Abstract
Microvascular angina (MVA), resulting from coronary microvascular dysfunction (CMD), is increasingly recognized as a contributor to adverse cardiovascular outcomes. However, the clinical factors for MVA remain unclear. In this retrospective case-control study, we investigated the clinical factors of MVA in 92 patients with MVA and 391 age- and sex-matched control participants without chest pain or cardiovascular diseases. All patients underwent coronary angiography including an acetylcholine (ACh)-provocation test and a coronary flow reserve (CFR) measurement. MVA was diagnosed based on the Coronary Vasomotion Disorders International Study Group (COVADIS) criteria. Multivariate logistic regression analysis showed mildly elevated hemoglobin A1c (HbA1c) (i.e., prediabetes), low high-density lipoprotein cholesterol (HDL-C), and low hemoglobin (Hgb) levels as independent factors significantly associated with MVA. Mean corpuscular volume (MCV) was also significantly lower in MVA patients. No significant differences in clinical characteristics were found between microvascular spasm (MVS) and MVA without MVS. MVS was more common in women than in men. In conclusion, mildly elevated HbA1c level, and low levels of HDL-C and Hgb may serve as modifiable risk markers for MVA. The study findings may aid in the management of MVA.
Keywords: Microvascular angina, Coronary microvascular dysfunction, Microvascular spasm, Glycated hemoglobin, High-density lipoprotein cholesterol, Hemoglobin
Introduction
Microvascular angina (MVA) due to coronary microvascular dysfunction (CMD) is a form of ischemia with non-obstructive coronary artery disease (INOCA). MVA has been a recent focus of clinical research because MVA has emerged as an important factor associated with adverse cardiovascular outcomes [1–6].
Previous studies have found that smoking, hypertension (HT), diabetes mellitus (DM), and dyslipidemia (DLP) can be associated with MVA [7–10]. In contrast, other studies have found that DM was uncommon in patients with angina and non-obstructive coronary artery disease (CAD) [11, 12]. Thus, the association between conventional cardiovascular risk factors and MVA has not yet been established [4].
The purpose of this study was to clarify the clinical factors of MVA in a case-control study.
Materials and methods
Study patients and definition of MVA
We retrospectively screened 5246 consecutive patients who underwent coronary angiography (CAG) for suspected angina pectoris in Kumamoto University Hospital between January 1993 and December 2015. Among them, we excluded 3092 patients for the following reasons: incompleteness of data due to the 2016 Kumamoto earthquakes (n = 157), epicardial coronary stenosis ≥50% (n = 2285), and not performed acetylcholine (ACh) provocation test (n = 650). Among the remaining 2154 patients, we further excluded 1998 patients for the following reasons: coronary spastic angina (vasospastic angina) (n = 1000), and symptoms unlikely to be cardiac in origin (n = 998). Finally, we enrolled 92 patients with MVA (39 men, 53 women) after excluding 64 patients with incompleteness of data due to the earthquakes (Fig. 1). All vasoactive drugs, including calcium channel blockers, nitrates, nicorandil, alpha-adrenergic blockers, and beta-adrenergic blockers were discontinued ≥ 48 h before CAG, which included an ACh-provocation test and a coronary flow reserve (CFR) measurement by intravenous infusion of adenosine triphosphate (ATP). Every study patient underwent CAG in the morning while fasting. After the ACh provocation test, isosorbide dinitrate (ISDN) was infused into the left and right coronary arteries, followed by examining the epicardial coronary artery for stenosis.
Fig. 1.
Flow chart of patient enrollment. ACh, acetylcholine; CFR, coronary flow reserve
MVA was diagnosed based on satisfying all the criteria for MVA proposed by the Coronary Vasomotion Disorders International Study Group (COVADIS) [13], as follows: (1) myocardial ischemia symptoms, (2) non-obstructive CAD (< 50% stenosis) by CAG, (3) objective evidence of myocardial ischemia (i.e., chest pain and ischemic ECG change) with non-epicardial coronary spasm by an ACh-provocation test, (4) CFR <2.0 by invasive measurement or microvascular spasm (MVS) (defined as reproduction of symptoms, ischemic ECG shifts but non-epicardial coronary spasm during an ACh-provocation test).
The study exclusion criteria were as follows: obstructive CAD (≥50% stenosis), decompensated heart failure, cardiomyopathy, severe valvular heart disease, and a previous history of coronary artery revascularization. Patients were also excluded for a diagnosis of epicardial coronary spasm that was based on JCS/CVIT/JCC 2023 Guideline Focused Update on Diagnosis and Treatment of Vasospastic Angina (Coronary Spastic Angina) and Coronary Microvascular Dysfunction by the Japanese Circulation Society [1]. In addition, patients were excluded for other factors as follows: undergoing hemodialysis, advanced chronic obstructive pulmonary disease, advanced collagen disease, active inflammatory disease, severe liver dysfunction, and/or neoplasms at the time of enrollment.
The control group enrolled 391 participants (166 men, 225 women) who were sex- and age-matched with MVA patients and had no history of chest pain or cardiovascular diseases (e.g., myocardial infarction, angina, cardiomyopathy, valvular heart disease or heart failure) among those who participated from the health-screening program at the Japanese Red Cross Kumamoto Health Center between 2006 and 2012. Medical histories were obtained through face-to-face interviews. Several previous case-control studies on cardiovascular diseases have enrolled control groups from health screening program participants who did not have a history of chest pain or cardiovascular disease [14, 15]. According to this method, we enrolled the 391 participants as the controls.
