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Keywords:

  • Age;
  • arterial stiffness;
  • donor;
  • glomerular filtration rate;
  • renal allograft

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. References

It is important whether impairment of renal allograft function may deteriorate arterial stiffness in renal transplant recipients. In a cross-sectional study, arterial vascular characteristics were non-invasively determined in 48 patients with renal allograft using applanation tonometry and digital photoplethysmography. Mean age was 51 ± 2 years (mean ± SEM), and studies were performed 17 ± 1 months after transplantation. The stage of chronic kidney disease was based on the glomerular filtration rate. We observed a significant association between the stage of chronic kidney disease and arterial stiffness of large arteries S1 and small arteries S2 in renal transplant recipients (each p < 0.05 by non-parametric Kruskal–Wallis test between groups). Multivariate linear regression analysis showed that male gender of patients with renal allograft (p < 0.01) reduced glomerular filtration rate (p = 0.01), and older age of kidney donor (p = 0.04) were independently associated with an increase of large artery stiffness S1. Furthermore, a significant association between the stage of chronic kidney disease and arterial vascular reactivity during reactive hyperemia was observed (p < 0.05 by non-parametric Kruskal–Wallis test between groups). It is concluded that impairment of renal allograft function is associated with an increased arterial stiffness in renal transplant recipients.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. References

Progressive impairment of renal function is frequently observed in patients with renal allograft. Decreasing glomerular filtration rate, increasing blood pressure, or proteinuria are markers of loss of renal allograft function, finally leading to end-stage renal failure (1,2). Cardiovascular disease is the most frequent cause of late allograft loss and a major hazard limiting life expectancy of renal transplant recipients (3–5). Patients with renal allograft often possess cardiovascular risk factors such as hypertension, diabetes mellitus, hyperlipidemia, smoking, anemia, or increased calcium × phosphate product (6–8). In renal transplant recipients and in patients with end-stage renal failure, increased arterial stiffness has been associated with increased cardiovascular mortality (9,10). In patients with end-stage renal failure, the odds ratio of all-cause mortality was 1.39 for each pulse wave velocity increase of 1 m/s, a marker of arterial stiffness (10).

Given the high impact of cardiovascular disease on patient and graft survival, arterial stiffness may affect the outcome in renal transplantation. Therefore, the purpose of the present study was to evaluate arterial stiffness in patients with renal allograft. We hypothesized that impairment of renal allograft function may deteriorate vascular characteristics, including arterial stiffness, which can be measured non-invasively using applanation tonometry and digital photoplethysmography. Our study showed a significant association between the impairment of renal allograft function and increased arterial stiffness in renal transplant recipients.

Patients and Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. References

Patients

The study was approved by the local ethics committee, and all patients gave written informed consent. Non-invasive measurements of vascular properties (arterial stiffness by applanation tonometry and reflective index by digital photoplethysmography) were performed in 48 recipients of a renal allograft (22 males, 26 females; age, 51 ± 2 years, mean ± SEM). Two patients (4%) were recipients of a kidney from a living donor and 46 patients (96%) received a deceased donor graft. The duration of dialysis before transplantation was 50 ± 5 months. The studies were performed 17 ± 1 months after transplantation. At the time of the present investigation, all patients were free of intercurrent illness. Blood pressure was obtained by conventional sphygmomanometric methods on three occasions in a sitting position after a rest of 10 min. Phases I and V of the Korotkoff sounds were considered as systolic blood pressure and diastolic blood pressure, respectively. Clinical and biochemical characteristics of patients and their allograft are shown in Tables 1 and 2. Patients with renal allograft were divided into three groups according to glomerular filtration rate: chronic renal failure stage 1 or 2 indicating a glomerular filtration rate ≥60 mL/min/1.73 m2, stage 3 indicating a glomerular filtration rate from 59 to 30 mL/min/1.73 m2, stage 4 or 5 indicating a glomerular filtration rate <30 mL/min/1.73 m2. Glomerular filtration rate was calculated according to the Modification of Diet in Renal Disease (MDRD) Study Group formula. In transplant recipients with chronic renal insufficiency, this MDRD formula showed better results than other formulas to estimate glomerular filtration rate (11,12). None of the patients returned to dialysis at the time of the study.

