Secondary Logo

Journal Logo

Original articles

Relationships between components of metabolic syndrome and coronary intravascular ultrasound atherosclerosis measures in women without obstructive coronary artery disease

the NHLBI-Sponsored Women’s Ischemia Syndrome Evaluation Study

Khaliq, Asmaa; Johnson, B. Deliad; Anderson, R. Davida; Bavry, Anthony A.a,c; Cooper-DeHoff, Rhonda M.a,b; Handberg, Eileen M.a; Bairey Merz, C. Noele; Nicholls, Stephen J.f,g; Nissen, Stevenf; Pepine, Carl J.a

Author Information
Cardiovascular Endocrinology: June 2015 - Volume 4 - Issue 2 - p 45-52
doi: 10.1097/XCE.0000000000000049
  • Free



Obesity is increasing in prevalence as about seven of 10 adult Americans are either obese (BMI>30 kg/m2) or overweight (BMI 25–29.9 kg/m2) 1. Among adults, the prevalence of grade 3 obesity (BMI≥40) is almost double in women (8.3%) versus men (4.4%). Among women aged at least 60 years, obesity prevalence rose from 31.5% in 2003–2004 to 38.1% in 2011–2012 2. Obese and overweight patients, particularly women with abdominal obesity, are at high risk for developing diabetes and ischemic heart disease (IHD) 3. Metabolic syndrome (MetS) has emerged as a health concern due to links with IHD 4, as has been described previously in the Women’s Ischemic Syndrome Evaluation (WISE) 5. Nevertheless, debate continues as to whether MetS, per se, is a distinct pathophysiologic entity or simply reflects an association of its component cardiovascular risk factors 6–8.

The present analysis assessed the relative contribution of MetS versus its individual components on intravascular ultrasound (IVUS) measures of coronary atherosclerosis in a cohort of women with symptoms/signs of ischemia but without obstructive coronary artery disease (CAD). The WISE is a National Heart, Lung and Blood Institute-sponsored prospective cohort study to improve the understanding of IHD in women 9. WISE and other studies have confirmed that many women referred for coronary angiography with signs and symptoms of suspected chronic stable IHD do not have obstructive CAD – about half of these women have so-called ‘normal coronary angiograms’ 9 and the remainder have only nonobstructive CAD 10. We and others have also found that these women, even in the absence of obstructive CAD, have an increased risk of adverse events 11–15. The exact mechanisms responsible, however, are not completely understood.

As opposed to the angiographic luminograms, IVUS provides a more comprehensive in-vivo assessment of atherosclerotic plaque. When utilized previously, in mostly men with ‘normal’ coronary angiograms, IVUS imaging has shown evidence of subclinical atherosclerosis. It is accepted that in the majority of patients with acute coronary syndrome, the culprit vessel often has relatively minor non-flow-limiting stenosis (<50%) 16,17. This finding has been seen more often in women than in men 18. We previously reported that IVUS imaging, in a subset of women with ischemic symptoms and ‘normal’ or nonobstructive CAD, identified a high prevalence of coronary atherosclerosis 19. The purpose of this analysis was to extend these observations to determine the impact of MetS relative to its individual components on IVUS measures of coronary atherosclerosis.



The WISE protocol, published in detail elsewhere 9, was approved by the local institutional review board at each participating center, and all women provided written informed consent. In addition, centers participating in the IVUS substudy had that protocol approved by local review boards and each participant provided additional informed consent.

Briefly, women were eligible if they were above 18 years of age and were undergoing a clinically indicated coronary angiogram as part of their regular medical care for symptoms and/or signs of myocardial ischemia. Major exclusion criteria included comorbid conditions that would compromise 1-year follow-up, pregnancy, contraindications to provocative diagnostic testing, cardiomyopathy, New York Heart Association class IV congestive heart failure, recent myocardial infarction, significant valvular or congenital heart disease, or a language barrier to questionnaire testing. Women with prior coronary angioplasty or coronary bypass surgery were excluded for this substudy.

