Abstract
Background. Atrial fibrillation (AF) and vascular disease share several risk factors and the two diseases often coexist. Heart rate (HR) is reported to be a major determinant of arterial stiffness. AF patients often have a transiently or persistently rapid HR. Hence, this study was to assess whether AF was significantly associated with arterial stiffness and HR could significantly influence the relationship between AF and arterial stiffness. Besides, we also determine the main correlates of arterial stiffness in AF patients and see whether HR was correlated with arterial stiffness in these patients.
Methods. We included 166 AF and 1336 non-AF patients from subjects arranged for echocardiographic examinations. Arterial stiffness was assessed by brachial-ankle pulse wave velocity (baPWV).
Results. Compared to non-AF patients, AF patients had a higher baPWV (p <0.001). In a multivariate model, including covariates of age, sex, blood pressures and so on, the presence of AF was significantly associated with baPWV (β = 0.079, P = 0.001). However, further adjustment for HR made this association disappear (β = 0.005, P = 0.832). In addition to age and systolic blood pressure, increased HR (β = 0.309, p <0.001) was a major determinant of increased baPWV in our AF patients.
Conclusions. This study demonstrated the presence of AF was associated with increased baPWV, but this association became insignificant after further adjustment for HR, which suggested HR could significantly influence the relationship between AF and baPWV. Besides, HR was positively correlated with arterial stiffness in our AF patients.
Keywords: atrial fibrillation, arterial stiffness, pulse wave velocity, heart rate
Introduction
Vascular disease has been found to increase the risk of atrial fibrillation (AF) 1, 2 and AF has similarly been shown to be a major risk factor of vascular disease 1, 3, 4. AF and vascular disease share several risk factors, including old age, obesity, diabetes, heart failure and hypertension, and the two diseases often coexist 2, 5, 6. Therefore, the presence of AF may have an influence on the vascular function.
Pulse wave velocity (PWV) reflects arterial stiffness and is a useful indicator of both the severity of vascular damage and the prognosis of cardiovascular and renal diseases 7-13. To assess arterial stiffness, many noninvasive methods have been developed, and they usually require expertise techniques 14. A clinical device, ABI-form (VP1000; Colin Co. Ltd., Komaki, Japan), has been developed to automatically and simultaneously record pulse waves of the brachial and posterior tibial arteries, using an automated oscillometric method. Using this device, we can easily and automatically calculate the brachial-ankle PWV (baPWV) 15, 16. The baPWV has been reported as a good marker for arterial stiffness 16.
Several studies have demonstrated that heart rate (HR) is positively associated with arterial stiffness 17-19. AF patients often have a transiently or persistently rapid HR, so AF patients may have an increased arterial stiffness and HR may significantly influence the relationship between AF and arterial stiffness. Besides, although tachycardia-induced cardiomyopathy is a well-known reason of cardiac dysfunction in patients with AF 20, there is no study to evaluate whether tachycardia is also correlated with vascular dysfunction in these patients.
Hence, the first aim of this study was to compare baPWV between patients with and without AF and see whether AF patients had an increased arterial stiffness. The second aim of this study was to assess whether AF per se was a major determinant of increased arterial stiffness and whether HR could significantly influence the relationship between AF and arterial stiffness. The third aim of this study was to determine the main correlates of baPWV in AF patients and see whether HR was a major determinant of arterial stiffness in these patients.
Methods
Study patients
This was a cross-sectional study. Study subjects were prospectively included from a group of patients who arranged for echocardiographic examinations at Kaohsiung Municipal Hsiao-Kang Hospital. Patients with inadequate image visualization were excluded. AF patients were consecutively included. However, non-AF patients were not consecutively included because baPWV measurement must be performed within 10 minutes after the completion of echocardiographic examination. Finally, 166 patients with persistent or permanent AF and 1336 non-AF patients were included in this study.
Ethics Statement
The study protocol was approved by the institutional review board of the Kaohsiung Medical University Hospital (KMUH-IRB-20130014). Informed consents have been obtained in written form from patients and all clinical investigation was conducted according to the principles expressed in the Declaration of Helsinki. The patients gave consent for the publication of the clinical details.
