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Carotid Arterial Stiffness as a Predictor of Cardiovascular and All-Cause Mortality in End-Stage Renal Disease

Originally published 1998;32:570–574


    Abstract—Damage of large arteries is a major contributory factor to the high pulse pressure observed in patients with end-stage renal disease. Whether incremental modulus of elasticity (Einc), a classic marker of arterial stiffness, can predict cardiovascular mortality has never been investigated. A cohort of 79 patients with end-stage renal disease undergoing hemodialysis was studied between September 1995 and January 1998. Mean age at entry was 58±15 years. The duration of follow-up was 25±7 months, during which 10 cardiovascular and 8 noncardiovascular fatal events occurred. At entry, carotid Einc was calculated from measurements of diameter, thickness (echo-tracking technique), and pulse pressure (tonometry). Based on Cox analyses, 2 dominant factors emerged as predictors of all-cause and cardiovascular mortality: increased Einc and decreased diastolic blood pressure. Lipid abnormalities and the presence of previous cardiovascular events interfered to a smaller extent. After adjustment for confounding variables, the odds ratio for Einc ≥1 kPa−3 was 9.2 (95% confidence interval, 2.4 to 35.0) for all-cause mortality. These results provide the first direct evidence that in patients with end-stage renal disease undergoing hemodialysis, arterial alterations, as determined from carotid Einc, are strong independent predictors of all-cause and cardiovascular mortality.

    Epidemiological and clinical studies have shown that damage of large arteries is a major contributory factor to the high cardiovascular morbidity and mortality of end-stage renal disease (ESRD) patients.1 Macrovascular disease develops rapidly in uremic patients and is responsible for the high incidence of ischemic heart disease, left ventricular (LV) hypertrophy, congestive heart disease, sudden death, and stroke.2 Although the majority of these may be due to atherosclerotic lesions, many complications arise in ESRD patients in the absence of clinically significant atherosclerotic disease.3 The principal arterial alteration in this latter situation consists of arterial stiffening and decreased compliance associated with arterial enlargement and increased wall thickness of major arteries.4 Arterial stiffening occurs normally with aging5 but also correlates with the prevalence of atherosclerosis.6 The most obvious consequences of arterial stiffening are increased pulsatile blood pressure due to higher systolic blood pressure (SBP) and lower diastolic blood pressure (DBP), thereby causing increased LV afterload and altering coronary perfusion.7 Higher SBP and pulse pressure, lower DBP, and LV hypertrophy have been identified as independent factors of cardiovascular morbidity and mortality in the general population891011 as well as in ESRD patients.12131415 Increased carotid intima-media thickness (IMT) is associated with future cerebrovascular and cardiovascular events.16 However, the specific impact of arterial stiffening on cardiovascular morbidity and mortality has never been established.

    Arterial stiffness can be assessed noninvasively by measuring the common carotid artery (CCA) incremental modulus of elasticity (Einc), providing information on the properties of the wall material independent of the geometry.7 To identify the impact of arterial stiffness on cardiovascular and/or all-cause mortality in hemodialyzed ESRD patients, we conducted a prospective study on a cohort of 79 patients followed up for a period of up to 28 months. The results indicate that arterial stiffening is the major independent predictor of all-cause and cardiovascular mortality in ESRD patients on chronic hemodialysis.



    This prospective cohort study was started at the F.H. Manhès Hospital, Fleury-Mérogis, France, in September 1995. Patients were eligible for entry into the study when (1) they had been on hemodialysis for at least 3 months (103±82 months, mean±SD) and (2) they had had no clinical cardiovascular disease during 6 months preceding entry. Follow-up ended in January 1998. A cohort of 79 patients who initially fulfilled the entry criteria entered the study. The mean patient follow-up was 25±7 months. Data on mortality were obtained for the entire cohort. The mean age of the cohort was 58±15 years, 60% were male, 10% had insulin-dependent diabetes mellitus, and 44% were treated with antihypertensive drugs including calcium channel blockers, angiotensin-converting enzyme inhibitors, β-blockers, and central-acting agents, either alone or in combination. Thirty-eight patients received recombinant human erythropoietin at some time during follow-up. Patients were dialyzed with synthetic membranes (AN69 and polysulfone). The duration of dialysis sessions was individually tailored (4 to 6 hours, 3 times weekly) to control body fluids and to achieve a Kt/V ≥1.2 (where Kt is dialyzer urea clearance and treatment time, and V is urea distribution volume). Each subject provided informed written consent to participate in the study, which was approved by our institutional review board.