After baseline clinical and laboratory data collection using standardized forms, the women underwent clinically indicated coronary angiography. Candidates for this substudy were eligible if angiography showed no evidence (≤20% diameter stenosis) or minimal evidence (>20% but <50% diameter stenosis) of CAD. Angiograms were assessed, masked to all other clinical data, by the WISE Coronary Angiographic Core Laboratory (Brown University) using quantitative and qualitative methods as described elsewhere 20.

Acquisition and analysis of IVUS images

IVUS was used to interrogate the proximal left anterior descending (LAD) (preferred site) or circumflex coronary artery if the LAD was technically inaccessible. Following intravenous heparin and intracoronary nitroglycerin, a 30 MHz, 2.6 Fr (0.87 mm) single element beveled IVUS transducer (Ultracross; Boston Scientific Scimed Inc., Maple Grove, Minnesota, USA) was advanced into the vessel over a guidewire, and the transducer was positioned distally. An automated pull-back device progressively withdrew the transducer at a speed of 0.5 mm/s. Images were obtained at 30 frames/s, stored on videotape, and then digitized for analysis in a core laboratory (Cleveland Clinic) by individuals masked to the clinical and angiographic data 19. Briefly, using the National Institutes of Health Image (version 1.62; National Institutes of Health public domain software, Bethesda, Maryland, USA), the operator performed a calibration by measuring 1 mm grid marks encoded in the image. The leading edge of the lumen and the external elastic membrane (EEM) were defined with the use of manual planimetry.

As described previously 19, for each woman, EEM volume, lumen volume, atheroma volume (difference between vessel and lumen volume), percent atheroma volume, percent vessel involvement (percentage of segments analyzed that contain atherosclerosis), and atherosclerosis (defined as plaque thickness ≥0.5 mm) were measured. Normal reference points with plaque thickness less than 0.5 mm that were adjacent to areas of atherosclerosis were used to determine vessel tapering and to calculate an expected vessel cross-sectional area (CSA) for each 1 mm diseased segment. Vessel and lumen volumes were calculated as the sum of their respective CSAs across all segments evaluated. Similarly, total atheroma volume was calculated as the sum of the differences between the EEM and lumen areas across all segments analyzed. Percent atheroma volume was calculated as atheroma volume/vessel volume times 100. All volumes were normalized for pull-back length. For each segment, the presence of atherosclerosis was defined as a maximum plaque thickness of at least 0.5 mm by IVUS. Percent vessel involvement was defined as the number of CSAs meeting criteria for atherosclerosis divided by the total number of CSAs analyzed.

From the standardized WISE demographic data forms, women were stratified according to the presence or absence of MetS at baseline, as defined by the National Cholesterol Education Program’s (NCEP) Adult Treatment Panel III criterion. Hence, participants were classified as having MetS if they fulfilled three or more of the following: (a) waist circumference of at least 88 cm (>35 inches); (b) triglycerides of at least 150 mg/dl; (c) HDL cholesterol less than 50 mg/dl; (d) blood pressure (BP) at least 130/85 mmHg; or (e) fasting glucose at least 100 mg/dl, per revised NCEP definition in concordance with American Diabetes Association criteria for impaired fasting glucose 21. Patients with or without MetS were compared with regard to clinical characteristics and the extent of coronary atherosclerosis by IVUS measures.

Statistical methods

Statistical analysis was performed with the SAS statistical software package (version 9.3; SAS Institute Inc., Cary, North Carolina, USA). Continuous and categorical variables were expressed as mean±SD and percentages, respectively. For univariate analysis comparing risk factors and IVUS measures in women with MetS versus without MetS, we used t-tests for continuous variables and χ2-analysis for categorical variables. For highly skewed variables, we show medians and interquartile ranges and used Kruskal–Wallis tests to compare differences.

For each IVUS measure, we performed stepwise forward linear regression analyses to evaluate MetS and its components as independent predictors. The MetS variables that were retained in the final model were then adjusted for other risk factors selected because they were significant univariate predictors of at least one of the IVUS measures. These included age, history of diabetes, family history of heart disease, history of dyslipidemia, ever smoking, and ever use of hormone replacement therapy. A P-value of less than 0.05 was considered statistically significant. Because of the small sample size, only significant independent predictors could be retained in the model.