Ethics approval
This study was conducted in accordance with the principles contained in the Declaration of Helsinki. The protocol of our study was approved by the ethics committee of the Faculty of Life Sciences, Kumamoto University, and the Japanese Red Cross Kumamoto Hospital Health Care Center (approval number: 473). We obtained a signed informed consent from each patient and participant. This study is registered at the University Hospital Medical Information Network (UMIN) Clinical Trials Registry (UMIN 000043834). Opt-out materials are available through the website: https://kumadai-junnai.com/archives/clinical.
Measurement of coronary flow reserve
Before the ACh provocation test, we inserted a 0.014-inch guidewire that was equipped with a Doppler velocity probe (FloWire; Philips Volcano, San Diego, CA) into the left anterior descending coronary artery. After the ACh provocation test was followed by the administration of intracoronary ISDN, ATP (150 µg/kg/min) was administered via the central vein until maximal hyperemia was achieved to allow the calculation of hemodynamic parameters. When maximal coronary hyperemia was attained, the FloWire was used to measure the CFR, as previously described [16].
Definition of risk factors for cardiovascular diseases
The conventional risk factors for cardiovascular diseases were defined as follows: current smoking, HT (blood pressure ≥ 140/90 mmHg or taking anti-hypertensive drugs), DLP (low-density lipoprotein cholesterol [LDL-C] ≥ 140 mg/dL [3.6 mmol/L], high-density lipoprotein cholesterol [HDL-C] < 40 mg/dL [1.0 mmol/L], triglycerides [TG] ≥ 150 mg/dL [1.7 mmol/L] or taking lipid-lowering drugs), and DM (fasting plasma glucose levels ≥ 126 mg/dL [7.0 mmol/L], > 200 mg/dL [11.1 mmol/L] during a 75-g oral glucose tolerance test, or taking anti-diabetic drugs). In regard to serum glycosylated hemoglobin A1c (HbA1c) level, until the end of March 2012, the measurements proposed by the Japan Diabetes Society (JDS) were applied for study patients; whereas starting in April 2012, the measurements described by the National Glycohemoglobin Standardization Program (NGSP) were adopted. In our study, the HbA1c levels (JDS) measured until March 2012 were adjusted to the NGSP levels (i.e., HbA1c [NGSP] [%] = HbA1c [JDS] [%] + 0.4) [17].
Statistical analysis
Continuous values were expressed as means ± standard deviation (SD), whereas data with a skewed distribution were expressed as medians (interquartile range). Continuous variables were compared by two-tailed unpaired t-tests. A Mann-Whitney U test was performed for continuous variables with a skewed distribution. Frequencies of clinical variables stratified into two groups were compared by the Fisher exact test.
Clinical parameters were assessed by univariate and multivariable logistic regression analyses for significant association with MVA. The multivariable logistic regression analysis was conducted to evaluate parameters that were identified as statistically significant (p <0.05) by univariate logistic regression analysis, with the exclusion of redundant and/or missing data on the variables. The variables ‘DM’ and ‘DLP’ were not included in the multivariate logistic regression analysis because of the strong correlation between ‘DM’ and HbA1c levels and between ‘DLP’ and HDL-C levels, respectively. The variables ‘current smoking’ and ‘proteinuria’ were not included in the multivariable logistic regression analysis because there were only a few patients who were current smokers or had proteinuria (Tables 3 and 4, and 5).
Table 3.
Univariate and multivariate logistic regression analysis for MVA
| Univariate | Multivariate | |||
|---|---|---|---|---|
| Odds ratio (95%CI) | p value | Odds ratio (95%CI) | p value | |
| BMI (kg/m2) | 1.05 (0.98–1.12) | 0.29 | ||
| Current smoking | 2.36 (1.23–4.52) | 0.010 | 1.62 (0.60–4.35) | 0.34 |
| HT | 1.62 (1.03–2.57) | 0.038 | 1.20 (0.64–2.26) | 0.57 |
| DM | 2.00 (1.11–3.61) | 0.022 | Not selected * | |
| DLP | 0.62 (0.39–0.98) | 0.039 | Not selected * | |
| eGFR (per 1 mL/min/1.73m2) | 1.00 (0.99–1.02) | 0.85 | ||
| Uric acid (per 1 mg/dL) | 1.11 (0.95–1.31) | 0.20 | ||
| FPG (per 1 mg/dL) | 0.99 (0.98–1.01) | 0.32 | ||
| HbA1c (per 1%) | 2.29 (1.67–3.15) | < 0.001 | 1.96 (1.38–2.79) | <0.001 |
| LDL-C (per 10 mg/dL) | 0.92 (0.84–0.99) | 0.037 | 0.85 (0.76–0.95) | 0.005 |
| HDL-C (per 10 mg/dL) | 0.60 (0.50–0.71) | < 0.001 | 0.59 (0.47–0.73) | <0.001 |
| TG (per 10 mg/dL) | 1.02 (0.99–1.05) | 0.14 | ||
| CRP (per 0.1 mg/dL) | 1.05 (0.97–1.14) | 0.25 | ||
| WBC (per 1000/µL) | 1.20 (1.04–1.39) | 0.012 | 1.12 (0.89–1.40) | 0.33 |
| Hgb (per 1 g/dL) | 0.54 (0.45–0.67) | < 0.001 | 0.52 (0.40–0.68) | < 0.001 |
| Platelets (per 1 × 104/µL) | 1.01 (0.96–1.05) | 0.83 | ||
| Proteinuria | 9.61 (2.94–31.4) | < 0.001 | Not selected ** |
* The variables ‘DM’ and ‘DLP’ were not included in the multivariate logistic regression analysis because of the strong correlation between ‘DM’ and HbA1c levels and between ‘DLP’ and HDL-C levels, respectively. ** The variable ‘Proteinuria’ was not included in the multivariate logistic regression analysis because the number of patients with proteinuria was low (regarding these contents, see also Statistical analysis in Methods)
MVA, microvascular angina; CI, confidence interval; BMI, body mass index; HT, hypertension; DM, diabetes mellitus; DLP, dyslipidemia; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; HbA1c, hemoglobin A1c; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TG, triglyceride; CRP, C-reactive protein; WBC, white blood cell; Hgb, hemoglobin
Table 4.