Table 1.  Clinical characteristics of patients with renal allograft. Continuous data are presented as mean ± SEM
Characteristic
Graft-related factors
 Age of the donor (years)42 ± 3
 Cold-ischemia time (h)16 ± 1
 Delayed graft function (>6 days; number (%))8 (11)
 Living kidney donor (number (%))2 (4)
 Time since transplantation (months)17 ± 1
 Number of HLA mismatches (range, 0–6) 4 ± 0
Patient-related factors
 Age (years)51 ± 2
 Gender
  Male, n (%)22 (46)
  Female, n (%)26 (54)
 Cause of chronic renal failure (number (%))
  Diabetic nephropathy2 (4)
  Hypertensive nephropathy3 (6)
  Glomerulonephritis15 (31)
  Interstitial nephritis7 (15)
  Polycystic kidney disease7 (15)
  Other/unknown renal disease14 (29)
 Number of patients with a history of >1 transplantation (%)4 (8)
 Duration of dialysis before transplantation (months)50 ± 5
 Body weight (kg)68 ± 2
 Body mass index (kg/m2)25 ± 1
 Systolic blood pressure (mmHg)138 ± 3 
 Diastolic blood pressure (mmHg)78 ± 2
 Pulse pressure (mmHg)60 ± 2
 Heart rate (per min)70 ± 2
 Immunosuppressive medication (number (%))
  Steroids43 (90)
  Cyclosporine or tacrolimus39 (81)
  Mycophenolate mofetil7 (15)
  Other6 (12)
 Number of classes of antihypertensive drugs2.9 ± 0.2
 Number of patients with cytomegalovirus infections (%)2 (4)
 Number of patients with rejection episodes (%)7 (15)
 Smoking (number (%))7 (15)
 Other diseases (number (%))
  Diabetes mellitus12 (25)
  Hypertension45 (94)
  History of cardiovascular events13 (27)
Table 2.  Biochemical characteristics of patients with renal allograft. Continuous data are presented as mean ± SEM
Characteristic
Hemoglobin (g/dL)12.6 ± 0.3
Glomerular filtration rate (mL/min/1.73 m2 body surface area)  38 ± 3
Blood urea nitrogen (mmol/L)21.6 ± 2.6
Trough level of cyclosporine (ng/mL) 126 ± 5
Proteinuria (g of protein excretion/day) 0.4 ± 0.1
Serum calcium (mmol/L)2.40 ± 0.03
Serum phosphate (mmol/L)1.20 ± 0.05
Calcium × phosphate product (mmol2/L2)2.86 ± 0.120
Total cholesterol (mmol/L) 5.8 ± 0.2
C-reactive protein (mg/L)  29 ± 7
Parathyroid hormone (pg/mL) 188 ± 45

Measurements of arterial stiffness by applanation tonometry

Arterial stiffness was determined by applanation tonometry of radial artery pulsewaves as recently described (13–20). The method has been used for screening subjects for early evidence of arterial vascular disease (13–18). Other authors and our group used this method for measurements of arterial stiffness in patients with chronic renal failure (19,20). To obtain radial artery pressure waves, an arterial tonometer (model CR-2000, Hypertension Diagnostics Inc., Eagan, MN) was used, which was applied to the radial artery of the patient. The arm of the patient was kept in a constant position by a wrist stabilizer, ensuring a constant wrist position. The tonometer consisted of a stainless-steel canister and diaphragm internally connected to a piezoelectric element used to amplify the arterial pressure waveform signal. The obtained arterial pressure waveforms were calibrated by oscillometric methods with a blood pressure cuff and a calibration system internal to the device (18). Since patients had an arteriovenous fistula on the forearm or a hemodialysis graft, the cuff and the tonometer were both placed on the contralateral arm to the vascular hemodialysis access. A computer-based model of the circulation was used to describe the diastolic pressure decay of the tonometrically obtained waveform and to quantify changes in the arterial pressure waveform morphology. The shape of the diastolic decay of the arterial pressure curve can be represented as the solution of a third-order differential equation. After a non-linear curve-fitting routine that matches the shape of the third-order equation to the diastolic decay of the waveform, the values for large and small artery elasticity index can be calculated. Details and equations of the procedure have been described elsewhere (11–20). Arterial stiffness S1 of large arteries and arterial stiffness S2 of small arteries were calculated as the reciprocal of the elasticity C1 and C2 obtained from the measurements. The values of S1 and S2 are the weighted averages of the values obtained on individual pulsewaves during a 30-s recording period (15,16).