There were 154 women who consented for the IVUS substudy. Fifty-four (35%) had CAD (>50% stenosis) by on-site angiogram readings, resulting in exclusion. The remaining 100 women without obstructive CAD were enrolled, and qualitative IVUS analysis for presence of atherosclerosis (yes/no) was available in 92, whereas quantitative analysis for IVUS measures of atherosclerosis was possible in 87 women. The primary reason for not being able to obtain a satisfactory recording was that the LAD and circumflex branches originated at acute angles prohibiting safe guidewire placement, or the vessels were too small to safely manipulate the IVUS transducer.

The pertinent clinical characteristics of the 87 women are summarized in Table 1 according to MetS status. Their mean age was 54±10 years. Of these, 31 (36%) had MetS and 56 did not. Over a sample pull-back length (mean 36±16 mm), 19 women (21%) had no evidence of atherosclerosis (e.g. plaque thickness <0.5 mm by IVUS). To adjust for pullbacks of differing lengths, ‘normalized atheroma volume’ was used in the current analyses. For the remaining 68 women (78%), the percent atheroma volume was 27±8% and the mean maximum plaque thickness was 0.53±0.22 mm. Figure 1 demonstrates the typical IVUS morphology in proximal LAD of a woman with no significant angiographic stenosis.

Table 1
Table 1:
Pertinent risk factors by metabolic syndrome status (means±SD, unless specified otherwise)
Fig. 1
Fig. 1:
Left coronary angiogram (top) and left anterior descending coronary artery (LAD) intravascular ultrasound images (bottom) from a 65-year-old woman with metabolic syndrome. Note plaque in the proximal LAD with maintenance of the lumen area. EEM, external elastic membrane.

In univarate analysis, IVUS measures of atherosclerosis were consistently larger in women with MetS versus without MetS, and differences were statistically significant for 60% (six of 10) of these measures (Table 2). As MetS is a composite variable, we also examined relationships between the specific MetS components and IVUS variables. Systolic BP and waist circumference and, to a lesser extent, HDL were significantly associated with several IVUS measures (data not shown). Specifically, systolic BP was significantly and positively associated with number of lesions [β (SE)=7.1 (2.6), P=0.009], mean maximum plaque [β (SE)=0.12 (0.05), P=0.011], atheroma volume [β (SE)=27.2 (11.5), P=0.020], percentage atheroma volume [β (SE)=0.05 (0.02), P=0.016], and mean internal CSA [β (SE)=0.83 (0.31), P=0.008]. Waist circumference was positively associated with atheroma volume [β (SE)=22.7 (10.7), P=0.034], mean EEM CSA [β (SE)=1.86 (0.75), P=0.015], and mean internal CSA [β (SE)=0.74 (0.28), P=0.011]. In the final multiple regression models, the association between MetS as a cluster and IVUS components became nonsignificant. However, after model adjustment, two components of MetS, systolic BP and waist circumference, were significantly and strongly associated with several IVUS measures of atherosclerosis and plaque burden (Table 3).

Table 2
Table 2:
Association between IVUS measures and metabolic syndrome (univariate analysis)
Table 3
Table 3:
Relationships of MetS cluster and MetS components with IVUS anatomy (multivariate analysis)

In addition, given the significant cross talk between diabetes and MetS, a sensitivity analysis excluding the women with diabetes (29% of the total cohort) was also conducted. Consistent with the prior analyses that included diabetes, women with MetS continued to have worse risk factors compared with those without MetS even though most of these differences (except BMI) did not reach statistical significance. Not surprisingly, the exceptions were those risk factors used to classify MetS. When excluding the women with diabetes, the women with MetS still had consistently higher IVUS measures, although the P-values were attenuated because of smaller numbers and high standard deviation resulting in diminished statistical power (Table 4).

