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Abstract

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitation and Strengths
  7. Conclusions
  8. Acknowledgement and disclosures:
  9. References

J Clin Hypertens (Greenwich). 2012; 14:855–860. ©2012 Wiley Periodicals, Inc.

Peripheral arterial disease (PAD) is associated with increased cardiovascular mortality that correlates with peripheral perfusion impairment as assessed by the ankle-brachial arterial pressure index (ABI). Furthermore, PAD is associated with arterial stiffness and elevated aortic augmentation index (AIx). The purpose of this study was to investigate whether ABI impairment correlates with AIx and subendocardial viability ratio (SEVR), a measure of cardiac perfusion during diastole. AIx and SEVR were assessed by radial applanation tonometry in 65 patients with stable PAD (Rutherford stage I–III) at a tertiary referral center. AIx corrected for heart rate and SEVR were tested in a multivariate linear and logistic regression model to determine the association with ABI. Mean ABI was 0.8±0.2, AIx 31%±7%, and SEVR 141%±26%. Multiple linear regression with AIx as a dependent variable revealed that AIx was significantly negatively associated with ABI (β=−11.5; 95% confidence interval [CI], −18.6 to −4.5; P=.002). Other variables that were associated with AIx were diastolic blood pressure (β=0.2; 95% CI, 0.1–0.4; P<.001), height (β=−46.2; 95% CI, −62.9 to −29.4; P<.001), body mass index (β=−0.4; 95% CI, −0.8 to −0.1; P=.023), and smoking (β=3.6; 95% CI, 0.6–6.6; P=.019). Multiple regression with SEVR as a dependent variable showed a significant correlation with ABI (β=33.2; 95% CI, 2.3–64.1; P=.036). Severity of lower limb perfusion impairment is related to central aortic pressure augmentation and to subendocardial viability ratio. This may be a potential pathophysiologic link that impacts cardiac prognosis in patients with PAD.

Peripheral arterial disease (PAD) is a common manifestation of atherosclerosis that affects more than 5% of the aged population.1,2 PAD is associated with impairment in functional activity and with an increased risk of cardiovascular events.3,4 For this reason, PAD is considered a marker for systemic atherosclerosis.5 To date, the most powerful prognostic indicator in PAD patients is the ankle-brachial arterial pressure index (ABI).6–8 ABI is a measure to define impairment of lower limb perfusion that has been shown to predict survival rate in patients with PAD.1,9,10

The mechanisms through which the presence of PAD increases this risk are not understood in detail. PAD represents a vascular disease with extensive atherosclerotic involvement. Systemic inflammation and increased levels of oxidative stress parallel this. Both are known to destabilize atherosclerotic plaque and thus may be associated with vascular events.11 In addition, the extensive atherosclerotic alterations along the vascular tree conduit are thought to increase pulse wave velocity, and lower limb arterial obstructions may favor premature pulse wave reflections.12,13

Khaleghi and colleagues12 reported significant differences in augmentation index (AIx) between subjects with normal and abnormal ABI. Furthermore, an association between ABI and the degree of subendocardial viability ratio (SEVR) impairment in patients with type 1 diabetes has been reported.14 A recent publication by Rabkin and colleagues15 describes an association between ABI and AIx in patients without PAD. Given that, we assume that ABI impairment might be associated with AIx and SEVR.

We therefore tested whether degree of ABI impairment is related to an increased AIx and decreased SVER as assessed noninvasively by radial pulse wave analysis in patients with stable PAD.

Methods

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitation and Strengths
  7. Conclusions
  8. Acknowledgement and disclosures:
  9. References

Patients

The study was a prospective, single-center evaluation assessing ABI and pulse wave analysis in consecutive patients with PAD conducted at a tertiary referral center. Only Caucasian patients with chronic and stable PAD were eligible for the study. The definition of PAD was based on ABI <0.9 or ABI >0.9 with a history of lower limb revascularization. Exclusion criteria were critical limb ischemia (Rutherford IV–VI), cardiac arrhythmia, and chronic inflammatory vascular disorders. Patients with incompressible tibial and peroneal arteries due to mediacalcinosis were excluded. Patients were not withdrawn from regular medication. Coronary and cerebrovascular diseases were assed by clinical history of either events or interventions. Impaired renal function was estimated by glomerular filtration rate (GFR) with Modification of Diet in Renal Disease (MDRD) study equations. Renal insufficiency was defined as an estimated GFR of <60 mL/min/1.72 m2 according to the Kidney Disease Outcome Quality Initiative (K/DOQI) guidlinies.16 The local ethics committee approved the study (Nr. 1741/2009) and all patients gave written informed consent. The study was conducted according to Good Clinical Practice standards. The following data were collected: medical history, peripheral systolic and diastolic blood pressures, body mass index, vascular risk factors (arterial hypertension, diabetes mellitus, dyslipidemia, smoking), comorbidities and medication, ankle-brachial index, and pulse wave analysis.

