Abstract
Background: Coronary microvascular dysfunction (CMD) is associated with myocardial ischemia in patients without obstructive coronary artery disease (CAD). Epicardial fat volume (EFV) has been reported to be associated with epicardial CAD and diastolic dysfunction. However, because its impact on CMD remains unclear, we aimed to investigate the relationship between CMD and EFV.
Methods and Results: This study included 103 patients without obstructive CAD who underwent assessment of CMD and EFV. CMD was defined as either coronary flow reserve (CFR) <2.0 or index of microcirculatory resistance (IMR) ≥25. EFV was quantified using computed tomography and the EFV index was calculated. CMD was identified in 34 (33%) patients. The EFV index was significantly larger in the CMD group than in the non-CMD group (86.1±27.9 vs. 65.8±20.0 cm3/m2; P<0.01). Notably, patients with low CFR (<2.0) and high IMR (≥25) had a larger EFV index (102.1±33.4 cm3/m2). Univariable logistic regression analysis indicated a significant relationship between CMD and the EFV index (odds ratio (OR): 1.04; P<0.01). In the multivariable model, EFV index was significantly associated with CMD (OR: 1.03; P<0.01). The EFV index significantly correlated with CFR (r=−0.39, P<0.01) and IMR (r=0.32, P<0.01).
Conclusions: EFV was associated with CMD in patients without obstructive CAD.
Myocardial ischemia is a common cause of various cardiac diseases, leading to significant efforts directed toward diagnosing and treating epicardial coronary artery disease (CAD). However, despite presenting with symptoms and signs suggestive of obstructive epicardial CAD, more than half of patients show no significant epicardial stenosis on coronary angiography (CAG).1 These patients are increasingly recognized as having coronary microvascular dysfunction (CMD), an endotype of ischemia with nonobstructive CAD (INOCA),2 which is associated with adverse clinical outcomes.3 Although wire-based invasive assessment of the coronary microcirculation is useful,4 and recommended5 for symptomatic patients without obstructive CAD, its routine use is limited due to its invasiveness and technical complexity. Therefore, identifying the factors related to coronary microvascular abnormalities and stratifying risk in symptomatic patients without obstructive CAD is crucial.
Epicardial adipose tissue (EAT) has been recognized as a source of several inflammatory mediators related to the development of cardiac diseases.6–9 Additionally, the epicardial fat volume (EFV) has been associated with CAD severity,10 plaque characteristics,11 impaired diastolic function,12 and future cardiovascular events.13,14 However, the relationship between EFV and coronary microvascular abnormalities remains unclear, so in this study we aimed to investigate the impact of EFV, quantified with electrocardiogram (ECG)-gated computed tomography (CT), on CMD assessed using a wire-based invasive procedure in patients without obstructive CAD.
Methods
Study Population
Between April 2019 and September 2024, 325 patients with chest pain, shortness of breath, or other symptoms clinically suggestive of stable angina pectoris underwent elective CAG, followed by invasive measurement of coronary physiological indices, including fractional flow reserve (FFR), coronary flow reserve (CFR), and index of microcirculatory resistance (IMR). After excluding patients with obstructive stenosis (>50% diameter reduction visualized on CAG or FFR ≤0.80), left ventricular (LV) ejection fraction <50%, infiltrative cardiomyopathy, history of myocardial infarction, or those receiving hemodialysis, we identified 103 patients who had had their EFV measured within 90 days of physiological measurements using non-contrast ECG-gated CT. The present study complied with the Declaration of Helsinki and was approved by the Institutional Review Board of Nagoya City University (approval number: 60-23-0054). The need for written informed consent was waived owing to the retrospective study design.
Analysis of CT and Echocardiographic Images
A CT examination was conducted with a dual-source 128-slice scanner (SOMATOM Force or NAEOTOM alpha, Siemens Healthineers, Erlangen, Germany). Non-contrast CT was used to calculate the coronary artery calcium score via the Agatston method.15 Prospective ECG triggering was applied, and images were acquired with a slice thickness of 3.0 mm. The CT datasets were transferred to an offline workstation (SYNAPSE VINCENT, Fujifilm Inc, Tokyo, Japan) for image analysis. The EFV was measured in 3 dimensions, defining epicardial fat as adipose tissue within the visceral epicardium. The epicardium was manually traced from the mid-left atrium to the LV apex, interpolating 8–12 slices per patient, excluding extrapericardial tissue. The software then automatically generated a 3-dimensional image of the epicardium, and EFV was quantified by summing the total volume of the tissues within a density range of −190 to −30 Hounsfield units.16 The EFV index was calculated by dividing the EFV by the body surface area.