Arnett et al. reported the normal range for S1 and S2 in young, healthy, non-transplanted subjects (17). In 179 healthy subjects (mean age, 24 years), the mean S1 was 0.47 mmHg/mL (range, 0.23–1.25 mmHg/mL), and the mean S2 was 12.04 mmHg/mL (range, 7.14–25.00 mmHg/mL).

In earlier studies, we compared measurements of arterial stiffness by applanation tonometry with an established marker of arterial stiffness, the pulse wave velocity, determined by simultaneous measurements of arterial pulse waves of carotid and femoral arteries (SphygmoCor, AtCor, Australia), in 20 healthy control subjects (mean age, 72 ± 2 years, systolic blood pressure, 134 ± 3 mmHg, diastolic blood pressure, 74 ± 3 mmHg, heart rate, 70 ± 2/min). A significant correlation was observed between pulse wave velocity and arterial stiffness S2 of small arteries (Spearman r = 0.48; p = 0.04). These findings are in accordance with results reported by Woodman et al., showing a significant correlation between pulse wave velocity and arterial stiffness S1 of large arteries and arterial stiffness S2 of small arteries, respectively (21). The coefficient of variation, which was determined by 10 measurements in a healthy control subject, was 12.5% for arterial stiffness S1 of large arteries and 5.2% for arterial stiffness S2 of small arteries, respectively. In addition, a good repeatability of two consecutive measurements where the tonometer was completely removed and re-applied was observed for arterial stiffness S1 of large arteries (Spearman r = 0.68; p = 0.01; n = 22) and arterial stiffness S2 of small arteries (Spearman r = 0.49; p = 0.02; n = 22). As recently published by our group, measurements of arterial stiffness in patients with chronic renal failure using this technique demonstrated also a good day-to-day repeatability (20).

Measurements of arterial vascular reactivity during reactive hyperemia by digital photoplethysmography

We non-invasively measured digital volume pulse using fingertip photoplethysmography. The basic principles of digital photoplethysmography and its applications have been described in detail by several authors including our group (22–29). The digital pulse waves were measured by the transmission of red and infrared light through the finger pulp using signal extraction technology (Masimo Corporation, Irvine, CA). Photoplethysmography was conducted using a Vitaguard VG3000 monitor (getemed, Teltow, Germany) with the sensor (LNOP-Adt SpO2 sensor; Masimo Corporation) located at the third digit of the hand (30). Photoplethysmographic measurements were performed at room temperature (21–23°C) in subjects lying in a supine position. Orthostatic changes were omitted during the study. Raw data were continuously collected at a rate of 32 per second and transferred to a personal computer. The first derivative of the digital pulse wave was calculated (GraphPad prism 3.0, Graph Pad Software, San Diego, CA). The local minimum of the first derivative of the digital pulse wave was determined, and the corresponding turning point (= inflection point) in the downslope of the pulse wave was thereby defined exactly. The reflective index was calculated as the mean of the third to the seventh data point after this turning point (= inflection point) and represents the ‘shoulder region’ of the diastolic component of the digital volume pulse wave, which arises from arterial pressure waves reflected back along the aorta from small arteries (25). Each reflective index was normalized to the amplitude of the first peak of the digital volume pulse wave, which was set to 100. Data of the reflective index obtained were averaged every 2.5 min. As such, the reflective index represents the mean value from 150 to 250 digital volume pulse waves obtained during a period of 2.5 min. The coefficient of variation, which was determined from 299 pulse waves in a healthy control subject, was 9.1% for the reflective index. Earlier experimental studies showed that an increased reflective index indicates increased reflection of arterial pressure waves from peripheral arteries, i.e. due to vasoconstriction or increased arterial stiffness (29).

To evaluate arterial vascular reactivity, the changes of the reflective index during reactive hyperemia evoked by the release of a cuff on the upper arm were investigated. The sphygmomanometric cuff was placed above the antecubital fossa and inflated to 240 mmHg for 5 min. The reflective index from all pulse waves obtained during a period of 150 s before inflating the cuff and 150 s after release of the cuff were averaged, respectively. Bonetti et al. showed that an attenuated digital response to reactive hyperemia measured by digital volume pulse changes identifies patients with impaired endothelial function (31). A strong correlation between forearm blood flow response to reactive hyperemia and intra-arterial infusion of acetylcholine has been observed, indicating that reactive hyperemia is at least in part related to endothelial function (32). However, other mechanisms have also been described (33). Myogenic and neural effects, and accumulation of vasodilator substances, such as adenosine and/or ischemic metabolites, play critical roles in the reactive hyperemic response due to transient disruption of the blood supply.