Assessment of baPWV
After at least 10 minutes of rest from the beginning of echocardiographic examination, baPWV was assessed using an ABI-form device, which automatically and simultaneously measures blood pressure in both arms and ankles using an oscillometric method 15. For measuring baPWV, pulse waves that were obtained from the brachial and tibial arteries were recorded simultaneously and the transmission time, which was defined as the time interval between the initial increase in brachial and tibial waveforms, was determined. The transmission distance from the arm to each ankle was calculated according to body height. The value of baPWV was automatically computed as the transmission distance divided by the transmission time. HR, systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured by the same device. In non-AF patients, the examination of ABI-form device was performed once. The average of bilateral baPWV values and the averages of SBP and DBP of bilateral arms were used for later analysis. In AF patients, the examination of ABI-form device was performed thrice and the average of 6 baPWV values, the average of 3 values of HR and the averages of 6 values of SBP and DBP obtained from the repeated examinations were used for later analysis.
Collection of demographic, medical and laboratory data
Demographic and medical data including age, gender, history of diabetes mellitus, hypertension, cerebrovascular accident, smoking and chronic heart failure and body mass index were obtained from medical records or interviews with patients. Body mass index was calculated as the ratio of weight in kilograms divided by the square of height in meters. Laboratory data including total cholesterol and triglyceride were also collected. The value of estimated glomerular filtration rate (eGFR) was calculated using the 4-variable equation in the Modification of Diet in Renal Disease study 21. In addition, information regarding patient medications including angiotensin converting enzyme inhibitors (ACEIs), angiotensin II receptor blockers (ARBs), β-blockers, calcium channel blockers (CCBs) and diuretics during the study period was obtained from medical records.
Statistical analysis
SPSS 18.0 software (SPSS, Chicago, IL, USA) was used for statistical analysis. Data were expressed as mean ± standard deviation or percentage. Continuous and categorical variables between groups were compared by independent samples t-test and Chi-square test, respectively. The multiple linear regression analysis was employed to identify the determinants of baPWV. The impact of HR on the relationship between AF and baPWV was assessed by a modified stepwise procedure in 4 modeling steps. The first model consisted of age and SBP. The second model consisted of the significant variables in the univariate analysis except HR. The third step was adding HR. To avoid over-adjustment of HR, we further performed an interaction-analysis in the final model by adding a variable of AF × HR. All tests were 2-sided and the level of significance was established as P < 0.05.
Results
Table 1 showed the comparison of baseline characteristics between patients with and without AF. Compared to patients without AF, patients with AF had a higher baPWV, older age, lower prevalence of female gender, higher HR, lower SBP and DBP, lower prevalence of hypertension, higher prevalence of cerebrovascular accident and chronic heart failure, lower total cholesterol and triglyceride and higher percentage of ACEI and/or ARB and diuretic uses.
Table 1.
Comparison of baPWV and baseline characteristics between patients with and without AF
| Characteristics | Patients with AF (n = 166) | Patients without AF (n = 1336) | P |
|---|---|---|---|
| baPWV (cm/s) | 1940 ± 526 | 1731 ± 438 | <0.001 |
| Age (yr) | 69 ± 10 | 61 ± 14 | <0.001 |
| Female gender (%) | 33 | 44 | 0.008 |
| HR (min-1) | 85 ± 18 | 70 ± 13 | <0.001 |
