Basal Coronary Microvascular Resistance Predicting Death and Heart Failure in Patients Without Functional Coronary Stenosis

Abstract

Background: Abnormal coronary microcirculation is linked to poor patient prognosis, so the aim of the present study was to assess the prognostic relevance of basal microvascular resistance (b-IMR) in patients without functional coronary stenosis.

Methods and Results: Analyses of 226 patients who underwent intracoronary physiological assessment of the left anterior descending artery included primary endpoints of all-cause death and heart failure, as well as secondary endpoints of cardiovascular death and atherosclerotic vascular events. During a median follow-up of 2 years, there were 12 (5.3%) primary and 21 (9.3 %) secondary endpoints. The optimal b-IMR cutoff for the primary endpoints was 47.1 U. Kaplan-Meier curve analysis demonstrated worse event-free survival of the primary endpoints in patients with a b-IMR below the cutoff (χ²=21.178, P<0.001). b-IMR was not significantly associated with the secondary endpoints (P=0.35). A low coronary flow reserve (CFR; <2.5) had prognostic value for both endpoints (primary endpoints: χ²=11.401, P=0.001; secondary endpoints: (χ²=6.015; P=0.014), and high hyperemic microvascular resistance (≥25) was associated only with the secondary endpoints (χ²=4.420; P=0.036). Incorporating b-IMR into a clinical model that included CFR improved the Net Reclassification Index and Integrated Discrimination Improvement for predicting the primary endpoints (P<0.001 and P=0.034, respectively).

Conclusions: b-IMR may be a specific marker of the risk of death and heart failure in patients without functional coronary stenosis.

Coronary blood flow is adequately autoregulated by multilayered tone control mechanisms in the coronary microvasculature to meet the oxygen demand of the myocardium.^1–4 In clinical practice, patients with high resting coronary flow due to abnormally low basal microvascular resistance (basal index of microcirculatory resistance: b-IMR) are occasionally encountered during catheterization. Previous studies have reported that abnormally low microcirculatory tone at rest can be caused by inefficiencies in the resting metabolic state of the myocardium,^5–7 and this abnormal microcirculatory condition has been recognized as an endotype of coronary microvascular dysfunction (CMD).^6,8,9

The presence of CMD, which is mainly detected by reduced coronary flow reserve (CFR) caused by high coronary microvascular resistance during hyperemia and/or low basal microvascular tone, is linked to poor prognosis in patients without functional coronary stenosis.^10–15 However, low b-IMR could indicate different aspects of microcirculatory conditions to those of high hyperemic microvascular resistance and thus its prognostic implications remain unclear.⁶ On this basis, we hypothesized that b-IMR, which is a direct indicator of the resting microcirculatory condition, may provide prognostic information that differs from other indices of coronary microcirculation requiring hyperemia. In this study we aimed to explore the factors related to b-IMR and its potential prognostic value in patients without functional coronary stenosis compared with CFR and hyperemic microvascular resistance (index of microcirculatory resistance: IMR).

Methods

Study Population

The South Kanagawa Intracoronary Physiology (SKIP) registry is a combined database comprising patients who have undergone intracoronary physiological assessments, including thermodilution-based coronary flow assessment (intracoronary physiological assessment: IPA), for suspected myocardial ischemia at 2 cardiovascular centers in Kanagawa Prefecture (Yokosuka Kyosai Hospital and Yokohama Minami Kyosai Hospital), Japan, from November 2019 to March 2022. The registry enrolled 441 patients who underwent IPA due to suspected ischemic symptoms, and had either no or less than intermediate coronary artery stenosis (≤70%; Yokosuka Kyosai Hospital: N=352; Yokohama Minami Kyosai Hospital: N=89). Patients with significant left main disease, a history of coronary artery bypass grafting, significant valvular disease requiring cardiac surgery, or a myocardial infarction within the past month were not enrolled from this registry. A total of 371 patients who underwent IPA performed in the left anterior descending artery were identified, and of them, patients were excluded if they had functionally significant coronary stenosis (fractional flow reserve [FFR] ≤0.80), had undergone any coronary revascularization, or had severe chronic kidney disease (estimated glomerular filtration rate <15 mL/min/1.73 m²). Regarding patients with heart failure (HF), those with suspected ischemic symptoms were included after achieving clinical stability and eliminating oxygen demand through appropriate medical management. Finally, we analyzed the data for 226 patients without functionally significant stenosis who underwent IPA in the left anterior descending artery. The inclusion flow chart is shown in Supplementary Figure 1. In this retrospective study, data derived from catheterization procedures conducted as part of standard clinical care at both hospitals were utilized for research purposes. Ethical approval was granted by the institutional review boards (approval number: YKH #23-59; approval number: YMKH #1-23-8-16), in accordance with the principles of the Declaration of Helsinki. During the briefing for catheterization, all participants were informed that the data collected might be used anonymously for future research endeavors. Notably, the requirement for written informed consent from the participating patients was waived, replaced by an opt-out process, the de details of which were prominently displayed on the hospitals’ bulletin boards.

