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Saudi Journal of Kidney Diseases and Transplantation
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Year : 2017  |  Volume : 28  |  Issue : 6  |  Page : 1338-1348
Assessment of abdominal aortic calcification in predialysis chronic kidney disease and maintenance hemodialysis patients


1 Department of Nephrology, Sri Ramachandra University, Chennai, Tamil Nadu, India
2 Department of Radiology, Sri Ramachandra University, Chennai, Tamil Nadu, India
3 Department of Clinical Nutrition, Sri Ramachandra University, Chennai, Tamil Nadu, India

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Date of Web Publication18-Dec-2017
 

   Abstract 


Vascular calcification is associated with increased morbidity and mortality among chronic kidney disease (CKD) patients. The aim of the study was to assess the abdominal aortic calcification (AAC) in predialysis CKD patients and patients on hemodialysis (HD) and to study the risk factors associated with it. In this prospective study, 205 patients were including 104 patients with predialysis CKD and 101 patients were on maintenance hemodialysis. AAC was assessed using lateral lumbar radiography. Blood urea nitrogen, serum creatinine, albumin, calcium, phosphorus, highly sensitive C-reactive protein (hsCRP) and total cholesterol were analyzed. AAC was observed in 26 % of predialysis CKD patients and 34% in HD patients. Using multivariate analysis, the age (P = 0.001) was identified as independent predictor for the presence of AAC in predialysis patients, and for HD, the predictors were age (P = 0.025), time on dialysis (P = 0.001), hsCRP (P = 0.002), and corrected calcium (P = 0.030). In conclusion, the prevalence of AAC varies mainly with age and glomerular filtration rate levels in predialysis CKD patients. Advanced age, time on dialysis, and inflammation may be associated with presence and extent of AAC in HD patients. Further research into the risk factors and outcome for AAC is warranted.

How to cite this article:
Dhakshinamoorthy J, Elumalai RP, Dev B, Hemamalini A J, Venkata Sai P M, Periasamy S. Assessment of abdominal aortic calcification in predialysis chronic kidney disease and maintenance hemodialysis patients. Saudi J Kidney Dis Transpl 2017;28:1338-48

How to cite this URL:
Dhakshinamoorthy J, Elumalai RP, Dev B, Hemamalini A J, Venkata Sai P M, Periasamy S. Assessment of abdominal aortic calcification in predialysis chronic kidney disease and maintenance hemodialysis patients. Saudi J Kidney Dis Transpl [serial online] 2017 [cited 2019 Sep 19];28:1338-48. Available from: http://www.sjkdt.org/text.asp?2017/28/6/1338/220855



   Introduction Top


Cardiovascular-related complications are the most important cause of mortality for patients with chronic kidney disease (CKD).[1] Vascular calcification is associated with increased hospitalization and death among CKD patients.[2],[3] Kidney Disease Improving Global Outcomes (KDIGO) recommends the utilization of lateral lumbar X-ray to detect the presence or absence of vascular calcification in CKD patients.[4] There is an high prevalence of abdominal aortic calcification (AAC) among CKD patients which ranges from 18.5% to 94.4%.[5],[6],[7] Multiple risk factors were linked with vascular calcification (VC) in CKD patients such as diabetes mellitus, serum calcium levels, and advanced age;[8],[9],[10] however, the AAC is not fully understood in predialysis CKD patients and maintenance hemodialysis (MHD) patients.

This study aims to assess the AAC in predialysis CKD patients and in those CKD patients undergoing HD using lateral lumbar radiography and to evaluate the effects of different patient parameters such as age, time on dialysis, and estimated glomerular filtration rate (eGFR) with AAC in our group of patients.


   Methods Top


Study design and participants

This was a prospective, single-center study of CKD patients and patients undergoing HD. The study participants were patients who attended the Nephrology Department, Sri Ramachandra Medical Center and Hospital, and met the following inclusion criteria: (1) age >18 years and ≤65 years old, (2) no past history of malignancy, (3) CKD stages 3 to 5 including CKD 5D (patients on MHD), and (4) CKD stage 5D patients who had received HD at least two times/week ≥3 months. Informed consent to participate in the study was obtained from all patients, and the Institutional Ethical Committee approval was obtained for the study.