Table 4
Table 4:
Relationships of MetS cluster and MetS components with IVUS anatomy excluding the women with diabetes


To the best of our knowledge, the current study is the first to analyze the relationship between MetS, its components and IVUS-derived measure of atherosclerotic burden in women with suspected ischemia, but without obstructive CAD. The major findings of our study follow: (a) the relationship between the MetS cluster and IVUS measures of coronary atherosclerosis is not significant in a multiple regression model, suggesting that the relationship is largely driven by individual MetS components rather than the cluster. These findings support our hypothesis that the MetS is a convenient clustering of risk factors, rather than a novel or an independent risk predictor. (b) Systemic hypertension was an independent predictor of IVUS-measured disease burden (as defined by number of lesions, percentage of lesions, atheroma volume, and percentage atheroma volume). (c) Larger waist circumference (i.e. abdominal obesity) was associated with EEM, internal elastic membrane, and luminal expansion, suggesting positive or adaptive remodeling. (d) In contrast, several risk factors, including diabetes/hyperglycemia and dyslipidemia (high-LDL cholesterol and low-HDL cholesterol), appeared less important than expected.

In recent years, investigators have used IVUS to study the correlation between the MetS and the morphological characteristics of atherosclerotic plaques with variable results 22–25. These studies largely focused on patients who had, or were undergoing, coronary intervention for severe obstructive CAD. The results from our study have important implications for understanding the relationship between MetS and major adverse cardiac events in this specific at-risk patient population. The concept of MetS evolved from the observation of a clustering of risk factors for CAD and diabetes in patients with abdominal obesity 26. However, it has not been conclusively shown that the impact of the syndrome cluster exceeds that of the sum of its parts. Several studies have shown that adverse outcomes appear to be driven by the presence of the individual risk factors 7,8,27. Our current results, in a sample of WISE women using invasive imaging to characterize the association between MetS and atherosclerotic coronary disease burden, are in line with those findings. Although in a univariate model several IVUS parameters were found to be significantly associated with presence of MetS, this association was lost in the subsequent multivariate model. Hypertension and waist circumference were observed to be the main variables associated with IVUS measures of CAD burden.

The interaction of CAD and hypertension is well established in both women and men, among those with and without known vascular disease 28. Others have shown in prospective studies that the effectiveness of BP-lowering treatments does not depend on starting BP level, but depends on the individual risk factors 29. It is therefore not surprising that, in this patient population, higher systolic BP was associated with greater disease burden as defined by IVUS. Similarly, demonstration of greater mean internal elastic lamina in patients with higher systolic BP is likely a response to pathologic remodeling.

Abdominal obesity is a key component of the MetS and a marker of dysfunctional adipose tissue that has been shown to independently predict CAD mortality in women 30. Adipose tissue is known to be a major endocrine organ that secretes a variety of bioactive substances, termed adipocytokines 30. Adipocytokine secretion profiles are altered as obesity develops, which may increase the risk of obesity-related cardiovascular disorders. Leptin, an adipocytokine up-regulation in obese individuals, has also been shown to play an important role in the pathophysiology of obesity-related atherogenesis through multiple mechanisms, such as its proinflammatory, prothrombotic, prooxidant, and proliferative effects. Similarly another adipocytokine, adiponectin down-regulation, leads to vascular remodeling and plaque destabilization among other atherogenic effects. Patients with excess of visceral adiposity have elevated plasma C-reactive protein concentrations accompanied by elevated interleukin-6 and tumor necrosis factor-α levels 31,32. It has been shown that visceral adiposity is associated with positive remodeling, low-attenuation noncalcified plaques, and spotty calcification. All of these are characteristic of early proliferative lesions, allowing considerable plaque accumulation despite normal luminal size. These early plaques may be particularly vulnerable to rupture, leading to acute coronary syndrome in the setting of modest luminal stenosis 33,34. Approximately 20% or more of women presenting with acute coronary syndrome have normal or nonobstructive CAD by angiography, yet these women have an increased risk of death or myocardial infarction at 30-day follow-up 18.

In addition, a pooled analysis of 97 cohort studies (with 1.8 million patients) showed that being overweight and obese is incrementally associated with higher risk of CAD and strokes. The hazard ratio for each 5 kg/m2 higher BMI was 1.27 (95% confidence interval 1.23–1.31) for coronary heart disease and 1.18 (1.14–1.22) for stroke after adjustment for confounders. The analysis showed that this risk is driven by the metabolic mediators BP, cholesterol, and glucose. Interestingly, of these, BP was the most important mediator, accounting for 31% (28–35) of the excess risk for coronary heart disease and 65% (56–75) for stroke 35.