Ankle-Brachial Arterial Pressure Index Assessment

Ankle-brachial arterial pressure index assessments were performed as part of the standard diagnostic procedure.17 Standard brachial systolic and diastolic blood pressures on both arms with a traditional cuff manometer were measured in triplicate according to the Riva Rocci methods. Systolic ankle blood pressures of the posterior tibial artery and anterior tibial artery on both legs were obtained by hand-held 6-MHz Doppler probe. For each leg, ABI was calculated as the ratio of the highest ankle systolic blood pressure divided by the highest brachial systolic blood pressure and the lower ABI was taken as the study parameter.

Radial Artery Pulse Wave Analysis

Applanation tonometry of the radial artery was performed by a single observer with patients in the supine position to acquire radial artery waveforms. A validated transfer function was used to generate the corresponding ascending aortic pressure waveform. Augmented pressure was defined as the difference between the second and the first systolic peak, and AIx was expressed as a percentage of the pulse pressure (difference between systolic and diastolic pressure).18–20 AIx and SEVR were corrected for a heart rate of 75 beats per minute (AIx@HR75). Subendocardial blood supply as a parameter evaluating the risk of myocardial ischemia was expressed with the SEVR, the ratio of the diastolic phase (diastolic time index) to that of the systolic phase (time tension index) as measured by applanation tonometry21–23 (Figure 1). Applanation tonometry has an excellent interobserver/intraobserver reproducibility.18,24 For AIx, interoperator measurement difference is around 0.4% and somewhat larger for Buckberg ratio (2.7%). Similar values were ported by Wilkinson and Siebenhofer, with intraobserver/interobserver variability of 0.49%/0.23%.18,24

image

Figure 1.  Schematic illustration of a central pulse wave profile in a patient with pathological ankle-brachial arterial pressure index (ABI) (<0.9, dashed line) and a patient with normal ABI (solid line). The subendocardial viability ratio is expressed as the ratio of the diastolic pressure time index (DPTI) and systolic pressure time index (SPTI). The augmentation of central aortic systolic pressure is quantified as the increase of pressure from the first systolic shoulder (P1) to the systolic pressure peak (P2) and is expressed as augmentation index as a percentage of central aortic pulse pressure (PP). Pd indicates diastolic pressure; ts, systolic time; td, diastolic time.

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Statistical Analysis

Descriptive statistics for continuous variables are given as mean±standard deviation. For categorical variables, results are presented as frequency and percentage. ABI was considered as independent variable and AIx and SEVR as dependent variables. We examined multiple linear regression models to determine the association between ABI and AIx (AIx@HR75) and SEVR with the following covariates: age, sex, systolic and diastolic blood pressure, height, body mass index, cardiovascular risk factors (hypertension, ever smoking, diabetes mellitus, and dyslipidemia), comorbidities (coronary artery disease, cerebrovascular disease, renal insufficiency), and use of antihypertensive medication. All continuous variables were centered at their respective means. Categorical variables were dichotomized as present or absent. Comorbidities were dichotomized and marked as present in patients with either prevalent cardiovascular or cerebrovascular disease or renal insufficiency. Similarly, medication was dichotomized and categorized as present in case a patient was under current treatment with an angiotensin-converting enzyme inhibitor, an angiotensin II receptor blocker, a calcium antagonist, a β-blocker, or a nitrate. We included interaction terms between all covariates in the model and the ABI. Interaction was graphically inspected in addition to a chunkwise statistical assessment using the multiple-partial F test to compare the unrestricted and restricted model. Next, a chunkwise elimination of nonsignificant main effects was performed. Robustness of the modeling strategy was verified by using other modeling strategies (stepwise backward and forward procedures). Values of two-sided P<.05 were considered statistically significant. All analyses were performed with Stata 11.1 for Windows (StataCorp LP, College Station, TX).

Results

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitation and Strengths
  7. Conclusions
  8. Acknowledgement and disclosures:
  9. References

The characteristics of the study population are summarized in Table I. Graphical as well as statistical examination did not indicate any relevant interaction between the candidate covariates and the two independent variables of interest (P=.186 for the model assessing AIx, and P=.576 for the model assessing SEVR). Data on ABI, heart rate, and pressure characteristics and for AIx and SEVR are given in Table II.

Table I.   Characteristics of the Study Sample (N=65)
  1. Values are expressed as mean±standard deviation for quantitative variables and numbers (percentages) for categorical variables.