| SBP (mmHg) | 132 ± 17 | 136 ± 21 | 0.031 |
| DBP (mmHg) | 75 ± 11 | 77 ± 12 | 0.010 |
| BMI (kg/m2) | 26.2 ± 4.2 | 26.1 ± 4.0 | 0.706 |
| Diabetes mellitus (%) | 30 | 29 | 0.681 |
| Hypertension (%) | 60 | 69 | 0.025 |
| CVA (%) | 17 | 6 | <0.001 |
| CHF (%) | 30 | 9 | <0.001 |
| Smoking (%) | 15 | 15 | 1.000 |
| Total cholesterol (mg/dL) | 177 ± 37 | 191 ± 44 | <0.001 |
| Triglyceride (mg/dL) | 122 ± 72 | 155 ± 150 | 0.016 |
| eGFR (mL/min/1.73 m2) | 58 ± 18 | 57 ± 21 | 0.544 |
| Medications | |||
| ACEIs and/or ARBs (%) | 61 | 54 | 0.039 |
| β blockers (%) | 47 | 40 | 0.075 |
| CCBs (%) | 33 | 35 | 0.569 |
| Diuretics (%) | 42 | 28 | <0.001 |
baPWV: brachial-ankle pulse wave velocity; AF: atrial fibrillation; HR: heart rate; SBP: systolic blood pressure; DBP: diastolic blood pressure; BMI: body mass index; CVA: cerebrovascular accident; CHF: chronic heart failure; eGFR: estimated glomerular filtration rate; ACEI, angiotensin converting enzyme inhibitor; ARB, angiotensin II receptor blocker; CCB: calcium channel blocker
In a univariate analysis, baPWV had a positively correlation with the presence of AF, age, female gender, HR, SBP and DBP, diabetes, hypertension, cerebrovascular accident and using of ACEIs and/or ARBs, CCBs and diuretics and negatively correlation with body mass index, smoking, triglyceride and eGFR (P ≦ 0.024). After a multivariate analysis, increased baPWV was associated positively with age, HR, SBP, DBP, and cerebrovascular accident and negatively with body mass index (P ≦0.019). A multiple linear regression equation showed that baPWV = -777.106 + 14.155 × (age) + 7.036 × (HR) + 9.266 × (SBP) + 1.698 × (DBP) + 104.167 × (cerebrovascular accident) - 9.526 × (body mass index). Table 2 displays the non-standardized coefficient, standardized coefficient β and coefficient of determination (R2) estimates for baPWV by the presence of AF with and without adjustment for demographic, clinical and biochemical parameters, HR and AF × HR. The presence of AF was associated with baPWV in the age- and SBP-adjusted model (standardized coefficient β = 0.106; 95% confidence interval [CI], 98 to 209; P < 0.001) and in the multivariate model adjusting for the significant variables in the univariate analysis except HR (standardized coefficient β = 0.079; 95% CI, 40 to 163; P = 0.001). This relation between AF and baPWV was disappeared after adjustment for HR (standardized coefficient β = 0.005; 95% CI, -58 to 72; P = 0.832). The association between AF and baPWV was still insignificant after further adjustment for AF × HR (standardized coefficient β = 0.232; 95% CI, -12 to 615; P = 0.059).
Table 2.
Relation of AF to baPWV
| AF | baPWV | ||||
|---|---|---|---|---|---|
| Non-standardized Coefficient |
Standardized Coefficient β |
95% CI | P | R2 | |
| Unadjusted | 208.437 | 0.143 | 135 - 282 | < 0.001 | 0.020 |
| Age and SBP adjusted | 153.647 | 0.106 | 98 - 209 | < 0.001 | 0.469 |
| Multivariate adjusted (1) | 101.785 | 0.079 | 40 - 163 | 0.001 | 0.520 |
| Multivariate adjusted (2) | 7.068 | 0.005 | -58 - 72 | 0.832 | 0.549 |
| Multivariate adjusted (3) | 301.537 | 0.232 | -12 - 615 | 0.059 | 0.551 |
CI: confidence interval; R2: coefficient of determination. The other abbreviations are the same as in Table 1.
Multivariate model (1): adjusted for age, sex, SBP, DBP, BMI, diabetes mellitus, hypertension, CVA, smoking, eGFR, triglyceride, ACEI/ARB use, CCB use, diuretic use.
Multivariate model (2): model (1) + HR.
Multivariate model (3): model (2) + AF × HR.
Table 3 shows the correlates of baPWV in patients with AF. In the univariate analysis, increased age, female gender, increased HR, high SBP and DBP, low body mass index, non-smoking and decreased eGFR were independently associated with increased baPWV. After the multivariate analysis, old age, high SBP and increased HR were still the major determinants of increased baPWV in our AF patients.
Table 3.