    Data Collection

    Information compiled from the questionnaire completed at inclusion included personal and family histories, smoking habits (43 patients were current or former smokers), and previous history of cardiovascular disease defined as follows.1 Coronary artery disease was defined as history of myocardial infarction, coronary bypass surgery, or percutaneous transluminal angioplasty; angina pectoris: precordial chest pain precipitated by exertion, relieved by rest or nitrates; cardiac disease: dyspnea, increased jugular venous pressure, interstitial edema on chest x-ray, bibasalar crackles; peripheral vascular disease: symptoms of or surgery for peripheral vascular disease, aortic disease, or disease of major arteries including renal and splanchnic circulation; and cerebrovascular disease: history of transient ischemic attacks, unspecified stroke, thrombotic stroke, or hemorrhagic stroke verified by CT. Causes of death, codified according to the World Health Organization International Classification of Disease, 9th Revision,17 were obtained from death certificates, hospital record forms, and autopsy data reviewed by the authors. Sudden death was defined as a witnessed death that occurred within 1 hour after the onset of acute symptoms, with no evidence that violence or accident played any role in the fatal outcome. During the mean follow-up period, we recorded 18 deaths, including 10 fatal cardiovascular events; among the latter, 3 deaths were attributed to coronary heart disease, 3 to cerebrovascular and/or aortic disease, 3 to sudden death, and 1 to congestive heart disease. The 8 fatal noncardiovascular events were 4 deaths due to cancer, 2 to infectious disease, 1 by withdrawal from dialysis because of dementia, and 1 suicide.

    At entry, clinical and hemodynamic assessments were undertaken. The measurements were performed during the 2 weeks that followed inclusion, on the morning before the midweek hemodialysis. Blood chemistry at baseline and monthly intervals included levels of serum creatinine and urea, hemoglobin, serum albumin, and blood lipids. Blood pressure (BP) was measured with a mercury sphygmomanometer after 15 minutes of recumbency in the arm contralateral to the arteriovenous shunt. Phases I and V of the Korotkoff sounds were taken as the SBP and DBP, respectively. The mean BP (MBP) was calculated as MBP=DBP+[(SBP−DBP)/3]. Five measurements determined at 2-minute intervals were averaged.

    The CCA systolic and diastolic diameters (Ds and Dd), IMT, and wall motion were measured by a high-resolution B-mode (7.5-MHz transducer) echo-tracking system (Wall track system) allowing the assessment of arterial wall displacement during the cardiac circle. A detailed description of this system has been published previously.4 Measurements were done on the right CCA, 2 cm beneath the bifurcation. A localized echostructure encroaching into the vessel lumen was considered to be a plaque if the CCA IMT was >50% thicker than neighboring sites.418 Measurements of CCA diameter and CCA IMT were always performed in plaque-free arterial segments. CCA IMT was measured on the far wall on the same level as the diameter measurements with computer-assisted acquisition, processing, and storage. The CCA-lumen cross-sectional area (LCSA) was calculated as LCSA=Π(CCA diameter)2/4. The intima-media cross-sectional area (IMCSA) was calculated as IMCSA=Π(CCA diameter/2+IMT)2−Π(CCA diameter/2)2, and wall/lumen ratio as (2 IMT/CCA diameter). CCA compliance and CCA distensibility were determined from changes in CCA diameter during the systole and simultaneously measured CCA pulse pressure (ΔP) according to following formulas: CCA compliance=[ΠDd(Ds−Dd)/2]/ΔP(m2 · kPa−1 · 10−7); and CCA distensibility=2[(Ds−Dd)/Dd]/ΔP(kPa−1 · 10−3).47 CCA pulse pressure (ΔP) was assessed by determination of CCA pressure waveform recorded noninvasively with a pencil-type probe incorporating a high-fidelity Millar strain-gauge transducer; a detailed description of this system has been published previously.418 While distensibility provides information about “elasticity” of the artery as a hollow structure, Einc provides information on the properties of the wall material, independent of the geometry. Einc was calculated as [3(1+LCSA/IMCSA)]/CCA distensibility.4 Repeatability and reproducibility of measurements have been published in detail elsewhere.4