Univariate and multivariate logistic regression analysis for MVA in men
| Univariate | Multivariate | |||
|---|---|---|---|---|
| Odds ratio (95%CI) | p value | Odds ratio (95%CI) | p value | |
| BMI (kg/m2) | 1.01 (0.89–1.14) | 0.92 | ||
| Current smoking | 1.63 (0.72–3.71) | 0.25 | ||
| HT | 1.72 (0.85–3.48) | 0.13 | ||
| DM | 1.39 (0.57–3.36) | 0.47 | ||
| DLP | 0.70 (0.34–1.41) | 0.31 | ||
| eGFR (per 1 mL/min/1.73m2) | 1.00 (0.98–1.03) | 0.72 | ||
| Uric acid (per 1 mg/dL) | 1.13 (0.87–1.46) | 0.36 | ||
| FPG (per 1 mg/dL) | 0.99 (0.98–1.01) | 0.57 | ||
| HbA1c (per 1%) | 1.75 (1.19–2.59) | 0.005 | 1.65 (1.06–2.56) | 0.026 |
| LDL-C (per 10 mg/dL) | 0.92 (0.80–1.02) | 0.10 | ||
| HDL-C (per 10 mg/dL) | 0.55 (0.40–0.74) | < 0.001 | 0.56 (0.39–0.82) | 0.002 |
| TG (per 10 mg/dL) | 1.04 (0.99–1.08) | 0.085 | ||
| CRP (per 0.1 mg/dL) | 1.01 (0.92–1.12) | 0.82 | ||
| WBC (per 1000/µL) | 1.15 (0.94–1.39) | 0.18 | ||
| Hgb (per 1 g/dL) | 0.47 (0.33–0.65) | < 0.001 | 0.54 (0.37–0.79) | 0.001 |
| Platelets (per 1 × 104/µL) | 0.99 (0.93–1.06) | 0.84 | ||
| Proteinuria | 8.11 (1.52–43.2) | 0.014 | Not selected * |
* The variable ‘Proteinuria’ was not included in the multivariate logistic regression analysis because the number of patients with proteinuria was low (regarding the content, see also Statistical analysis in Methods)
MVA, microvascular angina; CI, confidence interval; BMI, body mass index; HT, hypertension; DM, diabetes mellitus; DLP, dyslipidemia; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; HbA1c, hemoglobin A1c; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TG, triglyceride; CRP, C-reactive protein; WBC, white blood cell; Hgb, hemoglobin
Table 5.
Univariate and multivariate logistic regression analysis for MVA in women
| Univariate | Multivariate | |||
|---|---|---|---|---|
| Odds ratio (95%CI) | p value | Odds ratio (95%CI) | p value | |
| BMI (kg/m2) | 1.07 (0.98–1.16) | 0.12 | ||
| Current smoking | 9.45 (2.28–39.1) | 0.002 | Not selected * | |
| HT | 1.56 (0.85–2.86) | 0.15 | ||
| DM | 2.22 (0.94–5.23) | 0.069 | ||
| DLP | 0.56 (0.31–1.03) | 0.061 | ||
| eGFR (per 1 mL/min/1.73m2) | 1.00 (0.98–1.02) | 0.94 | ||
| Uric acid (per 1 mg/dL) | 1.20 (0.90–1.60) | 0.21 | ||
| FPG (per 1 mg/dL) | 0.99 (0.97–1.01) | 0.35 | ||
| HbA1c (per 1%) | 3.47 (1.97–6.11) | < 0.001 | 2.53 (1.44–4.45) | 0.001 |
| LDL-C (per 10 mg/dL) | 0.92 (0.82–1.04) | 0.19 | ||
| HDL-C (per 10 mg/dL) | 0.58 (0.47–0.73) | < 0.001 | 0.65 (0.49–0.86) | 0.003 |
| TG (per 10 mg/dL) | 1.01 (0.97–1.06) | 0.63 | ||
| CRP (per 0.1 mg/dL) | 1.23 (1.01–1.50) | 0.042 | 0.87 (0.60–1.26) | 0.47 |
| WBC (per 1000/µL) | 1.30 (1.04–1.62) | 0.024 | 1.50 (1.03–2.20) | 0.037 |
| Hgb (per 1 g/dL) | 0.39 (0.28–0.55) | < 0.001 | 0.41 (0.25–0.65) | <0.001 |
| Platelets (per 1 × 104/µL) | 1.02 (0.96–1.08) | 0.60 | ||
| Proteinuria | 12.4 (2.18–70.2) | 0.005 | Not selected * |
* The variables ‘current smoking’and ‘Proteinuria’ were not included in the multivariate logistic regression analysis because the numbers of patients with current smoking or proteinuria were low (regarding these contents, see also Statistical analysis in Methods)
MVA, microvascular angina; CI, confidence interval; BMI, body mass index; HT, hypertension; DM, diabetes mellitus; DLP, dyslipidemia; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; HbA1c, hemoglobin A1c; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TG, triglyceride; CRP, C-reactive protein; WBC, white blood cell; Hgb, hemoglobin
Stata version 18 (Stata Corp., College Station, TX, USA) and BellCurve for Excel, version 4.06 (Social Survey Research Information Co., Ltd., Tokyo, Japan) were used for statistical analysis. Statistical significance was defined as a p-value < 0.05.