Univariate and multivariate correlates of baPWV in patients with AF
| Univariate analysis | Multivariate analysis | ||||
|---|---|---|---|---|---|
| Standardized coefficient β | p | Standardized coefficient β | P | ||
| Age (yr) | 0.505 | <0.001 | 0.422 | <0.001 | |
| Female gender | 0.213 | 0.007 | 0.017 | 0.811 | |
| HR (min-1) | 0.166 | 0.038 | 0.309 | <0.001 | |
| SBP (mmHg) | 0.457 | <0.001 | 0.479 | <0.001 | |
| DBP (mmHg) | 0.262 | 0.001 | -0.119 | 0.240 | |
| BMI (kg/m2) | -0.18 | 0.026 | -0.085 | 0.210 | |
| Diabetes mellitus | 0.047 | 0.556 | |||
| Hypertension | 0.015 | 0.852 | |||
| CVA | 0.045 | 0.571 | |||
| CHF | -0.004 | 0.957 | |||
| Smoking | - 0.167 | 0.037 | -0.063 | 0.379 | |
| Total cholesterol (mg/dL) | 0.134 | 0.150 | |||
| Triglyceride (mg/dL) | -0.093 | 0.318 | |||
| eGFR (mL/min/1.73 m2) | -0.198 | 0.014 | -0.025 | 0.725 | |
| Medications | |||||
| ACEIs and/or ARBs | -0.076 | 0.343 | |||
| β blockers | -0.058 | 0.469 | |||
| CCBs | 0.123 | 0.124 | |||
| Diuretics | 0.022 | 0.783 | |||
Abbreviations are the same as in Table 1.
Discussion
In the present study, we compared baPWV between patients with and without AF and evaluated the determinants of baPWV in all patients and in patients with AF. We found that compared to non-AF patients, AF patients had a higher baPWV. AF was significantly associated with increased baPWV even after adjusting for demographic, clinical and biochemical risk factors. However, additional adjustment for HR made the association between AF and baPWV disappear. In order to avoid over-adjustment of HR, we further adjusted AF × HR, but AF was still not associated with baPWV in the final model of Table 2. Hence, HR had an important impact on the relationship between AF and baPWV. Furthermore, in addition to old age and high SBP, increased HR was also an important determinant of baPWV in our AF patients.
AF is the most common cardiac arrhythmia in clinical practice. AF shares several risk factors and pathophysiological features with atherosclerosis. In fact, peripheral vascular disease is highly prevalent in AF patients and associates with increased mortality 1, 2, 5, 6. Lee et al. evaluated the effects of AF on arterial stiffness in patients with hypertension and found the presence of AF was significantly correlated with a higher PWV, independently of age or blood pressure in their patients 22. In this study, we also demonstrated patients with AF had a higher baPWV than those without AF. After adjustment for many confounding factors, including age and SBP, this association remained significant. However, after additional adjustment for HR, such association disappeared. This association was still insignificant ever after further adjustment for AF × HR. Hence, HR could significantly influence the relationship between AF and baPWV in our present study. Several studies showed HR was significantly associated with arterial stiffness 17-19. Some mechanisms might explain the significant association between increased HR and arterial stiffness. First, a higher HR might suggest a higher sympathetic tone 23, which might result in increased vascular tone and resistance. Increased sympathetic tone was positively correlated with a higher rate of oxygen consumption and increased production of proinflammatory cytokines 24. These cytokines might cause endothelial dysfunction and alter arterial elastic properties, leading to structural stiffness. Second, an increased HR might also reflect an increased metabolic rate, leading to increased oxidative stress and chronic low-grade inflammation 19. Therefore, increased HR and arterial stiffness might be linked by a chronic low-grade inflammation in the vessel walls. Third, HR might impact directly on the status of the arterial wall, probably because of mechanical pulsatile stress, and also possibly involving the proinflammatory actions of oscillatory fluid shear stresses acting on the vascular endothelium 25. High HR was reported to be strongly and directly associated with increased arterial rigidity in hypertensive patients, independent of age and blood pressure 26. In fact, further adjustment for HR substantially attenuated the association between AF and arterial stiffness in the present study. Hence, AF per se might be not a major determinant of arterial stiffness in this study. The higher baPWV in our AF patients was probably resulted from the higher HR in these patients.