    Baseline echocardiography was performed using a Hewlett-Packard Sonos 100 device equipped with a 2.25-MHz probe, allowing M-mode, 2-dimensional, and pulsed Doppler measurements. Measurements were made according to the recommendations of the American Society of Echocardiography.19 LV mass was calculated according to the Penn convention.20 LV hypertrophy was defined as an LV mass index >136 g/m2 in men and >110 g/m2 in women. Adequate echocardiographic tracings were obtained for 70 subjects. LV hypertrophy was present in 84% of the patients, and the LV mass index was 165±52 g/m2 (mean±SD).


    The outcome events studied were cardiovascular mortality and all-cause mortality. Survival curves were estimated using the Kaplan-Meier product-limit method and compared by the Mantel (log-rank) test. Prognostic factors of survival were identified using logistic regression analysis and the Cox proportional hazards regression model. The assumption of proportional hazards over time was verified before the analyses were performed and was met by all covariates. The assumption concerning linearity of continuous covariates was also verified before analysis. All analyses, including echocardiographic LV mass among the covariates, were limited to the subset with adequate echocardiographic tracings. The cohort was divided into quartiles according to the CCA echographic variables. Variables were considered as prognostic when they were found to be statistically significant (P<0.05) in the logistic regression or the Cox proportional hazards regression models of all-cause or cardiovascular mortality. The adjusted relative risk of death during follow-up for the patients in the unfavorable quartile of CCA echographic variable compared with the risk of the patients in the 3 other quartiles was estimated as the odds ratio (OR). Adjusted ORs were calculated as the antilogarithm of the β coefficient of the logistic regression of all-cause mortality with the prognostic variables (DBP and total/HDL cholesterol ratio). Confidence intervals (95% CI) around the adjusted OR estimates were obtained with the following formula: antilogarithm(β±1.96 SE), where SE is the standard error of β.

    Data are expressed as mean±SD. ANOVA was used for comparison of normally distributed continuous variables. Differences in frequency were tested by χ2 analysis. Gender (1, male; 2, female) and previous history of cardiovascular disease (1, no; 2, yes) were used as dummy variables. Statistical analysis was performed using NCSS 6.0.21 software.21 Repeatability and reproducibility of the methods were defined as recommended by the British Standard Institution.22 A value of P<0.05 was considered significant. All tests were 2-sided.


    Patient Characteristics

    The characteristics of the cohort at the time of inclusion, according to prognosis (event-free, cardiovascular death, noncardiovascular death, and cardiovascular morbidity) are shown in Tables 1 and 2. Only age, the prevalence of previous cardiovascular events, and all CCA echographic parameters except wall/lumen ratio significantly differed among the 4 groups.

    Predictors of All-Cause Mortality

    During the follow-up period, 18 deaths were recorded. As assessed by proportional hazards regression analysis, the significant predictors of all-cause mortality were increased CCA diameter, decreased DBP, and increased total/HDL cholesterol ratio (Table 3). Although CCA Einc, instead of CCA diameter, could enter the multivariate model, the model was more powerful when using CCA diameter. Smoking, age, heart rate, hematocrit, serum albumin, LV mass index or hypertrophy, antihypertensive drug therapy, gender, the presence of diabetes mellitus, dialysis duration before inclusion, and previous cardiovascular events did not reach statistical significance in multivariate analysis. After adjustment for all the prognostic variables, CCA Einc was the strongest predictor of mortality (Table 4). Compared with patients in the 3 lower quartiles of CCA Einc, patients in the upper quartile had a 9.2-fold adjusted risk of all-cause mortality (Table 4). The Figure shows the probabilities of all-cause survival as a function of Einc values. Comparison between survival curves was highly significant.

    Predictors of Cardiovascular Mortality

    Ten cardiovascular deaths were documented during the follow-up period. As assessed by proportional hazards regression analysis, the significant determinants of cardiovascular mortality were increased CCA Einc, decreased DBP, and the presence of previous cardiovascular events (Table 3). Smoking, age, heart rate, hematocrit, serum albumin, LV mass index or hypertrophy, antihypertensive drug therapy, gender, the presence of diabetes mellitus, dialysis duration before inclusion, and serum lipids did not reach statistical significance in multivariate analysis.