Results
Clinical characteristics
Table 1 shows the clinical characteristics of 92 patients (39 men, 53 women) with MVA and 391 control participants (166 men, 225 women). The patients with MVA had significantly higher prevalence of current smoking, HT, and DM; lower prevalence of DLP; higher HbA1c; lower LDL-C and HDL-C; higher TG, CRP, and WBC; lower Hgb levels; and a significantly higher prevalence of proteinuria than the control participants. The HbA1c level was significantly higher in MVA patients with non-DM than in controls participants with non-DM (5.8 ± 0.4% vs. 5.3 ± 0.3%, p <0.001).
Table 1.
Clinical characteristics of MVA patients and control participants
| All (n = 483) |
MVA (n = 92) |
Control (n = 391) |
p value | |
|---|---|---|---|---|
| Age (years) | 63.9 ± 10.7 | 63.2 ± 12.1 | 64.0 ± 10.4 | 0.51 |
| Sex (women) (%) | 278 (58%) | 53 (58%) | 225 (58%) | 1.00 |
| BMI (kg/m2) | 22.9 ± 3.2 | 23.3 ± 3.7 | 22.9 ± 3.1 | 0.20 |
| Current smoking (%) | 48 (10%) | 16 (17%) | 32 (8%) | 0.012 |
| HT (%) | 190 (39%) | 45 (49%) | 145 (37%) | 0.044 |
| DM (%) | 64 (13%) | 19 (21%) | 45 (12%) | 0.026 |
| DLP (%) | 257 (53%) | 40 (43%) | 217 (55%) | 0.048 |
| eGFR (mL/min/1.73m2) | 74 ± 14 | 74 ± 18 | 74 ± 13 | 0.85 |
| Uric acid (mg/dL) | 5.2 ± 1.4 | 5.3 ± 1.5 | 5.1 ± 1.3 | 0.20 |
| FPG (mg/dL) | 99 ± 19 | 98 ± 24 | 100 ± 18 | 0.32 |
| HbA1c (%) | 5.7 ± 0.9 | 6.2 ± 1.0 | 5.5 ± 0.8 | <0.001 |
| HbA1c (%) in non-DM patients | 5.4 ± 0.4 | 5.8 ± 0.4 | 5.3 ± 0.3 | <0.001 |
| LDL-C (mg/dL) | 121 ± 28 | 116 ± 33 | 122 ± 26 | 0.036 |
| HDL-C (mg/dL) | 67 ± 18 | 57 ± 17 | 70 ± 17 | <0.001 |
| TG (mg/dL) | 94 (68–127) | 107 (81–140) | 90 (68–122) | 0.004 |
| CRP (mg/dL) | 0.05 (0.03–0.10) | 0.07 (0.03–0.16) | 0.05 (0.03–0.10) | 0.009 |
| WBC (/µL) | 5326 ± 1487 | 5685 ± 1595 | 5244 ± 1451 | 0.011 |
| RBC (×104/µL) | 449 ± 40 | 429 ± 44 | 454 ± 37 | < 0.001 |
| Hgb (g/dL) | 14.0 ± 1.3 | 13.2 ± 1.4 | 14.2 ± 1.2 | < 0.001 |
| Platelets (×104/µL) | 21.0 ± 4.9 | 21.3 ± 5.8 | 22.2 ± 4.8 | 0.83 |
| Proteinuria (%) | 12/413 (3%) | 7/58 (12%) | 5/355 (1%) | < 0.001 |
| CFR | – | 2.4 ± 1.0 (n = 55) | No data | |
| CFR <2.0 (%) | – | 20/55 (36%) | No data | |
| Medications (on admission) | ||||
| ACE-I or ARB (%) | – | 28 (30%) | No data | – |
| CCB (%) | – | 46 (50%) | No data | – |
| Nitrate (%) | – | 18 (20%) | No data | – |
| Beta-blocker (%) | – | 21 (23%) | No data | – |
| Statin (%) | – | 27 (29%) | No data | – |
Data are number of patients (%), means ± standard deviation (SD), and medians (interquartile range). MVA, microvascular angina; BMI, body mass index; HT, hypertension; DM, diabetes mellitus; DLP, dyslipidaemia; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; HbA1c, hemoglobin A1c; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TG, triglyceride; CRP, C-reactive protein; WBC, white blood cell; RBC, red blood cell; Hgb, hemoglobin; CFR, coronary flow reserve; ACE-I, angiotensin converting enzyme inhibitor; ARB, angiotensin II receptor blocker; CCB, calcium channel blocker
Table 2 shows the clinical characteristics of MVA patients and control participants stratified by sex. The men patients with MVA had significantly higher HbA1c, lower HDL-C, higher TG, and lower Hgb levels; and a higher prevalence of proteinuria than the control participants. The women patients with MVA had significantly higher HbA1c, lower HDL-C, higher TG, higher CRP, higher WBC, and lower Hgb levels; and significantly higher prevalence of current smoking and proteinuria than the control participants. The HbA1c level was significantly higher in MVA patients with non-DM than in controls with non-DM in both men and women (Men; 5.6 ± 0.4% vs. 5.2 ± 0.2%, p < 0.001: Women; 5.9 ± 0.3% vs. 5.3 ± 0.3%, p <0.001).
Table 2.