KDIGO Clinical Practice Guideline For Evaluation And Management of CKD-based criteria was used for diagnosis and classification of CKD.[11] eGFR was calculated using CKD EPI 2009 equation for the evaluation of kidney function: eGFR (mL/min/1.73 m2) = 141 × min (Scr/κ, 1) α × max (Scr/κ, 1)-1.209 × 0.993 age × 1.018 (if female) × 1.159 (if black). The baseline data such as demographic details, cause of CKD, history of cardiovascular disease, cerebrovascular disease, peripheral vascular disease, height, weight, and body mass index (BMI) were collected.

Clinical characteristics and laboratory data

Serum albumin, blood urea nitrogen, serum creatinine, phosphorus, calcium, highly sensitive C-reactive protein (hsCRP), total cholesterol, low-density lipoprotein (LDL), and highdensity lipoprotein (HDL) were analyzed. Total serum calcium was corrected for albumin using the following equation corrected total calcium (mg/dL) = total calcium (mg/dL) + 0.8 × [4.0 – serum albumin (g/dL)]. Weight and height were recorded and BMI was estimated.

Blood sample from CKD patients not on dialysis was drawn after visiting nephrology clinic, and for dialysis patients, the blood sample was drawn before initiation of HD. Biochemical variables were analyzed using the Biosystem A15 automated biochemical analyzer. Serum albumin was analyzed using ADVIA 1800 fully automated analyzer (Siemens), and HsCRP and TIBC levels were estimated by Dade Behring Dimension fully automated analyzer (Siemens).

Hyperlipidemia was defined as serum cholesterol and serum triglyceride levels of more than 200 mg/dL and 150 mg/dL, respectively. Blood pressure of the patient was recorded in supine position, and the average blood pressure and pulse pressure were then calculated.

Lateral lumbar radiograph of abdominal aorta

Lateral radiography was performed for the patient in the standing position. The X-ray was taken and scores were graded as per the description of techniques and grading defined by Kauppila et al[12] in which the severity of AAC was calculated from the level of L1 to L4 lumbar vertebral segment.


   Statistical Analysis Top


Data are expressed in mean ± standard deviation, count, and percentage. Differences between two groups were assessed by Student’s t-test for parametric data and Mann–Whitney U-test or Kruskal–Wallis test used for non-parametric data. One-way analysis of variance was used for comparison between three groups. Univariate logistic regression analysis was used to analyze the possible risk factors for AAC, and variables with a significant association (P <0.10) were included in multivariate logistic regression analysis (stepwise backward elimination) for both the study groups. Statistical significant was considered when P <0.05. Statistical analysis was performed using the IBM Statistical Package for the Social Sciences for Windows, version 20.0 (IBM Corporation, New York, USA).


   Results Top


A total of 205 patients (129 males, 76 females) were included in the study. The mean age was 47.2 ± 12.6 years. Among 205 patients, 104 patients were predialysis CKD and 101 patients were on MHD. The clinical characteristics and demography of study participants are presented in [Table 1]. The primary kidney disease was hypertensive nephrosclerosis (46%), diabetic nephropathy (25%), chronic glomerulonephritis (17%), and others (12%). Sixteen percent patients had previous history of cardiovascular disease. Forty-four (21.5%) patients had stage 3 CKD (GFR range, 30–59 mL/min), 38 (18.5%) had stage 4 CKD (GFR range, 15–29 mL/min), 22 (10.7%) had stage 5 CKD (GFR, <15 mL/ min), and 101 (49.3%) patients were CKD stage 5 on HD. The clinical characteristics of patients stratified based on the stage of CKD are presented in [Table 2]. Serum creatinine, serum phosphorus, systolic and diastolic blood pressure, and hsCRP levels were significantly higher in CKD stage 5 than other stages of CKD.
Table 1: Demographic details and laboratory variables of predialysis CKD patients and patients on HD (n=205).

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Table 2: Demographic details and laboratory variables of patients stratified based on CKD stages (n=205).

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Prevalence of abdominal aortic calcification

The mean AAC score calculated using lateral lumbar radiography was 5.1 ± 3.4. Thirty percent (61) of our study population had abdominal aortic calcification (AAC ≥1) including 26% (27/104) in predialysis CKD group and 34% (31/101) in HD group. The demographic profile and laboratory parameters of CKD patients with and without AAC are presented in [Table 3]. HD has significantly higher prevalence of AAC when compared with CKD stage 3 patients [Figure 1].
Table 3: Demographic details and laboratory variables of CKD patients with or without abdominal aortic calcification (n=205).