Cardiac function was examined by trained sonographers using an echocardiographic system (Vivid E9; GE Healthcare, Chicago, IL, USA). LV ejection fraction was measured using the biplane disk summation method. In the apical 4-chamber view, the peak velocity of the transmitral inflow during early and late diastole (E and A, respectively) and mitral annular movement (e′) at the septal and lateral annular corners of the mitral annulus were averaged. E/A and E/e′ were calculated as indices of LV diastolic function. Pulmonary artery systolic pressure (PASP) was estimated as 4 × (peak tricuspid regurgitation velocity)2+ estimated right atrial pressure.17
We calculated the H2FPEF-score from the following 6 items related to each patient’s background: body mass index (BMI) >30 kg/m2, ≥2 antihypertensive medicines, paroxysmal or persistent atrial fibrillation (AF), age >60 years and Doppler echocardiography data at rest (PASP >35 mmHg, E/e′ >9). Points were assigned: BMI, 2 points; AF, 3 points; the other variables, 1 point each. The H2FPEF score was the sum of these points. We divided the patients into 3 groups based on their H2FPEF score: low-risk (0–1 points), intermediate-risk (2–5 points), and high-risk (6–9 points).18
CAG and Coronary Physiological Measurements
CAG was performed using the standard Judkins technique. Following intracoronary administration of nitroglycerin, CAG confirmed no significant stenosis. Coronary physiological indices were assessed using a 0.014-inch coronary pressure-temperature guidewire (Certus, PressureWire X, Abbott Vascular, Santa Clara, CA, USA). The left anterior descending artery was typically selected as the target vessel, but operators made adjustments based on anatomical variations. Initially, the pressure of the wire was equalized to that of the 6Fr guiding catheter without a side hole. The wire was then advanced to the distal third of the target vessel. The transit time of 3 mL of room temperature saline injected into the coronary artery was measured 3 times and averaged to calculate the resting mean transit time. Maximal hyperemia was induced through continuous infusion of adenosine triphosphate via a peripheral forearm vein at a dosage of 180 μg/kg/min. During hyperemia, 3 injections of 3 mL of room temperature saline were administered, and the transit times were averaged to determine the hyperemic mean transit time. The pressure wire was then manually retracted from the distal portion of the vessel to the ostium. After the pressure sensor was returned to the guiding catheter, the pressures were checked to ensure there was no transducer drift. CFR was determined by dividing the resting mean transit time by the hyperemic mean transit time. IMR was calculated by multiplying the mean transit time by the distal coronary pressure at maximal hyperemia. FFR was calculated as the ratio of distal coronary pressure to aortic pressure during maximal hyperemia. CMD was defined as either a CFR <2.0 or an IMR ≥25.2 CFR and IMR were categorized as low (CFR <2.0, IMR <25) or high (CFR ≥2.0, IMR ≥25), respectively.
Statistical Analysis
Quantitative variables are presented as the mean±SD. Discrete variables are presented as counts and percentages. Student’s t-tests and one-way ANOVA were utilized to compare quantitative variables. For discrete variables, χ2
and Fisher’s exact tests were used, as appropriate. A logistic regression analysis was performed to identify potential factors associated with the presence of CMD. The covariates included in the univariable analysis were EFV index, diabetes, high-density lipoprotein cholesterol (HDL-C), serum creatinine, C-reactive protein (CRP), low-density lipoprotein cholesterol, total cholesterol, triglycerides (TG), hypertension, BMI, age, smoking, and male sex. Variables with a P value <0.10 in the univariable model were included in the multivariable model. Correlations between the EFV index and coronary physiological indices (CFR and IMR) were evaluated using Pearson’s correlation coefficient. Univariable and multivariable linear regression analyses were performed to investigate the relationships between the EFV index and other variables. The covariates used in the multivariable model were BMI, TG, HDL-C, CRP, and hypertension. A receiver operating characteristic (ROC) curve was created to determine the optimal cutoff level of the EFV index for predicting the presence of CMD. Statistical significance was defined as P<0.05. All statistical analyses were conducted using IBM SPSS Statistics version 26 (IBM Corp., Armonk, NY, USA).
