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Central versus peripheral arterial stiffness in association with coronary, cerebral and peripheral arterial disease
Atherosclerosis 211 (2010) 480–485
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Atherosclerosis journal homepage: www.elsevier.com/locate/atherosclerosis
Central versus peripheral arterial stiffness in association with coronary, cerebral and peripheral arterial disease Shoko Tsuchikura ∗ , Tetsuo Shoji , Eiji Kimoto , Kayo Shinohara , Sawako Hatsuda , Hidenori Koyama , Masanori Emoto, Yoshiki Nishizawa Department of Metabolism, Endocrinology and Molecular Medicine, Osaka City University Graduate School of Medicine, 1-4-3, Asahi-machi, Abeno-ku, Osaka 545-8585, Japan
a r t i c l e
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Article history: Received 16 September 2009 Received in revised form 26 March 2010 Accepted 29 March 2010 Available online 9 April 2010 Keywords: Arterial stiffness Compliance Distensibility Arteriosclerosis Coronary artery disease Cerebrovascular disease Peripheral artery disease
a b s t r a c t Background: Although stiffness of central arteries is more preferentially associated with coronary artery disease (CAD) than that of peripheral arteries, less is known for cerebrovascular disease (CVD) and peripheral artery disease (PAD). We measured pulse wave velocity (PWV) in four arterial segments, and examined the relative changes in the four regional PWVs in patients with CAD, CVD or PAD. Methods: The 2798 subjects were selected from 3300 consecutive participants of our non-invasive vascular lab. 342 subjects had one or more pre-existing atherosclerotic diseases including 128 CAD (N = 128), CVD (N = 195) and PAD (N = 83). PWVs were simultaneously measured using an automated pulse wave analyzer (model BP-203RPE, Colin) in the heart–femoral (hf, aorta), heart–carotid (hc), heart–brachial (hb), and femoral–ankle (fa) segments. Results: As compared to the subjects without atheroscletoric disease, those with CAD, CVD, or PAD showed higher levels of PWV in the four arterial segments, particularly in hfPWV. The relative increase in hfPWV remained significant after adjustment for age, sex, hypertension, pulse rate, smoking, diabetes mellistus, dyslipidemia, and chronic kidney disease. Conclusion: This study indicates that the preferential increase in central arterial stiffness is found not only in CAD but CVD and PAD as well. © 2010 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Arterial stiffness is an independent predictor for cardiovascular disease. Pulse wave velocity (PWV) of the aorta is increased in populations at high risk for cardiovascular disease such as elderly people [1] and patients with hypertension [2], type 2 diabetes mellitus (T2DM) [3], and chronic kidney disease (CKD) [4,5]. Also, aortic PWV predicts mortality from cardiovascular disease [6–8]. Although PWV of the aorta has been used as the standard measure for arterial stiffness, PWV can be determined in other segments of arterial tree. Previous studies revealed that impacts of some risk factors on arterial stiffness varied among different parts of arteries. We [9] previously demonstrated that the effects of age, T2DM on PWV were greater on central arteries than on peripheral arteries. Also, the association of decreased renal function was stronger on central than peripheral arteries in patients with T2DM [10]. In contrast, stiffness of peripheral arteries, as compared to central arteries, appears to be more sensitive to sex hormone [11], and lipid-lowering drugs [12,13]. Thus, arterial stiffening is not a uni-
∗ Corresponding author. Tel.: +81 6 6645 3806; fax: +81 6 6645 3808. E-mail address: [email protected] (S. Tsuchikura). 0021-9150/$ – see front matter © 2010 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.atherosclerosis.2010.03.037
form change, but rather heterogeneous in the arterial system. There is a possibility that patients groups with coronary artery disease (CAD), cerebrovascular disease (CVD) and peripheral artery disease (PAD) show different patterns of regional arterial stiffness, and that increased arterial stiffness is particularly evident in some segments specific to the type of cardiovascular disease. So far, however, no study has directly explored this hypothesis, although a few previous studies reported related observations in patients with CAD [14], CKD [15] and T2DM [16,17]. The purpose of the present study was to identify arterial segments that were most closely associated with the individual cardiovascular disease, namely CAD, CVD and PAD. To this end, we performed cross-sectional analyses using data of participants in our non-invasive vascular lab. 2. Subjects and methods 2.1. Subjects The subjects of this study were selected from 3300 consecutive participants of our vascular lab at the Osaka City University Hospital, including volunteers from the Health Promotion Center in Osaka City, Japan. The study was approved by the
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ethics committee of Graduate School of Medicine, Osaka City University, and all these subjects gave informed consent. We screened our clinical database for subjects who underwent regional PWV measurements performed during July 2000 through May 2009, and identified 3300 subjects. Among them, 289 were excluded because relevant clinical information was lacking. Furthermore, 213 were excluded because of a reduced ankle–brachial pressure index (ABI) less than 0.95, since PWV of leg arteries is known to be influenced in such subjects [18]. Data of the remaining 2798 subjects were used for the subsequent analyses. Among them, 342 subjects had one or more pre-existing atherosclerotic diseases (Fig. 1). Table 1 summarizes the characteristics of the subjects with CAD, CVD, PAD, or without these atherosclerotic disease as defined below. 2.2. Definition of cardiovascular disease Pre-existing cardiovascular diseases were recorded by carefully taking clinical history of each subject. Pre-existing CAD was diagnosed if the subject had a past history of myocardial infarction and/or angina pectoris [19], which had been confirmed by typical symptoms, increased serum levels of myocardial enzymes, electrocardiography, myocardial scintigraphy, or multi-detector computed tomography. In some cases, the diagnosis had been established by coronary angiography, and treated by percutaneous coronary intervention and/or coronary artery bypass grafting. We excluded those complaining equivocal symptoms without objective findings supporting myocardial ischemia. We identified 128 subjects who fulfilled the above criteria for pre-existing CAD. Pre-existing CVD was diagnosed if the subject had a past history of symptomatic cerebral infarction, cerebral hemorrhage, and/or sub-arachnoidal hemorrhage, which had been confirmed
Fig. 1. Chart for subject selection and distribution of atherosclerotic disease. Note that there was overlapping between CAD, CVD and PAD. The group with CAD represents patients with CAD including those with CAD and CVD, CAD and PAD, and all of the three. Abbreviations are: CAD, coronary arterial disease; CVD, cerebrovascular disease; PAD, peripheral arterial disease.
by typical symptoms, computed tomography, and/or magnetic resonance imaging (MRI). Some cases had undergone angiography. We excluded those complaining equivocal head and neck symptoms without objective findings supporting stroke. Also, we did not include asymptomatic subjects with lacunae and/or ischemic
Table 1 Characteristics of the subjects. No athero-sclerotic disease control
Number of subjects Age (years) Male (%) Smoker (%) Diabetes mellitus (%) Hypertension (%) Dyslipidemia (%) Chronic kidney disease (%) Systolic BP (mmHg) Diastolic BP (mmHg) ABI Plasma glucose (mg/dL) Total cholesterol (mg/dL) HDL-C (mg/dL) LDL-C (mg/dL) Triglycerides (mg/dL) eGFR (mL/min/1.73 m2 ) Pulse rate (beats/min) hcPWV (cm/s) hbPWV (cm/s) hfPWV (cm/s) faPWV (cm/s) Use of medications Anti-hypertensives (%) Anti-diabetics (%) Statins (%) Fibrates (%) Other lipid-lowering drugs (%) Anti-platelet drugs (%) Warfarin (%)
Atherosclerotic disease Any of the three
CAD
CVD
PAD
2456 58 ± 12 46.9 41.9 47.5 43.4 68.8 26.0 128 ± 18 77 ± 10 1.1 ± 0.1 118 ± 36 209 ± 42 56 ± 17 126 ± 40 131 ± 102 75 ± 24 66 ± 10 1008 ± 319 628 ± 115 1044 ± 267 1055 ± 153
342 65 ± 9** 67.3** 64.0** 79.2** 68.7** 78.4** 39.8** 133 ± 18** 77 ± 10 1.1 ± 0.1** 125 ± 36** 191 ± 42** 50 ± 16** 114 ± 40** 137 ± 91** 64 ± 26** 68 ± 12** 1172 ±280* 700 ± 118* 1293 ± 310* 1097 ± 164*
128 65 ± 9** 75.0** 64.8** 85.2** 70.3** 85.9** 46.1** 133 ± 18** 77 ± 9 1.1 ± 0.1 129 ± 37** 185 ± 39** 48 ± 15** 109 ± 38** 147 ± 114 60 ± 27** 68 ± 11 1181 ± 270* 698 ± 122* 1311 ± 329* 1060 ± 134
195 66 ± 8** 62.6** 62.6** 84.1** 70.8** 80.5** 40.0** 135 ± 18** 77 ± 11b 1.1 ± 0.1 127 ± 38** 195 ± 40** 50 ± 16** 117 ± 38 131 ± 67** 64 ± 25** 68 ± 12 1173 ± 273* 710 ± 115* 1298 ± 302* 1102 ± 147*
83 66 ± 9** 73.5** 71.1** 72.3** 67.5** 67.5 42.2** 133 ± 21** 76 ± 10 1.1 ± 0.1** 118 ± 35 184 ± 44** 52 ± 18* 105 ± 42** 125 ± 75 68 ± 28* 70 ± 12** 1182 ± 308* 707 ± 118* 1382 ± 339* 1090 ± 209
23 31 21 1.8 0.7 4.6 0.3
60** 69** 41** 2.3** 3.5** 34.5** 2.3**
63** 74** 50** 1.6 4.7** 39.8** 3.9**
61** 74** 41** 3.6* 4.1** 30.8** 0.5
57** 70** 42** 0.0 1.2 45.8** 3.6**
This table gives number of subjects, percentages, and mean ± standard deviation. * P < 0.05, ** P < 0.01 vs. the control group by Student’s t-test. Abbreviations are: CAD, coronary artery disease; CVD, cerebrovascular disease; PAD, peripheral arterial disease; BP, blood pressure; ABI, ankle–brachial pressure index; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; eGFR, estimated glomerular filtration rate; PWV, pulse wave velocity; hc, heart–carotid; hb, heart–brachial; hf, heart–femoral; fa, femoral–ankle.
