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Saudi Journal of Kidney Diseases and Transplantation
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Year : 2014  |  Volume : 25  |  Issue : 1  |  Page : 58-65
Carotid artery stenosis in patients with chronic kidney disease undergoing dialysis: Epidemiological aspects, main risk factors and appropriate diagnostic criteria

Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran

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Date of Web Publication7-Jan-2014


Knowledge of the epidemiology and risk profile of peripheral vascular disease among patients with chronic kidney disease (CKD) has a potential role for determining its outcome. This study assessed the epidemiological aspects and risk factors of carotid artery stenosis (CAS), assessed by clinical ankle brachial index (ABI), in patients on dialysis. This study was performed on 84 patients with CKD undergoing hemodialysis (HD; n = 65) or peritoneal dialysis (PD; n = 19). The ABI was measured using a concurrent oscillometric method and Color Doppler sonography. An ABI value >0.9 was defined as normal. Severity of the stenosis was determined using B-Mode sonography. Overall, CAS was seen in 51.2% of the study patients. No significant difference was found in the overall prevalence of CAS between the HD and PD groups (50.8% vs. 52.6%, P = 0.552). The mean ABI in the HD and PD groups was 1.13 and 1.06, respectively. Among patient characteristics, advanced age was found to be a predictor of CAS in the study patients. Gender, type of dialysis or underlying risk factors could not predict CAS. ABI measurement was an acceptable predictor of CAS, with a receiver operator characteristic of 0.645. The optimal cut-off for ABI for predicting CAS was identified at 1.0; this yielded a sensitivity of 70.8% and a specificity of 63.6% for the test. In conclusion, a notable number of patients undergoing dialysis for CKD had CAS. The main predictive factor was advanced age. ABI measurement seems to be an acceptable tool to diagnose CAS.

How to cite this article:
Hakimi SS, Saberi H, Rokniyazdi H, Salahi M. Carotid artery stenosis in patients with chronic kidney disease undergoing dialysis: Epidemiological aspects, main risk factors and appropriate diagnostic criteria. Saudi J Kidney Dis Transpl 2014;25:58-65

How to cite this URL:
Hakimi SS, Saberi H, Rokniyazdi H, Salahi M. Carotid artery stenosis in patients with chronic kidney disease undergoing dialysis: Epidemiological aspects, main risk factors and appropriate diagnostic criteria. Saudi J Kidney Dis Transpl [serial online] 2014 [cited 2021 Jun 19];25:58-65. Available from: https://www.sjkdt.org/text.asp?2014/25/1/58/124488

   Introduction Top

Appearance of peripheral arterial disease (PAD) has been one of the main topics of interest in patients with chronic kidney disease (CKD) undergoing dialysis. Numerous studies have been conducted on the epidemiological and risk factors related to PAD. [1],[2],[3],[4],[5] The estimated preva­lence of PAD is dependent on the diagnostic method selected and the population of interest. [6] Therefore, knowledge of the epidemiology and risk profile of PAD among patients with CKD has a potential role in determining its outcome and selecting the best treatment options. Pre­vious studies have reported that the overall pre­valence of PAD in the adult population is 12%.

However, this figure might vary because of the usage of different criteria and diagnostic parameters. [7] The most important established risk factors for PAD include male gender, advanced age, diabetes, smoking, hypertension, dyslipidemia, hyper-homocysteinemia and chronic in­flammation, while alcohol consumption and physical activity seem to have a protective role. [8],[9],[10],[11],[12],[13],[14] Among dialysis patients, some of the risk factors for PAD might be the same as for the general population, but there also seem to be associations that are unique to dialysis patients.

In clinical studies, several methods have been used to measure PAD and other types of arterial stiffness, including pulse wave velocity, sys­temic arterial compliance and augmentation index. One of the indices that is mostly used in clinical practice is the Ankle Brachial Index (ABI). The ABI is a quantitative marker of arte­rial stiffness and is assessed by measuring the volumetric changes of the brachial artery. In the general population, an ABI <0.90 correlates well with the presence of angiographic evi­dence of PAD. [15],[16]

Although several studies have previously add­ressed the epidemiological aspects and risk factors of carotid artery stenosis (CAS) in dia­lysis patients, these aspects have not been evaluated in our country. Moreover, the effects of the type of dialysis, namely hemodialysis (HD) or peritoneal dialysis (PD), on the preva­lence of CAS is not clear. The current study is designed to try and answer these issues.