Coronary Angiography (CAG) and IPA

CAG and IPA were performed using similar standard techniques at both institutions. Each patient initially underwent standard selective CAG following the administration of intracoronary nitrate (either 100 or 200 µg). After diagnostic CAG, intracoronary physiological parameters were measured using a pressure-temperature sensor-equipped guidewire (PressureWire; Abbott, St. Paul, MN, USA) as previously described.^16–18 Using the coronary thermodilution technique, resting and hyperemic thermodilution curves were obtained in triplicate using 3 injections of room-temperature saline (2 or 3 mL). The average basal (bTmn) and hyperemic (hTmn) mean transit times were then calculated as the inverse values of baseline and hyperemic flow, respectively. Hyperemia was induced either by intravenous infusion of adenosine (140 μg/kg/min) through a peripheral or central vein or by intracoronary bolus injection of nicorandil (3 mg). The FFR was calculated as the ratio of distal coronary pressure (Pd) to the mean aortic pressure (Pa) during hyperemia. The CFR was calculated as the ratio of bTmn to hTmn. The b-IMR and IMR were calculated as the product of Pd and Tmn at rest and during hyperemia, respectively. Off-line quantitative CAG analyses were performed with validated software (QCA-CMS version 7.3, MEDIS Medical, Leiden, The Netherlands). The reference diameter, minimum lumen diameter, percent diameter stenosis, and lesion length were obtained.

Follow-up Data

Follow-ups were conducted via outpatient visits or telephone interviews. Clinical follow-up data were carefully collected and adjudicated by the 2 investigators (M.Y. and A.I.) who were unaware of the patients’ coronary flow physiological measurements and baseline clinical characteristics. The primary endpoint was a composite of all-cause death and HF, the latter requiring hospitalization due to lung congestion and/or pleural effusion with specific symptoms. The secondary endpoint was the occurrence of adverse cardiovascular events: cardiovascular death; acute coronary syndrome necessitating repeated CAG; coronary revascularization, indicated by new onset of angina symptoms and progression of coronary lesions in any coronary artery; cerebral infarction, identified by new symptoms and confirmed via magnetic resonance imaging; and peripheral vascular events, characterized by new symptoms and the need for revascularization.

Statistical Analysis

Statistical analyses were performed using SPSS (version 22.0; SPSS, Inc., Chicago, IL, USA) and R version 4.1.2 (The R Foundation for Statistical Computing, Vienna, Austria). Continuous variables are expressed as mean±standard deviation for normally distributed variables and as median values (25–75th percentiles) for non-normally distributed variables. Categorical variables are presented as counts and proportions. Correlations between clinical variables and physiological indices were evaluated using Spearman’s rank correlation. We determined the cutoff value of b-IMR using receiver operating characteristic (ROC) curve analysis to predict the primary endpoint, as the cutoff value based on clinical outcomes has not yet been elucidated. The determinants of abnormal b-IMR based on the cutoff points were evaluated using univariate and multivariate logistic regression analyses. Event-free survival curves were traced using the Kaplan-Meier method, and compared using the log-rank test based on the determined cutoff values. To evaluate the prognostic significance of physiological indices, we utilized C-statistics, Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI) analyses. Univariate Cox proportional hazards regression analysis initially identified factors linked to the primary endpoint with P value <0.10. These factors were used to develop a clinical baseline model, selecting variables that achieved the lowest Akaike Information Criterion, termed the Clinical Model. CFR was then added to the Clinical Model, creating Clinical Model 1, and its prognostic value was assessed with C-statistics, NRI, and IDI. Lastly, b-IMR was included in Clinical Model 1, forming Clinical Model 2, to evaluate its incremental prognostic impact using the same analyses. This stepwise approach facilitated a detailed comparison between models to determine the incremental values of CFR and b-IMR. P values with a two-sided α-level of <0.05 were considered statistically significant.

Results

Baseline Characteristics and Physiological Indices

The study population consisted of 159 males (70.0%) with a mean age of 70.3±10.4 years. The clinical, angiographic, and physiological characteristics of the patients are shown in Table 1. The median values of FFR, CFR, b-IMR and IMR were 0.88 (interquartile range [IQR]: 0.85–0.91), 3.06 (IQR: 1.93–4.50), 68.6 (IQR: 45.1–98.0), and 17.1 (IQR: 12.4–24.4), respectively. Table 2 summarizes the Spearman’s rank correlation coefficients for the associations between the clinical variables and physiological indices. The clinical factors associated with a lower b-IMR were older age, smaller body size, lower hemoglobin level, higher value of C-reactive protein (CRP), and elevated E/e’. Among the cardiovascular risk factors, hyperlipidemia and factors related to diabetes mellitus, such as patients on diabetes medications, as well as higher levels of HbA1c and fasting blood glucose, showed a significant relationship with lower b-IMR values. In contrast, hypertension, history of HF, previous cerebral infarction, prior myocardial infarction, and B-type natriuretic peptide (BNP) levels were not significantly correlated with b-IMR in this study.

Table 1.

