeasured confounding. Conclusions Our results suggested that in Chinese patients with suspected CAD, EFV was significantly and positively associated with the risk of obstructive CAD, independent of traditional risk factors and coronary artery calcium.