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Table of Contents
ORIGINAL ARTICLE
Year : 2012  |  Volume : 13  |  Issue : 3  |  Page : 91-96  

A study of atherosclerosis in patients with chronic renal failure with special reference to Carotid Artery Intima Media Thickness


1 Department of Medicine, Burdwan Medical College, West Bengal, India
2 Department of Radiology, Burdwan Medical College, West Bengal, India
3 Department of General Medicine, N R S Medical College, West Bengal, India

Date of Web Publication9-Oct-2012

Correspondence Address:
Jayanta Paul
Department of General Medicine, Burdwan Medical College,C/o Jitendra Chandra Paul, J+B lodge, Santosh Sarani,Banamali Pur, Barasat, North 24 Parganas, West Bengal - 700124
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/1995-705X.102147

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   Abstract 

Objectives: Cardiovascular disease is the leading cause of morbidity and mortality in patients with chronic renal failure (CRF). This study attempts to identify the factors responsible for atherosclerosis in CRF patients using carotid artery intima media thickness (CAIMT) as a surrogate marker of atherosclerosis.
Materials and Methods: CAIMT was measured by high-resolution B-mode ultrasonography in 100 CRF patients and 50 age- and sex-matched healthy controls. Data were analyzed by software SPSS (17 th version) for Windows.
Results: CRF patients had a significantly higher CAIMT (1026.83 ± 17.19 micron, mean ± SE, P < 0.001) than age- and sex-matched healthy controls (722.46 ± 7.61 micron). There was inverse correlation between CAIMT and glomerular filtration rate (GFR) (P < 0.001) independent of traditional risk factors. There was also significant positive correlation between CAIMT and traditional risk factors of atherosclerosis. Ischemic heart disease (IHD) also showed positive correlation with CAIMT (P = 0.007) and inverse correlation with GFR (P = 0.005).
Conclusions: There is high prevalence of atherosclerosis in CRF patients. CAIMT can be used to detect and predict future incidence of IHD in CRF patients.

Keywords: Atherosclerosis, carotid artery intima media thickness, chronic renal failure, ischemic heart disease, traditional risk factors of atherosclerosis


How to cite this article:
Paul J, Dasgupta S, Ghosh MK, Shaw K, Roy KS, Niyogi SM. A study of atherosclerosis in patients with chronic renal failure with special reference to Carotid Artery Intima Media Thickness. Heart Views 2012;13:91-6

How to cite this URL:
Paul J, Dasgupta S, Ghosh MK, Shaw K, Roy KS, Niyogi SM. A study of atherosclerosis in patients with chronic renal failure with special reference to Carotid Artery Intima Media Thickness. Heart Views [serial online] 2012 [cited 2018 May 24];13:91-6. Available from: http://www.heartviews.org/text.asp?2012/13/3/91/102147


   Introduction Top


Chronic renal failure (CRF) is associated with premature atherosclerosis and increased cardiovascular morbidity and mortality in hemodialysis (HD), predialysis (PD) patients and also in patients who have undergone renal transplantation or who are on medical conservative treatment. [1],[2] In patients with CRF, cardiovascular disease (CVD) is twice as common as in the general population. [3] As compared with the general population, dialysis patients have more than a 10 times higher relative risk for cardiovascular mortality. [1] Carotid artery intima media thickness (CAIMT) is increasingly used as a surrogate marker of early atherosclerosis and it was shown that CAIMT is a strong predictor of future myocardial infarction and stroke. [4] The CAIMT can be easily, safely, reliably, and inexpensively measured with B-mode ultrasound, and the predictive value of this measurement is increased when CAIMT is measured at different extracranial carotid sites. [5]

The CAIMT was found to be increased in subjects with impaired renal function, [6],[7],[8] though contrasting results have also been published. [9] Therefore, there is still controversy regarding accelerated atherosclerosis in CRF and its assessment with CAIMT.

This study was directed (1) to find out the correlation between atherosclerosis and CRF using CAIMT as a surrogate marker, (2) to look into the relationship between various classical risk factors of atherosclerosis and CAIMT in CRF patients, (3) to look into the relationship between ischemic heart disease (IHD) and glomerular filtration rate (GFR) independent of classical risk factors.


   Materials and Methods Top


Study population

The study subjects included 100 CRF patients and 50 age- and sex-matched healthy controls. Healthy controls were nonsmoker, nonhypercholesterolemic, nonhypertensive, nondiabetic. 24-hours urine total albumin was not measurable by Esbach's albuminometer. Both CRF patients and healthy controls had normal body mass index, body weight, and waist circumference.

After taking consent, all subjects underwent a careful interview, a clinical examination with an evaluation of patient history based on hospital and outpatients records and laboratory investigations. Venous blood was taken in the morning after an overnight fast for at least 12 hours for biochemical analysis. All biochemical tests were performed at Department of Biochemistry, Burdwan Medical College, Burdwan, West Bengal, India.