Clinical characteristics of MVA patients and control participants in men and women
| Men (n = 205) | Women (n = 278) | |||||
|---|---|---|---|---|---|---|
| MVA (n = 39) |
Control (n = 166) |
p value | MVA (n = 53) |
Control (n = 225) |
p value | |
| Age (years) | 61.4 ± 13.9 | 61.5 ± 12.3 | 0.96 | 64.6 ± 10.5 | 65.9 ± 8.3 | 0.32 |
| BMI (kg/m2) | 23.6 ± 3.5 | 23.5 ± 2.6 | 0.92 | 23.2 ± 3.9 | 22.4 ± 3.3 | 0.12 |
| Current smoking (%) | 10 (26%) | 29 (17%) | 0.26 | 6 (11%) | 3 (1%) | 0.002 |
| HT (%) | 21 (54%) | 67 (40%) | 0.15 | 24 (45%) | 78 (35%) | 0.16 |
| DM (%) | 10 (26%) | 26 (16%) | 0.16 | 9 (17%) | 19 (8%) | 0.076 |
| DLP (%) | 16 (41%) | 83 (50%) | 0.37 | 24 (45%) | 134 (60%) | 0.066 |
| eGFR (mL/min/1.73m2) | 73 ± 19 | 72 ±14 | 0.72 | 74 ± 17 | 75 ± 13 | 0.94 |
| Uric acid (mg/dL) | 6.2 ± 15 | 5.9 ± 1.3 | 0.36 | 4.7 ± 1.2 | 4.5 ± 1.0 | 0.21 |
| FPG (mg/dL) | 101 ± 27 | 104 ± 22 | 0.57 | 95 ± 21 | 97 ± 14 | 0.35 |
| HbA1c (%) | 6.1 ± 1.0 | 5.5 ± 0.9 | 0.002 | 6.3 ± 1.0 | 5.5 ± 0.7 | < 0.001 |
| HbA1c (%) in non-DM patients | 5.6 ± 0.4 | 5.2 ± 0.2 | < 0.001 | 5.9 ± 0.3 | 5.3 ± 0.3 | < 0.001 |
| LDL-C (mg/dL) | 112 ± 38 | 121 ± 28 | 0.098 | 118 ± 29 | 123 ± 25 | 0.19 |
| HDL-C (mg/dL) | 52 ± 14 | 63 ± 15 | < 0.001 | 60 ± 19 | 74 ± 18 | < 0.001 |
| TG (mg/dL) | 121 (81–161) | 98 (71–134) | 0.037 | 102 (76–132) | 83 (66–112) | 0.032 |
| CRP (mg/dL) | 0.07 (0.03–0.12) | 0.05 (0.03–0.10) | 0.15 | 0.08(0.03–0.19) | 0.05 (0.03–0.10) | 0.024 |
| WBC (/µL) | 5979 ± 1721 | 5577 ± 1637 | 0.17 | 5461 ± 1469 | 4999 ± 1245 | 0.022 |
| RBC (×104/µL) | 446 ± 32 | 473 ± 37 | < 0.001 | 417 ± 48 | 440 ± 31 | < 0.001 |
| Hgb (g/dL) | 14.0 ± 1.4 | 15.0 ± 1.1 | < 0.001 | 12.6 ± 1.1 | 13.5 ± 0.9 | < 0.001 |
| Platelets (×104/µL) | 20.3 ± 5.8 | 20.5 ± 5.2 | 0.84 | 22.1 ± 5.7 | 21.7 ± 4.5 | 0.60 |
| Proteinuria (%) | 3/21 (14%) | 3/149 (2%) | 0.026 | 4/37 (11%) | 2/206 (1%) | 0.006 |
| CFR | 1.9±0.9 (n = 17) | No data | – | 2.7±0.9 (n = 38) | No data | – |
| CFR <2.0 (%) | 11/17 (65%) | No data | – | 9/38 (24%) | No data | – |
| Medications (on admission) | ||||||
| ACE-I or ARB (%) | 18 (46%) | No data | – | 10 (19%) | No data | – |
| CCB (%) | 17 (44%) | No data | – | 29 (55%) | No data | – |
| Nitrate (%) | 9 (23%) | No data | – | 9 (17%) | no data | – |
| Beta-blocker (%) | 16 (41%) | No data | – | 5 (9%) | No data | – |
| Statin (%) | 10 (25%) | No data | – | 17 (32%) | No data | – |
Data are number of patients (%), means ± standard deviation (SD), and medians (interquartile range). MVA, microvascular angina; BMI, body mass index; HT, hypertension; DM, diabetes mellitus; DLP, dyslipidemia; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; HbA1c, hemoglobin A1c; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TG, triglyceride; CRP, C-reactive protein; WBC, white blood cell; RBC, red blood cell; Hgb, hemoglobin; CFR, coronary flow reserve; ACE-I, angiotensin converting enzyme inhibitor; ARB, angiotensin II receptor blocker; CCB, calcium channel blocker
Univariate and multivariate logistic regression analysis of characteristics associated with MVA
Table 3 shows the results of univariate and multivariate logistic regression analysis for the association of variables with MVA. Univariate logistic regression analysis showed that current smoking, HT, DM, DLP, HbA1c, LDL-C, HDL-C, WBC, Hgb, and proteinuria were all significantly associated with MVA. Multivariate logistic regression analysis showed that HbA1c, LDL-C, HDL-C, and Hgb were significantly associated with MVA.
Table 4 shows the results of univariate and multivariate logistic regression analysis for MVA in men. Univariate logistic regression analysis showed that HbA1c, HDL-C, Hgb, and proteinuria were all significantly associated with MVA. Multivariate logistic regression analysis showed that HbA1c, HDL-C, and Hgb were significantly associated with MVA.