The absence of a strong association between HDL levels and IVUS measures of disease burden requires additional comment. Although HDL levels were predictive in univariate analysis, in a multiple regression model this association did not persist. Although some prior studies have shown HDL cholesterol concentration to be a strong predictor of coronary heart disease risk in women 36–38, current evidence shows otherwise. As indicated by recently published cholesterol guidelines, adding one or more nonstatin drugs to high-intensity statin therapy will not provide incremental cardiovascular disease risk reduction benefit with an acceptable margin of safety, suggesting that most likely HDL cholesterol is not a significant risk factor that merits intervention to reduce cardiovascular events 39. Similarly, AIM-HIGH showed a lack of benefit of adding niacin in individuals with low-HDL cholesterol and high triglycerides, and ACCORD demonstrated the futility of adding fenofibrate in persons with diabetes 40–43. Therefore, an association between HDL/triglyceride values and IVUS-defined CAD burden in the current analysis suggests an interaction of multiple complex mechanisms that drive atheroma accumulation.

As expected, there were significantly more diabetics in the MetS group versus the non-MetS group. Diabetes is known to confer higher risk of CAD in women than men (4–6- vs. 3–4-fold), a poorer prognosis after myocardial infarction, and a higher risk of death from cardiovascular disease 44. However, we did not observe a significant correlation with fasting glucose, either when used as a categorical or continuous variable. Whereas older studies have suggested a diabetes-associated cardiovascular disease risk similar to that observed among nondiabetic patients with a prior myocardial infarction (e.g. CAD risk equivalent), more recent trials suggest a substantially lower risk, likely due to improved effectiveness of contemporary antidiabetic and lipid therapies 45,46.

Our study has some limitations. First, the findings are based on a small cohort of women. Therefore, we cannot exclude the possibility that our study may lack power to demonstrate the interaction of dyslipidemia and fasting glucose with IVUS atherosclerosis measures. Second, IVUS examination was limited to only a small proximal portion of the left coronary distribution, and this sampling limitation is likely to underestimate the true prevalence of atherosclerosis in this cohort. Third, we did not include information about hemogobin A1C, as most were well controlled diabetic patients, contributing to the lack of association of diabetes status with atherosclerosis burden. Furthermore, all participants were likely to be somewhat glucose intolerant.

In summary, although the presence of atherosclerosis was observed in these women with MetS, this appears to be driven predominantly by individual components rather than the presence of the syndrome, per se. MetS as a cluster merely highlights presence of multiple atherogenic risk factors in an individual woman. This association appears to be largely driven by abdominal obesity and systolic BP.

Others have documented that intensive risk modification was as effective in causing plaque regression in women as in men: in women, substantial regression (defined as 5% reduction in atheroma volume vs. baseline) was observed with lowering of LDL cholesterol to less than 80 mg/dl, systolic BP less than 120 mmHg, and C-reactive protein less than 2 mg/l 47. These data suggest important targets for potential therapeutic intervention to more effectively reduce risk in women. Our findings also emphasize the importance of focusing on BP control and weight management, as opposed to HDL/triglyceride management.


This work was supported by contracts from the National Heart, Lung and Blood Institutes nos. N01-HV-68161, N01-HV-68162, N01-HV-68163, N01-HV-68164, grants U0164829, U01 HL649141, U01 HL649241, K23HL105787, T32HL69751, R01 HL090957, 1R03AG032631 from the National Institute on Aging, GCRC grant MO1-RR00425 from the National Center for Research Resources, the National Center for Advancing Translational Sciences Grant UL1TR000124 and UL1TR000064, and grants from the Gustavus and Louis Pfeiffer Research Foundation, Danville, NJ, The Women’s Guild of Cedars-Sinai Medical Center, Los Angeles, CA, The Ladies Hospital Aid Society of Western Pennsylvania, Pittsburgh, PA, and QMED Inc., Laurence Harbor, NJ, the Edythe L. Broad and the Constance Austin Women’s Heart Research Fellowships, Cedars-Sinai Medical Center, Los Angeles, California, the Barbra Streisand Women’s Cardiovascular Research and Education Program, Cedars-Sinai Medical Center, Los Angeles, The Society for Women’s Health Research (SWHR), Washington, DC, The Linda Joy Pollin Women’s Heart Health Program, and the Erika Glazer Women’s Heart Health Project, Cedars-Sinai Medical Center, Los Angeles, California, USA.