Results
The baseline patient characteristics are summarized in Table 1. CMD was identified in 34 (33%) patients. Patients with CMD had significantly higher EFV, EFV index and IMR levels than those without CMD. HDL-C levels tended to be lower, and serum creatinine tended to be higher in the CMD group. Diabetes was more prevalent in patients with CMD. The CFR and FFR values were significantly lower in the CMD group than in the non-CMD group. Regarding echocardiographic parameters, e′ was significantly lower, and E/e′ was significantly higher, in patients with CMD. The frequency of a high-risk H2FPEF score was greater in the CMD group. Figure 1 is a comparison of the EFV index among patient groups classified into 4 categories based on CFR and IMR cutoff values. The group with low CFR and high IMR had a significantly higher EFV index than the low IMR groups. Similarly, the group with high CFR and high IMR had a significantly higher EFV index compared to the high CFR and low IMR group. Univariable logistic regression analysis revealed a significant association between CMD presence and both EFV index and diabetes. In the multivariable analysis, EFV index and diabetes remained the significant factors associated with CMD (Table 2). Figure 2 shows the correlation between the EFV index and coronary physiologic indices. The EFV index significantly correlated with both CFR and IMR. Table 3 presents the results of the linear regression analysis for the EFV index. Univariable analysis revealed that BMI and TG correlated with the EFV index. In the multivariable analysis, BMI remained a significant factor associated with EFV index. ROC curve analysis identified a cutoff level of 68.0 cm3/m2
(area under the curve 0.73; sensitivity 0.62; specificity 0.82) for predicting CMD. Table 4 compares the physiological indices, echocardiographic parameters, and H2FPEF scores between patients with a high or low EFV index, stratified by the cutoff value of 68.0 cm3/m2. Patients with a high EFV index demonstrated significantly lower e′, higher E/e′, and a higher prevalence of high-risk H2FPEF score. Representative cases of patients with a large EFV index with CMD and a small EFV index without CMD, both showing no significant coronary artery stenosis, are illustrated in Figure 3.
Table 1.
Baseline Patient Characteristics
| |
All |
CMD
group |
Non-CMD
group |
P value |
| n |
103 |
34 |
69 |
|
| Age, years |
71.4±8.9 |
72.5±8.1 |
70.8±9.2 |
0.35 |
| Male |
62 (60) |
23 (68) |
39 (57) |
0.28 |
| BMI, kg/m2 |
23.8±3.4 |
24.3±3.3 |
23.5±3.5 |
0.26 |
| BSA, m2 |
1.64±0.18 |
1.68±0.18 |
1.62±0.18 |
0.10 |
| Diabetes |
32 (31) |
16 (47) |
16 (23) |
0.02 |
| Hypertension |
84 (82) |
29 (85) |
55 (80) |
0.49 |
| Smoking |
56 (54) |
22 (65) |
34 (49) |
0.14 |
| Dyslipidemia |
82 (80) |
30 (88) |
52 (75) |
0.12 |
| Total cholesterol, mg/dL |
186.6±33.7 |
183.8±36.2 |
188.1±32.5 |
0.55 |
| LDL-C, mg/dL |
105.0±29.0 |
107.8±30.9 |
103.7±28.1 |
0.51 |
| HDL-C, mg/dL |
55.3±15.2 |
51.3±13.4 |
57.3±15.8 |
0.06 |
| TG, mg/dL |
139.4±67.1 |
147.4±70.0 |
135.5±65.9 |
0.41 |
| CRP, mg/dL |
0.10±0.11 |
0.12±0.15 |
0.08±0.07 |
0.10 |
| Cr, mg/dL |
0.83±0.21 |
