|Year : 2012 | Volume
| Issue : 3 | Page : 91-96
A study of atherosclerosis in patients with chronic renal failure with special reference to Carotid Artery Intima Media Thickness
Jayanta Paul1, Somnath Dasgupta1, Mrinal Kanti Ghosh2, Kishore Shaw1, Keshab Sinha Roy3, Syamal Mitra Niyogi2
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 Publication||9-Oct-2012|
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
Source of Support: None, Conflict of Interest: None
| 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 2022 Jan 20];13:91-6. Available from: https://www.heartviews.org/text.asp?2012/13/3/91/102147
| Introduction|| |
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. , In patients with CRF, cardiovascular disease (CVD) is twice as common as in the general population.  As compared with the general population, dialysis patients have more than a 10 times higher relative risk for cardiovascular mortality.  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.  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. 
The CAIMT was found to be increased in subjects with impaired renal function, ,, though contrasting results have also been published.  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|| |
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.
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. 
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.  Estimated GFR (eGFR) was calculated using the "Modification of Diet in Renal Disease" (MDRD) formula  : eGFR = 186.3 × (serum creatinine−1.154 ) × (age−0.203 ) × 1.212 (if black)× 0.742 (if female).
Twenty-four hours urine total albumin excretion is the "gold standard" for measurement of albuminuria  and was measured by Esbach's albuninometer.
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. 
Participants were classified as nonsmokers if they responded that they had smoked fewer than 100 cigarettes or five packs of cigarettes during their lifetime. 
CRF patients, who had been on regular hemodialysis treatment (treated thrice weekly) for at least 6 months,  were identified as hemodialyzed patients.
Ischemic heart disease
IHD was diagnosed by history and ECG.
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.  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.  CAIMT measurements were always performed in plaque-free arterial segments.  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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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.
The ethical committee of the Burdwan Medical College, Burdwan, India approves this study.
| Results and Analysis|| |
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].
|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|| |
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. ,,
Kumar et al. 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. demonstrated that mean CAIMT of healthy population was <800 micron. Ricotta et al.  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, , 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 , 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. , 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. ,, 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. ,
In concordance with various previous studies, , 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, , 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  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. 
This study also observed that FBS was positively correlated with CAIMT as previous several studies. , 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. ,, Desbien et al. 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|| |
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|| |
|1.||Foley RN, Parfrey PS, Sarnak MJ. Clinical epidemiology of cardiovascular disease in chronic renal disease. Am J Kidney Dis 1998;32:S112-9. |
|2.||Goodman WG, Goldin J, Kuizon BD, Yoon C, Gales B, Sider D, et al. Coronary-artery calcification in young adults with end-stage renal disease who are undergoing dialysis. N Engl J Med 2000;342:1478-83. |
|3.||Collins AJ, Li S, Gilbertson DT, Liu J, Chen SC, Herzog CA. Chronic kidney disease and cardiovascular disease in the medicare population. Kidney Int Suppl 2003;64:S24-31. |
|4.||Lorenz MW, Markus HS, Bots ML, Rosvall M, Sitzer M. Prediction of clinical cardiovascular events with carotid intima-media thickness. A systematic review and meta-analysis. Circulation 2007;115:459-67. |
|5.||Simon A, Gariepy J, Chironi G, Megnien JL, Levenson J. Intima-media thickness: A new tool for diagnosis and treatment of cardiovascular risk. J Hypertens 2002;20:159-69. |
|6.||Zhang L, Zhao F, Yang Y, Qi L, Zhang B, Wang F, et al. Association between carotid artery intima-media thickness and early-stage CKD in a Chinese population. Am J Kidney Dis 2007;49:786-92. |
|7.||Ishizaka N, Ishizaka Y, Toda E, Koike K, Seki G, Nagai R, et al. Association between chronic kidney disease and carotid intima-media thickening in individuals with hypertension and impaired glucose metabolism. Hypertens Res 2007;30:1035-41. |
|8.||Lisowska A, Musia³ WJ, Lisowski P, Knapp M, Ma³yszko J, Latocha-Korecka G, et al. The influence of renal function and selected cardiovascular risk factors on the thickness of the intima-media complex in the peripheral arteries. Cardiol J 2007;14:59-66. |