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changes evidenced by MRI to avoid selection bias, because MRI was not performed in all subjects. We found 195 subjects who had pre-existing CVD as defined above. Since we excluded subjects with a reduced ABI < 0.95, the diagnosis of PAD in this study was based primarily on the history of successful percutaneous interventions, bypass grafting, and/or amputation for PAD. Complaints such as numbness, tingling and weakness of the lower-extremities were not included in the PAD symptoms, because it was difficult to distinguish them from symptoms of peripheral neuropathy. Symptoms due to orthopedic diseases were also excluded. There were 83 subjects with pre-existing PAD fulfilling the above criteria. None of them had undergone bilateral major amputation of the lower-extremities. 2.3. Definition of major risk factors Hypertension was diagnosed if the subject had blood pressure of 140/90 mmHg or higher according to The Japanese Society of Hypertension Guidelines for the Management of Hypertension (JSH 2009), and/or the subject received anti-hypertensive medication. Diabetes mellitus was diagnosed if the subjects had fasting plasma glucose of 126 mg/dL or higher according to the diagnostic criteria by Japan Diabetes Society (JDS 2007), and/or the subject received anti-diabetic medication. Dyslipidemia was diagnosed if the subject had low-density lipoprotein cholesterol of 140 mg/dL or higher, triglycerides of 150 mg/dL or higher, and/or high-density lipoprotein cholesterol lower than 40 mg/dL according to the criteria by Japan Atherosclerosis Society [20], and/or the subject received lipid-lowering medication. Smoking denotes current smoking. Chronic kidney disease (CKD) was diagnosed if the subject had overt proteinuria and/or reduced estimated glomerular filtration rate (eGFR) less than 60 mL/min/1.73 m2 [21].
atherosclerostic disease. If the four arterial segments in the patients are uniformly stiffened, the ratios of the four segments should be at the same level above 1.0. If arterial stiffening is not a uniform change within subjects, the ratios should vary among the four segments, with the difference being detected by analysis of variance for paired data (repeated measure ANOVA). The above did not take the difference in the risk factor profile among the groups. To adjust for the risk factors, we then developed formulas to calculate the expected PWV based on the risk factor profile among the control subjects using multiple regression models. Depending upon the risk factors of interest, various versions of formulas were developed. Then, using these formulas, we calculated expected PWV values based on the subject’s risk factor profile in groups with atherosclerotic disease. Then, the ratio of the actual PWV to the expected PWV was calculated for the four arterial segments for each subject. The four ratios among the different arterial segments were compared by repeated measure ANOVA. Categorical variables were expressed in percentage. Continuous variables were summarized as mean ± standard deviation or mean ± standard error as indicated. Difference in mean between two groups was evaluated by Student t-test. Repeated measure ANOVA was applied to paired data. Multiple logistic regression models were used to analyze associations between PWV of each arterial segment and cardiovascular disease independent of other clinical parameters. P values less than 0.05 was taken as statistically significant. These statistics were performed using StatView 5 (SAS Institute, Cary, NC) and PASW Statistics 17.0 (formerly called SPSS statistics, SPSS Inc, Tokyo) for Windows PC. 3. Results 3.1. Comparison of PWV between subjects with and without atherosclerotic disease
2.4. PWV and blood pressure measurements PWV and blood pressure measurements were performed in the supine position after 5 min bed rest using an automatic waveform analyzer (model BP-203RPE, Colin, Komaki City, Japan) as previously described [9,10,16].The coefficients of variation were 6.0%, 3.3%, 4.9%, 3.3% for hcPWV, hbPWV, hfPWV, and faPWV, respectively [9].
As compared to the subjects without any pre-existing cardiovascular disease (control group), those with either CAD, CVD or PAD showed significantly higher levels in hfPWV, hcPWV and hbPWV (Table 1). The patients with CVD had a higher faPWV than the control group, whereas the difference was not significant for those with CAD or PAD. 3.2. Risk factor profile in groups with atherosclerotic disease
2.5. Other measurements Venous blood was obtained into plastic tubes in the morning after overnight fast. We measured plasma glucose, serum total cholesterol (TC), triglycerides (TG), and creatinine by enzymatic methods using an auto-analyzer. High-density lipoprotein cholesterol level (HDL-C) was measured by a precipitation method. LDL-C was calculated by the Friedewald formula. In subjects with elevated TG > 400 mg/dL, LDL-C was measured by ultracentrifugation or a homogenous assay. We estimated glomerular filtration rate (eGFR) according the formula for the Japanese [22]. Proteinuria was determined by a dip-stick method using spot urine samples obtained in the morning. 2.6. Statistical methods In order to compare the relative changes in PWV among the four arterial segments in patients with atherosclerotic disease as compared to the control group without such disease, we first calculated the ratios of PWV in the patients to the mean PWV level of the control group. Since each patient had four PWV ratios corresponding to the arterial segments, these ratios can be treated as paired data. If atherosclerotic diseases are not associated with PWV at all, the ratios of the four segments should be 1.0 in the group with
As compared to the control group, the groups with either CAD, CVD or PAD showed a higher age, higher percentages of men, smokers, diabetes mellitus, hypertension, and CKD (Table 1). The percentage of dyslipidemia was higher in the CAD and CVD group, but not in the PAD subjects. The PAD group showed a higher pulse rate than the control subjects. 3.3. Logistic regression analysis To examine the association of PWVs of different arterial segments with atherosclerotic disease, we performed two sets of multivariate logistic regression analysis. In the first set of analysis, we searched factors other than PWV which were independently associated with atherosclerotic cardiovascular disease (Table 2). CAD was independently associated with higher age, male sex, diabetes mellitus, dyslipidemia, and CKD. CVD was independently associated with higher age, hypertension, diabetes mellitus, and dyslipidemia. PAD was independently associated with higher age, smoking, and higher pulse rate. Then, in the second set of multivariate logistic regression analysis, we examined the independent association between atherosclerotic cardiovascular disease and PWVs of the four arterial segments after adjustment for the eight covariates identified
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Table 2 Factors independently associated with pre-existing cardiovascular disease. Variables
Any of the three
CAD
***
***
CVD ***
PAD
Age (per 1 year) Sex (male vs. female) Hypertension (presence vs. absence) Diabetes mellitus (presence vs. absence) Dyslipidemia (presence vs. absence) Smoking (smoker vs. non-smoker) Chronic kidney disease (presence vs. absence) Pulse rate (per 1 bpm)
1.07 (1.06–1.09) 1.43* (1.05–1.95) 1.65*** (1.26–2.16) 2.44*** (1.82–3.28) 1.55** (1.15–2.08) 1.96*** (1.45–2.64) 1.22 (0.94–1.59) 1.01 (1.00–1.05)
1.06 (1.04–1.08) 2.31** (1.41–3.81) 1.45 (0.95–2.20) 3.35*** (1.98–5.67) 2.65*** (1.57–4.46) 1.35 (0.86–2.11) 1.52* (1.03–2.25) 1.00 (0.98–1.02)
1.07 (1.05–1.09) 1.00 (0.68–1.47) 1.65** (1.17–2.33) 3.25*** (2.16–4.90) 1.72** (1.17–2.53) 1.99*** (1.36–2.91) 1.19 (0.86–1.65) 1.01 (0.99–1.02)
1.07*** (1.04–1.10) 1.60 (0.87–2.95) 1.51 (0.91–2.51) 1.30 (0.76–2.21) 0.78 (0.49–1.29) 2.40** (1.33–4.31) 1.25 (0.77–2.02) 1.03** (1.01–1.05)
Global model significance
P < 0.0001
P < 0.0001
P < 0.0001
P < 0.0001
The table gives adjusted hazards rations (95% confidence intervals) of the eight factors for the pre-existence of CAD, CVD, PAD and any of the three by multivariate logistic regression models. * P < 0.05, ** P < 0.001, *** P < 0.001. Abbreviations; CAD, coronary arterial disease; CVD, cerebrovascular disease; PAD, peripheral arterial disease; bpm, beats per minute.