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Figure 1: Prevalence of AAC in CKD patients.
AAC: Abdominal aortic calcification, CKD: Chronic kidney disease.


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The patients with AAC had significantly elevated hsCRP levels, advanced age, dialysis vintage, serum corrected calcium, intact parathyroid hormone, positive history of cardiovascular disease, and significantly lower eGFR compared to patients without AAC [Table 3].

Factors associated with abdominal aortic calcification scores

To identify the risk factors of AAC, univariate logistic regression analysis was done with the existence or absence of AAC as the dependent variable and 10 other variables as covariates [Table 4]. Age, dialysis vintage, serum corrected calcium, and hsCRP have significant association with AAC. Stepwise backward elimination method in multivariate logistic regression analysis was performed using existence or absence of AAC as a dependent variable and 10 other variables were selected as independent variables [Table 4]. Advanced age, longer dialysis vintage, higher serum calcium levels, and increased hsCRP were found to be independent risk factors for abdominal aortic calcification.
Table 4: Clinical factors and its association with presence of abdominal aortic calcification in univariate and multivariate logistic regression analysis (Stepwise backward elimination).

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Predictors of abdominal aortic calcification in predialysis chronic kidney disease patients

Using univariate logistic regression analysis, we observed that AAC was significantly associated with age and hsCRP [Table 5]. There was no significant association between AAC and serum calcium levels. Multiple logistic regression analysis was performed to examine the independent predictors of AAC. Age, hsCRP, cholesterol, triglycerides, diabetes mellitus, GFR, and previous history of cardiovascular disease were included in the model before stepwise backward elimination [Table 5]. In the final model of analysis, the age [odds ratio (OR) 1.19/year (1.08, 1.32), P <0.001] was found to be independent predictor for the presence of AAC.
Table 5: Clinical factors and its association with presence of abdominal aortic calcification in nondialysis CKD patients using univariate and multivariate logistic regression analysis (Stepwise backward elimination).

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Predictors of abdominal aortic calcification in hemodialysis patients

In univariate logistic regression analysis, the significant risk factors for the presence of AAC were age, time on dialysis, hsCRP, serum calcium levels, serum total cholesterol, and triglyceride [Table 6]. There was no significant association observed between presence of AAC and positive history of cardiovascular disease which was one of the important risk factor AACs in predialysis CKD patients. To examine the independent predictors of AAC in HD patients, multiple logistic regression analysis was used. Age, dialysis vintage, hsCRP, cholesterol, triglycerides, diabetes mellitus, GFR, previous history of cardiovascular disease, and calcium-phosphorus product were included primarily in the model before stepwise backward elimination [Table 6]. In the final model, the independent risk factors for the presence of AAC in HD were age (OR 1.08/year (1.01, 1.15), P <0.05), longer dialysis vintage (OR 1.16 (1.06, 1.27), P = 0.001), hsCRP (OR 1.75 (1.22, 2.92), P = 0.002), and corrected calcium (OR 2.92 (1.11, 7.72), P = 0.030).
Table 6: Clinical factors and its association with presence of abdominal aortic calcification in CKD patients on hemodialysis using univariate and multivariate logistic regression analysis (Stepwise backward elimination).

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   Discussion Top


In this study, the prevalence of AAC was 26% in predialysis CKD patients and 34% in HD patients. Several studies report between 18.5% and 95% of patients having aortic vascular calcification based on patient’s age, comorbid conditions such diabetes, positive history of cardiovascular disease, and method of detection of vascular calcification.[5],[7],[13],[14],[15],[16],[17],[18],[19]

Chuang et al,[20] from the Framingham Heart Study group observed AAC, was 22% in subsample participants under the age of 45 years while above age 65, nearly 90% of participants had AAC among general population. The prevalence of AAC increases with increase in the age of CKD patients.[21] In most of the studies with AAC prevalence of 60% and above, the mean age of the patients was above 60 years. In the present study, a significant age-related increase of AAC was observed among both predialysis CKD and HD. These findings are in line with previous observations on AAC prevalence which in-creases with increase in age of patients which may explain the reason for the prevalence of AAC in 26% of our predialysis CKD patients and 34% of HD patients with a mean age of 50.7 years and 43.5 years, respectively.