Conflicts of interest

Dr Noel Bairey Merz would like to declare that she worked with QMED Inc., Laurence Harbour, NJ, a commercial funder, in the context of receiving digital Holter monitors free of charge for several other Women’s Ischemic Syndrome Evaluation (WISE) substudies. This has no conflict of interest with the content of this paper as no Holters were used in the methods. For the remaining authors there are no conflicts of interest.


1. Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999–2010. JAMA 2012; 307:491–497.
2. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the United States, 2011–2012. JAMA 2014; 311:806–814.
3. Dentali F, Romualdi E, Ageno W. The metabolic syndrome and the risk of thrombosis. Haematologica 2007; 92:297–299.
4. Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults: findings from the third National Health and Nutrition Examination Survey. JAMA 2002; 287:356–359.
5. Marroquin OC, Kip KE, Kelley DE, Johnson BD, Shaw LJ, Bairey Merz CN, et al.. Metabolic syndrome modifies the cardiovascular risk associated with angiographic coronary artery disease in women: a report from the Women’s Ischemia Syndrome Evaluation. Circulation 2004; 109:714–721.
6. Kahn R, Buse J, Ferrannini E, Stern M. The metabolic syndrome: time for a critical appraisal. Joint statement from the American Diabetes Association and the European Association for the Study of Diabetes. Diabetologia 2005; 48:1684–1699.
7. Sattar N, McConnachie A, Shaper AG, Blauw GJ, Buckley BM, de Craen AJ, et al.. Can metabolic syndrome usefully predict cardiovascular disease and diabetes? Outcome data from two prospective studies. Lancet 2008; 371:1927–1935.
8. Wang J, Ruotsalainen S, Moilanen L, Lepisto P, Laakso M, Kuusisto J. The metabolic syndrome predicts cardiovascular mortality: a 13-year follow-up study in elderly non-diabetic Finns. Eur Heart J 2007; 28:857–864.
9. Merz CN, Kelsey SF, Pepine CJ, Reichek N, Reis SE, Rogers WJ, et al.. The Women’s Ischemia Syndrome Evaluation (WISE) study: protocol design, methodology and feasibility report. J Am Coll Cardiol 1999; 33:1453–1461.
10. Johnson BD, Shaw LJ, Pepine CJ, Reis SE, Kelsey SF, Sopko G, et al.. Persistent chest pain predicts cardiovascular events in women without obstructive coronary artery disease: results from the NIH-NHLBI-sponsored Women’s Ischaemia Syndrome Evaluation (WISE) study. Eur Heart J 2006; 27:1408–1415.
11. Gulati M, Cooper-DeHoff RM, McClure C, Johnson BD, Shaw LJ, Handberg EM, et al.. Adverse cardiovascular outcomes in women with nonobstructive coronary artery disease: a report from the Women’s Ischemia Syndrome Evaluation Study and the St James Women Take Heart Project. Arch Intern Med 2009; 169:843–850.
12. Jespersen L, Hvelplund A, Abildstrom SZ, Pedersen F, Galatius S, Madsen JK, et al.. Stable angina pectoris with no obstructive coronary artery disease is associated with increased risks of major adverse cardiovascular events. Eur Heart J 2012; 33:734–744.
13. Johnson BD, Shaw LJ, Buchthal SD, Bairey Merz CN, Kim HW, Scott KN, et al.. Prognosis in women with myocardial ischemia in the absence of obstructive coronary disease: results from the National Institutes of Health-National Heart, Lung, and Blood Institute-Sponsored Women’s Ischemia Syndrome Evaluation (WISE). Circulation 2004; 109:2993–2999.
14. Murthy VL, Naya M, Taqueti VR, Foster CR, Gaber M, Hainer J, et al.. Effects of sex on coronary microvascular dysfunction and cardiac outcomes. Circulation 2014; 129:2518–2527.
15. 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.