Hypertension

The average of three blood pressure measurements was used for analysis. Hypertension was diagnosed when a patient had received medicine for hypertension or had systolic blood pressure ≤140 mmHg and/or diastolic blood pressure ≤90 mmHg after taking 5 min rest. [10]

Diabetes

Plasma glucose was measured by a "glucose oxidase-peroxidase" method. Diabetes was diagnosed according to "American Diabetes Association" when a previous or current 12 hours fasting glucose level is 7 mmol/l or greater (≥126 mg/dl).

Glomerular Filtration Rate

CRF was identified when GFR was <60 ml/min/1.73 m 2 for consecutive 3 months or more. [11] Estimated GFR (eGFR) was calculated using the "Modification of Diet in Renal Disease" (MDRD) formula [12] : eGFR = 186.3 × (serum creatinine−1.154 ) × (age−0.203 ) × 1.212 (if black)× 0.742 (if female).

Albuminuria

Twenty-four hours urine total albumin excretion is the "gold standard" for measurement of albuminuria [13] and was measured by Esbach's albuninometer.

Hypercholesterolemia

Serum total cholesterol was measured by "cholesterol oxidase-peroxidase" method. Patients who used cholesterol lowering medication or had a total serum cholesterol level ≥200 mg/dl were classified as having hypercholesterolemia. [14]

Smoking

Participants were classified as nonsmokers if they responded that they had smoked fewer than 100 cigarettes or five packs of cigarettes during their lifetime. [15]

Dialysis

CRF patients, who had been on regular hemodialysis treatment (treated thrice weekly) for at least 6 months, [16] were identified as hemodialyzed patients.

Ischemic heart disease

IHD was diagnosed by history and ECG.

Carotid ultrasound

Examination of the carotid arteries was performed with a 7-MHz B-mode ultrasound system (Philips-HD7 Diagnostic Ultrasound System, made in China). CAIMT is defined as a low-level echo gray band that does not project into the arterial lumen was measured at the diastolic phase as the distance between the leading edge of the first and second echogenic lines of the far walls of the distal segment of the common carotid artery, the carotid bifurcation, and the internal carotid artery on both sides. [16] CAIMT was measured [Figure 1] at the right and left common carotid arteries (3 cm before the carotid bifurcation), carotid bifurcation, as well as of the internal carotid artery 2 cm distally from the carotid bifurcation. [17] CAIMT measurements were always performed in plaque-free arterial segments. [16] All examinations and measurements were performed by same examiner to exclude examiner bias.
Figure 1: Measurement of intima media thickness at right carotid bifurcation (RT CC BULB) and right common carotid artery (RT CCA)

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Statistical analysis

Chi-square test, paired t test, independent samples t-test, and linear multivariate regression analysis with 95% confidence interval was done for data analysis. P value less than 0.05 was taken as statistically significant. Data were expressed as means ± SE (Standard Error). All these analysis were performed using a commercially available software SPSS (17 th version for Windows) on a personal computer.

Ethical clearance

The ethical committee of the Burdwan Medical College, Burdwan, India approves this study.


   Results and Analysis Top


Out of 100 CRF patients, 71 were male and 29 were female, and out of 50 normal healthy controls, 30 were male and 20 were female [Table 1]. Demographic characters of CRF patients and healthy controls are shown in [Table 1] and [Figure 2].
Figure 2: Comparison of CAIMT of different groups of CRF patients

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Table 1: Demographic characters and clinical data of CRF patients and healthy controls

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Independent samples t test and chi-square test showed that healthy controls were age-matched (P = 0.075) and sex-matched (P = 0.176) with CRF patients, respectively.

Mean CAIMT value of CRF patients and healthy controls were 1026.83 ± 17.19 micron and 722.46 ± 7.61 micron, respectively. This difference is statistically significant (P < 0.001). CAIMT was positively correlated with age, sex, hypertension, hypercholesterolemia, smoking, dialysis, fasting blood sugar, and 24-hours total urine albumin excretion. But GFR was inversely correlated with CAIMT [Table 2].
Table 2: Linear multivariate regression analysis of traditional risk factors correlating with CAIMT

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CAIMT of male CRF patients (1064.48 ± 17.37 micron, P = 0.003) was significantly higher than that of female (934.66 ± 36.49 micron).

Hypercholesterolemic CRF patients had higher CAIMT (1136.44 ± 17.4 micron, P < 0.001) than patients with normal cholesterol level (982.5 ± 20.98 micron). Hypertensive patients were associated with significantly higher CAIMT (1091.18 ± 17.81 micron, P < 0.001) than nonhypertensive CRF patients (907.31 ± 26.51 micron). Diabetic CRF patients had significantly higher CAIMT (1107.31 ± 14.88 micron, P value = 0.001) than nondiabetic CRF patients (988.95 ± 20.98 micron) [Table 3]. CRF patents with albuminuria ≥1000 mg had significantly higher CAIMT (1124.83 ± 30.85 micron, P = 0.000) than patients with albuminuria <1000 mg (976.34 ± 17.82 micron) [Table 3].
Table 3: Comparison of CAIMT of different groups of CRF patients by independent samples t test

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Smokers had significantly higher mean CAIMT (1117.44 ± 19.26 micron, P < 0.001) than nonsmoker (958.47 ± 22.64 micron) CRF patients. Dialyzed patients had higher CAIMT (1107.80 ± 24.56 micron, P = 0.000) than nondialyzed CRF patients (960.58 ± 20.05 micron).