above. Each PWV was entered as the ninth variable in the multivariate logistic models (Table 3). In such analyses, increased hfPWV was positively associated with the likelihood to have CAD, CVD and PAD. In contrast, reduced faPWV was positively associated with the likelihood to have CAD. None of CAD, CVD or PAD showed no significant association with hcPWV nor hbPWV independent of the eight covariates. 3.4. Comparison of changes in PWV among the four arterial segments in patients with atherosclerotic disease relative to the controls Fig. 2 (upper panel) shows the comparison of the relative changes in PWV among the four arterial segments in patients with atherosclerotic disease as compared to the control group without such disease. When no adjustment was done for the different risk factor profile between groups, the PWV value relative to the control (ratio to the control mean) in the patients with atherosclerotic disease was the highest for hfPWV and the lowest for faPWV. Although such trend was attenuated to some extent by further adjustment for age, hypertension, pulse rate, and other factors, the difference in relative PWV change among the four arterial segments remained highly significant. In the fully adjusted model, the relative change was in the order of hfPWV > hcPWV > hbPWV > faPWV. Essentially the same was true, when atherosclerotic cardiovascular disease was divided into CAD, CVD, and PAD as shown in Fig. 2 (lower panel). 4. Discussion Increased arterial stiffness is one of the key factors associated with cardiovascular disease. Previous cross-sectional studies [14,16] showed that CAD was more closely associated with increased stiffness of the aorta than other arterial segments. In a longitudinal cohort study in hemodialysis patients [15], death from composite cardiovascular disease including congestive heart failure was independently associated with aortic PWV but not
with PWV of peripheral arteries. In this study, we tested the hypothesis that patient groups with CAD, CVD and PAD show different patterns of regional arterial stiffness, and that increased arterial stiffness is particularly evident in some segments specific to the type of cardiovascular disease. We simultaneously measured PWVs in the four arterial segments as indexes for regional arterial stiffness in 2798 participants at our non-invasive vascular lab. Contrary to the hypothesis, the results clearly indicated that increased aortic PWV was most closely associated with all of CAD, CVD and PAD among the four PWV measurements. This was again confirmed after adjustment for eight major risk factors for cardiovascular disease. This study indicates that the preferential stiffening of the aorta over the other arterial segments is not specific to CAD, but that it can be generalized to other atherosclerotic cardiovascular diseases such as CVD and PAD. There are only a few studies reporting the comparison in the association of cardiovascular disease with stiffness of different arterial segments. Pannier et al. [15] measured PWV of the aorta and arteries in the upper and lower extremities in 305 hemodialysis patients, showing that only PWV of the aorta significantly predicted death from cardiovascular disease. In their study, individual vascular events were combined as cardiovascular disease because of the size of the cohort. According to Kingwell et al. [14], time to STsegment depression during a treadmill exercise test was inversely correlated with aortic PWV but not with femoral–tibial PWV in 96 patients with CAD. We [16] previously evaluated the crosssectional association of CAD with regional PWV measurements, and found that the presence of CAD was more closely associated with aortic PWV than PWV in the heart–brachial, heart–carotid, and femoral–ankle segments in 595 T2DM patients. These studies by Kingwell et al. and by us, however, did not examine the relationship of PWV with other cardiovascular disease than CAD. Regarding regional changes in arterial stiffness in PAD patients, although early studies by Simonson et al. [23], Eliakim et al. [24], and Safar et al. [25] reported normal levels in brachial–radial PWV and the reduction in PWV of the heart–feet and femoral–dorsalis
Table 3 Associations of PWVs in four arterial segments with cardiovascular disease after adjustment for major risk factors. Variables
Any of the three
CAD
CVD
PAD
hfPWV (per 1SD increase) hcPWV (per 1SD increase) hbPWV (per 1SD increase) faPWV (per 1SD increase)
1.40*** (1.19–1.64) 1.01 (0.88–1.16) 1.11 (0.96–1.28) 0.89 (0.77–1.04)
1.26* (1.01–1.58) 0.99 (0.81–1.23) 0.96 (0.77–1.20) 0.60*** (0.47–0.76)
1.28* (1.06–1.55) 1.00 (0.84–1.19) 1.23 (1.03–1.46) 0.94 (0.78–1.13)
1.77*** (1.38–2.28) 1.00 (0.78–1.29) 1.15 (0.89–1.48) 0.81 (0.62–1.06)
The table gives hazards ratios (95% confidence intervals) of PWV of four arterial segments for the pre-existence of CAD, CVD, PAD and any of the three after adjustment for age, sex, hypertension, diabetes mellistus, dyslipidemia, chronic kidney disease, smoking, and pulse rate using multivariate logistic regression models. Note that increased hfPWV was consistently associated with the pre-existence of CAD, CVD, and PAD. Abbreviations; CAD, coronary arterial disease; CVD, cerebrovascular disease; PAD, peripheral arterial disease; PWV, pulse wave velocity; hf, heart–femoral segment; hc, heart–carotid segment; hb, heart–brachial segment; fa, femoral–ankle segment; SD, standard deviation.
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Fig. 2. PWV in subjects with atherosclerotic disease relative to the controls without atherosclerotic disease. PWV values of the four arterial segments in subjects with pre-existing atherosclerotic disease were expressed as the ratios relative to the corresponding PWV values in the subjects with no atherosclerotic disease (control group), and comparison among the four arterial segments was performed by repeated measure analysis of variance. Mean ± standard error. Comparison was done with four versions of adjustment as indicated in the insert. The full adjustment was made for 8 factors including age, sex, hypertension, pulse rate, smoking, diabetes mellitus, dyslipidemia, and chronic kidney disease. Abbreviations are: CAD, coronary artery disease; CVD, cerebrovascluar disease; PAD, peripheral artery disease; hf, heart–femoral; hc, heart–carotid; hb, heart–brachial; fa, femoral–ankle; PWV, pulse wave velocity; HT, hypertension; PR, pulse rate.