Patients’ Baseline Characteristics

Clinical characteristics
Patient characteristics
Age, years	70.3±10.4
Male, n (%)	158 (69.9)
Height, cm	162.5±8.6
Weight, kg	62.5 (54.0–70.2)
BMI, kg/m2	23.9 (21.1–26.0)
BSA, m2	1.67±0.19
Coronary risk factors
Hypertension, n (%)	160 (70.8)
Hyperlipidemia, n (%)	127 (56.2)
Diabetes mellitus, n (%)	82 (36.3)
Current smoker, n (%)	44 (19.5)
Smoking history, n (%)	131 (58.0)
Prior myocardial infarction, n (%)	35 (15.5)
History of coronary revascularization	86 (38.1)
Prior cerebral infarction, n (%)	10 (4.4)
History of heart failure, n (%)	41 (18.1)
Medications, n (%)
ACE-I or ARB	111 (49.1)
β-blocker	82 (36.3)
CCB	114 (50.4)
Statin	151 (66.8)
DM drugs	68 (30.1)
Laboratory data
WBC, /μL	6,200 (5,000–7,300)
Hb, g/dL	13.9±1.6
Albmin, g/dL	4.2 (3.9–4.4)
LDL-C, mg/dL	94 (75–116)
HDL-C, mg/dL	54 (48–65)
TG, mg/dL	121 (81–172)
Creatinine, mg/dL	0.85 (0.70–0.98)
eGFR, mL/min/1.73 m2	65.6 (55.6–74.4)
Glucose, g/mL	114 (101–140)
HbA1c, %	6.0 (5.7–6.7)
BNP, pg/mL	34.7 (17.1–90.9)
CRP, mg/dL	0.08 (0.04–0.20)
Angiographic characteristics
Minimal lumen diameter, mm	1.77 (1.51–2.08)
Reference vessel diameter, mm	2.64 (2.27–2.99)
% stenosis diameter, %	31.0 (21.5–39.8)
Lesion length, mm	9.7 (7.6–12.3)
TTE findings
IVSd	11.0 (10.1–11.9)
PWd	10.6 (9.9–11.5)
LVDd	45.6 (42.2–49.3)
LVDs	29.0 (26.8–32.5)
LV mass	173 (147–211)
LVEF	65.0 (58.8–69.0)
TR PG	20 (15–24)
E/e′	10.5 (8.3–13.0)
Physiological parameters and indices
Pa at rest, mmHg	89 (81–98)
Pa at hyperemia, mmHg	77 (69–88)
Pd at rest, mmHg	83 (75–93)
Pd at hyperemia, mmHg	68 (60–78)
Tmn at rest, sec	0.78 (0.53–1.12)
Tmn at hyperemia, sec	0.24 (0.18–0.35)
FFR	0.88 (0.85–0.91)
CFR	3.06 (1.93–4.50)
b-IMR	68.6 (45.1–98.0)
IMR	17.1 (12.4–24.4)
CFR ≤2.5, n (%)	85 (37.6)
b-IMR ≤47.1, n (%)	62 (27.4)
IMR ≥25, n (%)	53 (23.5)

ACE-I, angiotensin-converting enzyme inhibitor; ARB, angiotensin-receptor blocker; b-IMR, basal index of microcirculatory resistance; BNP, B-type natriuretic peptide; BMI, body mass index; BSA, body surface area; CCB, calcium-channel blocker; CFR, coronary flow reserve; CRP, C-reactive protein; DM, diabetes mellitus; eGFR, estimated glomerular filtration rate; FFR, fractional flow reserve; Hb, hemoglobin; HbA1c, glycated hemoglobin; HDL-C, high-density lipoprotein cholesterol; IMR, index of microcirculatory resistance; IVSd, interventricular septum thickness; LDL-C, low-density lipoprotein cholesterol; LVDd, left ventricular diameter at end-diastole; LVDs, left ventricular diameter at endsystole; LVEF, left ventricular ejection fraction; PWd, left ventricular posterior wall thickness; Pa, mean aortic pressure; Pd, mean distal coronary pressure; TG, triglyceride; Tmn, mean transit time; TR PG, tricuspid regurgitation peak gradient; TTE, transthoracic echocardiography; WBC, white blood cell.

Table 2.