Statistics

Data are presented as mean ± SEM. Data were analyzed using GraphPad prism software (version 3.0, GraphPad Software) and SPSS for windows (version 11.5, SPSS, Chicago, IL). Data between groups were compared using non-parametric Wilcoxon–Mann–Whitney test or non-parametric Kruskal–Wallis test as appropriate. A two-sided value of p < 0.05 was regarded as statistically significant. The association between selected parameters was calculated by non-parametric Spearman correlation. Multivariate linear regression analysis was used to determine those variables independently associated with arterial stiffness. The variables tested were age of the donor, cold-ischemia time, delayed graft function (>6 days), living kidney donor, time since transplantation, number of HLA mismatches, episodes of cytomegalovirus infections, episodes of rejection, age of renal allograft recipient, cause of chronic renal failure, number of transplantations, duration of dialysis before transplantation, body mass index, systolic blood pressure, diastolic blood pressure, types of immunosuppression, number of antihypertensive drugs, other diseases and history of cardiovascular events, glomerular filtration rate, proteinuria and calcium × phosphate product. In a stepwise forward regression analysis, variables with a p-value of 0.10 or more were removed from the analysis and variables with a p-value of 0.05 or less were retained.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. References

Non-invasive measurements of arterial vascular properties were performed in 48 recipients of a renal allograft. Eight patients (17%) had chronic kidney disease, stage 1 or 2; 17 patients (35%) had chronic kidney disease stage 3; and 23 patients (48%) had chronic kidney disease stage 4 or 5.

First, arterial stiffness was determined by applanation tonometry. Mean large artery stiffness S1 was 1.0 ± 0.1 mmHg/mL and mean small artery stiffness S2 was 24.0 ± 2.2 mmHg/mL in 48 patients with renal allograft. Reduced glomerular filtration rate was significantly associated with increased arterial stiffness of large arteries S1 and arterial stiffness of small arteries S2. There was a significant association between increased arterial stiffness of large arteries S1 and advanced stage of chronic kidney disease (stage 1 or 2, 0.8 ± 0.1 mmHg/mL; stage 3, 0.9 ± 0.1 mmHg/mL; stage 4 or 5, 1.3 ± 0.1 mmHg/mL; p < 0.05 by non-parametric Kruskal–Wallis test; Kruskal–Wallis statistic = 7.36; Figure 1A). Also, regression analysis showed a significant correlation between increased large artery stiffness S1 and reduced glomerular filtration rate (Spearman r =−0.45; p < 0.01). Furthermore, there was a significant correlation between increased large artery stiffness S1 and older age of kidney donor (Spearman r = 0.38; p = 0.03), higher systolic blood pressure (Spearman r = 0.41; p < 0.01) and higher diastolic blood pressure of renal allograft recipients (Spearman r = 0.31; p = 0.04). On the other hand, there was no significant association between large artery stiffness S1 and age of kidney recipient (Spearman r = 0.20; p = 0.18), duration of dialysis before transplantation (Spearman r =−0.23; p = 0.14) and time since transplantation (Spearman r = 0.20; p = 0.18). Multivariate linear regression analysis demonstrated that male gender of patients with renal allograft (β= 0.46; p < 0.01), reduced glomerular filtration rate (β= 0.35; p = 0.01) and older age of kidney donor (β= 0.28; p = 0.04) were independently associated with increased large artery stiffness S1.

image

Figure 1. Arterial stiffness in patients with renal allograft. Arterial stiffness S1 of large arteries (A) and arterial stiffness S2 of small arteries (B) were measured non-invasively by applanation tonometry in 48 patients with renal allograft and grouped according to glomerular filtration rate. Data are mean ± SEM. *p < 0.05 by non-parametric Kruskal–Wallis test between the groups (Kruskal–Wallis statistic = 7.36 for arterial stiffness S1 and Kruskal–Wallis statistic = 6.20 for arterial stiffness S2).