    Arterial stiffness increases with age57 and hypertension23 and is also enhanced in subjects with diabetes mellitus,24 atherosclerosis,7 and ESRD.24 In ESRD patients, the increased arterial stiffness is associated with acceleration of the arterial aging process, namely dilation and increased wall thickness of major arteries, and to a lesser degree with atherosclerosis.24 In this study, we found that CCA Einc, a major marker of arterial stiffness, was a strong predictor of all-cause and cardiovascular mortality in ESRD patients. The role of arterial stiffening was independent of other factors known to affect the outcome of uremic patients, namely serum lipids and preexisting cardiovascular disease.

    In the past, the mechanical properties of arteries were evaluated from the Moens-Korteweg equation, which usually assumed a thin arterial wall.7 Thus, wall thickness was neglected in the calculation, and the results were presented mainly in terms of distensibility. Recent studies clearly show that by using high-resolution echo-tracking techniques, substantial differences in wall thickness may be observed. First, vascular hypertrophy is present in subjects with essential hypertension and in patients with ESRD.1825 Second, the degree of vascular hypertrophy is proportional to the level of BP, according to the classic Laplace law.72526 Thus, it is relevant to characterize the mechanical properties of wall material in patients with ESRD. We previously showed that carotid Einc is increased in ESRD patients for the same wall stress as in control subjects.26 The present study indicates that Einc is the strongest predicting factor of cardiovascular mortality. The crude and adjusted ORs related to Einc were stronger than those related to diameter or distensibility, indicating that both structural and functional components of carotid stiffness played a role in the predictive value of Einc. However, whether increased Einc is a risk factor contributing to the development of cardiovascular disease or a marker of established cardiovascular disease is a matter of debate. A study in Chinese and Australians27 has suggested that morphological and structural alterations of the aorta may be influenced by both environmental and genetic factors. A role for genetic factors was also supported by the data from Benetos et al,28 who observed that the angiotensin II type 1 receptor gene can influence aortic stiffness. These examples suggest that changes of biomechanical properties of major arteries might precede the development of clinically overt disease.

    An association of both cardiovascular and all-cause mortality with low DBP was also observed in the present study. Contrary to the observation made by Charra et al29 but in agreement with others,303132 we did not find an independent relationship between hypertension (mean BP or the presence of antihypertensive therapy) and patient survival. As previously discussed, the deleterious role of low DBP, independent of carotid arterial stiffness, might suggest that incipient LV dysfunction plays a role in cardiovascular mortality.

    To qualify as a risk factor, increased Einc must raise the probability of an adverse outcome. The results of the present analysis suggest that this is indeed the case. Although correlation does not imply causation, increased Einc is a strong independent predictor of cardiovascular and all-cause mortality in patients with ESRD on hemodialysis. Such measurements could serve as an important tool in identifying patients at risk of cardiovascular disease. The ability to identify these patients would lead to better risk stratification and earlier and more cost-effective preventive therapy.

          Figure 1.

    Figure 1. Probability of survival in the study population according to the level of Einc. Comparison between survival curves was highly significant (χ2=10.41; P=0.0013).

    Table 1. Baseline Clinical and Biochemical Characteristics of Patients at Inclusion, According to Prognosis

    ParameterEvent-Free (n=50)CV Death (n=10)Non-CV Death (n=8)CV Morbidity (n=11)ANOVA, P
    Age, y54±1667±1170±1162 ±90.003
    Gender, M/F ratio1.4±0.51.4 ±0.51.4±0.51.5±0.5
    Diabetes mellitus, %1001318
    Dialysis duration before inclusion, mo105±87102±82110±7989 ±67
    Previous cardiovascular events, %408925540.028
    Antihypertensive therapy at inclusion, %42445045
    Tobacco lifelong dose, pack-years9±1725±2818±2211 ±18
    Serum total cholesterol, mmol/L4.9±1.15.3 ±1.25.0±1.24.4±1.1
    Serum HDL cholesterol, mmol/L1.1±0.41.1±0.30.9±0.21.0 ±0.4
    Total/HDL cholesterol ratio4.7±1.55.1 ±1.85.7±1.74.6±1.1
    Hematocrit, %32 ±533±331±530±4

    Continuous variables are expressed as mean±SD. CV indicates cardiovascular.