16. Ambrose JA, Tannenbaum MA, Alexopoulos D, Hjemdahl-Monsen CE, Leavy J, Weiss M, et al.. Angiographic progression of coronary artery disease and the development of myocardial infarction. J Am Coll Cardiol 1988; 12:56–62.
17. Little WC, Constantinescu M, Applegate RJ, Kutcher MA, Burrows MT, Kahl FR, Santamore WP. Can coronary angiography predict the site of a subsequent myocardial infarction in patients with mild-to-moderate coronary artery disease? Circulation 1988; 78 (Pt 1):1157–1166.
18. Anderson RD, Pepine CJ. Gender differences in the treatment for acute myocardial infarction: bias or biology? Circulation 2007; 115:823–826.
19. Khuddus MA, Pepine CJ, Handberg EM, Bairey Merz CN, Sopko G, Bavry AA, et al.. An intravascular ultrasound analysis in women experiencing chest pain in the absence of obstructive coronary artery disease: a substudy from the National Heart, Lung and Blood Institute-Sponsored Women's Ischemia Syndrome Evaluation (WISE). J Interv Cardiol 2010; 23:511–519.
20. Sharaf B, Wood T, Shaw L, Johnson BD, Kelsey S, Anderson RD, et al.. Adverse outcomes among women presenting with signs and symptoms of ischemia and no obstructive coronary artery disease: findings from the National Heart, Lung, and Blood Institute-sponsored Women’s Ischemia Syndrome Evaluation (WISE) angiographic core laboratory. Am Heart J 2013; 166:134–141.
21. Grundy SM, Hansen B, Smith SC Jr, Cleeman JI, Kahn RA. Clinical management of metabolic syndrome: report of the American Heart Association/National Heart, Lung, and Blood Institute/American Diabetes Association conference on scientific issues related to management. Circulation 2004; 109:551–556.
22. Amano T, Matsubara T, Uetani T, Nanki M, Marui N, Kato M, et al.. Impact of metabolic syndrome on tissue characteristics of angiographically mild to moderate coronary lesions integrated backscatter intravascular ultrasound study. J Am Coll Cardiol 2007; 49:1149–1156.
23. Kunimura A, Amano T, Uetani T, Harada K, Yoshida T, Suzuki A, et al.. Prognostic impact of concurrence of metabolic syndrome and chronic kidney disease in patients undergoing coronary intervention: involvement of coronary plaque composition. J Cardiol 2013; 61:189–195.
24. Nicholls SJ, Tuzcu EM, Crowe T, Sipahi I, Schoenhagen P, Kapadia S, et al.. Relationship between cardiovascular risk factors and atherosclerotic disease burden measured by intravascular ultrasound. J Am Coll Cardiol 2006; 47:1967–1975.
25. Zheng M, Choi SY, Tahk SJ, Lim HS, Yang HM, Choi BJ, et al.. The relationship between volumetric plaque components and classical cardiovascular risk factors and the metabolic syndrome a 3-vessel coronary artery virtual histology-intravascular ultrasound analysis. JACC Cardiovasc Interv 2011; 4:503–510.
26. Haffner SM. Abdominal obesity, insulin resistance, and cardiovascular risk in pre-diabetes and type 2 diabetes. Eur Heart J Suppl 2006; 8 (Suppl B):B20–B25.
27. Psaty BM, Lumley T, Furberg CD. The metabolic syndrome: time for a critical appraisal: joint statement from the American Diabetes Association and the European Association for the Study of Diabetes: response to Kahn et al. Diabetes Care 2006; 29:177.
28. Pepine CJ, Handberg EM. The vascular biology of hypertension and atherosclerosis and intervention with calcium antagonists and angiotensin-converting enzyme inhibitors. Clin Cardiol 2001; 24 (Suppl):V1–V5.
29. Czernichow S, Zanchetti A, Turnbull F, Barzi F, Ninomiya T, Kengne AP, et al.. The effects of blood pressure reduction and of different blood pressure-lowering regimens on major cardiovascular events according to baseline blood pressure: meta-analysis of randomized trials. J Hypertens 2011; 29:4–16.