segments, information is lacking about central arterial stiffness in PAD. Thus, the present study confirmed the previous findings regarding CAD and aortic stiffness in much larger number of subjects, and extended the similar knowledge to CVD and PAD. Stiffness of the aorta and its primary branches (central arteries) is implicated in the development of CAD [26]. Stiffening of central arteries increases systolic pressure, decreases diastolic pressure, resulting in increased pulse pressure. The increased systolic pressure increases cardiac afterload, left ventricular mass, and oxygen demand in one hand. In the other hand, the decrease in diastolic pressure can reduce coronary blood flow during the diastole. These changes can results in development and worsening of CAD. We showed the higher association of cerebrovascular disase with PWV of the aorta than PWV of other arterial segments. Laurent et al. [27] reported that aortic PWV was an independent predictor of stroke death in 1715 patients with essential hypertension. In 2835 subjects of the Rotterdam study [28], aortic PWV predicted the occurrence of CAD and stroke, but carotid distensibility did not. Thus, aortic stiffness may have more important roles in stroke than stiffness of other arterial segments. This may be explained by several mechanisms. First, aortic stiffening may increase pulse pressure and mechanical stretching of arterial cells, which then may stimulate arterial remodeling, increasing carotid arterial thickness and plaque formation. These morphological changes in the
carotid arteries were reported to positively correlate with cerebral white matter lesions [29]. Second, because cerebral hemorrhage and infarction occur most frequently in the area of small perforating arteries that are exposed to high pressure and large pressure gradient, these cerebral ‘strain vessels’ may be more susceptible to increased pulsatility of aortic pressure. Third, aortic PWV may also reflect parallel changes in cerebral vasculature. Increased aortic stiffness is caused by various alterations, including fibrosis, medial smooth muscle necrosis, elastin fiber degeneration, calcifications, and diffusion of macromolecules within the arterial wall. These have also been described at the site of the cerebral vasculature. However, the third mechanism does not fully explain the preferential association between cerebrovascular disease and PWV of the aorta over other arterial segments. With regard to PAD, Safar et al. [25] previously reported that patients with PAD had normal PWV of brachial arteries and increased brachial pulse pressure as compared with those of ageand sex-matched controls. Although increased pulse pressure is suggestive of increase in central arterial stiffness, no direct measurement was reported. Suzuki et al. [17] showed that a higher brachial–ankle PWV was associated with reduced blood flow of popliteal arteries in 60 patients with T2DM having normal ABI, but they did not compare the effects of brachial–ankle PWV with PWVs of other arterial segments on the blood flow of the lower extremities. We previously reported that stiffness parameter ˇ measured at the femoral artery was independently associated with ischemic leg symptoms in 315 patients with T2DM [30]. Also, decrease in transcutaneous oxygen tension (TcPO2 ) of foot during a treadmill exercise was significantly correlated with stiffness parameter ˇ of femoral artery, but not of carotid artery in 68 patients with T2DM [31]. The present results indicate preferential association of PAD with aortic PWV over PWV of other arterial regions. Taken together, ischemia of lower-extremities appears to be related with arterial stiffness of upstream rather than downstream. As Suzuki et al. [17] showed, arterial stiffness was closely associated with popliteal blood flow during the diastole, presumably due to impairment in ‘the second heart’ function of the central arteries. We found the paradoxical association between reduced faPWV and CAD. This association remained significant even after adjustment for eight factors. We do not know the precise mechanisms for it, but there are a few possibilities that may explain the finding. First, some of CAD patients had impaired leg circulation that was not evident from ABI. It is reported that PWV of the lowerlimb arteries is decreased in the presence of significant stenosis in these arteries [23,24,32]. It is also known that, calcified arteries are often incompressible, resulting in higher ABI and masking the presence of PAD. In this study, 24 patients out of 128 CAD patients (19%) were also complicated with PAD, whereas 22 patients out of 195 CVD patients (11%) had PAD, suggesting a higher prevalence of leg artery lesions in CAD patients. Thus, we speculate such occult lesions in leg arteries may be one of the reasons for the paradoxical finding with CAD. Second, the use of statin may be related to the decreased faPWV in CAD patients, because statins are known to decrease stiffness of lower-limb arteries [12,13]. The percentage of statin use was the highest in the patients with CAD (50%) and the lowest in the control group (21%). There are several limitations in this study that should be noted. First, because of the cross-sectional nature, this study does not indicate causality. To examine it, longitudinal studies will be needed. Second, because the diagnosis of cardiovascular disease was based primarily on history taking and reviewing their medical records, we did not include silent cardiovascular disease that might account for the decreased faPWV in patients with CAD. Third, because of the lack of precise information, we did not distinguish ischemic and hemorrhagic CVD. Therefore, we cannot elucidate possible difference in the association with PWV between these types of
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stroke. Fourth, we measured hfPWV, instead of carotid–femoral (cf) PWV, as the measure for aortic stiffness. It is the European consensus that cfPWV is the gold standard method for arterial stiffness [33]. The measurement of hfPWV is similar to that of cfPWV, both being based on the time delay between the carotid and femoral pulse waves [9,10]. The difference between the two methods is that hfPWV is calculated taking the differences in travelling time and distance between the aortic orifice and the carotid artery into account. In this view, hfPWV is a little more specific to the aorta. Both cfPWV [6] and hfPWV [7] are the independent predictor of cardiovascular disease. Among such cohort studies, the majority of studies employed cfPWV, whereas hfPWV was used only in one study. Since no previous study compared their predictive powers, we do not know which is a better index for central arterial stiffness, or which is a better predictor for future cardiovascular disease. And fifth, LDL-C was calculated by the Friedewald formula, whereas it was directly measured in those with severe hypertriglyceridemia of TG > 400 mg/dL. Although such procedure was in accordance with the clinical practice guidelines [20], the difference between the methods may have affected the results of this study. The number of the subjects with an increased TG > 400 mg/dL was 53 out of 2798 total subjects, indicating that calculated LDL-C levels were used for the great majority of the subjects (98.1%). In addition, we entered the presence of dyslipidemia, not individual lipid values, as a covariate into the multivariate models. Because the subjects with TG > 400 mg/dL were classified as having dyslipidemia regardless of their LDL-C levels, the diagnosis of the presence of dyslipidemia was hardly affected by the methodologies of LDL-C determination. Thus, the difference in LDL-C determination would have only a minor impact, if any, on the major findings of PWV analysis. In conclusion, we demonstrated that aortic PWV was more closely associated with not only CAD but also CVD and PAD than PWVs of the other arterial segments. These results do not prove but support the current concept that central arterial stiffness plays an important role in cardiovascular disease. In clinical practice, the results suggest that the measurement of aortic stiffness is most helpful in the risk assessment of CAD, CVD, and PAD. However, prospective studies are necessary to compare the predictive powers of stiffness of different arterial segments for future events of individual cardiovascular disease. References [1] Smulyan H, Asmar RG, Rudnicki A, London GM, Safar ME. Comparative effects of aging in men and women on the properties of the arterial tree. J Am Coll Cardiol 2001;37:1374–80. [2] London GM. Large artery function and alterations in hypertension. J Hypertens Suppl 1995;13:S35–38. [3] Taniwaki H, Kawagishi T, Emoto M, et al. Correlation between the intima–media thickness of the carotid artery and aortic pulse-wave velocity in patients with type 2 diabetes. Vessel wall properties in type 2 diabetes. Diabetes Care 1999;22:1851–7. [4] London GM, Marchais SJ, Safar ME, et al. Aortic and large artery compliance in end-stage renal failure. Kidney Int 1990;37:137–42. [5] Shoji T, Nishizawa Y, Kawagishi T, et al. Intermediate-density lipoprotein as an independent risk factor for aortic atherosclerosis in hemodialysis patients. J Am Soc Nephrol 1998;9:1277–84. [6] Blacher J, Guerin AP, Pannier B, et al. Impact of aortic stiffness on survival in end-stage renal disease. Circulation 1999;99:2434–9.