Correlation Between Physiological Parameters and Clinical Variables

	b-IMR		IMR		CFR
	Correlation coefficient	P value	Correlation coefficient	P value	Correlation coefficient	P value
b-IMR			0.535	<0.001	0.541	<0.001
IMR	0.535	<0.001			−0.315	<0.001
CFR	0.541	<0.001	−0.315	<0.001
Age	−0.241	<0.001	−0.002	0.97	−0.276	<0.001
Female sex	−0.130	0.050	−0.030	0.65	−0.106	0.11
Height	0.161	0.016	−0.019	0.77	0.161	0.016
Weight	0.148	0.026	0.039	0.56	0.095	0.15
BMI	0.071	0.29	0.057	0.40	0.005	0.94
BSA	0.172	0.010	0.017	0.80	0.136	0.042
Hypertension	0.000	1.00	0.105	0.11	−0.058	0.39
Hyperlipidemia	−0.184	0.006	−0.169	0.011	−0.055	0.41
Diabetes mellitus	−0.111	0.097	−0.078	0.24	−0.016	0.81
Current smoker	−0.005	0.94	−0.060	0.37	0.016	0.81
History of smoking	0.067	0.32	−0.042	0.53	0.062	0.36
Prior myocardial infarction	0.049	0.47	0.086	0.20	−0.053	0.43
History of coronary revascularization	0.058	0.39	0.016	0.82	0.054	0.42
Prior cerebral infarction	−0.029	0.66	0.037	0.58	−0.087	0.19
History of heart failure	−0.038	0.57	0.050	0.46	−0.112	0.094
Medications
ACE-I or ARB	−0.002	0.97	0.046	0.49	−0.055	0.41
β-blocker	0.067	0.31	0.163	0.014	−0.098	0.14
CCB	−0.041	0.54	−0.014	0.83	0.005	0.94
Statin	−0.176	0.008	−0.134	0.045	−0.053	0.43
DM drugs	−0.132	0.048	−0.078	0.24	−0.039	0.56
Laboratory data
WBC	−0.111	0.096	−0.023	0.73	−0.042	0.53
Hb	0.234	<0.001	0.092	0.17	0.175	0.008
Albumin	0.101	0.13	0.050	0.46	0.090	0.18
LDL-C	0.017	0.80	0.051	0.45	0.008	0.90
HDL-C	0.005	0.94	−0.018	0.79	0.115	0.086
TG	−0.052	0.44	−0.071	0.29	−0.005	0.94
Creatinine	0.050	0.46	0.007	0.91	−0.007	0.92
eGFR	0.045	0.50	0.016	0.81	0.068	0.31
Glucose	−0.138	0.046	−0.138	0.046	−0.017	0.81
HbA1c	−0.156	0.021	−0.100	0.14	−0.081	0.23
BNP	−0.032	0.63	0.194	0.004	−0.256	<0.001
CRP	−0.150	0.024	−0.065	0.33	−0.132	0.047
TTE findings
IVSd	0.035	0.60	0.125	0.063	−0.069	0.31
PWDd	0.013	0.85	0.147	0.037	−0.124	0.079
LVDd	0.125	0.064	0.050	0.46	0.045	0.51
LVDs	0.100	0.14	0.034	0.62	0.024	0.72
LV mass	0.122	0.083	0.079	0.26	0.021	0.77
LVEF	−0.079	0.24	−0.008	0.90	−0.029	0.67
TR PG	−0.106	0.12	0.113	0.097	−0.286	<0.001
E/e′	−0.144	0.034	0.086	0.21	−0.241	<0.001

Abbreviations as in Table 1.

Clinical Outcomes and the Physiological Indices of Coronary Microcirculation

During the 2-year follow-up (median follow-up, 788 days [IQR: 628–983]), 12 (5.3%) primary endpoints were observed, including 6 deaths and 9 cases of HF (3 cases experienced both heart failure and death). The 6 deaths comprised 1 cardiovascular death, 4 deaths due to malignant diseases, and 1 sudden death. Of those with HF, 6 (66.7%) had preserved ejection fraction (>50%). The secondary endpoint occurred in 21 (9.3%) patients, comprising 1 cardiovascular death, 3 cases of acute coronary syndrome, 13 coronary revascularizations, 2 cerebral infarctions, and 8 endovascular revascularizations. The details of the occurrence of coronary and endovascular revascularizations are shown in the Supplementary Files. The ROC curve analysis indicated that the optimal cutoff value for b-IMR to predict the primary endpoint was 47.1 U, which had a sensitivity of 83.3%, specificity of 75.7%, and area under the curve of 0.794 (Figure 1A); a total of 62 patients (27.4%) had a b-IMR value below the threshold. However, b-IMR was not associated with the secondary endpoint (P=0.35) (Figures 1B,2B). Kaplan-Meier curve analysis demonstrated that patients with b-IMR values ≤47.1 U had a significantly worse event-free survival for the primary endpoint (χ²=21.178; P<0.001) (Figure 2A). Regarding other microcirculation assessment indices, low CFR (≤2.5) had prognostic value for both endpoints (primary endpoint: χ²=11.401, P=0.001; secondary endpoint: (χ²=6.015; P=0.014) (Figure 3A,B), and high hyperemic microvascular resistance (IMR; ≥25 U) was associated only with the secondary endpoint (χ²=4.420; P=0.036) (Figure 3C,D). Table 3 presents the results of the C-statistics, NRI and IDI analyses conducted to assess the prognostic value of adding physiological indices to the clinical baseline model. Factors associated with the primary endpoint, identified by univariate Cox regression analysis, are listed in Supplementary Table 1. From these factors, CRP and hemoglobin levels were selected to construct the baseline Clinical Model. We first compared Clinical Model 1, which included CFR, with the baseline model to assess the prognostic impact of CFR. Although the C-statistic did not reach statistical significance, CFR showed incremental prognostic efficacy for the primary endpoint (NRI: 1.132, P<0.001; IDI 0.056, P<0.001) Then, we compared Clinical Model 2, which was created by adding b-IMR to Clinical Model 1, with Clinical Model 1 to evaluate the additional prognostic benefit of b-IMR. Adding b-IMR to Clinical Model 1, which already included CFR, further improved the prognostic value, as demonstrated by significant improvements in both NRI (1.014, P<0.001) and IDI (0.033, P=0.034).

Figure 1.

Receiver operating characteristic curve analysis of basal microvascular resistance (b-IMR) for predicting the primary and secondary endpoints. The area under the curve (AUC) for the primary endpoint demonstrates a significant predictive value (A), whereas that for the secondary endpoint is not significant (B).

Figure 2.

Kaplan-Meier plots of the primary and secondary endpoints for patients with and without abnormal values for basal microvascular resistance (b-IMR). The primary endpoint, comprising the incidence of all-cause death and heart failure, is significantly different between patients with low and high b-IMR values (P<0.001) (A), but b-IMR does not significantly predict the secondary endpoint, which includes the incidence of cardiovascular death, acute coronary syndrome, any coronary revascularization, cerebral infarction, and peripheral vascular events (B).