   Materials and Methods Top

This case series study was performed at the Imam Khomeini Hospital in Tehran, Iran. Bet­ween 1 April 2009 and 1 April 2010, 84 pa­tients with CKD who underwent HD (n = 65) or PD (n = 19) were consecutively enrolled and entered into the study. Informed consent was obtained from all study participants. Underlying etiology of the kidney disease included chronic glomerulonephritis in five patients, hyperten­sive nephrosclerosis in 21 patients, diabetic nephropathy in 30 patients and other diseases in 28 patients. This study was approved by the ethics committee of the Tehran University of Medical Sciences. Data on the age, sex, weight, history of traditional risk factors, laboratory parameters, comorbid conditions, underlying etiologies, medications and type as well as du­ration on dialysis were obtained from the hos­pital records.

The values of the ABI were measured 10-30 min before dialysis. The ABI was measured by using a concurrent oscillometric method and Color Doppler sonography (Siemens G40, Germany) and was calculated by the ratio of the ankle systolic blood pressure (BP) divided by the arm systolic BP. The systolic BP of the arm not having the dialysis access and the lower value of the ankle systolic BP were used for the calculation. The ABI measurement was per­formed once in each patient. An ABI value >0.9 was defined as normal. Severity of CAS was determined by the standard method using B-Mode (gray scale) sonography (Siemens G40, Germany).

Data are expressed as mean ± standard devia­tion (SD) or percentages. Continuous data were compared by unpaired Student's t-test. Cate­gorical variables were compared by chi-square or Fisher's exact test, as appropriate. Multiple regression analysis was performed to identify factors independently correlated with CAS in dialysis patients. The cut-off score of the ABI, for prediction of CAS in dialysis patients, was estimated by the receiver operator characteristic (ROC) curve analysis (the empirical point that maximizes sensitivity and specificity of ABI for predicting ROC PAD). All tests were two-tailed and a P-value of 0.05 or less was considered statistically significant. All calculations were performed with SPSS version 0 (SPSS Inc., Chicago, IL, USA).

   Results Top

The demographic and clinical characteristics of our subjects are listed in [Table 1]. A total of 84 patients were included for analysis in this study; 65 patients were on HD while 19 were on PD. The two groups were similar in terms of baseline demographic characteristics as well as underlying risk profile. Analysis of the labora­tory parameters revealed some differences bet­ween the groups. The total cholesterol, triglyceride and low-density lipoprotein levels were all higher in the PD group, while the serum albu­min, uric acid and total bilirubin levels were significantly higher in the HD group.
Table 1: Baseline characteristics and clinical data of the study participants on hemodialysis and peritoneal dialysis.

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The overall prevalence of CAS was 51.2%, and no significant difference was found bet­ween patients on HD and PD (50.8% vs. 52.6%, P = 0.552). The mean ABI in the HD and PD groups was 1.13 and 1.06, respectively; the dif­ference was not statistically significant. Accor­ding to the ROC curve analysis, ABI measure­ment was an acceptable indicator of CAS, with the area under the ROC curve being 0.645 (95% CI: 0.452-0.838) [Figure 1]. The optimal cut-off value for ABI for predicting CAS was iden­tified as 1.0, yielding a sensitivity of 70.8% and a specificity of 63.6% [Figure 2].
Figure 1: Receiver operator characteristic (ROC) curves constructed to investigate the diagnostic capability of ankle brachial index for predicting carotid artery stenosis.

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Figure 2: Optimal cut-off value of ankle brachial index for prediction of carotid artery stenosis (best cutoff point was 1.0).

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The most common diseases associated with CAS were diabetes mellitus (33.8% in the HD group and 42.1% in the PD group), followed by hypertension (27.7% in the HD group and 15.8% in the PD group) and glomerulonephritis (6.2% in the HD group and 5.3% in the PD group). Other uncommon causes included polycystic kidney, renal stone, pyelonephritis, benign pros­tate hyperplasia and Wegener's granulomatosis.

Study of the prevalence of CAS in different sub-groups [Table 2] revealed that it was more prevalent in older patients and diabetic patients and, to a lesser extent, among those with con­comitant coronary artery disease. Multivariate logistic regression analysis showed that among patient characteristics, only advanced age was a predictor of appearance of CAS in patients undergoing dialysis [Table 3]. Gender, type of dialysis or underlying risk factors could not predict CAS in the study subjects.
Table 2: Prevalence of carotid artery stenosis in the different sub-groups.