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[7] Shoji T, Emoto M, Shinohara K, et al. Diabetes mellitus, aortic stiffness, and cardiovascular mortality in end-stage renal disease. J Am Soc Nephrol 2001;12:2117–24. [8] Cruickshank K, Riste L, Anderson SG, et al. Aortic pulse-wave velocity and its relationship to mortality in diabetes and glucose intolerance: an integrated index of vascular function? Circulation 2002;106:2085–90. [9] Kimoto E, Shoji T, Shinohara K, et al. Preferential stiffening of central over peripheral arteries in type 2 diabetes. Diabetes 2003;52:448–52. [10] Kimoto E, Shoji T, Shinohara K, et al. Regional arterial stiffness in patients with type 2 diabetes and chronic kidney disease. J Am Soc Nephrol 2006;17:2245–52. [11] Waddell TK, Rajkumar C, Cameron JD, et al. Withdrawal of hormonal therapy for 4 weeks decreases arterial compliance in postmenopausal women. J Hypertens 1999;17:413–8. [12] Shige H, Dart A, Nestel P. Simvastatin improves arterial compliance in the lower limb but not in the aorta. Atherosclerosis 2001;155:245–50. [13] Shinohara K, Shoji T, Kimoto E, et al. Effect of atorvastatin on regional arterial stiffness in patients with type 2 diabetes mellitus. J Atheroscler Thromb 2005;12:205–10. [14] Kingwell BA, Waddell TK, Medley TL, Cameron JD, Dart AM. Large artery stiffness predicts ischemic threshold in patients with coronary artery disease. J Am Coll Cardiol 2002;40:773–9. [15] Pannier B, Guerin AP, Marchais SJ, Safar ME, London GM. Stiffness of capacitive and conduit arteries: prognostic significance for end-stage renal disease patients. Hypertension 2005;45:592–6. [16] Hatsuda S, Shoji T, Shinohara K, et al. Regional arterial stiffness associated with ischemic heart disease in type 2 diabetes mellitus. J Atheroscler Thromb 2006;13:114–21. [17] Suzuki E, Kashiwagi A, Nishio Y, et al. Increased arterial wall stiffness limits flow volume in the lower extremities in type 2 diabetic patients. Diabetes Care 2001;24:2107–14. [18] Motobe K, Tomiyama H, Koji Y, et al. Cut-off value of the ankle–brachial pressure index at which the accuracy of brachial–ankle pulse wave velocity measurement is diminished. Circ J 2005;69:55–60. [19] Design and baseline characteristics of a study of primary prevention of coronary events with pravastatin among Japanese with mildly elevated cholesterol levels. Circ J 2004;68:860–7. [20] Japan Atherosclerosis Society (JAS) guidelines for prevention of atherosclerotic cardiovascular diseases. Chapter 2: diagnostic criteria for dyslipidemia. J Atheroscler Thromb 2009;16(Suppl.):7–10. [21] K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis 2002;39:S1–266. [22] Matsuo S, Imai E, Horio M, et al. Revised equations for estimated GFR from serum creatinine in Japan. Am J Kidney Dis 2009;53:982–92. [23] Simonson E, Koff S, Keys A, Minckler J. Contour of the toe pulse, reactive hyperemia, and pulse transmission velocity: group and repeat variability, effect of age, exercise, and disease. Am Heart J 1955;50:260–79. [24] Eliakim M, Sapoznikov D, Weinman J. Pulse wave velocity in healthy subjects and in patients with various disease states. Am Heart J 1971;82:448–57. [25] Safar ME, Laurent S, Asmar RE, Safavian A, London GM. Systolic hypertension in patients with arteriosclerosis obliterans of the lower limbs. Angiology 1987;38:287–95. [26] O’Rourke M. Mechanical principles in arterial disease. Hypertension 1995;26:2–9. [27] Laurent S, Katsahian S, Fassot C, et al. Aortic stiffness is an independent predictor of fatal stroke in essential hypertension. Stroke 2003;34:1203–6. [28] Mattace-Raso FU, van der Cammen TJ, Hofman A, et al. Arterial stiffness and risk of coronary heart disease and stroke: the Rotterdam Study. Circulation 2006;113:657–63. [29] de Leeuw FE, de Groot JC, Bots ML, et al. Carotid atherosclerosis and cerebral white matter lesions in a population based magnetic resonance imaging study. J Neurol 2000;247:291–6. [30] Taniwaki H, Shoji T, Emoto M, et al. Femoral artery wall thickness and stiffness in evaluation of peripheral vascular disease in type 2 diabetes mellitus. Atherosclerosis 2001;158:207–14. [31] Kizu A, Koyama H, Tanaka S, et al. Arterial wall stiffness is associated with peripheral circulation in patients with type 2 diabetes. Atherosclerosis 2003;170:87–91. [32] Yokoyama H, Shoji T, Kimoto E, et al. Pulse wave velocity in lower-limb arteries among diabetic patients with peripheral arterial disease. J Atheroscler Thromb 2003;10:253–8. [33] Laurent S, Cockcroft J, Van Bortel L, et al. Expert consensus document on arterial stiffness: methodological issues and clinical applications. Eur Heart J 2006;27:2588–605.
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Atherosclerosis journal homepage: www.elsevier.com/locate/atherosclerosis
Central versus peripheral arterial stiffness in association with coronary, cerebral and peripheral arterial disease Shoko Tsuchikura ∗ , Tetsuo Shoji , Eiji Kimoto , Kayo Shinohara , Sawako Hatsuda , Hidenori Koyama , Masanori Emoto, Yoshiki Nishizawa Department of Metabolism, Endocrinology and Molecular Medicine, Osaka City University Graduate School of Medicine, 1-4-3, Asahi-machi, Abeno-ku, Osaka 545-8585, Japan
a r t i c l e
i n f o
Article history: Received 16 September 2009 Received in revised form 26 March 2010 Accepted 29 March 2010 Available online 9 April 2010 Keywords: Arterial stiffness Compliance Distensibility Arteriosclerosis Coronary artery disease Cerebrovascular disease Peripheral artery disease
a b s t r a c t Background: Although stiffness of central arteries is more preferentially associated with coronary artery disease (CAD) than that of peripheral arteries, less is known for cerebrovascular disease (CVD) and peripheral artery disease (PAD). We measured pulse wave velocity (PWV) in four arterial segments, and examined the relative changes in the four regional PWVs in patients with CAD, CVD or PAD. Methods: The 2798 subjects were selected from 3300 consecutive participants of our non-invasive vascular lab. 342 subjects had one or more pre-existing atherosclerotic diseases including 128 CAD (N = 128), CVD (N = 195) and PAD (N = 83). PWVs were simultaneously measured using an automated pulse wave analyzer (model BP-203RPE, Colin) in the heart–femoral (hf, aorta), heart–carotid (hc), heart–brachial (hb), and femoral–ankle (fa) segments. Results: As compared to the subjects without atheroscletoric disease, those with CAD, CVD, or PAD showed higher levels of PWV in the four arterial segments, particularly in hfPWV. The relative increase in hfPWV remained significant after adjustment for age, sex, hypertension, pulse rate, smoking, diabetes mellistus, dyslipidemia, and chronic kidney disease. Conclusion: This study indicates that the preferential increase in central arterial stiffness is found not only in CAD but CVD and PAD as well. © 2010 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Arterial stiffness is an independent predictor for cardiovascular disease. Pulse wave velocity (PWV) of the aorta is increased in populations at high risk for cardiovascular disease such as elderly people [1] and patients with hypertension [2], type 2 diabetes mellitus (T2DM) [3], and chronic kidney disease (CKD) [4,5]. Also, aortic PWV predicts mortality from cardiovascular disease [6–8]. Although PWV of the aorta has been used as the standard measure for arterial stiffness, PWV can be determined in other segments of arterial tree. Previous studies revealed that impacts of some risk factors on arterial stiffness varied among different parts of arteries. We [9] previously demonstrated that the effects of age, T2DM on PWV were greater on central arteries than on peripheral arteries. Also, the association of decreased renal function was stronger on central than peripheral arteries in patients with T2DM [10]. In contrast, stiffness of peripheral arteries, as compared to central arteries, appears to be more sensitive to sex hormone [11], and lipid-lowering drugs [12,13]. Thus, arterial stiffening is not a uni-
∗ Corresponding author. Tel.: +81 6 6645 3806; fax: +81 6 6645 3808. E-mail address: [email protected] (S. Tsuchikura). 0021-9150/$ – see front matter © 2010 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.atherosclerosis.2010.03.037
form change, but rather heterogeneous in the arterial system. There is a possibility that patients groups with coronary artery disease (CAD), cerebrovascular disease (CVD) and peripheral artery disease (PAD) show different patterns of regional arterial stiffness, and that increased arterial stiffness is particularly evident in some segments specific to the type of cardiovascular disease. So far, however, no study has directly explored this hypothesis, although a few previous studies reported related observations in patients with CAD [14], CKD [15] and T2DM [16,17]. The purpose of the present study was to identify arterial segments that were most closely associated with the individual cardiovascular disease, namely CAD, CVD and PAD. To this end, we performed cross-sectional analyses using data of participants in our non-invasive vascular lab. 2. Subjects and methods 2.1. Subjects The subjects of this study were selected from 3300 consecutive participants of our vascular lab at the Osaka City University Hospital, including volunteers from the Health Promotion Center in Osaka City, Japan. The study was approved by the
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ethics committee of Graduate School of Medicine, Osaka City University, and all these subjects gave informed consent. We screened our clinical database for subjects who underwent regional PWV measurements performed during July 2000 through May 2009, and identified 3300 subjects. Among them, 289 were excluded because relevant clinical information was lacking. Furthermore, 213 were excluded because of a reduced ankle–brachial pressure index (ABI) less than 0.95, since PWV of leg arteries is known to be influenced in such subjects [18]. Data of the remaining 2798 subjects were used for the subsequent analyses. Among them, 342 subjects had one or more pre-existing atherosclerotic diseases (Fig. 1). Table 1 summarizes the characteristics of the subjects with CAD, CVD, PAD, or without these atherosclerotic disease as defined below. 2.2. Definition of cardiovascular disease Pre-existing cardiovascular diseases were recorded by carefully taking clinical history of each subject. Pre-existing CAD was diagnosed if the subject had a past history of myocardial infarction and/or angina pectoris [19], which had been confirmed by typical symptoms, increased serum levels of myocardial enzymes, electrocardiography, myocardial scintigraphy, or multi-detector computed tomography. In some cases, the diagnosis had been established by coronary angiography, and treated by percutaneous coronary intervention and/or coronary artery bypass grafting. We excluded those complaining equivocal symptoms without objective findings supporting myocardial ischemia. We identified 128 subjects who fulfilled the above criteria for pre-existing CAD. Pre-existing CVD was diagnosed if the subject had a past history of symptomatic cerebral infarction, cerebral hemorrhage, and/or sub-arachnoidal hemorrhage, which had been confirmed
Fig. 1. Chart for subject selection and distribution of atherosclerotic disease. Note that there was overlapping between CAD, CVD and PAD. The group with CAD represents patients with CAD including those with CAD and CVD, CAD and PAD, and all of the three. Abbreviations are: CAD, coronary arterial disease; CVD, cerebrovascular disease; PAD, peripheral arterial disease.