Figure 3.

Kaplan-Meier plots of the primary and secondary endpoints for patients with and without abnormal values of coronary flow reserve (CFR) and the index of microcirculatory resistance (IMR). Patients with low CFR showed a significant higher incidence of both endpoints (A,B), whereas high IMR was associated with the occurrence of the secondary endpoint but not the primary endpoint (C,D).

Table 3.

Predictive Performance of Clinical Models With CFR and b-IMR for Primary Endpoint

Model	C-statistic	P value	NRI	P value	IDI	P value
Clinical Model (reference model)*	0.798		Ref.		Ref.
Clinical Model 1 (Clinical Model + CFR)	0.877	0.14	1.132	<0.001	0.056	<0.001
Clinical Model 2 (Clinical Model 1 + b-IMR)	0.891	0.47	1.014	<0.001	0.033	0.034

*Clinical Model = CRP + Hb levels. IDI, Integrated Discrimination Improvement; NRI, Net Reclassification Improvement. Other abbreviations as in Table 1.

Discussion

Our study results revealed that lower b-IMR was significantly associated with worse clinical outcomes, as were several adverse factors and comorbidities including aging, anemia, dyslipidemia, diabetes mellitus, increased inflammation, and diastolic dysfunction. We observed that low b-IMR was significantly associated with an increased incidence of death and HF, but was not significantly associated with atherosclerotic events such as adverse coronary events, cerebral infarction, and peripheral vascular events, during a short-term follow-up. This finding is in contrast to that of IMR, which showed an association with the occurrence of atherosclerotic events but not hard endpoints. Furthermore, CFR was indicative of both endpoints. Our results suggest that b-IMR may be a more specific marker of the short-term risk of death and HF compared with other metrics such as CFR, and thus has potential for risk stratification in patients with abnormal coronary microcirculation but without functional coronary stenosis.

Abnormal Basal Microvascular Tone as an Endotype of CMD

The abnormal coronary microcirculatory condition termed CMD has been of clinical interest for investigating myocardial ischemia in patients without functional coronary stenosis. CMD involves various pathogenic mechanisms leading to functional and/or structural alterations in the coronary microvasculature.^7,19–21 CMD, which is mainly diagnosed by reduced CFR, has been linked to death, HF, and adverse cardiovascular events.^10–15,22 In recent years, an abnormally low coronary microvascular tone at rest has been increasingly recognized as an important endotype of CMD, not just as an indicator of poor health conditions and elevated myocardial work.^6,8,9 A recent study by Rahman et al demonstrated the different pathophysiological characteristics of 2 endotypes of CMD based on low CFR with and without elevated hyperemic microvascular resistance.⁶ A low CFR accompanied by high hyperemic microvascular resistance is considered indicative of a structural alteration in the coronary microvasculature that limits coronary flow during increased demand. On the other hand, a low CFR without an increase in microvascular resistance is characterized by high resting coronary flow resulting from a low basal microvascular tone. That study suggested a higher basal metabolic requirement without an elevation of myocardial work underlies this abnormal resting microcirculatory condition. One possible explanation for abnormal resting metabolic requirements could be impaired myocardial efficiency, such as increased myocardial stiffness, which requires higher oxygen consumption for a given level of myocardial work.^7,20 Another possible mechanism might be ineffective myocardial perfusion, such as advanced heterogeneous microcirculation, leading to functional arteriovenous shunting.²³ Considering these pathophysiological backgrounds, a low b-IMR might indicate advanced deterioration in the myocardium and microcirculation that cannot be assessed during hyperemic testing. Therefore, b-IMR could reflect different aspects of coronary microcirculation from those assessed by indices of microcirculation requiring induction of hyperemia such as CFR and IMR.

Factors Associated With Low b-IMR

To clarify the characteristics associated with low b-IMR, we compared clinical factors between patients with b-IMR values above and below the 47.1 cutoff for the primary endpoint, as detailed in the Supplementary Table 2. In line with previous studies, patients with lower b-IMR values were older, showed an increased prevalence of hyperlipidemia, and had elevated E/e′, along with deteriorated conditions such as anemia and elevated levels of inflammation.^2,7,14 We found no significant difference in the severity of epicardial disease (FFR: 0.88±0.04 for b-IMR >47.1 vs. 0.88±0.04 for b-IMR ≤47.1), which suggests that the utility of b-IMR in estimating cardiovascular outcomes might be independent of the severity of epicardial artery stenosis. Logistic regression analysis identified hyperlipidemia, elevated fasting blood glucose, decreased hemoglobin levels, and elevated E/e′ as independent predictors of low b-IMR values below the primary endpoint cutoff (Table 4). Notably, the association between metabolic disorders, such as hyperlipidemia and diabetes mellitus, and higher resting coronary flow, which is indicative of low microvascular resistance at rest, has been repeatedly reported.^5,24 Many of these comorbidities are also common risk factors for HF with preserved ejection fraction (HFpEF).²² Studies using swine models have demonstrated the adverse cascade of increased oxidative stress and inflammation caused by metabolic disorders leading to CMD and myocardial stiffness.^7,20 They suggested that such unfavorable conditions could lead to impaired myocardial efficiency, resulting in higher oxygen consumption and increased resting flow, and could underlie the pathophysiology of HFpEF. Consistent with their findings, in the present study we found an association of metabolic disorders and diastolic dysfunction with low resting microvascular tone, which indirectly suggests that an abnormally low b-IMR might represent an inefficient resting myocardial metabolic state or impaired autoregulation that could be linked with worsened patient health and adverse clinical outcomes.