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Table 3: Multivariate analysis for determining main predictors of carotid artery stenosis in dialysis patients.

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   Discussion Top

The mechanisms for arterial stenosis and stiff­ness in patients undergoing dialysis are as yet unclear. However, some probable mechanisms have been considered to be involved in this pa­thological state, including arterial calcification, chronic volume overload, increased mechanical stress by hypertension, chronic micro-inflam­mation, sympathetic over-activity, lipid peroxidation and abnormalities of the nitric oxide system. [17] It has been noted that even mild de­terioration in kidney function might be a risk factor in itself for the development of PAD in these patients. [18]

To the best of our knowledge, the current study is the first study describing the preva­lence of CAS and its risk factors, main etio­logies and diagnostic criteria among the Iranian population. Additionally, this study determined the value of ABI index in the diagnosis of CAS (confirmed by sonography). Our study showed that the prevalence of CAS in our study patients was 51.2%. Also, the mean ABI in the HD and PD groups was 1.13 and 1.06, respectively. We assessed the traditional risk factors for CAS in our patients and found that only advanced age was associated with a higher prevalence of this complication. In our study, we considered ste­nosis with different levels of severity; some other studies have assessed only stenosis more than 50% for assessing carotid artery disease. As described in community-cohort studies, the prevalence of an ABI less than 0.90 has ranged from less than 5% to as high as 12.4%. [19],[20] The prevalence-estimates among patient-cohorts recruited from medical clinics tend to be consi­derably higher; [21],[22] thus, 29% of the high-risk patients enrolled from primary-care clinics had an ABI of less than 0.90. [22] However, patients eligible for this study included those over 70 years old and those between the ages of 50 and 69 years who had diabetes or a smoking his­tory. In a study by Chen et al, the prevalence of ABI <0.9 was 15.6%, and this was associated with advanced age, increased pulse pressure, increased hematocrit and decreased serum albu­min level. [23] In another study by Bilancini et al, 20% of dialysis patients showed CAS versus 12% in the control group, adjusted to sex, age and hypertension. [24] Apart from the well-defined risk factors for the development of arterial ste­nosis in patients on dialysis, such as hyper-phosphatemia, hyperparathyroidism and hyper-calcemia, there are some other risk factors that are thought to play a role; they include malnu­trition, homocysteine levels, use of beta-blockers, derangements in bone mineral metabo­lism and some infections such as hepatitis C. [25],[26] Therefore, taking into consideration all probable risk factors and etiologies, beside traditional parameters, it is required to properly manage patients on dialysis with CAS.

We took 1.0 as the optimal cut-off point for ABI for differentiating CAS from normal arteries. Some studies have shown that a low ABI is only partially sensitive and specific for the presence of greater than 50% stenosis of lower extremity vessels on angiography. [27] In our study patients, the prevalence of PAD (based on ABI <0.9) was 15.5%. Other studies used different cut-off points for the assessment of CAS in patients with CKD. In support of this observation, Leskinen et al [27] reported an ex­tremely high prevalence of ABI above 1.30 among Finnish pre-dialysis patients, HD pat­ients and post-renal transplant patients. These numbers are much higher than those reported for several larger dialysis-patient cohorts. For example, 7% among a sample of 132 patients on HD in the United States [28] and 10.9% among a sample of 1010 Japanese patients on HD had an ABI higher than 1.30. For comparison, in the latter study, 0.67% of patients in an age- and gender-matched control group of healthy vo­lunteers had an ABI higher than 1.30. [29] Col­lectively, our results and these findings suggest that a broader range of ABI measurements may be encountered in dialysis patients. In fact, in our patient population, a cut-off point of 1.0 can be the most appropriate value in the diagnosis of CAS in dialysis patients. However, the use of the sum of diagnostic criteria such as imaging techniques, clinical parameters and laboratory indices concurrently seems to be better and more reliable in these subjects.

   References Top

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Correspondence Address:
Shahram Shams Hakimi
Radiology Department, Imam Khomeini Hospital, Tehran
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DOI: 10.4103/1319-2442.124488

PMID: 24434383

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  [Figure 1], [Figure 2]

  [Table 1], [Table 2], [Table 3]


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