Age, y69±11
Female, No. (%)17 (26)
Body height, cm170±7.9
Weight, kg74.5±12.6
Body mass index, kg/m225.7±3.7
Cardiovascular risk factors, No. (%)
 Hypertension52 (80)
 Ever smokers48 (74)
 Diabetes15 (23)
 Dyslipidemia39 (60)
Comorbidities, No. (%)
Coronary artery disease19 (29)
Cerebrovascular disease15 (23)
Renal insufficiency8 (12)
Medication, No. (%)
 Nitrates2 (3)
 β-Blockers35 (54)
 Angiotensin-converting enzyme inhibitors28 (43)
 Angiotensin receptor blockers16 (25)
 Calcium channel blockers19 (29)
 Diuretics30 (46)
 Lipid-lowering medication54 (83)
Table II.   Pressure Characteristics of PAD Patients (N=65)
  1. Abbreviations: ABI, ankle-brachial arterial pressure index; AIx@75HR, aortic augmentation index corrected for heart rate 75 per minute; DBP, diastolic blood pressure; PAD, peripheral arterial disease; PP, pulse pressure; SBP, systolic blood pressure; SEVR, subendocardial viability index. Values are expressed as mean±standard deviation (range).

ABI0.8±0.2 (0.4–1.2)
AIx@75HR31±7 (17–47)
SEVR141±26 (90–230)
Heart rate, beats per min67±9 (48–89)
SBP, mm Hg152±21 (120–250)
DBP, mm Hg81±11 (60–110)
Brachial PP, mm Hg71±18 (40–150)
Central PP, mm Hg59±17 (29–135)

When using univariate linear regression, AIx was significantly associated with ABI, with a coefficient of −13.0 (95% CI, −21.6 to −4.4; P=.004). All covariates except diastolic blood pressure, ever smoker, height, and BMI were eliminated from the model in backward multiple linear regression elimination, with AIx@HR75 as a dependent variable (Table III). Significance from the multiple-partial F test between the unrestricted model and the final model was 0.351. Total variance of AIx@HR75 explained by the final model was 51%. The selection of variables included into the model was confirmed in the stepwise selection procedures. Partial regression plot for AIx@HR75 and ABI are shown in Figure 2, indicating that the lower the ABI, the higher the AIx@HR75.

Table III.   Variables Associated With Aortic Augmentation Index in Patients With Peripheral Arterial Disease
 Unrestricted ModelRestricted Model
Coefficient95% CI P ValueCoefficient95% CI P Value
  1. Abbreviations: ABI, ankle-brachial arterial pressure index; BP, blood pressure; CI, confidence interval.

ABI−10.67−18.36−2.97.008−11.5−18.6−4.5.002
Age, y0.060.100.23.449    
Sex0.17−3.664.00.929    
Height, cm−42.27−63.38−21.16<.001−46.2−62.93−29.43<.001
Body mass index, kg/m2−0.45−0.87−0.024.039−0.43−0.80−0.06.023
Smoker5.201.548.86.0063.60.606.59.019
Dyslipidemia0.25−2.643.14.862    
Hypertension0.56−3.985.09.806    
Diabetes0.10−3.563.77.955    
Systolic BP0.02−0.070.11.680    
Diastolic BP0.230.060.40.0090.240.120.36<.001
Comorbidity−0.99−4.242.27.546    
Antihypertensive drugs2.49−1.396.36.203    
image

Figure 2.  Partial regression plot for aortic augmentation index (AIx) and ankle-brachial arterial pressure index (ABI) in patients with peripheral arterial disease. Aortic AIx and ABI are centered by their means.

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Likewise, univariate linear regression revealed a statistically significant association between SEVR and ABI with coefficient of 54.0 (95% CI, 22.0–86.0; P=.001). In the multiple linear regression model, the β for the ABI was 33 (95% CI, 2.29–64.06; P=.036) (Table IV). Significance from the multiple-partial F test between the unrestricted model and the final model was 0.657. Variance of SEVR explained by the model was 0.35. Partial regression plot for SEVR and ABI are shown in Figure 3 and exhibit a positive correlation between ABI and SEVR. Stepwise procedures again confirmed variable selection in the model.

Table IV.   Variables Associated With Subendocardial Viability Ratio in Patients With Peripheral Arterial Disease
 Unrestricted ModelRestricted Model
Coefficient95% Confidence Intervall P ValueCoefficient95% Confidence Intervall P Value
  1. Abbreviations: ABI, ankle-brachial arterial pressure index; BP, blood pressure.

ABI37.294.1270.45.02833.172.2964.06.036
Age, y0.02−0.690.73.952    
Sex−17.05−33.55−0.54.043−14.96−30.060.14.052
Height, cm96.555.59187.52.03876.76−6.67160.18.071
Body mass index, kg/m20.36−1.472.18.696    
Smoker1.35−14.417.12.864    
Dyslipidemia−1.08−13.5411.39.863    
Hypertension14.07−5.4833.61.155    
Diabetes−8.07−23.857.72.310    
Systolic BP−0.72−1.12−0.32.001−0.61−0.96−0.25.001
Diastolic BP0.990.261.71.0090.800.171.43.014
Comorbidities7.44−6.5821.46.292    
Antihypertensive drugs0.24−16.4616.93.978    
image

Figure 3.  Partial regression plot for subendocardial viability ratio (SEVR) and ankle-brachial arterial pressure index (ABI) in patients with peripheral arterial disease. Aortic augmentation index and ABI are centered by their means.