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For arterial stiffness of small arteries S2, there was a significant association between increased S2 and advanced stage of chronic kidney disease (stage 1 or 2, 15.0 ± 3.0 mmHg/mL; stage 3, 23.2 ± 2.5 mmHg/mL; stage 4 or 5, 29.7 ± 3.9 mmHg/mL; p < 0.05 by non-parametric Kruskal–Wallis test; Kruskal–Wallis statistic = 6.20; Figure 1B). Also, regression analysis showed a significant correlation between increased small artery stiffness S2 and reduced glomerular filtration rate (Spearman r =−0.34; p = 0.02).

Taken together, our results indicated a significantly increased arterial stiffness of large and small arteries in patients with progressive impairment of renal allograft function.

Second, arterial vascular reactivity during reactive hyperemia was measured by digital photoplethysmography and quantified by determination of the reflective index. A typical digital volume pulse wave and determination of the reflective index in one patient with renal allograft at baseline and during reactive hyperemia after the release of a sphygmomanometric cuff is depicted in Figure 2. The original trace shows the digital volume pulse wave (Figure 2A) and the first derivative of the volume pulse wave (Figure 2B) in one patient with renal allograft at baseline and during reactive hyperemia. The area covered by the reflective index represents the ‘shoulder region’ of the diastolic component of the digital volume pulse wave arising from pressure waves reflected back along the aorta from small arteries.

image

Figure 2. Reflective index in patients with renal allograft. (A and B) Original traces showing the digital volume pulse wave (A) and the first derivative of the volume pulse wave (B) in one patient with renal allograft at baseline and during reactive hyperemia. The reflective index was calculated as described in Methods. × denotes the calculated inflection point (= turning point) of the digital volume pulse wave. The shaded area indicates the area of the pulse wave described by the reflective index, which represents the ‘shoulder region’ of the diastolic component of the digital volume pulse wave. The ‘shoulder region’ arises from pressure waves reflected back along the aorta from small arteries. In this patient showing a glomerular filtration rate of 88 mL/min, the reflective index was 36.9 at baseline and 23.9 during reactive hyperemia, respectively. (C) Summary data of the reflective index in 48 patients with renal allograft. The reflective index was obtained at baseline and during reactive hyperemia. Data are mean ± SEM. **p < 0.01 by non-parametric Wilcoxon–Mann–Whitney test. (D) The changes of the reflective index during reactive hyperemia were grouped according to glomerular filtration rate. *p < 0.05 by non-parametric Kruskal–Wallis test between the groups (Kruskal–Wallis statistic = 6.61).

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The mean reflective index was 33.3 ± 1.8 in 48 patients with renal allograft. After the release of a sphygmomanometric cuff, the reflective index in these patients was significantly reduced to 29.3 ± 1.6 (p < 0.001 by Wilcoxon–Mann–Whitney test; Figure 2C). This reduction of the reflective index indicated vasodilation. The mean change of reflective index during reactive hyperemia was 4.0 ± 0.9. There was a significant association between reduced vasodilation, i.e. a smaller change of reflective index, and advanced stage of chronic kidney disease (stage 1 or 2, 8.5 ± 1.5; stage 3, 4.1 ± 1.8; stage 4 or 5, 2.5 ± 1.1; p < 0.05 by non-parametric Kruskal–Wallis test; Kruskal–Wallis statistic = 6.61; Figure 2D). These results indicated an impaired vascular response during reactive hyperemia with progressive loss of renal allograft function.

As shown in Figure 3, there was a significant correlation between an increased calcium × phosphate product and a smaller change of reflective index during reactive hyperemia (Spearman r = 0.29; p = 0.04). When multivariate linear regression analysis was performed, a reduced change of the reflective index was significantly associated with a reduced glomerular filtration rate (β= 0.42; p = 0.01), but calcium × phosphate product was no longer independently associated, probably since calcium × phosphate product is inversely proportional related to glomerular filtration rate. These results underscored the importance of progressive loss of renal allograft function also on vascular reactivity.

image

Figure 3. Correlation between calcium × phosphate product and change of reflective index in patients with renal allograft. The changes of the reflective index during reactive hyperemia, representing arterial vascular reactivity, were plotted against the calcium × phosphate product. Linear regression and 95% confidence interval are shown (Spearman r = 0.29; p = 0.04).

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Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. References

Non-invasive measurements of arterial vascular properties in patients with renal allograft showed a significant association between advanced stage of chronic kidney disease and increased arterial stiffness in renal transplant recipients. In addition, our measurements showed an impaired arterial vascular reactivity with progressive loss of renal allograft function.