In this study, age, SBP and HR were the major determinants of baPWV in our AF patients. Old age and high SBP were well-established parameters of increased arterial stiffness in non-AF patients 27-30. Our study in AF patients was consistent with these well-established findings. However, whether HR also influences PWV remains controversial. Several cross-sectional population studies in non-AF patients have found either no correlation 31, 32 or a positive correlation between PWV and resting HR 19, 33. Lee et al. evaluated the determinants of PWV in 68 patients combined non-AF and AF and found HR had no correlation with PWV 22. Discrepancies in results from these studies might be explained, in part, by different study populations and methodologies in measuring PWV. In the present study, we found HR was a major determinate of baPWV in AF patients. Hence, rapid ventricular response in AF may be a risk factor of increased arterial stiffness. Good rate control in AF patients may be beneficial in reducing the arterial stiffness.
Obesity might be associated with early vascular changes. Some studies had demonstrated an association between obesity and increased aortic stiffness 34-36. However, Rodrigues et al. found carotid-femoral PWV was negatively correlated with body mass index and concluded that the previously reported finding of an association between obesity and aortic stiffness was probably confounded by the progressive increase in blood pressure observed in obesity 37. In this study, we similarly found body mass index had a negative correlation with baPWV in our AF patients in the univariate analysis. After the multivariate analysis, the associate between body mass index and baPWV disappeared. Hence, obesity was not a major determinant of baPWV in our AF patients. Because the effect of smoking discontinuation on arterial stiffness remained uncertain, previous studies showed no difference in arterial stiffness between nonsmokers and long-term smokers 38, 39. In our study, after the multivariate analysis, we similarly found smoking was not associated with baPWV both in all study patients and in AF patients.
Impairment of renal function might increase arterial stiffness. Several studies had shown decreased eGFR had a significant association with increased arterial stiffness in non-AF patients 13, 40, 41. In our AF patients, we consistently found eGFR had a negative correlation with baPWV in the univariate analysis. However, after the multivariate analysis, this correlation disappeared. Hence, the association between eGFR and baPWV in our AF patients was probably confounded by age, SBP and HR.
Study limitations
The majority of our patients were treated chronically with antihypertensive medications. For ethical reasons, we did not withdraw these medications. Hence, we could not exclude the influence of antihypertensive agents on our findings. However, in order to minimize the influence of drugs, we had added different classes of antihypertensive drugs in the multivariate analysis. Although we averaged the values of blood pressures, HR and baPWV from 3 time examination in AF patients, the beat-to-beat variation of these values during AF might make the measurement technically difficult and inaccurate. In addition, only resting HR was measured in this study. The evaluation of HR by 24-hour Holter monitoring should be more accurate and reliable than only evaluation of resting HR.
Conclusions
This study demonstrated the presence of AF was associated with increased baPWV in a multivariate model, but this association became insignificant after further adjustment for HR, which suggested HR could significantly influence the relationship between AF and baPWV. Hence, an association between AF and arterial stiffness was probably confounded by the increased HR in AF patients. Besides, HR was positively correlated with arterial stiffness in our AF patients.