Table 4.

Univariate and Multivariate Logistic Regression Analyses to Predict the Factors of Low b-IMR Value (≤47.1)

	Univariate logistic regression			Multivariate logistic regression
	OR	95% CI	P value	OR	95% CI	P value
Age	1.039	1.006–1.073	0.019
Height	0.966	0.933–1.000	0.048
Hyperlipidemia	2.647	1.401–5.002	0.003	2.880	1.371–6.051	0.005
Hb	0.803	0.665–0.968	0.021	0.775	0.622–0.966	0.023
Albumin	0.473	0.256–0.874	0.017
BNP	1.001	1.000–1.003	0.098
Glucose	1.006	1.000–1.012	0.061	1.009	1.001–1.016	0.020
HbA1c	1.369	0.997–1.879	0.052
CRP	1.228	0.970–1.554	0.089
DM drugs	1.722	0.930–3.192	0.084
E/e′	1.094	1.030–1.161	0.003	1.115	1.035–1.201	0.004

CI, confidence interval; OR, odds ratio. Other abbreviations as in Table 1.

The factors associated with abnormal IMR values differed from those related to b-IMR; higher IMR values were associated with higher BNP levels and increased left ventricular thickness (Table 2). Therefore, b-IMR might reflect different aspects of coronary microvascular conditions, as well as a different prognostic efficacy, from those of IMR.

Predictive Efficacy of b-IMR as a Marker of Death and HF

A previous study by van de Hoef et al indicated that reduced basal microvascular resistance is linked to high mortality rates in patients with chronic coronary syndrome.²⁵ In line with their study, our results showed that low b-IMR independently predicted death and HF in the patients without functional coronary stenosis. Notably, patients with low b-IMR exhibited a significantly higher incidence of HF than those with normal b-IMR (χ²=13.018; P<0.001). Furthermore, all patients who died had b-IMR values below the cutoff value; a significant proportion of all-cause deaths in our cohort was attributed to malignant diseases. Consistent with previous findings, our results imply that a markedly reduced resting microvascular tone might be associated with a deteriorating cardiac condition as well as overall worsened general health status.⁶ Recently, Rajai et al reported that reduced CFR is associated with a higher incidence of cancer in patients with nonobstructive coronary artery disease.²⁶ Our result seem to align with their findings. However, it is crucial to note that the specific mechanisms linking low CFR (or more precisely, its components, such as resting or hyperemic flow) to the progression of malignant diseases are still unclear.

In our findings, b-IMR was not associated with atherosclerotic vascular events during a short-term follow-up (Figure 2B). Although a longer observational period is needed to confirm these findings, b-IMR appears to be a more specific marker than CFR of high-risk patients prone to death or HF. In addition, b-IMR might provide additional information on CFR to more effectively discriminate patients at high risk for death or HF. Figure 4 shows that patients below the cutoff values for both CFR and b-IMR had the highest risk of the primary endpoint, and those above these cutoff values had a favorable prognosis.

Figure 4.

Prognostic efficacy of combined assessments using coronary flow reserve (CFR) and basal microcirculatory resistance (b-IMR). Kaplan-Meier plots illustrate the effect of combining assessments of CFR and b-IMR on patient outcomes. Patients with low values of both CFR and b-IMR exhibit the highest frequency of the primary endpoint compared with other groups (A). In contrast, b-IMR did not provide additional prognostic information for the secondary endpoint beyond that provided by CFR (B).

In addition, addressing whether Tmn or Pd at rest contributes more significantly to b-IMR and prognostication, we additionally explored the effect of each component on b-IMR. Tmn at rest significantly correlated with b-IMR (Spearman’s rho: 0.952, 95% confidence interval (CI) 0.938 to 0.963, P<0.001), unlike Pd at rest (Spearman’s rho: 0.100, 95% CI −0.136 to 0.227, P=0.14, Supplementary Figure 2). Although the area under the curve (AUC) for prognostic efficacy of b-IMR for was slightly higher, no statistically significant difference between these 2 factors in prognostication was observed (AUC for b-IMR: 0.794, 95% CI 0.736 to 0.845; AUC for Tmn at rest: 0.758, 95% CI 0.696 to 0.812, Supplementary Figure 3). Among the indices including b-IMR, Tmn at rest, and Pd, b-IMR demonstrated the highest χ² value, indicating a stronger prognostic efficacy than either Tmn or Pd at rest alone (χ² for b-IMR: 21.178 vs. χ² for Tmn at rest: 10.039 vs. χ² for Pd at rest: 4.790, Supplementary Figure 4). Our results indicate that b-IMR, by integrating both Tmn and Pd measures, offered a more comprehensive assessment of risk, effectively identifying patients with a higher risk of adverse outcomes.