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Discussion

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitation and Strengths
  7. Conclusions
  8. Acknowledgement and disclosures:
  9. References

In previously published studies, an association between AIx and ABI has been demostrated.12,14,15 We now describe for the first time a correlation between AIx and SEVR and the degree of impairment as assessed by ABI in patients with well-defined PAD.

Khaleghi and colleagues have shown an association between ABI and AIx, but mean ABI was 1.12, and only a small portion of the patients (n=20) had clearly defined PAD with ABI <0.9.12,25 Likewise, Prince and colleagues14 reported significantly lower SEVR in association with ABI impairment in patients with type I diabetes, but only 11% of the patients had an ABI <0.9. Both groups reported impaired biomarkers for arterial stiffness between patients with and without PAD. By including only patients with PAD, our study extends the knowledge on biomarkers of arterial stiffness in atherosclerotic patients. So far, an important marker for the severity of PAD and prognosis of patients is the ABI, with the lower the ABI the worse the survival rate.26 We therefore assumed that the lower the ABI, the higher the AIx and the lower the SEVR, which proved to be robust in the multivariate regression analysis.

A possible pathomechanistic explanation is that arteriosclerosis harms vascular compliance and increases arterial stiffness that results in an accelerated pulse wave propagation. In addition, arterial obstructions and arteriosclerotic bifurcations may cause premature pulse wave reflection. The extent of arterial stiffness and amount of obstruction in peripheral arteries are important determinates of the timing and amplitude of the arterial wall reflection that might be linked to AIx and SVER.27 Premature arterial wave reflection impact on cardiovascular risk since elevated AIx has been reported to be associated with coronary artery disease and cardiovascular events.23,28,29 These hemodynamic changes in the central aorta unfavorably affect heart function by increasing cardiac afterload and decreasing myocardial perfusion due to a lower pressure during diastole.30 It has been demonstrated that SVER has a close correlation with the blood supply to the subendocardium.22,31 The effects of elevated AIx and lower SEVR may cause acceleration of coronary artery disease and render atherosclerotic plaque more vulnerable due to possibly impaired coronary blood flow during diastole.30

PAD and arterial stiffness share the same risk factors and are both prevalent in older populations. However, until now there has been no evidence on whether the presence of arterial stiffness increases the likelihood of developing PAD or whether arteriosclerotic disease is the cause for impaired makers of arterial stiffness, as suggested in our study. Since both SEVR and AIx are independently associated with degree of lower limb perfusion impairment, we believe that this might indicate a pathomechanistic link between these findings. Although our study does not give evidence that arteriosclerosis is responsible for arterial stiffness, peripheral atherosclerosis is associated with markers that refer to arterial stiffness. The importance of this new information needs to be verified by long-term studies.

Limitation and Strengths

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitation and Strengths
  7. Conclusions
  8. Acknowledgement and disclosures:
  9. References

The sample size of our study was limited and only Caucasian patients were included. Therefore, these findings might not extend to other populations with PAD. Furthermore, it remains uncertain whether AIx and SEVR provide more information concerning the prognosis of these high-risk patients compared with the measurement of ABI. Prospective studies with a larger sample size are needed to test tonometric assessment of AIx and SEVR with regard to cardiovascular prognosis. In addition, other confounding factors that are potentially involved between ABI and cardiovascular prognosis were not assessed in our study: extension of vascular involvement, inflammation, and physical activity are cofactors that may impair prognosis in PAD. However, our study provides information about how vascular parameters such as AIx and SEVR are related to ABI in a sample of a vascular medicine outpatient clinic with clearly defined PAD who were under standard therapy based on international guidelines.

Conclusions

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitation and Strengths
  7. Conclusions
  8. Acknowledgement and disclosures:
  9. References

Aortic AIx and SEVR are associated with ankle-brachial arterial pressure index in patients with PAD independent of age, comorbidity, and medication, indicating a link between peripheral arterial perfusion impairment and central aortic pressure augmentation.

Acknowledgement and disclosures:

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitation and Strengths
  7. Conclusions
  8. Acknowledgement and disclosures:
  9. References

The study was supported by grants of the Swiss Heart Foundation and Matching Funds of the University of Zurich. Drs Mosimann and Jacomella contributed equally to this manuscript.

References

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Limitation and Strengths
  7. Conclusions
  8. Acknowledgement and disclosures:
  9. References
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