References
- 1.Goto S, Bhatt DL, Rother J, Alberts M, Hill MD, Ikeda Y. et al. Prevalence, clinical profile, and cardiovascular outcomes of atrial fibrillation patients with atherothrombosis. Am Heart J. 2008;156:855–63. doi: 10.1016/j.ahj.2008.06.029. [DOI] [PubMed] [Google Scholar]
- 2.Benjamin EJ, Levy D, Vaziri SM, D'Agostino RB, Belanger AJ, Wolf PA. Independent risk factors for atrial fibrillation in a population-based cohort. The Framingham Heart Study. JAMA. 1994;271:840–4. [PubMed] [Google Scholar]
- 3.Conway DS, Lip GY. Comparison of outcomes of patients with symptomatic peripheral artery disease with and without atrial fibrillation (the West Birmingham Atrial Fibrillation Project) Am J Cardiol. 2004;93:1422–5. doi: 10.1016/j.amjcard.2004.02.047. [DOI] [PubMed] [Google Scholar]
- 4.Conen D, Chae CU, Glynn RJ, Tedrow UB, Everett BM, Buring JE. et al. Risk of death and cardiovascular events in initially healthy women with new-onset atrial fibrillation. JAMA. 2011;305:2080–7. doi: 10.1001/jama.2011.659. doi:10.1001/jama.2011.659. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Depta JP, Bhatt DL. Atherothrombosis and atrial fibrillation: Important and often overlapping clinical syndromes. Thromb Haemost. 2010;104:657–63. doi: 10.1160/TH10-05-0332. doi:10.1160/th10-05-0332. [DOI] [PubMed] [Google Scholar]
- 6.Kannel WB, Wolf PA, Benjamin EJ, Levy D. Prevalence, incidence, prognosis, and predisposing conditions for atrial fibrillation: population-based estimates. Am J Cardiol. 1998;82:2N–9N. doi: 10.1016/s0002-9149(98)00583-9. [DOI] [PubMed] [Google Scholar]
- 7.van Popele NM, Grobbee DE, Bots ML, Asmar R, Topouchian J, Reneman RS. et al. Association between arterial stiffness and atherosclerosis: the Rotterdam Study. Stroke. 2001;32:454–60. doi: 10.1161/01.str.32.2.454. [DOI] [PubMed] [Google Scholar]
- 8.Laurent S, Boutouyrie P, Asmar R, Gautier I, Laloux B, Guize L. et al. Aortic stiffness is an independent predictor of all-cause and cardiovascular mortality in hypertensive patients. Hypertension. 2001;37:1236–41. doi: 10.1161/01.hyp.37.5.1236. [DOI] [PubMed] [Google Scholar]
- 9.Cruickshank K, Riste L, Anderson SG, Wright JS, Dunn G, Gosling RG. 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. doi: 10.1161/01.cir.0000033824.02722.f7. [DOI] [PubMed] [Google Scholar]
- 10.Chen SC, Chang JM, Tsai YC, Su HM, Chen HC. Brachial-ankle pulse wave velocity and brachial pre-ejection period to ejection time ratio with renal outcomes in chronic kidney disease. Hypertens Res. 2012;35:1159–63. doi: 10.1038/hr.2012.114. doi:10.1038/hr.2012.114. [DOI] [PubMed] [Google Scholar]
- 11.Su HM, Lin TH, Hsu PC, Chu CY, Lee WH, Tsai WC. et al. Brachial-ankle pulse wave velocity and systolic time intervals in risk stratification for progression of renal function decline. Am J Hypertens. 2012;25:1002–10. doi: 10.1038/ajh.2012.77. doi:10.1038/ajh.2012.77. [DOI] [PubMed] [Google Scholar]
- 12.Chen SC, Lin TH, Hsu PC, Chang JM, Lee CS, Tsai WC. et al. Impaired left ventricular systolic function and increased brachial-ankle pulse-wave velocity are independently associated with rapid renal function progression. Hypertens Res. 2011;34:1052–8. doi: 10.1038/hr.2011.95. doi:10.1038/hr.2011.95. [DOI] [PubMed] [Google Scholar]