by typical symptoms, computed tomography, and/or magnetic resonance imaging (MRI). Some cases had undergone angiography. We excluded those complaining equivocal head and neck symptoms without objective findings supporting stroke. Also, we did not include asymptomatic subjects with lacunae and/or ischemic
Table 1 Characteristics of the subjects. No athero-sclerotic disease control
Number of subjects Age (years) Male (%) Smoker (%) Diabetes mellitus (%) Hypertension (%) Dyslipidemia (%) Chronic kidney disease (%) Systolic BP (mmHg) Diastolic BP (mmHg) ABI Plasma glucose (mg/dL) Total cholesterol (mg/dL) HDL-C (mg/dL) LDL-C (mg/dL) Triglycerides (mg/dL) eGFR (mL/min/1.73 m2 ) Pulse rate (beats/min) hcPWV (cm/s) hbPWV (cm/s) hfPWV (cm/s) faPWV (cm/s) Use of medications Anti-hypertensives (%) Anti-diabetics (%) Statins (%) Fibrates (%) Other lipid-lowering drugs (%) Anti-platelet drugs (%) Warfarin (%)
Atherosclerotic disease Any of the three
CAD
CVD
PAD
2456 58 ± 12 46.9 41.9 47.5 43.4 68.8 26.0 128 ± 18 77 ± 10 1.1 ± 0.1 118 ± 36 209 ± 42 56 ± 17 126 ± 40 131 ± 102 75 ± 24 66 ± 10 1008 ± 319 628 ± 115 1044 ± 267 1055 ± 153
342 65 ± 9** 67.3** 64.0** 79.2** 68.7** 78.4** 39.8** 133 ± 18** 77 ± 10 1.1 ± 0.1** 125 ± 36** 191 ± 42** 50 ± 16** 114 ± 40** 137 ± 91** 64 ± 26** 68 ± 12** 1172 ±280* 700 ± 118* 1293 ± 310* 1097 ± 164*
128 65 ± 9** 75.0** 64.8** 85.2** 70.3** 85.9** 46.1** 133 ± 18** 77 ± 9 1.1 ± 0.1 129 ± 37** 185 ± 39** 48 ± 15** 109 ± 38** 147 ± 114 60 ± 27** 68 ± 11 1181 ± 270* 698 ± 122* 1311 ± 329* 1060 ± 134
195 66 ± 8** 62.6** 62.6** 84.1** 70.8** 80.5** 40.0** 135 ± 18** 77 ± 11b 1.1 ± 0.1 127 ± 38** 195 ± 40** 50 ± 16** 117 ± 38 131 ± 67** 64 ± 25** 68 ± 12 1173 ± 273* 710 ± 115* 1298 ± 302* 1102 ± 147*
83 66 ± 9** 73.5** 71.1** 72.3** 67.5** 67.5 42.2** 133 ± 21** 76 ± 10 1.1 ± 0.1** 118 ± 35 184 ± 44** 52 ± 18* 105 ± 42** 125 ± 75 68 ± 28* 70 ± 12** 1182 ± 308* 707 ± 118* 1382 ± 339* 1090 ± 209
23 31 21 1.8 0.7 4.6 0.3
60** 69** 41** 2.3** 3.5** 34.5** 2.3**
63** 74** 50** 1.6 4.7** 39.8** 3.9**
61** 74** 41** 3.6* 4.1** 30.8** 0.5
57** 70** 42** 0.0 1.2 45.8** 3.6**
This table gives number of subjects, percentages, and mean ± standard deviation. * P < 0.05, ** P < 0.01 vs. the control group by Student’s t-test. Abbreviations are: CAD, coronary artery disease; CVD, cerebrovascular disease; PAD, peripheral arterial disease; BP, blood pressure; ABI, ankle–brachial pressure index; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; eGFR, estimated glomerular filtration rate; PWV, pulse wave velocity; hc, heart–carotid; hb, heart–brachial; hf, heart–femoral; fa, femoral–ankle.
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changes evidenced by MRI to avoid selection bias, because MRI was not performed in all subjects. We found 195 subjects who had pre-existing CVD as defined above. Since we excluded subjects with a reduced ABI < 0.95, the diagnosis of PAD in this study was based primarily on the history of successful percutaneous interventions, bypass grafting, and/or amputation for PAD. Complaints such as numbness, tingling and weakness of the lower-extremities were not included in the PAD symptoms, because it was difficult to distinguish them from symptoms of peripheral neuropathy. Symptoms due to orthopedic diseases were also excluded. There were 83 subjects with pre-existing PAD fulfilling the above criteria. None of them had undergone bilateral major amputation of the lower-extremities. 2.3. Definition of major risk factors Hypertension was diagnosed if the subject had blood pressure of 140/90 mmHg or higher according to The Japanese Society of Hypertension Guidelines for the Management of Hypertension (JSH 2009), and/or the subject received anti-hypertensive medication. Diabetes mellitus was diagnosed if the subjects had fasting plasma glucose of 126 mg/dL or higher according to the diagnostic criteria by Japan Diabetes Society (JDS 2007), and/or the subject received anti-diabetic medication. Dyslipidemia was diagnosed if the subject had low-density lipoprotein cholesterol of 140 mg/dL or higher, triglycerides of 150 mg/dL or higher, and/or high-density lipoprotein cholesterol lower than 40 mg/dL according to the criteria by Japan Atherosclerosis Society [20], and/or the subject received lipid-lowering medication. Smoking denotes current smoking. Chronic kidney disease (CKD) was diagnosed if the subject had overt proteinuria and/or reduced estimated glomerular filtration rate (eGFR) less than 60 mL/min/1.73 m2 [21].
atherosclerostic disease. If the four arterial segments in the patients are uniformly stiffened, the ratios of the four segments should be at the same level above 1.0. If arterial stiffening is not a uniform change within subjects, the ratios should vary among the four segments, with the difference being detected by analysis of variance for paired data (repeated measure ANOVA). The above did not take the difference in the risk factor profile among the groups. To adjust for the risk factors, we then developed formulas to calculate the expected PWV based on the risk factor profile among the control subjects using multiple regression models. Depending upon the risk factors of interest, various versions of formulas were developed. Then, using these formulas, we calculated expected PWV values based on the subject’s risk factor profile in groups with atherosclerotic disease. Then, the ratio of the actual PWV to the expected PWV was calculated for the four arterial segments for each subject. The four ratios among the different arterial segments were compared by repeated measure ANOVA. Categorical variables were expressed in percentage. Continuous variables were summarized as mean ± standard deviation or mean ± standard error as indicated. Difference in mean between two groups was evaluated by Student t-test. Repeated measure ANOVA was applied to paired data. Multiple logistic regression models were used to analyze associations between PWV of each arterial segment and cardiovascular disease independent of other clinical parameters. P values less than 0.05 was taken as statistically significant. These statistics were performed using StatView 5 (SAS Institute, Cary, NC) and PASW Statistics 17.0 (formerly called SPSS statistics, SPSS Inc, Tokyo) for Windows PC. 3. Results 3.1. Comparison of PWV between subjects with and without atherosclerotic disease
2.4. PWV and blood pressure measurements PWV and blood pressure measurements were performed in the supine position after 5 min bed rest using an automatic waveform analyzer (model BP-203RPE, Colin, Komaki City, Japan) as previously described [9,10,16].The coefficients of variation were 6.0%, 3.3%, 4.9%, 3.3% for hcPWV, hbPWV, hfPWV, and faPWV, respectively [9].