|9.||Bui AL, Katz R, Kestenbaum B, de Boer IH, Fried LF, Polak JF, et al. Cystatin C and carotid intima-media thickness in asymptomatic adults: The multi-ethnic study of atherosclerosis (MESA). Am J Kidney Dis 2009;53:389-98. |
|10.||Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, et al. The seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure: The JNC 7 report. JAMA 2003;289:2560-72. |
|11.||Clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Am J Kidney Dis 2002;39:S17-31. |
|12.||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;130:461-70. |
|13.||Joanne M, Bargman, Karl Skorecki. Chronic Kidney Disease. Harrison's Principals of Internal Medicine. 17 th ed. New York: Mcgraw-hill Companies; vol 2. 2008. p. 1761-71. |
|14.||Nesar Hoseini V, Taziki O. Relationship between microalbuminuria and severity of coronary artery disease in non-diabetic patients. Iran Cardiovasc Res J 2008;4:234-7. |
|15.||Howard G, Wagenknecht LE, Burke GL, Diez-Roux A, Evans GW, McGovern P, et al. Cigarette smoking and progression of atherosclerosis: The atherosclerosis risk in communities (ARIC) study. JAMA 1998;279:119-24. |
|16.||Francesco AB, Francesca M, Giovanni T, Carmine Z. Prognostic value of ultrasonographic measurement of carotid intima media thickness in dialysis patients. J Am Soc Nephrol 2001;12:2458-64. |
|17.||Leskinen Y, Lehtimaki T, Loimaala A, Lautamatti V, Kallio T, Huhtala H, et al. Carotid atherosclerosis in chronic renal failure- the central role of increased plaque burden. Atherosclerosis 2003;171:295-302. |
|18.||Sunil Kumar K, Lakshmi AY, Srinivasa Rao PV, Das GC, Siva Kumar V. Carotid intima-medial thickness in patients with end-stage renal disease. Indian J Nephrol 2009;19:13-4. |
|19.||Cornel BA. The extracranial cerebral vessels. In: Rumak CM, Wilson SR, Charboneau JW, Johnson JM, editors. Diagnostic Ultrasound. Saint Louis, USA: Mosby Inc; 2005. p. 946-7. |
|20.||Rahn KH, Barenbrok M, Kosch M, Suelak B, Witta J. Vessel wall alterations in patients with renal failure. Hypertens Res 2000;23:3-6. |
|21.||Ricotta JJ, Bryan FA, Bond MG, Kurtz A, O'Leary DH, Raines JK, et al. Multicenter validation study of real time (B-mode) ultrasound, arteriography, and pathologic examination. J Vast Surg 1987;6:512-20. |
|22.||Desbien AM, Chonchol M, Gnahn H, Sander D. Kidney function and progression of carotid intima-media thickness in a community study. Am J Kidney Dis 2008;51:584-93. |
|23.||Ritz E. Minor renal dysfunction: An emerging independent cardiovascular risk factor. Heart 2003;89:963-4. |
|24.||Shoji T, Emoto M, Tabata T, Kimoto E, Shinohara K, Maekawa K, et al. Advanced atherosclerosis in predialysis patients with chronic renal failure. Kidney Int 2002;61:2187-92. |
|25.||Stein JH, Douglas PS, Srinivasan SR, Bond MG, Tang R, Li S, et al. Distribution and cross-sectional age-related increases of carotid artery intima-media thickness in young adults: The bogalusa heart study. Stroke 2004;35:2782-7. |
|26.||Haroun MK, Jaar BG, Hoffman SC, Comstock GW, Klag MJ, Coresh J. Risk factors for chronic kidney disease: A prospective study of 23,534 men and women in Washington County, Maryland. J Am Soc Nephrol 2003;14:2934-41. |
|27.||Kablak-Ziembicka A, Przewlocki T, Tracz W, Pieniazek P, Musialek P, Sokolowski A. Gender differences in carotid intima-media thickness in patients with suspected coronary artery disease. Am J Cardiol 2005;96:1217-22. |
|28.||Sander D, Schulze-Horn C, Bickel H, Gnahn H, Bartels E, Conrad B. Combined effects of hemoglobin A1c and C-reactive protein on the progression of subclinical carotid atherosclerosis: The INVADE study. Stroke 2006;2037:351-7. |
|29.||Kushiya F, Wada H, Sakakura M, Mori Y, Gabazza EC, Nishikawa M, et al. Atherosclerotic and hemostatic abnormalities in patients undergoing hemodialysis. Clin Appl Thromb Hemost 2003;9:53-60. |
|30.||Dejanova B, Filipce V, Dejanov P, Sikole A, Grozdanovski R, Maleska V. Atherosclerosis risk factors related to hemodialysisduration and erythropoietin therapy. Clin Chem Lab Med 2001;39:484-6. |
|31.||Benedetto FA, Mallamaci F, Tripepi G, Zoccali C. Prognostic value of ultrasonographic measurement of carotid intima media thickness in dialysis patients. J Am Soc Nephrol 2001;12:2458-64. |
|32.||Parikh NI, Hwang SJ, Larson MG, Meigs JB, Levy D, Fox CS. Cardiovascular disease risk factors in chronic kidney disease: Overall burden and rates of treatment and control. Arch Intern Med 2006;166:1884-91. |
|33.||Ossareh S, Alaei A, Saedi D. Carotid intima-media thickness in maintenance hemodialysis patients role of cardiovascular risk factor. Iran J Kidney Dis 2010;5:169-74. |
|34.||Tseke P, Grapsa E, Stamatelopoulos K, Samouilidou E, Protogerou A, Papamichael C, et al. Atherosclerotic risk factors and carotid stiffness in elderly asymptomatic HD patients. Int Urol Nephrol 2006;38:801-9. |
|35.||Tonelli M, Isles C, Craven T, Tonkin A, Pfeffer MA, Shepherd J, et al. Effect of pravastatin on rate of kidney function loss in people with or at risk for coronary disease. Circulation 2005;112:171-8. |
|36.||Gerstein HC, Mann JF, Yi Q, Zinman B, Dinneen SF, Hoogwerf B, et al. Albuminuria and risk of cardiovascular events, death, and heart failure in diabetic and nondiabetic individuals. JAMA 2001;286:421-6. |
|37.||Ruilope LM,van Veldhuisen DJ, Ritz E, Luscher TF. Renal function: The cinderella of cardiovascular risk profile. J Am Coll Cardiol 2001;38:1782-7. |
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3]
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