Lateral lumbar radiography has been widely used in many studies as reliable and reproducible method for detecting AAC. Kauppila et al[12] using lateral lumbar X-rays established the use of 24-point scale quantification method for AAC in a subgroup of patients from Framingham Heart Study. KDIGO 2017 guidelines on CKD-mineral and bone disorder recommend the utilization of lateral lumbar abdominal radiograph to detect the presence or absence of vascular calcification.

Taniwaki et al[10] reported diabetes as a risk factor for AAC in HD patients. In our study, the prevalence of diabetes was higher in CKD nondialysis patients. Thirty-one percent (16/52) of our diabetic patients had AAC. Among predialysis CKD patients, 27.5% (11/40) of diabetic patients had AAC and 41% (5/12) of the diabetic patients had AAC in dialysis group. In our study, though we observed diabetes as a risk factor for occurrence of AAC in both CKD and HD patients, it was not found to be statistically significant probably due to smaller sample size of diabetic patients.

Several studies have reported the association of inflammation with atherosclerosis and cardiovascular events in dialysis patients.[8],[14] In the present study, there is a significant association between inflammation and AAC. Patients with AAC had significantly higher levels of hsCRP. Inflammation and oxidative stress induces osteoblastic differentiation of vascular smooth muscle cells (VSMCs) which in turn aggravates the process of vascular calcification.[22] There were few reports that tumor necrosis factor-α (TNF-α), a cytokine, plays a key role in vascular calcification.[23],[24],[25] TNF-α in a dosage-dependent manner induces osteoblastic differentiation of VSMCs. Stimulation of TNF-α is facilitated through the VSMCs, osteoblastic differentiation, and cAMP pathway.

In our study, we also observed corrected calcium as a predictor for AAC in HD. Calcium accelerates the mineralization of VSMCs.[26],[27] Vascular mineralization induced by calcium is dependent on the function of Pit-1.[27] Continuous treatment of human VSMCs with high calcium for a longer duration induces the expression of Pit-1, signifying that both calcium and phosphorus activate Pit-1 and intense the influx of phosphorus into VSMCs synergistically. Interestingly, expression of calciumsensing receptor was observed in VSMCs. In CKD patients, the calcium-sensing receptor expression is downregulated in VSMCs when compared with normal individuals.[28] Thus, for the progression of vascular calcification in CKD patients, extracellular calcium and calcium receptor axis may play a major role.

NKF KDOQI guidelines recommend that serum calcium-phosphorus product should be maintained at <55 mg2/dL2. Higher calciumphosphorus product was associated with higher risk of calcification. In our study, the mean calcium-phosphorus product was 48 ± 16 mg2/dL2 in patients with AAC and 44 ± 15 mg2/dL2 in patients without AAC. Since our patient’s calcium-phosphorus product levels were less than 55 mg2/dL2 probably, we did not had any statistically significant difference between the AAC group and the group without AAC.

In the present study, we further analyzed the predictors for AAC in pre-end stage renal disease patients and found that decreased GFR is a predictor for AAC in predialysis CKD patients. Predialysis CKD patients with AAC were stratified into three CKD stages based on GFR, and we observed that AAC prevalence was 26% in patients with GFR (30–60 mL/ min), 37% in GFR (15–30 mL/min), and 37% in patients with GFR less than 15 mL/min [Figure 2]. The prevalence of AAC increased with reduction in GFR levels, and it was found to be statistically significant (P <0.05). Similarly, the mean AAC score increased with the increase in the stage of CKD, and it was not statistically significant [Table 2]. Hanada et al[6] and Mitsuru Ichii et al[29] reported similar finding that decreased e-GFR was associated independently and significantly with the quantitative degree of aortic calcification. Decrease in renal function may disrupt the interaction of inhibitors and inducers of vascular calcification, which is believed to be a highly regulated process such as the formation of bone.[30] There were a few limitations in our study. The study was observational, and there were smaller sample size across each group of CKD. Dietary calcium intake was not quantified in our study population, and 25-hydroxy Vitamin D levels were not assessed due to increased cost even though this would be worthwhile in the CKD population when assessing for AAC.
Figure 2: Association of GFR and prevalence of AAC in predialysis CKD patients.
GFR: Glomerular filtration rate, AAC: Abdominal aortic calcification, CKD: Chronic kidney disease.