Table 5 shows the results of univariate and multivariate logistic regression analysis for MVA in women. Univariate logistic regression analysis showed that current smoking, HbA1c, HDL-C, CRP, WBC, Hgb, and proteinuria were all significantly associated with MVA. Multivariate logistic regression analysis showed that HbA1c, HDL-C, WBC, and Hgb were significantly associated with MVA.
Erythrocyte indices of MVA in men and women
Table 6 shows the erythrocyte indices between patients with MVA and control participants stratified by sex. Men with MVA had significantly lower Hgb level and mean corpuscular volume (MCV) than the control men. Women with MVA had significantly lower Hgb levels, MCV, and lower serum iron level than the control women.
Table 6.
Erythrocyte indices of MVA in men and women
| Men (n = 205) | Women (n = 278) | |||||
|---|---|---|---|---|---|---|
| MVA (n = 39) |
Control (n = 166) |
p value | MVA (n = 53) |
Control (n = 225) |
p value | |
| RBC (×104/µL) | 447 ± 32 | 473 ± 37 | < 0.001 | 417 ± 48 | 440 ± 31 | < 0.001 |
| Hematocrit (%) | 41.0 ± 3.7 | 44.6 ± 2.8 | < 0.001 | 37.8 ± 3.2 | 41.1 ± 2.6 | < 0.001 |
| Hgb (g/dL) | 14.0 ± 1.4 | 15.0 ± 1.1 | < 0.001 | 12.6 ± 1.1 | 13.5 ± 0.9 | < 0.001 |
| MCV (fL) | 91.8 ± 4.0 | 95.0 ± 3.6 | < 0.001 | 92.0 ± 4.0 | 93.8 ± 3.9 | < 0.001 |
| Serum iron (µg/dL) | 109 ± 67 | 122 ± 43 | 0.19 | 91 ± 33 | 110 ± 31 | < 0.001 |
| Ferritin (ng/mL) | 168 ± 121 | 127 ± 93 | 0.13 | 83 ± 80 | 75 ± 55 | 0.62 |
Data are number of patients (%), means ± standard deviation (SD). MVA, microvascular angina; Hgb, hemoglobin; MCV, mean corpuscular volume
Clinical characteristics of patients with MVS among those with MVA
Table 7 shows the clinical characteristics of patients with MVS among 92 patients with MVA. No significant differences in clinical characteristics were found between MVS and MVA without MVS. MVS was more common in women than in men.
Table 7.
Clinical characteristics of patient with microvascular spasm among 92 patients with MVA
| MVS (n = 72) |
MVA without MVS (n = 20) |
p value | |
|---|---|---|---|
| Age (years) | 62.8 ± 11.9 | 64.6 ± 12.9 | 0.58 |
| Sex (women), (%) | 44 (61%) | 9 (45%) | 0.21 |
| BMI (kg/m2) | 23.3 ± 3.7 | 23.3 ± 4.1 | 0.91 |
| Current smoking (%) | 15 (21%) | 1 (5%) | 0.18 |
| HT (%) | 38 (53%) | 7 (35%) | 0.21 |
| DM (%) | 16 (22%) | 3 (15%) | 0.76 |
| DLP (%) | 32 (44%) | 8 (40%) | 0.80 |
| eGFR (mL/min/1.73m2) | 75 ± 19 | 71 ± 15 | 0.40 |
| Uric acid (mg/dL) | 5.4 ± 1.5 | 5.0 ± 1.7 | 0.24 |
| FPG (mg/dL) | 97 ± 25 | 100 ± 19 | 0.60 |
| HbA1c (%) | 6.3 ± 1.1 | 6.0 ± 0.7 | 0.30 |
| HbA1c (%) in non-DM patients | 5.8 ± 0.4 | 5.7 ± 0.4 | 0.70 |
| LDL-C (mg/dL) | 117 ± 35 | 110 ± 28 | 0.40 |
| HDL-C (mg/dL) | 56 ± 18 | 59 ± 16 | 0.57 |
| TG (mg/dL) | 110 (85–137) | 107 (74–145) | 0.89 |
| CRP (mg/dL) | 0.09 (0.04–0.20) | 0.03 (0.03–0.13) | 0.17 |
| WBC (/µL) | 5567 ± 1363 | 6099 ± 2223 | 0.19 |
| RBC (×104/µL) | 429 ± 45 | 431 ± 41 | 0.84 |
| Hgb (g/dL) | 13.1 ± 1.4 | 13.5 ± 1.3 | 0.38 |
| Platelets (×104/µL) | 21.7 ± 5.6 | 20.0 ± 6.5 | 0.26 |
| Proteinuria (%) | 6/46 (13%) | 1/12 (8%) | 1.00 |
| Medications (on admission) | |||
| ACE-I or ARB (%) | 20 (28%) | 8 (40%) | 0.41 |
| CCB (%) | 36 (50%) | 10 (50%) | 1.00 |
| Nitrate (%) | 13 (18%) | 5 (25%) | 0.53 |
| Beta-blocker (%) | 15 (21%) | 6 (30%) | 0.38 |
| Statin (%) | 18 (25%) | 9 (45%) | 0.10 |
Data are number of patients (%), means ± standard deviation (SD), and medians (interquartile range). MVS, microvascular spasm; MVA, microvascular angina; BMI, body mass index; HT, hypertension; DM, diabetes mellitus; DLP, dyslipidemia; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; HbA1c, hemoglobin A1c; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TG, triglyceride; CRP, C-reactive protein; WBC, white blood cell; RBC, red blood cell; Hgb, hemoglobin; ACE-I, angiotensin converting enzyme inhibitor; ARB, angiotensin II receptor blocker; CCB, calcium channel blocker
Discussion
This case-control study investigated the clinical characteristics of patients with MVA. The major findings were as follows: (1) mildly elevated HbA1c, and low HDL-C and Hgb levels were significantly associated with MVA (Table 3); (2) MCV was significantly lower in men and women patients with MVA than in control men and women, respectively (Table 6); (3) no significant differences in clinical characteristics were found between MVS and MVA without MVS.