- 13.Chen SC, Chang JM, Liu WC, Tsai YC, Tsai JC, Hsu PC. et al. Brachial-ankle pulse wave velocity and rate of renal function decline and mortality in chronic kidney disease. Clin J Am Soc Nephrol. 2011;6:724–32. doi: 10.2215/CJN.07700910. doi:10.2215/cjn.07700910. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Oliver JJ, Webb DJ. Noninvasive assessment of arterial stiffness and risk of atherosclerotic events. Arterioscler Thromb Vasc Biol. 2003;23:554–66. doi: 10.1161/01.ATV.0000060460.52916.D6. doi:10.1161/01.atv.0000060460.52916.d6. [DOI] [PubMed] [Google Scholar]
- 15.Tomiyama H, Yamashina A, Arai T, Hirose K, Koji Y, Chikamori T. et al. Influences of age and gender on results of noninvasive brachial-ankle pulse wave velocity measurement--a survey of 12517 subjects. Atherosclerosis. 2003;166:303–9. doi: 10.1016/s0021-9150(02)00332-5. [DOI] [PubMed] [Google Scholar]
- 16.Yamashina A, Tomiyama H, Takeda K, Tsuda H, Arai T, Hirose K. et al. Validity, reproducibility, and clinical significance of noninvasive brachial-ankle pulse wave velocity measurement. Hypertens Res. 2002;25:359–64. doi: 10.1291/hypres.25.359. [DOI] [PubMed] [Google Scholar]
- 17.Su HM, Lee KT, Chu CS, Lee MY, Lin TH, Voon WC. et al. Effects of heart rate on brachial-ankle pulse wave velocity and ankle-brachial pressure index in patients without significant organic heart disease. Angiology. 2007;58:67–74. doi: 10.1177/0003319706295481. doi:10.1177/0003319706295481. [DOI] [PubMed] [Google Scholar]
- 18.Lantelme P, Mestre C, Lievre M, Gressard A, Milon H. Heart rate: an important confounder of pulse wave velocity assessment. Hypertension. 2002;39:1083–7. doi: 10.1161/01.hyp.0000019132.41066.95. [DOI] [PubMed] [Google Scholar]
- 19.Park BJ, Lee HR, Shim JY, Lee JH, Jung DH, Lee YJ. Association between resting heart rate and arterial stiffness in Korean adults. Arch Cardiovasc Dis. 2010;103:246–52. doi: 10.1016/j.acvd.2010.03.004. doi:10.1016/j.acvd.2010.03.004. [DOI] [PubMed] [Google Scholar]
- 20.Shinbane JS, Wood MA, Jensen DN, Ellenbogen KA, Fitzpatrick AP, Scheinman MM. Tachycardia-induced cardiomyopathy: a review of animal models and clinical studies. J Am Coll Cardiol. 1997;29:709–15. doi: 10.1016/s0735-1097(96)00592-x. [DOI] [PubMed] [Google Scholar]
- 21.Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med. 1999;130:461–70. doi: 10.7326/0003-4819-130-6-199903160-00002. [DOI] [PubMed] [Google Scholar]
- 22.Lee SH, Choi S, Jung JH, Lee N. Effects of atrial fibrillation on arterial stiffness in patients with hypertension. Angiology. 2008;59:459–63. doi: 10.1177/0003319707309305. doi:10.1177/0003319707309305. [DOI] [PubMed] [Google Scholar]
- 23.Jose AD, Collison D. The normal range and determinants of the intrinsic heart rate in man. Cardiovasc Res. 1970;4:160–7. doi: 10.1093/cvr/4.2.160. [DOI] [PubMed] [Google Scholar]
- 24.Tracey KJ. The inflammatory reflex. Nature. 2002;420:853–9. doi: 10.1038/nature01321. doi:10.1038/nature01321. [DOI] [PubMed] [Google Scholar]
- 25.Traub O, Berk BC. Laminar shear stress: mechanisms by which endothelial cells transduce an atheroprotective force. Arterioscler Thromb Vasc Biol. 1998;18:677–85. doi: 10.1161/01.atv.18.5.677. [DOI] [PubMed] [Google Scholar]
- 26.Sa Cunha R, Pannier B, Benetos A, Siche JP, London GM, Mallion JM. et al. Association between high heart rate and high arterial rigidity in normotensive and hypertensive subjects. J Hypertens. 1997;15:1423–30. doi: 10.1097/00004872-199715120-00009. [DOI] [PubMed] [Google Scholar]
- 27.Su HM, Lin TH, Lee CS, Lee HC, Chu CY, Hsu PC. et al. Myocardial performance index derived from brachial-ankle pulse wave velocity: a novel and feasible parameter in evaluation of cardiac performance. Am J Hypertens. 2009;22:871–6. doi: 10.1038/ajh.2009.94. doi:10.1038/ajh.2009.94. [DOI] [PubMed] [Google Scholar]