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In conclusion, the prevalence of AAC varies mainly with age and GFR levels in predialysis CKD patients. In HD advanced age, time on dialysis and inflammation may be linked with occurrence and magnitude of AAC. Further research into the factors and outcome for AAC is warranted.

Source(s) of support: Partly supported from Young faculty grant from Sri Ramachandra University

Conflict of interest: None declared.



 
   References Top

1.
Foley RN, Parfrey PS, Sarnak MJ. Clinical epidemiology of cardiovascular disease in chronic renal disease. Am J Kidney Dis 1998; 32:S112-9.  Back to cited text no. 1
[PUBMED]    
2.
Mizobuchi M, Towler D, Slatopolsky E. Vascular calcification: The killer of patients with chronic kidney disease. J Am Soc Nephrol 2009;20:1453-64.  Back to cited text no. 2
[PUBMED]    
3.
London GM, Guérin AP, Marchais SJ, et al. Arterial media calcification in end-stage renal disease: Impact on all-cause and cardiovascular mortality. Nephrol Dial Transplant 2003;18:1731-40.  Back to cited text no. 3
    
4.
Kidney Disease: Improving Global Outcomes (KDIGO) CKD-MBD Work Group. KDIGO clinical practice guideline for the diagnosis, evaluation, prevention, and treatment of chronic kidney disease-mineral and bone disorder (CKD-MBD). Kidney Int Suppl 2009; 113:S1-130.  Back to cited text no. 4
    
5.
Hashim Al-Saedi AJ, Jameel NS, Qais A, Kareem AH, Mohssen TS. Frequency of abdominal aortic calcification in a group of Iraqi hemodialysis patients. Saudi J Kidney Dis Transpl 2014;25:1098-104.  Back to cited text no. 5
[PUBMED]    
6.
Hanada S, Ando R, Naito S, et al. Assessment and significance of abdominal aortic calcification in chronic kidney disease. Nephrol Dial Transplant 2010;25:1888-95.  Back to cited text no. 6
[PUBMED]    
7.
Toussaint ND, Pedagogos E, Lau KK, et al. Lateral lumbar X-ray assessment of abdominal aortic calcification in Australian haemodialysis patients. Nephrology (Carlton) 2011;16:389-95.  Back to cited text no. 7
[PUBMED]    
8.
Yamada K, Fujimoto S, Nishiura R, et al. Risk factors of the progression of abdominal aortic calcification in patients on chronic haemodialysis. Nephrol Dial Transplant 2007;22: 2032-7.  Back to cited text no. 8
[PUBMED]    
9.
Wang M, Wang M, Gan LY, et al. Vascular calcification in maintenance hemodialysis patients. Blood Purif 2009;28:15-20.  Back to cited text no. 9
[PUBMED]    
10.
Taniwaki H, Ishimura E, Tabata T, et al. Aortic calcification in haemodialysis patients with diabetes mellitus. Nephrol Dial Transplant 2005;20:2472-8.  Back to cited text no. 10
[PUBMED]    
11.
Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl 2013;3:1-150.  Back to cited text no. 11
    
12.
Kauppila LI, Polak JF, Cupples LA, et al. New indices to classify location, severity and progression of calcific lesions in the abdominal aorta: A 25-year follow-up study. Atherosclerosis 1997;132:245-50.  Back to cited text no. 12
[PUBMED]    
13.
Shigematsu T, Kono T, Satoh K, et al. Phosphate overload accelerates vascular calcium deposition in end-stage renal disease patients. Nephrol Dial Transplant 2003;18 Suppl 3:iii86-9.  Back to cited text no. 13
[PUBMED]    
14.
Okuno S, Ishimura E, Kitatani K, et al. Presence of abdominal aortic calcification is significantly associated with all-cause and cardiovascular mortality in maintenance hemodialysis patients. Am J Kidney Dis 2007;49:417-25.  Back to cited text no. 14
[PUBMED]    
15.
Toussaint ND, Lau KK, Strauss BJ, Polkinghorne KR, Kerr PG. Relationship between vascular calcification, arterial stiffness and bone mineral density in a crosssectional study of prevalent Australian haemodialysis patients. Nephrology (Carlton) 2009; 14:105-12.  Back to cited text no. 15
[PUBMED]    
16.
Honkanen E, Kauppila L, Wikström B, et al. Abdominal aortic calcification in dialysis patients: Results of the CORD study. Nephrol Dial Transplant 2008;23:4009-15.  Back to cited text no. 16
    