0.88±0.20 |
0.81±0.21 |
0.09 |
| Fasting plasma glucose, mg/dL |
113.9±31.5 |
118.5±40.0 |
111.7±26.4 |
0.30 |
| Hemoglobin A1c, % |
6.4±0.9 |
6.6±0.8 |
6.3±0.9 |
0.15 |
| BNP, pg/dL |
66.2±77.9 |
81.4±86.9 |
58.6±72.6 |
0.16 |
| Medications |
| Calcium-channel blocker |
66 (64) |
23 (68) |
43 (62) |
0.60 |
| ACE-inhibitor/ARB |
50 (49) |
20 (59) |
30 (43) |
0.14 |
| β-blocker |
28 (27) |
8 (24) |
20 (29) |
0.62 |
| Nitrate |
15 (15) |
5 (15) |
10 (14) |
0.98 |
| Statin |
55 (53) |
19 (56) |
36 (52) |
0.72 |
| Vessel |
|
|
|
0.19 |
| LAD |
75 (73) |
22 (65) |
53 (77) |
|
| LCX |
20 (19) |
10 (29) |
10 (14) |
|
| RCA |
8 (8) |
2 (6) |
6 (9) |
|
| EFV, cm3 |
120.0±47.1 |
146.3±54.7 |
107.1±36.9 |
<0.01 |
| EFV index, cm3/m2 |
72.5±24.8 |
86.1±27.9 |
65.8±20.0 |
<0.01 |
| Calcium score |
|
|
|
0.83 |
| 0 |
17 (17) |
4 (12) |
13 (19) |
|
| 1–100 |
19 (18) |
7 (21) |
12 (17) |
|
| 101–400 |
21 (20) |
7 (21) |
14 (20) |
|
| ≥400 |
46 (45) |
16 (47) |
30 (43) |
|
| Coronary physiologic indices |
| CFR |
3.4±1.8 |
2.0±0.7 |
4.2±1.7 |
<0.01 |
| IMR |
18.1±10.0 |
26.7±12.4 |
13.9±4.7 |
<0.01 |
| FFR |
0.89±0.06 |
0.87±0.06 |
0.90±0.06 |
0.02 |
| Echocardiographic parameters |
| LVEF, % |
64.9±7.0 |
65.0±7.0 |
64.8±7.1 |
0.87 |
| E/A |
0.87±0.37 |
0.92±0.37 |
0.85±0.38 |
0.42 |
| e′, cm/s |
6.9±2.0 |
6.1±1.6 |
7.3±2.1 |
<0.01 |
| E/e′ |
10.4±3.9 |
11.8±5.1 |
9.6±2.9 |
<0.01 |
| H2FPEF score |
|
|
|
0.02 |
| Low (0–1) |
28 (27) |
5 (15) |
23 (33) |
|
| Intermediate (2–5) |
66 (64) |
23 (68) |
43 (62) |
|
| High (6–9) |
9 (9) |
6 (18) |
3 (4) |
|
Data presented as either n (%) or the mean±SD. ACE-inhibitor/ARB, angiotensin-converting enzyme-inhibitor/angiotensin-receptor blocker; BMI, body mass index; BSA, body surface area; CFR, coronary flow reserve; CMD, coronary microvascular dysfunction; Cr, creatinine; CRP, C-reactive protein; EFV, epicardial fat volume; FFR, fractional flow reserve; HDL-C, high-density lipoprotein cholesterol; IMR, index of myocardial resistance; LAD, left anterior descending artery; LCX, left circumflex artery; LDL-C, low-density lipoprotein cholesterol; LVEF, left ventricular ejection fraction; RCA, right coronary artery; TG, triglycerides.
Table 2.
Logistic Regression Results: Association With Coronary Microvascular Dysfunction
| Variable |
Univariable |
Multivariable |
| OR (95% CI) |
P value |
OR (95% CI) |
P value |
| EFV index |
1.04 (1.02–1.06) |
<0.01 |
1.03 (1.01–1.06) |
<0.01 |
| Diabetes |
2.42 (1.23–7.07) |
0.02 |
2.79 (1.03–7.52) |
0.04 |
| HDL-C |
0.97 (0.94–1.00) |
0.06 |
0.99 (0.96–1.03) |
0.59 |
| Cr, per 0.1 mg/dL |
1.19 (0.97–1.46) |
0.09 |
1.18 (0.92–1.50) |
0.19 |
| CRP, per 0.01 mg/dL |
1.04 (0.99–1.08) |
0.14 |
– |
– |
| LDL-C, |
1.00 (0.99–1.02) |
0.51 |
– |
– |
| Total cholesterol |
1.00 (0.98–1.01) |
0.54 |
– |
– |
| TG |
1.00 (0.99–1.01) |
0.40 |
– |
– |
| Hypertension |
1.48 (0.48–4.51) |
0.49 |
– |
– |
| BMI, kg/m2 |
1.07 (0.95–1.21) |
0.26 |
– |
– |
| Age, years |
1.02 (0.98–1.07) |
0.34 |
– |
– |
| Smoking |
1.89 (0.81–4.40) |
0.14 |
– |
– |
| Male |
1.61 (0.68 –3.81) |
0.28 |
– |
– |
CI, confidence interval; OR, odds ratio. Other abbreviations as in Table 1.