This study showed that an mildly elevated HbA1c level was significantly associated with MVA (Tables 1 and 2, and 3). This association remained significant in sex-stratified analyses (Tables 4 and 5). The mean HbA1c levels in MVA patients were 6.2 ± 1.0%, 6.1 ± 1.0%, 6.3 ± 1.0% in all patients, men, women, respectively, indicating these levels were prediabetes [18] (Tables 1 and 2). Some reports have shown that diabetic microvascular diseases, such as retinopathy or nephropathy, can precede the appearance of type 2 diabetes in patients with prediabetes or hyperglycemia [19, 20]. In the present study, the HbA1c level was significantly higher in MVA patients with non-DM than in controls with non-DM (Tables 1 and 2). These findings suggested that mildly elevated HbA1c levels, such as prediabetes, could be critically involved in the development of MVA. In previous reports, hyperglycemia prior to the appearance of DM may contribute to microvascular diseases by impaired vascular endothelium [21, 22]. Microvascular diseases associated with mildly elevated HbA1c levels may represent systemic phenomena that extend beyond pathologic manifestations such as nephropathy to the coronary circulation. Therefore, a mildly elevated HbA1c level (i.e., prediabetes) may be a critical marker for MVA.
This study showed that a low Hgb level was significantly associated with MVA. This association remained significant in sex-stratified analyses (Tables 3 and 4, and 5). A previous paper reported that reduced hemoglobin could predict adverse outcomes in patients with ischemic heart disease not only through reduced oxygen delivery but also through reduced nitric oxide availability [23]. In this study, although the Hgb levels did not meet the criterion for anemia, Hgb and MCV levels were significantly lower in patients with MVA than in control participants, in both men and women (Table 6). The serum iron level was significantly lower in the MVA women patients than in the control women. By contrast, the difference between the ferritin levels in MVA women patients and control women was not significant. Based on these observations, hematopoietic dysfunction caused by an iron disorder could be associated with MVA, although the etiology could not be clarified by the available data in this study.
This study found that a low HDL-C level was significantly associated with MVA. This association remained significant in sex-stratified analyses (Tables 3 and 4, and 5). Low HDL-C is an established risk factor not only for macrovascular events, but also for microvascular diseases in diabetic patients [24]. The underlying mechanisms involved in the microvascular and macrovascular diseases in diabetes have been found to be the association of low HDL-C levels with increased oxidative stress, increased inflammation, and dysfunctional endothelium [25]. Other reports have shown that HDL-C could be a factor involved in reduced CFR [7, 26]. Based on these findings altogether, low HDL-C could be associated with MVA.
In this study, of 92 MVA patients, 72 patients (78%) had MVS. No significant differences in clinical characteristics were found between MVS and MVA without MVS. Our finding that MVS was more common in women than in men was consistent with the findings of previous studies [27–29]. In our study, the women patients with MVS were aged 63.2 ± 10.9 years (data not shown), suggesting a predominance of postmenopausal estrogen deficiency. Estrogen can modulate coronary microvascular vasomotor function [22]. There are several types of MVA, which include MVS (increased vasoconstriction), impaired vasodilator capacity, and structural alterations (luminal narrowing, vascular remodeling, etc.) [1]. The different types of MVA may be sex specific. Further studies on the association of MVA subtypes with the sex of study patients are needed.
CMD leading to MVA can play an important role not only in angina, but also in various cardiovascular diseases such as acute coronary syndrome, left ventricular hypertrophy, Takotsubo syndrome, heart failure [22, 30–35]. Patients with anginal symptoms and angiographically nonobstructive CAD currently have large burdens of cardiovascular disease, including repeated hospitalizations and CAG, which also indicate that the economic burden of MVA is increasing [36]. The majority of MVA patients remain undertreated because of the lack of evidence-based data. This study showed that mildly elevated HbA1c level (i.e., prediabetes) and low HDL-C and Hgb levels were significantly associated with MVA. Given no specific treatment for MVA, the management of modifiable risk factors, including conventional risk factors, can play an important role in the management of MVA [4, 22]. Therefore, our observational findings may be helpful for the management of MVA.
Our study is hypothesis-generating and cannot prove causation because of observational study. We emphasize that the associations observed between mildly elevated HbA1c (prediabetes), low HDL-C, lower hemoglobin/MCV and MVA require confirmation in prospective cohorts and mechanistic studies. On the other hand, our findings suggest that these factors may impair coronary microvascular function through endothelial dysfunction, oxidative stress, and reduced nitric oxide bioavailability, as previously described [21–26]. Most prior MVA cohorts focused on established diabetes or classic risk factors; our finding that subclinical metabolic and hematological abnormalities (prediabetes and subtle hemoglobin/iron changes below diagnostic thresholds) may associate with MVA adds a new dimension to risk stratification. Further prospective and mechanistic studies are warranted.