17.
Ogawa T, Ishida H, Matsuda N, et al. Simple evaluation of aortic arch calcification by chest radiography in hemodialysis patients. Hemodial Int 2009;13:301-6.  Back to cited text no. 17
[PUBMED]    
18.
Ogawa T, Ishida H, Akamatsu M, et al. Progression of aortic arch calcification and allcause and cardiovascular mortality in chronic hemodialysis patients. Int Urol Nephrol 2010; 42:187-94.  Back to cited text no. 18
[PUBMED]    
19.
London GM, Marchais SJ, Guérin AP, et al. Association of bone activity, calcium load, aortic stiffness, and calcifications in ESRD. J Am Soc Nephrol 2008;19:1827-35.  Back to cited text no. 19
    
20.
Chuang ML, Massaro JM, Levitzky YS, et al. Prevalence and distribution of abdominal aortic calcium by gender and age group in a community-based cohort (from the Framingham heart study). Am J Cardiol 2012;110:891-6.  Back to cited text no. 20
[PUBMED]    
21.
Pencak P, Czerwieńska B, Ficek R, et al. Calcification of coronary arteries and abdominal aorta in relation to traditional and novel risk factors of atherosclerosis in hemodialysis patients. BMC Nephrol 2013;14:10.  Back to cited text no. 21
    
22.
Byon CH, Javed A, Dai Q, et al. Oxidative stress induces vascular calcification through modulation of the osteogenic transcription factor runx2 by AKT signaling. J Biol Chem 2008;283:15319-27.  Back to cited text no. 22
[PUBMED]    
23.
Shioi A, Katagi M, Okuno Y, et al. Induction of bone-type alkaline phosphatase in human vascular smooth muscle cells: Roles of tumor necrosis factor-alpha and oncostatin M derived from macrophages. Circ Res 2002;91:9-16.  Back to cited text no. 23
[PUBMED]    
24.
Tintut Y, Patel J, Territo M, et al. Monocyte/ macrophage regulation of vascular calcification in vitro. Circulation 2002;105:650-5.  Back to cited text no. 24
[PUBMED]    
25.
Tintut Y, Patel J, Parhami F, Demer LL. Tumor necrosis factor-alpha promotes in vitro calcification of vascular cells via the cAMP pathway. Circulation 2000;102:2636-42.  Back to cited text no. 25
[PUBMED]    
26.
Lomashvili K, Garg P, O’Neill WC. Chemical and hormonal determinants of vascular calcification in vitro. Kidney Int 2006;69: 1464-70.  Back to cited text no. 26
    
27.
Yang H, Curinga G, Giachelli CM. Elevated extracellular calcium levels induce smooth muscle cell matrix mineralization in vitro. Kidney Int 2004;66:2293-9.  Back to cited text no. 27
[PUBMED]    
28.
Molostvov G, James S, Fletcher S, et al. Extracellular calcium-sensing receptor is functionally expressed in human artery. Am J Physiol Renal Physiol 2007;293:F946-55.  Back to cited text no. 28
[PUBMED]    
29.
Ichii M, Ishimura E, Shima H, et al. Quantitative analysis of abdominal aortic calcification in CKD patients without dialysis therapy by use of the Agatston score. Kidney Blood Press Res 2013;38:196-204.  Back to cited text no. 29
[PUBMED]    
30.
Jono S, Shioi A, Ikari Y, Nishizawa Y. Vascular calcification in chronic kidney disease. J Bone Miner Metab 2006;24:176-81.  Back to cited text no. 30
[PUBMED]    

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Correspondence Address:
Jagadeswaran Dhakshinamoorthy
Department of Nephrology, Sri Ramachandra University, Chennai, Tamil Nadu
India
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DOI: 10.4103/1319-2442.220855

PMID: 29265045

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