As compared to the subjects without any pre-existing cardiovascular disease (control group), those with either CAD, CVD or PAD showed significantly higher levels in hfPWV, hcPWV and hbPWV (Table 1). The patients with CVD had a higher faPWV than the control group, whereas the difference was not significant for those with CAD or PAD. 3.2. Risk factor profile in groups with atherosclerotic disease
2.5. Other measurements Venous blood was obtained into plastic tubes in the morning after overnight fast. We measured plasma glucose, serum total cholesterol (TC), triglycerides (TG), and creatinine by enzymatic methods using an auto-analyzer. High-density lipoprotein cholesterol level (HDL-C) was measured by a precipitation method. LDL-C was calculated by the Friedewald formula. In subjects with elevated TG > 400 mg/dL, LDL-C was measured by ultracentrifugation or a homogenous assay. We estimated glomerular filtration rate (eGFR) according the formula for the Japanese [22]. Proteinuria was determined by a dip-stick method using spot urine samples obtained in the morning. 2.6. Statistical methods In order to compare the relative changes in PWV among the four arterial segments in patients with atherosclerotic disease as compared to the control group without such disease, we first calculated the ratios of PWV in the patients to the mean PWV level of the control group. Since each patient had four PWV ratios corresponding to the arterial segments, these ratios can be treated as paired data. If atherosclerotic diseases are not associated with PWV at all, the ratios of the four segments should be 1.0 in the group with
As compared to the control group, the groups with either CAD, CVD or PAD showed a higher age, higher percentages of men, smokers, diabetes mellitus, hypertension, and CKD (Table 1). The percentage of dyslipidemia was higher in the CAD and CVD group, but not in the PAD subjects. The PAD group showed a higher pulse rate than the control subjects. 3.3. Logistic regression analysis To examine the association of PWVs of different arterial segments with atherosclerotic disease, we performed two sets of multivariate logistic regression analysis. In the first set of analysis, we searched factors other than PWV which were independently associated with atherosclerotic cardiovascular disease (Table 2). CAD was independently associated with higher age, male sex, diabetes mellitus, dyslipidemia, and CKD. CVD was independently associated with higher age, hypertension, diabetes mellitus, and dyslipidemia. PAD was independently associated with higher age, smoking, and higher pulse rate. Then, in the second set of multivariate logistic regression analysis, we examined the independent association between atherosclerotic cardiovascular disease and PWVs of the four arterial segments after adjustment for the eight covariates identified
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Table 2 Factors independently associated with pre-existing cardiovascular disease. Variables
Any of the three
CAD
***
***
CVD ***
PAD
Age (per 1 year) Sex (male vs. female) Hypertension (presence vs. absence) Diabetes mellitus (presence vs. absence) Dyslipidemia (presence vs. absence) Smoking (smoker vs. non-smoker) Chronic kidney disease (presence vs. absence) Pulse rate (per 1 bpm)
1.07 (1.06–1.09) 1.43* (1.05–1.95) 1.65*** (1.26–2.16) 2.44*** (1.82–3.28) 1.55** (1.15–2.08) 1.96*** (1.45–2.64) 1.22 (0.94–1.59) 1.01 (1.00–1.05)
1.06 (1.04–1.08) 2.31** (1.41–3.81) 1.45 (0.95–2.20) 3.35*** (1.98–5.67) 2.65*** (1.57–4.46) 1.35 (0.86–2.11) 1.52* (1.03–2.25) 1.00 (0.98–1.02)
1.07 (1.05–1.09) 1.00 (0.68–1.47) 1.65** (1.17–2.33) 3.25*** (2.16–4.90) 1.72** (1.17–2.53) 1.99*** (1.36–2.91) 1.19 (0.86–1.65) 1.01 (0.99–1.02)
1.07*** (1.04–1.10) 1.60 (0.87–2.95) 1.51 (0.91–2.51) 1.30 (0.76–2.21) 0.78 (0.49–1.29) 2.40** (1.33–4.31) 1.25 (0.77–2.02) 1.03** (1.01–1.05)
Global model significance
P < 0.0001
P < 0.0001
P < 0.0001
P < 0.0001
The table gives adjusted hazards rations (95% confidence intervals) of the eight factors for the pre-existence of CAD, CVD, PAD and any of the three by multivariate logistic regression models. * P < 0.05, ** P < 0.001, *** P < 0.001. Abbreviations; CAD, coronary arterial disease; CVD, cerebrovascular disease; PAD, peripheral arterial disease; bpm, beats per minute.
above. Each PWV was entered as the ninth variable in the multivariate logistic models (Table 3). In such analyses, increased hfPWV was positively associated with the likelihood to have CAD, CVD and PAD. In contrast, reduced faPWV was positively associated with the likelihood to have CAD. None of CAD, CVD or PAD showed no significant association with hcPWV nor hbPWV independent of the eight covariates. 3.4. Comparison of changes in PWV among the four arterial segments in patients with atherosclerotic disease relative to the controls Fig. 2 (upper panel) shows the comparison of the relative changes in PWV among the four arterial segments in patients with atherosclerotic disease as compared to the control group without such disease. When no adjustment was done for the different risk factor profile between groups, the PWV value relative to the control (ratio to the control mean) in the patients with atherosclerotic disease was the highest for hfPWV and the lowest for faPWV. Although such trend was attenuated to some extent by further adjustment for age, hypertension, pulse rate, and other factors, the difference in relative PWV change among the four arterial segments remained highly significant. In the fully adjusted model, the relative change was in the order of hfPWV > hcPWV > hbPWV > faPWV. Essentially the same was true, when atherosclerotic cardiovascular disease was divided into CAD, CVD, and PAD as shown in Fig. 2 (lower panel). 4. Discussion Increased arterial stiffness is one of the key factors associated with cardiovascular disease. Previous cross-sectional studies [14,16] showed that CAD was more closely associated with increased stiffness of the aorta than other arterial segments. In a longitudinal cohort study in hemodialysis patients [15], death from composite cardiovascular disease including congestive heart failure was independently associated with aortic PWV but not
with PWV of peripheral arteries. In this study, we tested the hypothesis that patient groups with CAD, CVD and PAD show different patterns of regional arterial stiffness, and that increased arterial stiffness is particularly evident in some segments specific to the type of cardiovascular disease. We simultaneously measured PWVs in the four arterial segments as indexes for regional arterial stiffness in 2798 participants at our non-invasive vascular lab. Contrary to the hypothesis, the results clearly indicated that increased aortic PWV was most closely associated with all of CAD, CVD and PAD among the four PWV measurements. This was again confirmed after adjustment for eight major risk factors for cardiovascular disease. This study indicates that the preferential stiffening of the aorta over the other arterial segments is not specific to CAD, but that it can be generalized to other atherosclerotic cardiovascular diseases such as CVD and PAD. There are only a few studies reporting the comparison in the association of cardiovascular disease with stiffness of different arterial segments. Pannier et al. [15] measured PWV of the aorta and arteries in the upper and lower extremities in 305 hemodialysis patients, showing that only PWV of the aorta significantly predicted death from cardiovascular disease. In their study, individual vascular events were combined as cardiovascular disease because of the size of the cohort. According to Kingwell et al. [14], time to STsegment depression during a treadmill exercise test was inversely correlated with aortic PWV but not with femoral–tibial PWV in 96 patients with CAD. We [16] previously evaluated the crosssectional association of CAD with regional PWV measurements, and found that the presence of CAD was more closely associated with aortic PWV than PWV in the heart–brachial, heart–carotid, and femoral–ankle segments in 595 T2DM patients. These studies by Kingwell et al. and by us, however, did not examine the relationship of PWV with other cardiovascular disease than CAD. Regarding regional changes in arterial stiffness in PAD patients, although early studies by Simonson et al. [23], Eliakim et al. [24], and Safar et al. [25] reported normal levels in brachial–radial PWV and the reduction in PWV of the heart–feet and femoral–dorsalis
Table 3 Associations of PWVs in four arterial segments with cardiovascular disease after adjustment for major risk factors. Variables
Any of the three
CAD
CVD
PAD
hfPWV (per 1SD increase) hcPWV (per 1SD increase) hbPWV (per 1SD increase) faPWV (per 1SD increase)
1.40*** (1.19–1.64) 1.01 (0.88–1.16) 1.11 (0.96–1.28) 0.89 (0.77–1.04)
1.26* (1.01–1.58) 0.99 (0.81–1.23) 0.96 (0.77–1.20) 0.60*** (0.47–0.76)
1.28* (1.06–1.55) 1.00 (0.84–1.19) 1.23 (1.03–1.46) 0.94 (0.78–1.13)
1.77*** (1.38–2.28) 1.00 (0.78–1.29) 1.15 (0.89–1.48) 0.81 (0.62–1.06)
The table gives hazards ratios (95% confidence intervals) of PWV of four arterial segments for the pre-existence of CAD, CVD, PAD and any of the three after adjustment for age, sex, hypertension, diabetes mellistus, dyslipidemia, chronic kidney disease, smoking, and pulse rate using multivariate logistic regression models. Note that increased hfPWV was consistently associated with the pre-existence of CAD, CVD, and PAD. Abbreviations; CAD, coronary arterial disease; CVD, cerebrovascular disease; PAD, peripheral arterial disease; PWV, pulse wave velocity; hf, heart–femoral segment; hc, heart–carotid segment; hb, heart–brachial segment; fa, femoral–ankle segment; SD, standard deviation.