    Table 2. Baseline Hemodynamic and Echographic Characteristics of Patients at Inclusion, According to Prognosis

    ParameterEvent-Free (n=50)CV Death (n=10)Non-CV Death (n=8)CV Morbidity (n=11)ANOVA, P
    SBP, mm Hg149±28139±27162 ±39154±33
    DBP, mm Hg83±1472±1174 ±1480±14
    MBP, mm Hg105±1794±14103 ±21105±17
    Pulse pressure, mm Hg66±2268 ±2487±2975±31
    LV mass index, g/m2160±43186±59175±31163 ±88
    LV hypertrophy, %848910073
    CCA calcifications, %5090100910.003
    CCA diameter, mm6.2±0.96.9±0.87.0±1.06.6 ±0.80.028
    CCA IMT, μm771±110858±79834 ±86822±670.039
    CCA wall/lumen ratio0.25 ±0.030.25±0.020.24±0.020.25±0.04
    CCA compliance, m2 · kPa−1 · 10−75.0 ±2.03.7±1.93.8±1.03.6±0.90.027
    CCA distensibility, kPa−1 · 10−317.2 ±8.610.4±5.810.1±5.710.6±3.20.003
    CCA Einc, kPa · 1030.6±0.31.1 ±0.71.1±0.60.9±0.40.0009

    Continuous variables are expressed as mean±SD. CV indicates cardiovascular.

    Table 3. Proportional Hazards Regression Analysis of Cardiovascular and All-Cause Mortality

    ParameterRegression CoefficientSEzPseudo R2P
    All-cause mortality (yes, no)1
    CCA diameter, mm0.980.283.460.140.0005
    DBP, mm Hg−0.060.02−
    Total/HDL cholesterol, ratio0.380.152.610.080.009
    Cardiovascular mortality (yes, no)2
    Einc, kPa · 1032.020.663.090.120.002
    Previous cardiovascular events, %
    DBP, mm Hg−0.060.03−

    1Model pseudo R2=0.21; model χ2=20.59; model probability=0.0001.

    2Model pseudo R2=0.23; model χ2=20.86; model probability=0.0001.

    Table 4. Odds Ratio of All-Cause Mortality During Mean Follow-Up of 25 Months, According to Prognostic Variables (Unfavorable Quartile Versus 3 Other Quartiles)

    Prognostic VariableNo. of SubjectsAll-Cause Mortality
    Deaths, n (%)Crude OR (95% CI)Adjusted OR (95% CI)
    CCA diameter, mm7918 (23)
    <715910 (17)1.01.0
    ≥7208 (40)3.3 (1.1–10.1)7.7 (1.9–31.8)
    CCA IMT, μm
    <86415911 (19)1.01.0
    ≥864207 (35)2.4 (0.8–7.3)3.2 (0.9–11.1)
    CCA wall/lumen ratio
    <0.26515915 (25)1.01.0
    ≥0.265203 (15)0.5 (0.1–2)0.2 (0.1–1.0)
    CCA compliance, m2 · kPa−1 · 10−7
    >315911 (19)1.01.0
    ≥3207 (35)2.4 (0.8–7.3)2.9 (0.8–10.1)
    CCA distensibility, kPa−1 · 10−3
    >91599 (15)1.01.0
    ≥9209 (45)4.5 (1.5–14.1)6.4 (1.8–23.3)
    CCA Einc, kPa · 103
    <11598 (14)1.01.0
    ≥12010 (50)6.4 (2.0–20.2)9.2 (2.4–35.0)

    Adjustments were made on DBP and total/HDL cholesterol ratio.

    1The patients in this category served as the reference group.

    The authors thank Daniel Brun and the Organica Association for their generous financial contribution.


    Correspondence to Dr G.M. London, Hôpital F.H. Manhès, 8, Grande Rue, Fleury-Mérogis, 91712 Ste Geneviève des Bois, Cedex, France.


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