Table 3.
Univariable and Multivariable Regression Analysis for Epicardial Fat Volume Index
| Variable |
Univariable |
Multivariable |
| r |
P value |
Standardized
coefficient β |
P value |
| BMI |
0.38 |
<0.01 |
0.28 |
<0.01 |
| TG, mg/dL |
0.30 |
<0.01 |
0.19 |
0.07 |
| HDL-C, mg/dL |
–0.18 |
0.06 |
−0.01 |
0.91 |
| CRP, mg/dL |
0.18 |
0.07 |
0.14 |
0.14 |
| Hypertension |
0.18 |
0.08 |
0.08 |
0.41 |
| Cr, mg/dL |
0.12 |
0.25 |
– |
– |
| Smoking |
0.02 |
0.83 |
– |
– |
| Diabetes |
0.13 |
0.19 |
– |
– |
| Male |
–0.01 |
0.89 |
– |
– |
| Age, years |
0.09 |
0.39 |
– |
– |
| LDL-C, mg/dL |
0.03 |
0.74 |
– |
– |
| Total cholesterol, mg/dL |
−0.03 |
0.76 |
– |
– |
Abbreviations as in Table 1.
Table 4.
Comparison of Physiological Indices, Echocardiographic Parameters, and H2FPEF Score Between Patients With High or Low EFV Index
| Variable |
High EFV index
(≥68.0 cm3/m2) |
Low EFV index
(<68.0 cm3/m2) |
P value |
| n |
53 |
50 |
|
| CMD |
27 (51) |
7 (14) |
<0.01 |
| CFR |
2.7±1.3 |
4.2±1.9 |
<0.01 |
| IMR |
20.9±10.4 |
15.2±8.7 |
<0.01 |
| Echocardiographic parameters |
| LVEF, % |
64.4±7.0 |
65.5±7.1 |
0.41 |
| E/A |
0.86±0.34 |
0.89±0.41 |
0.73 |
| e′, cm/s |
6.4±1.9 |
7.4±2.1 |
0.01 |
| E/e′ |
11.1±4.6 |
9.5±2.9 |
0.05 |
| H2FPEF score |
|
|
<0.01 |
| Low (0–1) |
8 (15) |
20 (40) |
|
| Intermediate (2–5) |
38 (72) |
28 (56) |
|
| High (6–9) |
7 (13) |
2 (4) |
|
Data presented as either n (%) or the mean±SD. Abbreviations as in Table 1.
Discussion
This observational study investigated the clinical impact of EFV measured by CT on CMD as determined by invasive coronary physiological measurements. The main finding of our analysis was that the EFV index was larger in patients with CMD, and was significantly associated with the presence of CMD. Moreover, we found that the EFV index correlated with CFR and IMR.
Importance of Recognizing CMD in Patients Without Obstructive CAD
Although CAG is widely performed for patients with chest symptoms, over half of patients are diagnosed as not having obstructive CAD on CAG.1 In this subset, CMD, a major cause of INOCA, is highly prevalent.19 Furthermore, CMD in individuals without obstructive CAD is associated with death, myocardial infarction, and heart failure-related hospitalizations,3 resulting in significant healthcare costs,20 underscoring the need to assess coronary microcirculation in patients undergoing CAG, not only to determine the cause of the symptoms but also to stratify the future risk of cardiac events. However, patients with CMD have been underdiagnosed and undertreated in clinical practice because traditional diagnostic approaches have focused on detecting epicardial CAD. Recently, invasive techniques for diagnosing coronary microvascular physiology using a pressure-temperature guidewire have emerged as an attractive method of assessing both CFR and IMR.4 Our study found that 33% of the patients had CMD detected through invasive testing.