Our findings suggest that b-IMR has the potential to be a useful tool for identifying patients at a higher risk of adverse outcomes, such as death and HF. Those with low b-IMR might benefit from more intensive monitoring and therapeutic interventions. Further research should focus on exploring potential treatment strategies that could ameliorate this abnormal resting microcirculatory condition and should assess whether improving this condition can lead to better patient outcomes.

Study Limitations

First, the study was retrospective and observational and included patients with various cardiovascular diseases. In the present study, 38% (86 of 226) had a history of coronary revascularization and 20 had a % diameter stenosis >50%, although all patients showed FFR >0.80 and did not require coronary revascularization at enrollment. With the inclusion criteria of “FFR >0.80”, our study aimed to explore the prognostic value of b-IMR in individuals without functionally significant coronary artery stenosis, regardless of the degree of angiographic stenosis. This inclusion criterion enabled a more clinically relevant exploration of the role of microvascular dysfunction in patients considered to have no significant coronary artery stenosis but who might still be at risk due to microvascular issues. However, this heterogeneity may have affected the generalizability of the findings. As a response to that concern, we conducted separate analyses for the prognostic efficacy of b-IMR in a subset of patients without a history of coronary revascularization (N=140). Interestingly, the results were quite similar to those of the original total cohort (AUC 0.792, the best cutoff value of b-IMR ≤47.1, P<0.001 by ROC curve analysis; log-rank χ² 19.662; P<0.001 by Kaplan-Meier curve analysis; Supplementary Figure 5).

Recently, several novel indices such as the Resistive Reserve Ratio (RRR) have been introduced to evaluate coronary circulation.²⁷ RRR, the ratio of basal to hyperemic microvascular resistance, may provide predictive capabilities superior to CFR. RRR showed similar prognostication to CFR, but no superior prognostic efficacy for the primary endpoint compared with b-IMR (see Supplementary Figure 6). The present study predominantly involved Japanese patients, which raises concerns about the applicability of the b-IMR cutoff value to diverse ethnic or demographic groups. Further studies are required to test our hypothesis in general populations. It is essential to validate these findings in a broader patient population to confirm their universal applicability. In addition, the follow-up was relatively short. Although our findings suggested that significantly low b-IMR can predict short-term adverse events, long-term follow-up is necessary to fully understand the prognostic value and implications for patient outcomes. Further investigations, including prospective studies and multicenter trials with diverse and large patient populations, are warranted to confirm our findings and enhance the robustness and generalizability of the results.

Conclusions

Abnormally low microvascular tone was associated with factors related to ineffective myocardial metabolism and adverse health conditions. Our findings suggested that b-IMR could serve as an informative marker of patients without functional coronary stenosis who are at increased risk of death or HF. Further research is necessary to elucidate the role of b-IMR in the clinical management of patients with abnormal coronary microcirculation, including its potential as a target for therapeutic intervention.

Disclosure of Interest

T.M. has received fees from Abbott Medical Japan for educational events. T.W. has received speaker fee from Abbott Medical Japan, Boston Scientific Japan and Philips Japan.

IRB Information

Ethical approval was obtained from all institutional review boards, and the name of the principal ethics committee was the Ethics Committees of Yokosuka Kyosai Hospital (approval number 23-59).

Supplementary Files

Please find supplementary file(s);