Study limitations
This study has several limitations. First, it was a single-center study with a relatively small sample size. Second, it was a retrospective study. Third, our results may not be applicable to patients who are outside of the age range we studied. Forth, we did not have any information on the medications taken by the control participants. Moreover, we could not completely rule out that a control participant might have asymptomatic CAD. Potential misclassification would bias the results toward the null. Fifth, the FlowWire could theoretically influence the coronary artery tone because the it was positioned in the LAD during the ACh provocation test. Sixth, we did not measure CFR in all the study patients and all the control participants. Further analyses and recalibrations of a larger and independent study population are needed.
Conclusions
A mildly elevated HbA1c level (i.e., prediabetes), and low levels of HDL-C and Hgb may serve as modifiable risk markers for MVA. The study findings may aid in the management of MVA.
Acknowledgements
We thank Michiyo Saito, MT, at our institution for her excellent technical assistance.
Author contributions
Satoru Suzuki: Writing—original draft, Conceptualization, Data curation, Formal analysis, Investigation. Kenshi Yamanaga: Writing—original draft, Conceptualization, Data curation, Formal analysis, Investigation. Masanobu Ishii: Writing—riginal draft, Conceptualization, Data curation, Formal analysis, Investigation. Erika Matsumoto: Data curation, Investigation. Naoto Kuyama: Conceptualization, Data curation, Investigation. Kyoko Hirakawa: Conceptualization, Data curation, Investigation. Noriaki Tabata: Conceptualization, Data curation, Investigation. Tomonori Akasaka: Data curation, Investigation. Koichiro Fujisue: Conceptualization, Data curation, Investigation. Shinsuke Hanatani: Conceptualization, Data curation, Investigation. Yuichiro Arima: Conceptualization, Data curation, Investigation. Hiroki Usuku: Conceptualization, Data curation, Formal analysis, Investigation. Eiichiro Yamamoto: Writing—review and editing, Investigation. Kentaro Oniki: Conceptualization, Data curation, Formal analysis, Investigation. Hirofumi Soejima: Conceptualization, Data curation, Investigation. Junji Saruwatari: Conceptualization, Data curation, Formal analysis, Investigation. Hiroaki Kawano: Conceptualization, Data curation, Investigation. Hideaki Jinnouchi: Data curation, Investigation. Koichi Kaikita: Conceptualization, Supervision. Hirofumi Yasue: Writing—review and editing, Conceptualization, Supervision. Hisao Ogawa: Conceptualization, Supervision. Kenichi Tsujita: Writing—review and editing, Conceptualization, Data curation, Investigation. Project administration, Supervision.
Satoru Suzuki, Kenshi Yamanaga, and Masanobu Ishii contributed equally to this manuscript.
Funding
Open Access funding provided by Kumamoto University. This research receive no grant from any funding agency in the public, commercial, or not-for-profit sectors.
Data availability
The data that support the findings of this study are available upon reasonable request.
Declarations
Conflict of interest
Dr. Hisao Ogawa has received remuneration for lectures from AstraZeneca, Bayer Yakuhin, Ltd., Daiichi Sankyo Co., Ltd., Eisai, Kowa Pharmaceutical Co. Ltd., Takeda Pharmaceutical Co., Ltd., Teijin Pharma, JSR, Nxera Pharma. Dr. Koichi Kaikita received grants from Grants-in-Aid for Scientific Research (23K07534) from the Ministry of Education, Culture, Sports, Science and Technology of Japan; received remuneration for lecture from Bayer Yakuhin, Ltd., Daiichi-Sankyo Co., Ltd., Novartis Pharma AG., Otsuka Pharmaceutical Co., Ltd., Bristol-Myers K.K., and Kowa Pharmaceutical Co. Ltd.; received trust research/joint research funds from Bayer Yakuhin, Ltd., and Daiichi-Sankyo Co., Ltd.; and received scholarship fund from Abbott Medical Co., Ltd. Dr. Kenichi Tsujita has received remuneration for lectures from Abbott Medical Co., Ltd, Amgen K.K., Bayer Yakuhin, Ltd., Daiichi Sankyo Co., Ltd., Kowa Pharmaceutical Co. Ltd., Nippon Boehringer Ingelheim Co., Ltd., Novartis Pharma K.K., Otsuka Pharmaceutical Co.,Ltd., Pfizer Japan Inc., Takeda Pharmaceutical Co., Ltd., and TERUMO Co, Ltd.; has received trust research/joint research funds from Bayer Yakuhin, Ltd., Bristol-Myers K.K., Daiichi Sankyo Co., Ltd., MOCHIDA PHARMACEUTICAL CO., LTD., Novo Nordisk Pharma Ltd., and PRA Health Sciences.; has received scholarship fund from Abbott Medical Co., Ltd., ITI Co.,Ltd., Boehringer Ingelheim Japan, Otsuka Pharmaceutical Co.,Ltd., and Boston Scientific Japan K.K.; has received Affiliation with Endowed Department from Abbott Japan Co., Ltd., Boston Scientific Japan K.K., Fides-one, Inc., GM Medical Co., Ltd., ITI Co.,Ltd., Kaneka Medix Co., Ltd., NIPRO CORPORATION, TERUMO Co, Ltd., Philips Japan Ltd., Getinge Group Japan K.K., Orbusneich Medical K. K, Abbott Medical Co., Ltd., BIOTRONIK JAPAN, INC, Boston Scientific Japan K.K., Fukuda Denshi Co., Ltd., Japan Lifeline Co.,Ltd., Medtoronic Japan Co., Ltd., Nippon Boehringer Ingelheim Co., Ltd., and NIPRO CORPORATION. The remaining authors have no competing interests of declare.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Satoru Suzuki, Kenshi Yamanaga and Masanobu Ishii have contributed equally to this work.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available upon reasonable request.