In the literature, non-invasive measurements of arterial stiffness using applanation tonometry have been described repeatedly for screening subjects for early evidence of vascular disease (13–18) or for the determination of arterial stiffness in patients with chronic renal failure (19,20). Also, analysis of pulse waves obtained from digital photoplethysmography has been used to determine increased arterial stiffness and impaired vascular reactivity (23,26). Our results indicated an impaired arterial vascular response during reactive hyperemia, with progressive loss of renal allograft function. An impaired arterial vascular response to reactive hyperemia has been associated with cardiovascular diseases in several populations, including patients with chronic renal failure (34). London et al. showed for patients with end-stage renal failure that the reduced arterial vascular response to reactive hyperemia was associated with increased mortality (35).

In patients with end-stage renal failure, increased arterial stiffness is associated with increased mortality (10,36,37). To date, only a few studies on arterial stiffness have been performed in patients with renal allograft and impaired renal function (9,38,39). Bahous et al. showed that increased aortic stiffness was associated with increased cardiovascular risk in patients with renal allograft (9). Barenbrock et al. showed that increased stiffness of the common carotid artery in patients with renal allograft predicted occurrence of cardiovascular events (38). Furthermore, Bahous et al. demonstrated interactions between kidney function and arterial stiffness in living kidney donors and also in their corresponding recipients (39).

Since multivariate analysis of our data showed that older age of kidney donor, reduced glomerular filtration rate and male gender of renal allograft recipient were independently associated with increased arterial stiffness, the question arises as to how impaired renal allograft function affects arterial stiffness and vascular response. It has been shown that donor age is a predictor of poor long-term renal allograft survival (40) and that lesions of chronic allograft nephropathy strongly correlate with older donor age (41). Chronic allograft nephropathy in turn is characterized by a reduction of glomerular filtration rate. A reduced glomerular filtration rate has been directly correlated with an increased arterial stiffness in patients with chronic renal failure (42). Mechanisms that can cause an increase of arterial stiffness in patients with chronic renal failure are the remodeling of arteries, including medial and intimal hypertrophy, fibrosis and arterial calcifications that are enhanced in uremic patients (43). These changes are in part reversible after improving renal function, since Zoungas et al. showed an improvement of arterial pulse wave velocity 1 year after successful renal transplantation (44). These findings are in accordance with our notion that glomerular filtration rate is one of the major factors contributing to arterial stiffness in patients with renal allograft. Therefore, preservation of renal function could be of major importance for the reduction of cardiovascular disease and, therefore, probably, improvement of long-term survival of renal transplant recipients. Furthermore, our data showed that older donor age was significantly associated with an increase of arterial stiffness in renal transplant recipients. Hence, our data also may point to older donor age as an important challenge following the expansion of the donor pool. Our findings underscore the importance of achieving the best possible glomerular filtration rate, i.e. by further improvements of pre-transplantation procedures as reported recently (45,46).

The present cross-sectional study, which gives a ‘point-in-time’ picture of the present glomerular filtration rate and arterial vascular status, generates a hypothesis; however, it cannot give a cause-to-effect relationship. Furthermore, assessment of the relationship between arterial stiffness and the large number of variables that may be independently associated with arterial vascular stiffness warrants additional studies including a higher number of patients.