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Fig. 2. PWV in subjects with atherosclerotic disease relative to the controls without atherosclerotic disease. PWV values of the four arterial segments in subjects with pre-existing atherosclerotic disease were expressed as the ratios relative to the corresponding PWV values in the subjects with no atherosclerotic disease (control group), and comparison among the four arterial segments was performed by repeated measure analysis of variance. Mean ± standard error. Comparison was done with four versions of adjustment as indicated in the insert. The full adjustment was made for 8 factors including age, sex, hypertension, pulse rate, smoking, diabetes mellitus, dyslipidemia, and chronic kidney disease. Abbreviations are: CAD, coronary artery disease; CVD, cerebrovascluar disease; PAD, peripheral artery disease; hf, heart–femoral; hc, heart–carotid; hb, heart–brachial; fa, femoral–ankle; PWV, pulse wave velocity; HT, hypertension; PR, pulse rate.
segments, information is lacking about central arterial stiffness in PAD. Thus, the present study confirmed the previous findings regarding CAD and aortic stiffness in much larger number of subjects, and extended the similar knowledge to CVD and PAD. Stiffness of the aorta and its primary branches (central arteries) is implicated in the development of CAD [26]. Stiffening of central arteries increases systolic pressure, decreases diastolic pressure, resulting in increased pulse pressure. The increased systolic pressure increases cardiac afterload, left ventricular mass, and oxygen demand in one hand. In the other hand, the decrease in diastolic pressure can reduce coronary blood flow during the diastole. These changes can results in development and worsening of CAD. We showed the higher association of cerebrovascular disase with PWV of the aorta than PWV of other arterial segments. Laurent et al. [27] reported that aortic PWV was an independent predictor of stroke death in 1715 patients with essential hypertension. In 2835 subjects of the Rotterdam study [28], aortic PWV predicted the occurrence of CAD and stroke, but carotid distensibility did not. Thus, aortic stiffness may have more important roles in stroke than stiffness of other arterial segments. This may be explained by several mechanisms. First, aortic stiffening may increase pulse pressure and mechanical stretching of arterial cells, which then may stimulate arterial remodeling, increasing carotid arterial thickness and plaque formation. These morphological changes in the
carotid arteries were reported to positively correlate with cerebral white matter lesions [29]. Second, because cerebral hemorrhage and infarction occur most frequently in the area of small perforating arteries that are exposed to high pressure and large pressure gradient, these cerebral ‘strain vessels’ may be more susceptible to increased pulsatility of aortic pressure. Third, aortic PWV may also reflect parallel changes in cerebral vasculature. Increased aortic stiffness is caused by various alterations, including fibrosis, medial smooth muscle necrosis, elastin fiber degeneration, calcifications, and diffusion of macromolecules within the arterial wall. These have also been described at the site of the cerebral vasculature. However, the third mechanism does not fully explain the preferential association between cerebrovascular disease and PWV of the aorta over other arterial segments. With regard to PAD, Safar et al. [25] previously reported that patients with PAD had normal PWV of brachial arteries and increased brachial pulse pressure as compared with those of ageand sex-matched controls. Although increased pulse pressure is suggestive of increase in central arterial stiffness, no direct measurement was reported. Suzuki et al. [17] showed that a higher brachial–ankle PWV was associated with reduced blood flow of popliteal arteries in 60 patients with T2DM having normal ABI, but they did not compare the effects of brachial–ankle PWV with PWVs of other arterial segments on the blood flow of the lower extremities. We previously reported that stiffness parameter ˇ measured at the femoral artery was independently associated with ischemic leg symptoms in 315 patients with T2DM [30]. Also, decrease in transcutaneous oxygen tension (TcPO2 ) of foot during a treadmill exercise was significantly correlated with stiffness parameter ˇ of femoral artery, but not of carotid artery in 68 patients with T2DM [31]. The present results indicate preferential association of PAD with aortic PWV over PWV of other arterial regions. Taken together, ischemia of lower-extremities appears to be related with arterial stiffness of upstream rather than downstream. As Suzuki et al. [17] showed, arterial stiffness was closely associated with popliteal blood flow during the diastole, presumably due to impairment in ‘the second heart’ function of the central arteries. We found the paradoxical association between reduced faPWV and CAD. This association remained significant even after adjustment for eight factors. We do not know the precise mechanisms for it, but there are a few possibilities that may explain the finding. First, some of CAD patients had impaired leg circulation that was not evident from ABI. It is reported that PWV of the lowerlimb arteries is decreased in the presence of significant stenosis in these arteries [23,24,32]. It is also known that, calcified arteries are often incompressible, resulting in higher ABI and masking the presence of PAD. In this study, 24 patients out of 128 CAD patients (19%) were also complicated with PAD, whereas 22 patients out of 195 CVD patients (11%) had PAD, suggesting a higher prevalence of leg artery lesions in CAD patients. Thus, we speculate such occult lesions in leg arteries may be one of the reasons for the paradoxical finding with CAD. Second, the use of statin may be related to the decreased faPWV in CAD patients, because statins are known to decrease stiffness of lower-limb arteries [12,13]. The percentage of statin use was the highest in the patients with CAD (50%) and the lowest in the control group (21%). There are several limitations in this study that should be noted. First, because of the cross-sectional nature, this study does not indicate causality. To examine it, longitudinal studies will be needed. Second, because the diagnosis of cardiovascular disease was based primarily on history taking and reviewing their medical records, we did not include silent cardiovascular disease that might account for the decreased faPWV in patients with CAD. Third, because of the lack of precise information, we did not distinguish ischemic and hemorrhagic CVD. Therefore, we cannot elucidate possible difference in the association with PWV between these types of
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stroke. Fourth, we measured hfPWV, instead of carotid–femoral (cf) PWV, as the measure for aortic stiffness. It is the European consensus that cfPWV is the gold standard method for arterial stiffness [33]. The measurement of hfPWV is similar to that of cfPWV, both being based on the time delay between the carotid and femoral pulse waves [9,10]. The difference between the two methods is that hfPWV is calculated taking the differences in travelling time and distance between the aortic orifice and the carotid artery into account. In this view, hfPWV is a little more specific to the aorta. Both cfPWV [6] and hfPWV [7] are the independent predictor of cardiovascular disease. Among such cohort studies, the majority of studies employed cfPWV, whereas hfPWV was used only in one study. Since no previous study compared their predictive powers, we do not know which is a better index for central arterial stiffness, or which is a better predictor for future cardiovascular disease. And fifth, LDL-C was calculated by the Friedewald formula, whereas it was directly measured in those with severe hypertriglyceridemia of TG > 400 mg/dL. Although such procedure was in accordance with the clinical practice guidelines [20], the difference between the methods may have affected the results of this study. The number of the subjects with an increased TG > 400 mg/dL was 53 out of 2798 total subjects, indicating that calculated LDL-C levels were used for the great majority of the subjects (98.1%). In addition, we entered the presence of dyslipidemia, not individual lipid values, as a covariate into the multivariate models. Because the subjects with TG > 400 mg/dL were classified as having dyslipidemia regardless of their LDL-C levels, the diagnosis of the presence of dyslipidemia was hardly affected by the methodologies of LDL-C determination. Thus, the difference in LDL-C determination would have only a minor impact, if any, on the major findings of PWV analysis. In conclusion, we demonstrated that aortic PWV was more closely associated with not only CAD but also CVD and PAD than PWVs of the other arterial segments. These results do not prove but support the current concept that central arterial stiffness plays an important role in cardiovascular disease. In clinical practice, the results suggest that the measurement of aortic stiffness is most helpful in the risk assessment of CAD, CVD, and PAD. However, prospective studies are necessary to compare the predictive powers of stiffness of different arterial segments for future events of individual cardiovascular disease. References [1] Smulyan H, Asmar RG, Rudnicki A, London GM, Safar ME. Comparative effects of aging in men and women on the properties of the arterial tree. J Am Coll Cardiol 2001;37:1374–80. [2] London GM. Large artery function and alterations in hypertension. J Hypertens Suppl 1995;13:S35–38. [3] Taniwaki H, Kawagishi T, Emoto M, et al. Correlation between the intima–media thickness of the carotid artery and aortic pulse-wave velocity in patients with type 2 diabetes. Vessel wall properties in type 2 diabetes. Diabetes Care 1999;22:1851–7. [4] London GM, Marchais SJ, Safar ME, et al. Aortic and large artery compliance in end-stage renal failure. Kidney Int 1990;37:137–42. [5] Shoji T, Nishizawa Y, Kawagishi T, et al. Intermediate-density lipoprotein as an independent risk factor for aortic atherosclerosis in hemodialysis patients. J Am Soc Nephrol 1998;9:1277–84. [6] Blacher J, Guerin AP, Pannier B, et al. Impact of aortic stiffness on survival in end-stage renal disease. Circulation 1999;99:2434–9.
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