In this study, 13 CRF patients were suffering from IHD. There was significant inverse correlation between GFR and IHD (P = 0.005) and positive correlation between GFR and CAIMT (P = 0.007).


   Discussion Top


In this study, it was found that the mean CAIMT in CRF patients was significantly higher than age- and sex-matched healthy controls (P < 0.001). This result is similar to other previous several studies. [18],[19],[20]

Kumar et al.[18] observed that the mean CAIMT value in CRF patients was 1000 micron as compared with 730 micron in healthy control group in their study. Cornel et al.[19] demonstrated that mean CAIMT of healthy population was <800 micron. Ricotta et al. [21] again demonstrated that CAIMT >1000 micron is indicative of atherosclerosis. According to the above criteria, in our study, 66% CRF patients were suffering from atherosclerosis.

In concordance with various previous studies, [22],[23] our study also showed that CAIMT was independently correlated with age, sex, smoking, hypertension, hypercholesterolemia, dialysis, 24-hours total urine protein excretion, fasting blood sugar, and GFR.

Observed correlation between CAIMT and age in various previous studies [24],[25] was also seen in our study. It was also found that there was independent positive correlation between age and CAIMT (P = 0.014). Higher CAIMT was seen in CRF patients with advanced age.

In several studies, it was observed that the CAIMT changes in relation to sex and always higher in men than in women. [26],[27] Our study also contributed this finding.

"Smoking is an independent risk factor for atherosclerosis"-this statement was proved by our study, as in several previous studies. [15],[24],[28] In our study, 86.04% of smokers and 50.87% of nonsmokers with CRF were suffering from atherosclerosis and there was significant positive correlation between smoking and CAIMT, and smoker had significantly higher mean CAIMT than nonsmoker. Therefore, smoking secession program should be advised to CRF patients to halt atherosclerosis progression.

Our study also showed that dialysis was positively correlated with CAIMT. Hemodialyzed patients had significant higher CAIMT than nondialyzed patients as many previous studies. [29],[30]

In concordance with various previous studies, [31],[32] hypertension had an independent positive correlation with CAIMT in CRF patients. In this study, 96.92% hypertensive CRF patients were suffering from atherosclerosis. Therefore, blood pressure should be controlled in the patient with CRF to halt the progression of atherosclerosis.

In concordance with various previous studies, [33],[34] hypercholesterolemia was also identified as an independent risk factor of atherosclerosis by this study. Some study showed that the treatment of hyperlipidemia may reduce the rate of kidney function decline in individuals with CRF [35] and this outcome may help to reduce atherosclerosis progression.

In our study, 66% of all CRF patients with macroalbuminuria and 85.29% of CRF patients with albuminuria ≥1000 mg/24 hours were suffering from atherosclerosis. Measures should be taken to halt albuminuria because Albuminuria is a powerful independent risk factor for both the progression of kidney disease, as well as for the development of CVD. [36]

This study also observed that FBS was positively correlated with CAIMT as previous several studies. [24],[37] 90.62% of the patients among the patients of CRF with diabetes had atherosclerosis and had significantly higher CAIMT than nondiabetic CRF patients. So tight glycemic control is required in diabetic CRF patients to halt or slow the progression of atherosclerosis.

GFR was inversely correlated with CAIMT in our study. This result is supported by several previous studies. [22],[23],[37] Desbien et al.[22] in their cohort study described that decreased kidney function was strongly associated with faster change in CAIMT. In addition, decreased kidney function and faster change in CAIMT are associated with cardiovascular events. In our study, there was also significant negative correlation between GFR and IHD.

There are a number of possible explanations for the independent association of reduced GFR and CAIMT. First, a reduced GFR may be associated with an increased level of nontraditional atherosclerosis risk factors that frequently are not assessed in many studies. Second, reduced GFR may be a measurement of residual confounding from traditional atherosclerosis risk factors. Third, reduced GFR are less likely to receive medications such as angiotensin converting enzyme inhibitors, β-blockers, aspirin, platelet inhibitors, and thrombolytics than patients with preserved GFR. Fourth, reduced GFR may be a marker of undiagnosed vascular disease or a marker for the severity of diagnosed vascular disease.

There were some limitations in this study because (1) premature atherosclerosis, serum homocysteine, lipoprotein (a), physical activity, atherogenic diet, pro-inflammatory factors, and pro-thrombotic factors could not be examined due to the limitations of budget and study design and (2) small numbers of participants were included.


   Conclusion Top


This study shows that CRF increases risk of atherosclerosis independent of traditional risk factors. Traditional risk factors add to the possibility of atherosclerosis in CRF patients. Atherosclerosis as measured by CAIMT is indicative of IHD also. Hence, this study suggests that CAIMT may be used for detection and prediction of IHD and aggressive control of traditional risk factors may lower incidence of cardiovascular events in CRF patients.

 
   References Top

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    Figures

  [Figure 1], [Figure 2]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]


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