Taken together, our results show that progressive impairment of renal allograft function is associated with an increased arterial stiffness and an impaired arterial vascular reactivity in renal transplant recipients.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. References
  • 1
    Ponticelli C, Villa M, Cesana B, Montagnino G, Tarantino A. Risk factors for late kidney allograft failure. Kidney Int 2002; 62: 18481854.
  • 2
    Howard RJ, Patton PR, Reed AI et al. The changing causes of graft loss and death after kidney transplantation. Transplantation 2002; 73: 19231928.
  • 3
    Rabbat CG, Thorpe KE, Russell JD, Churchill DN. Comparison of mortality risk for dialysis patients and cadaveric first renal transplant recipients in Ontario, Canada. J Am Soc Nephrol 2000; 11: 917922.
  • 4
    Dimeny EM. Cardiovascular disease after renal transplantation. Kidney Int 2002; 80 (Suppl): 7884.
  • 5
    Rao PS, Schaubel DE, Saran R. Impact of graft failure on patient survival on dialysis: A comparison of transplant-naive and post-graft failure mortality rates. Nephrol Dial Transplant 2005; 20: 387391.
  • 6
    Kasiske BL, Guijarro C, Massy ZA, Wiederkehr MR, Ma JZ. Cardiovascular disease after renal transplantation. J Am Soc Nephrol 1996; 7: 158165.
  • 7
    EBPG Expert Group on Renal Transplantation. European best practice guidelines for renal transplantation. Section IV: Long-term management of the transplant recipient. IV.5.1. Cardiovascular risks. Cardiovascular disease after renal transplantation. Nephrol Dial Transplant 2002; 17 (Suppl 4): 2425.
  • 8
    Gill JS, Abichandani R, Kausz AT, Pereira BJ. Mortality after kidney transplant failure: The impact of non-immunologic factors. Kidney Int 2002; 62: 18751883.
  • 9
    Bahous SA, Stephan A, Barakat W, Blacher J, Asmar R, Safar ME. Aortic pulse wave velocity in renal transplant patients. Kidney Int 2004; 66: 14861492.
  • 10
    Blacher J, Guerin AP, Pannier B, Marchais SJ, Safar ME, London GM. Impact of aortic stiffness on survival in end-stage renal disease. Circulation 1999; 99: 24342439.
  • 11
    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: 461470.
  • 12
    Rodrigo E, Fernandez-Fresnedo G, Ruiz JC et al. Assessment of glomerular filtration rate in transplant recipients with severe renal insufficiency by Nankivell, Modification of Diet in Renal Disease (MDRD), and Cockroft–Gault equations. Transplant Proc 2003; 35: 16711672.
  • 13
    Finkelstein SM, Cohn JN. First- and third-order models for determining arterial compliance. J Hypertens 1992; 10 (Suppl): S11S14.
  • 14
    McVeigh GE, Bratteli CW, Morgan DJ et al. Age-related abnormalities in arterial compliance identified by pressure pulse contour analysis: Aging and arterial compliance. Hypertension 1999; 33: 13921398.
  • 15
    Cohn JN, Finkelstein S, McVeigh G et al. Noninvasive pulse wave analysis for the early detection of vascular disease. Hypertension 1995; 26: 503508.
  • 16
    Rietzschel ER, Boeykens E, De Buyzere ML, Duprez DA, Clement DL. A comparison between systolic and diastolic pulse contour analysis in the evaluation of arterial stiffness. Hypertension 2001; 37: E15E22.
  • 17
    Arnett DK, Glasser SP, McVeigh G et al. Blood pressure and arterial compliance in young adults: The Minnesota Children's Blood Pressure Study. Am J Hypertens 2001; 14: 200205.
  • 18
    Duprez DA, Kaiser DR, Whitwam W et al. Determinants of radial artery pulse wave analysis in asymptomatic individuals. Am J Hypertens 2004; 17: 647653.
  • 19
    Cohen DL, Townsend RR. Large and small artery compliance changes during hemodialysis. Am J Hypertens 2002; 15: 236239.
  • 20
    Scholze A, Maier A, Stocks F et al. Sustained increase of extracellular calcium concentration causes arterial vasoconstriction in humans. J Hypertens 2005; 23: 20492054.
  • 21
    Woodman RJ, Kingwell BA, Beilin LJ et al. Assessment of central and peripheral arterial stiffness: Studies indicating the need to use a combination of techniques. Am J Hypertens 2005; 18: 249260.
  • 22
    Takazawa K, Tanaka N, Fujita M et al. Assessment of vasoactive agents and vascular aging by the second derivative of photoplethysmogram waveform. Hypertension 1998; 32: 365370.
  • 23
    Chowienczyk PJ, Kelly RP, MacCallum BN et al. Photoplethysmographic assessment of pulse wave reflection. J Am Coll Cardiol 1999; 34: 20072014.