Relationship Between EAT and CMD
The precise mechanism of CMD in nonobstructive CAD is not fully understood. Structural remodeling and functional dysregulation of resistive microvasculature are thought to be the underlying pathophysiology of CMD, leading to myocardial ischemia.21–23 These microvascular abnormalities are reported to be present in patients with atherosclerotic risk factors, such as diabetes,24 hypertension,25 familial hypercholesterolemia,26 chronic kidney disease,27 and smoking.28 Our study found that the EFV index was more strongly associated with CMD than with other conventional atherosclerotic risk factors. Several possible explanations for how increased EFV induces CMD can be proposed. EAT is the visceral fat depot located between the myocardium and the visceral layer of the pericardium, surrounding the coronary arteries. Unlike other fat depots, EAT is metabolically active and located close to the coronary vasculature and myocardium. Increased EAT is associated with elevated production of pro-inflammatory mediators such as tumor necrosis factor and interleukin 6.6 Through endocrine effects exerted via the coronary adventitial vasa vasorum, EAT induces coronary vascular wall inflammation, resulting in the inhibition of vasodilator production,29,30 and reduction of coronary microvascular density,31 which can contribute to the development of CMD. Furthermore, through paracrine effects, the pro-inflammatory and pro-fibrotic factors from EAT32 can diffuse in the interstitial fluid across the myocardium and may act towards microvascular remodeling and fibrosis.
Potential Role of CMD and EFV in the Development of HFpEF
CMD has been shown to be a potential underlying cause of heart failure with preserved ejection fraction (HFpEF).33 Impaired microvascular perfusion and myocardial fibrosis related to CMD can lead to diastolic dysfunction, ultimately contributing to the development of HFpEF. In our study, low e′ and high E/e′ values, echocardiographic indicators of diastolic dysfunction, were observed in patients with CMD and a high EFV index. Additionally, a higher H2FPEF score, which aids in diagnosing and managing HFpEF, was more common in the CMD and high EFV index groups. Among patients undergoing catheterization with atypical anginal symptoms such as shortness of breath and exercise intolerance, some patients with HFpEF may be included. When investigating the cause of symptoms related to CMD, we need to consider HFpEF as a potential differential diagnosis alongside microvascular angina. Further studies are warranted to elucidate the potential utility of EFV measurement in the management of HFpEF.
Clinical Implications
Cardiologists must consider the possibility of a microcirculatory origin of symptoms during the diagnostic workup in patients without obstructive CAD.34 On the other hand, evaluating CMD for all symptomatic patients is not clinically practical due to invasiveness and technical complexity. Therefore, it is crucial to identify markers associated with CMD. In our study, we found that the EFV index was independently associated with the presence of CMD. Hence, measuring the EFV index may aid in decision-making before invasive procedures and risk stratification for patients without obstructive CAD. Our results demonstrating the close relationship between EFV and CMD are consistent with those of a previous study in young and obese patients.35 Although there are several differences in the characteristics of the patients with CMD between our study and those in previous reports,19,26–28 these differences may be attributed to variations in the patient populations – namely, older and non-obese individuals with coronary atherosclerosis and different ethnic backgrounds. Our study strengthens the existing evidence by examining a patient population with distinct characteristics and by exploring the associations among CMD, EFV, and HFpEF. Our finding that BMI was associated with the EFV index suggests that obese patients may be ideal candidates for EFV measurement. To date, therapy for CMD has not been established because of its multifactorial pathophysiology. Although treatment should target the dominant mechanism of CMD, the difficulty in identifying the cause in each individual often leads to uniform treatment, such as β-blockers, renin-angiotensin system inhibitors, and lifestyle modifications.34 Although our findings are hypothesis-generating, prospective studies should confirm the effectiveness of medical EFV reduction therapy,36–39 and determine whether a large EFV may be a target for treatment in patients with CMD.
Study Limitations
First, this was a retrospective observational study with a small number of patients recruited from a single center. Our study population primarily consisted of elderly patients with multiple coronary risk factors and coronary atherosclerosis, with few obese patients included. These patients’ characteristics differ from those reported in previous studies, but we frequently encounter this type of patient in daily clinical practice. Our findings should be confirmed prospectively in a larger population. Second, medications, such as statins, vasodilators, and β-blockers, could modify the results of physiological indices. Third, we did not evaluate the coronary physiological indices in all the coronary arteries. Fourth, our study was cross-sectional in design, and the causal relationship is unclear. Finally, we did not analyze the outcome data.
Conclusions
Increased EFV was associated with CMD in patients without obstructive CAD.
Disclosures
The authors declare that they have no conflicts of interest. Y.S. is a member of Circulation Reports’ Editorial Team.
IRB Information
Nagoya City University, Reference number: 60-23-0054.
Data Availability
The deidentified participant data will not be shared.
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