https://doi.org/10.1253/circj.CJ-24-0022

References

• 1.   Pries AR, Badimon L, Bugiardini R, Camici PG, Dorobantu M, Duncker DJ, et al. Coronary vascular regulation, remodelling, and collateralization: Mechanisms and clinical implications on behalf of the Working Group on coronary pathophysiology and microcirculation. Eur Heart J 2015; 36: 3134–3146.
• 2.   Johnson NP, Gould KL, De Bruyne B. Autoregulation of coronary blood supply in response to demand. J Am Coll Cardiol 2021; 77: 2335–2345.
• 3.   Duncker DJ, Koller A, Merkus D, Canty JM Jr. Regulation of coronary blood flow in health and ischemic heart disease. Prog Cardiovasc Dis 2015; 57: 409–422.
• 4.   Camici PG, Crea F. Coronary microvascular dysfunction. N Engl J Med 2007; 356: 830–840.
• 5.   Picchi A, Limbruno U, Focardi M, Cortese B, Micheli A, Boschi L, et al. Increased basal coronary blood flow as a cause of reduced coronary flow reserve in diabetic patients. Am J Physiol Heart Circ Physiol 2011; 301: H2279–H2284.
• 6.   Rahman H, Demir OM, Khan F, Ryan M, Ellis H, Mills MT, et al. Physiological stratification of patients with angina due to coronary microvascular dysfunction. J Am Coll Cardiol 2020; 75: 2538–2549.
• 7.   van de Wouw J, Sorop O, van Drie RWA, van Duin RWB, Nguyen ITN, Joles JA, et al. Perturbations in myocardial perfusion and oxygen balance in swine with multiple risk factors: A novel model of ischemia and no obstructive coronary artery disease. Basic Res Cardiol 2020; 115: 21.
• 8.   Boerhout CKM, de Waard GA, Lee JM, Mejia-Renteria H, Lee SH, Jung JH, et al. Prognostic value of structural and functional coronary microvascular dysfunction in patients with non-obstructive coronary artery disease; from the multicentre international ILIAS registry. EuroIntervention 2022; 18: 719–728.
• 9.   Schindler TH, Fearon WF, Pelletier-Galarneau M, Ambrosio G, Sechtem U, Ruddy TD, et al. Myocardial perfusion PET for the detection and reporting of coronary microvascular dysfunction: A JACC: Cardiovascular Imaging Expert Panel Statement. JACC Cardiovasc Imaging 2023; 16: 536–548.
• 10.   Kelshiker MA, Seligman H, Howard JP, Rahman H, Foley M, Nowbar AN, et al; Coronary Flow Outcomes Reviewing Committee. Coronary flow reserve and cardiovascular outcomes: A systematic review and meta-analysis. Eur Heart J 2022; 43: 1582–1593.
• 11.   Pepine CJ, Anderson RD, Sharaf BL, Reis SE, Smith KM, Handberg EM, et al. Coronary microvascular reactivity to adenosine predicts adverse outcome in women evaluated for suspected ischemia results from the National Heart, Lung and Blood Institute WISE (Women’s Ischemia Syndrome Evaluation) study. J Am Coll Cardiol 2010; 55: 2825–2832.
• 12.   Gdowski MA, Murthy VL, Doering M, Monroy-Gonzalez AG, Slart R, Brown DL. Association of isolated coronary microvascular dysfunction with mortality and major adverse cardiac events: A systematic review and meta-analysis of aggregate data. J Am Heart Assoc 2020; 9: e014954.
• 13.   Kato S, Saito N, Kirigaya H, Gyotoku D, Iinuma N, Kusakawa Y, et al. Impairment of coronary flow reserve evaluated by phase contrast cine-magnetic resonance imaging in patients with heart failure with preserved ejection fraction. J Am Heart Assoc 2016; 5: e002649.
• 14.   Taqueti VR, Solomon SD, Shah AM, Desai AS, Groarke JD, Osborne MT, et al. Coronary microvascular dysfunction and future risk of heart failure in patients with preserved ejection fraction. Eur Heart J 2018; 39: 840–849.
• 15.   Lee JM, Jung JH, Hwang D, Park J, Fan Y, Na SH, et al. Coronary flow reserve and microcirculatory resistance in patients with intermediate coronary stenosis. J Am Coll Cardiol 2016; 67: 1158–1169.
• 16.   Fearon WF, Balsam LB, Farouque HM, Caffarelli AD, Robbins RC, Fitzgerald PJ, et al. Novel index for invasively assessing the coronary microcirculation. Circulation 2003; 107: 3129–3132.
• 17.   De Bruyne B, Pijls NH, Smith L, Wievegg M, Heyndrickx GR. Coronary thermodilution to assess flow reserve: Experimental validation. Circulation 2001; 104: 2003–2006.
• 18.   Pijls NH, De Bruyne B, Smith L, Aarnoudse W, Barbato E, Bartunek J, et al. Coronary thermodilution to assess flow reserve: Validation in humans. Circulation 2002; 105: 2482–248.
• 19.   Crea F, Montone RA, Rinaldi R. Pathophysiology of coronary microvascular dysfunction. Circ J 2022; 86: 1319–1328.
• 20.   Sorop O, Heinonen I, van Kranenburg M, van de Wouw J, de Beer VJ, Nguyen ITN, et al. Multiple common comorbidities produce left ventricular diastolic dysfunction associated with coronary microvascular dysfunction, oxidative stress, and myocardial stiffening. Cardiovasc Res 2018; 114: 954–964.
• 21.   Hokimoto S, Kaikita K, Yasuda S, Tsujita K, Ishihara M, Matoba T, et al; Japanese Circulation Society and Japanese Association of Cardiovascular Intervention and Therapeutics and Japanese College of Cardiology Joint Working Group. JCS/CVIT/JCC 2023 Guideline Focused Update on diagnosis and treatment of vasospastic angina (coronary spastic angina) and coronary microvascular dysfunction. Circ J 2023; 87: 879–936.
• 22.   Srivaratharajah K, Coutinho T, deKemp R, Liu P, Haddad H, Stadnick E, et al. Reduced myocardial flow in heart failure patients with preserved ejection fraction. Circ Heart Fail 2016; 9: e002562.
• 23.   Pries AR, Reglin B. Coronary microcirculatory pathophysiology: Can we afford it to remain a black box? Eur Heart J 2017; 38: 478–488.
• 24.   Takei Y, Tomiyama H, Tanaka N, Yamashina A, Chikamori T. Association between insulin resistance, oxidative stress, sympathetic activity, and coronary microvascular function in patients with early-stage impaired glucose metabolism. Circ J 2022; 86: 866–873.
• 25.   van de Hoef TP, Bax M, Damman P, Delewi R, Hassell ME, Piek MA, et al. Impaired coronary autoregulation is associated with long-term fatal events in patients with stable coronary artery disease. Circ Cardiovasc Interv 2013; 6: 329–335.
• 26.   Rajai N, Ahmad A, Toya T, Sara JD, Herrmann J, Lerman LO, et al. Coronary microvascular dysfunction is an independent predictor of developing cancer in patients with non-obstructive coronary artery disease. Eur J Prev Cardiol 2023; 30: 209–216.
• 27.   Toya T, Ahmad A, Corban MT, Özcan I, Sara JD, Sebaali F, et al. Risk stratification of patients with nonobstructive coronary artery disease using resistive reserve ratio. J Am Heart Assoc 2021; 10: e020464.