  • 24
    Millasseau SC, Guigui FG, Kelly RP et al. Noninvasive assessment of the digital volume pulse. Comparison with the peripheral pressure pulse. Hypertension 2000; 36: 952956.
  • 25
    Millasseau SC, Kelly RP, Ritter JM, Chowienczyk PJ. Determination of age-related increases in large artery stiffness by digital pulse contour analysis. Clin Sci 2002; 103: 371377.
  • 26
    Woodmann RJ, Watts GF, Kingwell BA, Dart AM. Interpretation of the digital volume pulse: Its relationship with large and small artery compliance. Clin Sci (Lond) 2003; 104: 283285.
  • 27
    Avolio A. The finger volume pulse and assessment of arterial properties. J Hypertens 2002; 20: 23412343.
  • 28
    Scholze A, Rinder C, Beige J, Riezler R, Zidek W, Tepel M. Acetylcysteine reduces plasma homocysteine concentration and improves pulse pressure and endothelial function in patients with end-stage renal failure. Circulation 2004; 109: 369374.
  • 29
    Burkert A, Scholze A, Tepel M. Non-invasive continuous monitoring of digital pulse waves during hemodialysis. ASAIO J 2006 (in press).
  • 30
    Goldman JM, Petterson MT, Kopotic RJ, Barker SJ. Masimo signal extraction pulse oximetry. J Clin Monit Comput 2000; 16: 475483.
  • 31
    Bonetti PO, Pumper GM, Higano ST, Holmes DR Jr, Kuvin JT, Lerman A. Noninvasive identification of patients with early coronary atherosclerosis by assessment of digital reactive hyperemia. J Am Coll Cardiol 2004; 44: 21372141.
  • 32
    Higashi Y, Sasaki S, Nakagawa K, Matsuura H, Kajiyama G, Oshima T. A noninvasive measurement of reactive hyperemia that can be used to assess resistance artery endothelial function in humans. Am J Cardiol 2001; 87: 121125.
  • 33
    Pyke KE, Tschakovsky ME. The relationship between shear stress and flow-mediated dilatation: Implications for the assessment of endothelial function. J Physiol 2005; 568: 357369.
  • 34
    Gokce N, Keaney JF Jr, Hunter LM et al. Predictive value of noninvasively determined endothelial dysfunction for long-term cardiovascular events in patients with peripheral vascular disease. J Am Coll Cardiol 2003; 41: 17691775.
  • 35
    London GM, Pannier B, Agharazii M, Guerin AP, Verbeke FMH, Marchais SJ. Forearm reactive hyperemia and mortality in end-stage renal disease. Kidney Int 2004; 65: 700704.
  • 36
    Groothoff JW, Gruppen MP, Offringa M et al. Increased arterial stiffness in young adults with end-stage renal disease since childhood. J Am Soc Nephrol 2002; 13: 29532961.
  • 37
    Guerin AP, Blacher J, Pannier B, Marchais SJ, Safar ME, London GM. Impact of aortic stiffness attenuation on survival of patients in end-stage renal failure. Circulation 2001; 103: 987992.
  • 38
    Barenbrock M, Kosch M, Joster E, Kisters K, Rahn KH, Hausberg M. Reduced arterial distensibility is a predictor of cardiovascular disease in patients after renal transplantation. J Hypertens 2002; 20: 7984.
  • 39
    Bahous SA, Stephan A, Blacher J, Safar ME. Aortic stiffness, living donors, and renal transplantation. Hypertension 2006; 47: 216221.
  • 40
    Halloran PF, Melk A, Barth C. Rethinking chronic allograft nephropathy: The concept of accelerated senescence. J Am Soc Nephrol 1999; 10: 167181.
  • 41
    Nickerson P, Jeffery J, Gough J et al. Identification of clinical and histopathologic risk factors for diminished renal function 2 years posttransplant. J Am Soc Nephrol 1998; 9: 482487.
  • 42
    Mourad JJ, Pannier B, Blacher J et al. Creatinine clearance, pulse wave velocity, carotid compliance and essential hypertension. Kidney Int 2001; 59: 18341841.
  • 43
    Goldsmith D, Ritz E, Covic A. Vascular calcification: A stiff challenge for the nephrologist: Does preventing bone disease cause arterial disease? Kidney Int 2004; 66: 13151333.
  • 44
    Zoungas S, Kerr PG, Chadban S et al. Arterial function after successful renal transplantation. Kidney Int 2004; 65: 18821889.
  • 45
    Baid-Agrawal S, Reinke P, Schindler R, Tullius S, Frei U. WCN 2003 satellite symposium on kidney transplantation in the elderly, Weimar, Germany, June 12–14, 2003. Nephrol Dial Transplant 2004; 19: 4346.
  • 46
    Remuzzi G, Cravedi P, Perna A et al. Dual Kidney Transplant Group. Long-term outcome of renal transplantation from older donors. N Engl J Med 2006; 354: 343352.