- 28.Chen JH, Chen SC, Liu WC, Su HM, Chen CY, Mai HC. et al. Determinants of peripheral arterial stiffness in patients with chronic kidney disease in southern Taiwan. Kaohsiung J Med Sci. 2009;25:366–73. doi: 10.1016/S1607-551X(09)70529-7. doi:10.1016/s1607-551x(09)70529-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Munakata M, Konno S, Miura Y, Yoshinaga K. Prognostic significance of the brachial-ankle pulse wave velocity in patients with essential hypertension: final results of the J-TOPP study. Hypertens Res. 2012;35:839–42. doi: 10.1038/hr.2012.53. doi:10.1038/hr.2012.53. [DOI] [PubMed] [Google Scholar]
- 30.Sonoda H, Takase H, Dohi Y, Kimura G. Factors associated with brachial-ankle pulse wave velocity in the general population. J Hum Hypertens. 2012;26:701–5. doi: 10.1038/jhh.2011.100. doi:10.1038/jhh.2011.100. [DOI] [PubMed] [Google Scholar]
- 31.Albaladejo P, Asmar R, Safar M, Benetos A. Association between 24-hour ambulatory heart rate and arterial stiffness. J Hum Hypertens. 2000;14:137–41. doi: 10.1038/sj.jhh.1000961. [DOI] [PubMed] [Google Scholar]
- 32.Yasmin Brown MJ. Similarities and differences between augmentation index and pulse wave velocity in the assessment of arterial stiffness. QJM. 1999;92:595–600. doi: 10.1093/qjmed/92.10.595. [DOI] [PubMed] [Google Scholar]
- 33.Asmar R, Rudnichi A, Blacher J, London GM, Safar ME. Pulse pressure and aortic pulse wave are markers of cardiovascular risk in hypertensive populations. Am J Hypertens. 2001;14:91–7. doi: 10.1016/s0895-7061(00)01232-2. [DOI] [PubMed] [Google Scholar]
- 34.Mackey RH, Sutton-Tyrrell K, Vaitkevicius PV, Sakkinen PA, Lyles MF, Spurgeon HA. et al. Correlates of aortic stiffness in elderly individuals: a subgroup of the Cardiovascular Health Study. Am J Hypertens. 2002;15:16–23. doi: 10.1016/s0895-7061(01)02228-2. [DOI] [PubMed] [Google Scholar]
- 35.Sutton-Tyrrell K, Newman A, Simonsick EM, Havlik R, Pahor M, Lakatta E. et al. Aortic stiffness is associated with visceral adiposity in older adults enrolled in the study of health, aging, and body composition. Hypertension. 2001;38:429–33. doi: 10.1161/01.hyp.38.3.429. [DOI] [PubMed] [Google Scholar]
- 36.Wildman RP, Mackey RH, Bostom A, Thompson T, Sutton-Tyrrell K. Measures of obesity are associated with vascular stiffness in young and older adults. Hypertension. 2003;42:468–73. doi: 10.1161/01.HYP.0000090360.78539.CD. doi:10.1161/01.hyp.0000090360.78539.cd. [DOI] [PubMed] [Google Scholar]
- 37.Rodrigues SL, Baldo MP, Lani L, Nogueira L, Mill JG, Sa Cunha R. Body mass index is not independently associated with increased aortic stiffness in a Brazilian population. Am J Hypertens. 2012;25:1064–9. doi: 10.1038/ajh.2012.91. doi:10.1038/ajh.2012.91. [DOI] [PubMed] [Google Scholar]
- 38.Doonan RJ, Hausvater A, Scallan C, Mikhailidis DP, Pilote L, Daskalopoulou SS. The effect of smoking on arterial stiffness. Hypertens Res. 2010;33:398–410. doi: 10.1038/hr.2010.25. doi:10.1038/hr.2010.25. [DOI] [PubMed] [Google Scholar]
- 39.Yufu K, Takahashi N, Hara M, Saikawa T, Yoshimatsu H. Measurement of the brachial-ankle pulse wave velocity and flow-mediated dilatation in young, healthy smokers. Hypertens Res. 2007;30:607–12. doi: 10.1291/hypres.30.607. doi:10.1291/hypres.30.607. [DOI] [PubMed] [Google Scholar]
- 40.Schillaci G, Pirro M, Mannarino MR, Pucci G, Savarese G, Franklin SS. et al. Relation between renal function within the normal range and central and peripheral arterial stiffness in hypertension. Hypertension. 2006;48:616–21. doi: 10.1161/01.HYP.0000240346.42873.f6. doi:10.1161/01.HYP.0000240346.42873.f6. [DOI] [PubMed] [Google Scholar]
- 41.Kawamoto R, Kohara K, Tabara Y, Miki T, Ohtsuka N, Kusunoki T. et al. An association between decreased estimated glomerular filtration rate and arterial stiffness. Intern Med. 2008;47:593–8. doi: 10.2169/internalmedicine.47.0825. [DOI] [PubMed] [Google Scholar]