30. Zhang C, Rexrode KM, van Dam RM, Li TY, Hu FB. Abdominal obesity and the risk of all-cause, cardiovascular, and cancer mortality: sixteen years of follow-up in US women. Circulation 2008; 117:1658–1667.
31. Després JP, Lemieux I. Abdominal obesity and metabolic syndrome. Nature 2006; 444:881–887.
32. Katagiri H, Yamada T, Oka Y. Adiposity and cardiovascular disorders: disturbance of the regulatory system consisting of humoral and neuronal signals. Circ Res 2007; 101:27–39.
33. Imai A, Komatsu S, Ohara T, Kamata T, Yoshida J, Miyaji K, et al.. Visceral abdominal fat accumulation predicts the progression of noncalcified coronary plaque. Atherosclerosis 2012; 222:524–529.
34. Ohashi N, Yamamoto H, Horiguchi J, Kitagawa T, Kunita E, Utsunomiya H, et al.. Association between visceral adipose tissue area and coronary plaque morphology assessed by CT angiography. JACC Cardiovasc Imaging 2010; 3:908–917.
35. Lu Y, Hajifathalian K, Ezzati M, Woodward M, Rimm EB, Danaei G. Metabolic mediators of the effects of body-mass index, overweight, and obesity on coronary heart disease and stroke: a pooled analysis of 97 prospective cohorts with 1.8 million participants. Lancet 2014; 383:970–983.
36. Bass KM, Newschaffer CJ, Klag MJ, Bush TL. Plasma lipoprotein levels as predictors of cardiovascular death in women. Arch Intern Med 1993; 153:2209–2216.
37. Goldbourt U, Medalie JH. High density lipoprotein cholesterol and incidence of coronary heart disease – the Israeli Ischemic Heart Disease Study. Am J Epidemiol 1979; 109:296–308.
38. Wilson PW, Abbott RD, Castelli WP. High density lipoprotein cholesterol and mortality. The Framingham Heart Study. Arteriosclerosis 1988; 8:737–741.
39. Psaty BM, Weiss NS. 2013 ACC/AHA guideline on the treatment of blood cholesterol: a fresh interpretation of old evidence. JAMA 2014; 311:461–462.
40. Boden WE, Probstfield JL, Anderson T, Chaitman BR, Desvignes-Nickens P, Koprowicz K, et al.. Niacin in patients with low HDL cholesterol levels receiving intensive statin therapy. N Engl J Med 2011; 365:2255–2267.
41. Ginsberg HN, Elam MB, Lovato LC, Crouse JR 3rd, Leiter LA, Linz P, et al.. Effects of combination lipid therapy in type 2 diabetes mellitus. N Engl J Med 2010; 362:1563–1574.
42. Landray MJ, Haynes R, Hopewell JC, Parish S, Aung T, Tomson J, et al.. Effects of extended-release niacin with laropiprant in high-risk patients. N Engl J Med 2014; 371:203–212.
43. Lloyd-Jones DM. Niacin and HDL cholesterol – time to face facts. N Engl J Med 2014; 371:271–273.
44. Legato MJ, Gelzer A, Goland R, Ebner SA, Rajan S, Villagra V, Kosowski M. Gender-specific care of the patient with diabetes: review and recommendations. Gend Med 2006; 3:131–158.
45. Gerstein HC, Miller ME, Byington RP, Goff DC Jr, Bigger JT, Buse JB, et al.. Effects of intensive glucose lowering in type 2 diabetes. N Engl J Med 2008; 358:2545–2559.
46. Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HA. 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med 2008; 359:1577–1589.
47. Nicholls SJ, Wolski K, Sipahi I, Schoenhagen P, Crowe T, Kapadia SR, et al.. Rate of progression of coronary atherosclerotic plaque in women. J Am Coll Cardiol 2007; 49:1546–1551.

adverse outcomes; coronary angiography; coronary artery disease; coronary atherosclerosis; intravascular ultrasound; ischemic heart disease; metabolic syndrome; risk assessment; women

Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved.