Creative Commons Open Access Journal No author-side fee 
  • Users Online: 68
  • Print this page
  • Email this page
Submit article

Table of Contents
Year : 2021  |  Volume : 3  |  Issue : 1  |  Page : 33-38

Patterns and Predictors of Left Ventricular Hypertrophy in Nigerians with chronic kidney disease

1 Department of Medicine, Cedarcrest Hospitals, Gudu, Abuja, Nigeria
2 Department of Medicine, Al Isawiya General Hospital, Directorate of Al Gurayat, Ministry of Health, Saudi Arabia
3 Department of Community Medicine, Nnamdi Azikiwe University Teaching Hospital, Nnewi, Anambra State, Nigeria
4 Department of Medicine, Nnamdi Azikiwe University Teaching Hospital, Nnewi, Anambra State, Nigeria
5 Department of Medicine, Faculty of Medicine, College of Health Sciences, Nnamdi Azikiwe University, Awka, Nigeria

Date of Submission24-Nov-2020
Date of Decision23-Mar-2021
Date of Acceptance25-Apr-2021
Date of Web Publication28-May-2021

Correspondence Address:
Onwukwe Chikezie Hart
Al Isawiya General Hospital, Directorate of Al Gurayat, Ministry of Health
Saudi Arabia
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ACCJ.ACCJ_41_20

Rights and Permissions

Background: Chronic kidney disease (CKD) impacts hugely on cardiovascular morbidity and mortality. Nigerian data on patterns and predictors of left ventricular hypertrophy (LVH) in persons living with CKD are scarce. The objective of the study is to describe the patterns and predictors of LVH in Nigerians with CKD. Methods: Recruitment and clinical assessment of adult Nigerians with CKD were done using standard procedures. Statistical analysis was done using appropriate statistical software. Results: Fifty-seven participants were involved in this study. Concentric and eccentric LVH occurred in 50% and 25% of the predialysis CKD patients, respectively, while 24% and 36% of the maintenance dialysis CKD patients had concentric and eccentric LVH, respectively. LVH patterns in dialysis-naive individuals were not significantly different from LVH patterns in persons on dialysis. The significant predictors of LVH in study participants were proteinuria, anemia, hypoalbuminemia, estimated glomerular filtration rate <30 mL/1.73 m2/min, and hypertensive nephrosclerosis. High calcium-phosphate product was a significant predictor of LVH in only participants on dialysis. Conclusion: This study showed no significant difference in LVH patterns among predialysis and maintenance dialysis CKD patients. Indices of deteriorating renal function were significant predictors of LVH in both categories of CKD patients. Early screening and treatment of significant risk factors of LVH are required in reducing CVD burden among CKD patients.

Keywords: Chronic kidney disease, left ventricular hypertrophy, Nigeria, predictors

How to cite this article:
Kalu OK, Hart OC, Ifeoma CN, Thaddeus NC, Kalu O, Ukachukwu OC. Patterns and Predictors of Left Ventricular Hypertrophy in Nigerians with chronic kidney disease. Ann Clin Cardiol 2021;3:33-8

How to cite this URL:
Kalu OK, Hart OC, Ifeoma CN, Thaddeus NC, Kalu O, Ukachukwu OC. Patterns and Predictors of Left Ventricular Hypertrophy in Nigerians with chronic kidney disease. Ann Clin Cardiol [serial online] 2021 [cited 2021 Nov 28];3:33-8. Available from:

  Introduction Top

Cardiovascular disease (CVD) accounts for up to 50% of mortality in CKD patients on long-term hemodialysis.[1] Left ventricular hypertrophy (LVH) is a significant determinant of cardiovascular outcomes in persons with chronic kidney disease (CKD).[2] Left ventricular dysfunction is often preceded by LVH, and this confers a poor prognostic value in persons with end-stage renal disease (ESRD).[2],[3]

The development of LVH in ESRD is partly explained by increased preload and afterload from hypervolemia with increased peripheral vascular resistance.[4],[5] These subsequently lead to addition of sarcomeres, myofibril lengthening, and LVH. CKD duration and dialysis treatment are associated with increase in left ventricular mass.[5],[6],[7] Left ventricular dysfunction and congestive heart failure worsen morbidity and mortality in individuals with CKD.[8],[9],[10] There are scanty Nigerian data (especially in the South-Eastern part of Nigeria) on the patterns and predictors of LVH in predialysis and maintenance dialysis CKD patients. The aim of this research work was to describe the geometrical patterns and predictors of LVH in Nigerians with CKD.

  Methods Top

This was a cross-sectional observational study involving prehemodialysis and maintenance hemodialysis CKD patients attending the Nnamdi Azikiwe University Teaching Hospital (NAUTH), Nnewi, South-East Nigeria adult nephrology clinic. Consenting adult CKD patients were identified and consecutively recruited for the study. Exclusion criteria included heart failure, chronic liver disease, postrenal transplant, and history of malignancy. The weight (in kilograms) and height (in meters) of study participants were determined using the WHO STEPS tool.[11] Body mass index (BMI) in kilograms per square meters was calculated as weight (in kilograms) divided by the square of the height (in meters). Obesity was defined as BMI ≥30 kg/m2.[12] Blood pressure (BP) was measured with a mercury sphygmomanometer (Accoson Greenlight 300) in the sitting position with the appropriate cuff based on patients' arm sizes.[13] Systolic and diastolic BP were measured using the American Society of Hypertension guidelines.[13] Systolic BP ≥140 mmHg, and/or diastolic BP ≥90 mmHg, or use of antihypertensive drug treatment are defined hypertension.[13]

Ten mL of venous blood was collected from each individual between 8 am and 10 am after overnight fast of 8 h to 12 h. Two mL of the sample was put in an ethylene diaminatetraacetic acid bottle for hemoglobin (Hb) estimation and the remaining 8 mL was put in a plain tube for phosphate, calcium, albumin, creatinine, and lipid estimation. Hemoglobin was determined using a HemoCue hemoglobin photometer.[14] Serum phosphate levels were estimated using Fiske-Subbarow method.[15] Total serum calcium estimation was done using Cresolphthalein-Complexone method.[16] Serum albumin estimation was determined using Bromocresol green colorimetric dye method.[17] Serum creatinine estimation was done using fixed-time kinetic method.[18] The concentrations of total cholesterol, triglycerides, low-density lipoprotein-cholesterol, and high-density lipoprotein-cholesterol were measured by enzymatic colorimetric methods using an autoanalyzer (Roche Diagnostics GmbH, Mannheim, Germany).[19]

Ten mL of midstream urine was collected from each individual for the detection of proteinuria using Urinalysis Dipstick Reagent Strips® (Rapid Labs Ltd. Colchester, Essex, C078SD, UK).[20] All samples were analyzed at the Chemical Pathology Laboratory of NAUTH, Nnewi, Nigeria.

Transthoracic M-mode, two-dimensional echocardiography was performed on study participants using an echocardiography machine (Esaote Europe, Aj Maastricht, The Netherlands) with an installed internal analysis software for calculating cardiac indices. Two-dimensional views were used for real-time description of cardiac morphology and as reference for M-mode beam selection. Echocardiographic assessment was done based on American Society of Echocardiography guidelines.[21]

LVH was defined as left ventricular mass index >115 g/m2 (in men) and >95 g/m2 (in women).[22]

Calculation of relative wall thickness (RWT) was done using the formula RWT = (2 × PWTd)/LVIDd, where PWTd is the posterior wall thickness in diastole and LVIDd is the left ventricular internal diameter in diastole.[22] Concentric hypertrophy was defined as RWT >0.42 while eccentric hypertrophy was defined as RWT <0.4.[22]

For quality assurance, two cardiologists performed the echocardiography procedure and measured the echocardiographic indices to reduce intraobserver bias.

Estimated glomerular filtration rate (eGFR) was determined using the modification of diet in renal disease formula as follows:[23]

eGFR = 186 × (Scr)−1.154 × (age)−0.203 × (0.742 if female) × (1.210 if black), where Scr = serum creatinine in mg/dL.

Hemoglobin level <13.5 g/dL (in males) and <12 g/dL (in females) are defined anemia.[24] A urine dipstick protein reading of +, 2+, and 3+ which corresponds to albumin concentrations of 30 mg/dL, 100 mg/dL, and 500 mg/dL, respectively, are defined proteinuria.[24]

Hypoalbuminemia was defined as serum albumin < 3.5 g/dL[24] while calcium-phosphate product (in mg2/dL2) was calculated as serum calcium (mg/dL) multiplied by serum phosphate (mg/dL). Calcium-phosphate product above 55 mg2/dL2 was considered elevated.[24]

Dyslipidemia was defined as any or a combination of the following: total cholesterol >200 mg/dL, low-density lipoprotein cholesterol >130 mg/dL, triglycerides >150 mg/dL, or low high-density lipoprotein cholesterol (defined as high-density lipoprotein cholesterol <40 mg/dL in males and <50 mg/dL in females).[25]

Collected data were entered in study pro forma and transferred to the Statistical Package for the Social Sciences version 20 (IBM Corporation, California, USA) for statistical analysis. Illustration of analyzed data was done using tables. Determination of normality was done using the Kolmogorov–Smirnov test. Quantitative variables were presented as mean ± standard deviation (SD) while qualitative variables were presented as proportions, n (%). Comparison of quantitative variables across two groups was done with Student's t-test while qualitative variables were compared across groups using Chi-squared test. Significant predictors of LVH were determined using logistic regression models. P < 0.05 was defined statistical significance.

Ethical statement

This research was approved by the NAUTH, Nnewi Research and Ethics Committee. The ethical certificate was issued on March 4, 2016, with reference number NAUTH/CS/66/VOL8/38.

  Results Top

Fifty-seven CKD patients consisting of 32 (56.1%) dialysis-naive persons and 25 (43.9%) participants on maintenance dialysis were identified and selected for this study. [Table 1] shows the clinical and laboratory variables in study participants. The mean ± SD age of study participants was 46.75 ± 12.16 and 39.32 ± 8.68 years in predialysis and hemodialysis patients, respectively (P = 0.07).
Table 1: Clinical and laboratory variables in study participants

Click here to view

The mean BMI was higher in predialysis patients compared to hemodialysis participants (P = 0.03). The mean eGFR, calcium-phosphate product, triglyceride, and low-density lipoprotein cholesterol were significantly higher in hemodialysis CKD patients (P = 0.001) while albumin and high-density lipoprotein-cholesterol were significantly higher in maintenance hemodialysis patients (P = 0.001). Diastolic BP, serum calcium, total cholesterol, and hemoglobin did not significantly differ among predialysis and maintenance dialysis patients.

[Table 2] shows sex distribution and CKD etiology in participants. Of the 32 predialysis patients, there were 12 (37.5%) males and 20 (62.5%) females while the 25 maintenance dialysis patients consisted of 11 (44.0%) males and 14 (56.0%) females (χ2 = 0.44, P = 0.62). The most common cause of CKD in participants who were not on dialysis was hypertensive nephrosclerosis, occurring in 12 (37.5%) patients while DM nephropathy was the most common CKD etiology in maintenance dialysis CKD patients, occurring in 9 (36%) patients. Etiologies of CKD did not significantly differ in predialysis and maintenance dialysis CKD patients (χ2 = 2.44, P = 0.66).
Table 2: Sex distribution and chronic kidney disease etiology in study participants (n=57)

Click here to view

[Table 3] shows the occurrence and patterns of LVH among study participants. LVH prevalence was 75% and 60% in predialysis participants and persons on hemodialysis, respectively. Hypertrophy of the left ventricle occurred in 24 (75%) predialysis CKD participants and 15 (60%) maintenance dialysis CKD patients. Concentric and eccentric LVH occurred in 16 (50%) and 8 (25%) predialysis patients, respectively, while six (24%) and 9 (36%) maintenance dialysis patients had concentric and eccentric LVH, respectively (χ2 = 4.03, P = 0.13).
Table 3: Left ventricular geometrical patterns in study participants (n=57)

Click here to view

[Table 4] shows the LVH predictors among predialysis CKD patients. Proteinuria (odds ratio [OR] = 2.55, P = 0.02), anemia (OR = 2.01, P = 0.04), hypoalbuminemia (OR = 2.50, P = 0.03), eGFR < 30 ml/1.73 m2/min (OR = 2.90, P = 0.01), and hypertensive nephrosclerosis (OR = 3.11, P < 0.01) significantly predicted LVH in predialysis CKD patients.
Table 4: Determinants of left ventricular hypertrophy in dialysis-naive participants (n=57)

Click here to view

[Table 5] shows the determinants of LVH in maintenance dialysis CKD patients. The significant predictors of LVH in hemodialysis patients include proteinuria (OR = 3.00, P = 0.02), high calcium-phosphate product (OR = 1.84, P = 0.03), anemia (OR = 2.57, P = 0.02), eGFR <30 ml/m2/1.73/min (OR = 3.12, P = 0.01), and hypertensive nephrosclerosis (OR = 3.56, P < 0.01). Dyslipidemia, increased BMI, and other causes of CKD apart from hypertensive nephrosclerosis were not significant predictors of LVH in participants irrespective of dialysis status.
Table 5: Determinants of left ventricular hypertrophy in participants on dialysis (n=57)

Click here to view

  Discussion Top

The general aim of this research was to describe LVH patterns and predictors in Nigerians with CKD. The mean age of participants who were not on dialysis and those on dialysis was 47 and 39 years, respectively.

In this study, LVH was present in 75% of dialysis-naive participants and 60% of those on dialysis. Fifty percent of the predialysis patients had concentric LVH while 25% had eccentric LVH pattern. Twenty-four percent and 36% of hemodialysis patients had concentric and eccentric LVH geometrical patterns, respectively. Ulasi et al. in Enugu, South-East Nigeria,[26] reported 54.6% and 40.9% eccentric and concentric LVH prevalence, respectively, among predialysis CKD patients studied. The mean Hb of the patients studied by Ulasi et al. was lower (7.79 g/dl) compared to the mean Hb of 9.96 g/dl in predialysis participants who took part in the present study. Anemia known to be a hyperdynamic state is associated with tachycardia, fluid overload, increased peripheral resistance, and subsequent eccentric hypertrophy.[2],[9] This could explain why the predialysis CKD patients in the study carried out in Enugu, Nigeria, had a higher eccentric LVH occurrence. The study by Ulasi et al also excluded participants who were on antihypertensive medications unlike the present study where antihypertensive use was not an exclusion criteria due to ethical concerns. This may also explain the higher concentric LVH preponderance in the present study.

In this study, proteinuria, anemia, hypoalbuminemia, eGFR <30 ml/1.73 m2/min, and hypertensive nephrosclerosis significantly predicted LVH in predialysis CKD patients. The significant predictors of LVH in maintenance hemodialysis patients include proteinuria, high calcium-phosphate-product, anemia, eGFR <30 ml/m2/1.73/min, and hypertensive nephrosclerosis. Increased BMI, dyslipidemia, and other causes of CKD (HIVAN, CGN, DM nephropathy) did not significantly predict LVH in both categories of study participants. The researchers in Enugu, Nigeria, reported reduced GFR, hypertension, and anemia significantly predicted LVH in predialysis CKD patients.[26] Tucker et al. reported that baseline CRP, decreased GFR, and hypertension significantly predicted LVH in CKD patients.[27] In the present study, hypoalbuminemia, an indirect marker of inflammation and CRP, significantly predicted LVH in both categories of CKD patients studied. Although the mechanism is not clearly known, the presence of pro-inflammatory cytokines in individuals with CKD patients possibly increases the risk for LVH and cardiovascular disease.[27]

Previous studies have also reported that high calcium-phosphate product predicts LVH, vascular calcifications, and increased cardiovascular events in CKD patients.[28],[29] Our study showed that high calcium-phosphate product is a significant LVH predictor in study participants on dialysis. Deficiency of vitamin D, secondary hyperparathyroidism, and high calcium-phosphate product levels are documented risk factors contributing to LVH and high cardiovascular events in individuals with CKD.[28],[29] A growth factor known as fibroblast growth factor 23 (FGF23) is implicated in the proliferation of cardiac cells. Because of its phosphaturic property in renal tubules, FGF23 blocks vitamin D3 synthesis and inhibits proximal renal tubular reabsorption.[30]

The present study clearly demonstrates that proteinuria is a predictor of LVH in individuals with CKD. The mechanism for this association in both categories of CKD patients is unclear. However, this finding may indicate the role of proteinuria as an indirect marker of vessel damage in individuals with CKD.[31] This agrees with a study that reported higher albumin-creatinine ratio among CKD patients with LVH and diastolic dysfunction.[32]

This study has some limitations. Novel cardiovascular risk factors in CKD patients[33] such as serum homocysteine, parathormone, fibroblast growth factor-23 (FGF-23), carotid intima thickness, and asymmetric dimethylarginine could not be assessed due to cost constraints.

  Conclusion Top

This study found prevalent concentric and eccentric LVH patterns in study participants. Anemia, hypoalbuminemia, proteinuria, eGFR <30 ml/1.73 m2/min, and hypertensive nephrosclerosis were prevalent in CKD patients. These variables significantly predicted LVH in the study participants. High-calcium phosphate product was an LVH predictor in participants on hemodialysis.

Early biochemical screening and echocardiographic evaluation of predialysis and maintenance dialysis CKD patients are hereby recommended to identify cardiovascular risk factors and LVH in persons with CKD. Treatment of these comorbidities will help improve poor cardiovascular outcomes in CKD patients.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Sarnak MJ, Levey AS. Cardiovascular disease and chronic renal disease: A new paradigm. Am J Kidney Dis 2000;35:S117-31.  Back to cited text no. 1
Silberberg JS, Barre PE, Prichard SS, Sniderman AD. Impact of left ventricular hypertrophy on survival in end-stage renal disease. Kidney Int 1989;36:286-90.  Back to cited text no. 2
Orofino L, Marcén R, Quereda C, Villafruela JJ, Sabater J, Matesanz R, et al. Epidemiology of symptomatic hypotension in hemodialysis: Is cool dialysate beneficial for all patients? Am J Nephrol 1990;10:177-80.  Back to cited text no. 3
Moon KH, Song IS, Yang WS, Shin YT, Kim SB, Song JK, et al. Hypoalbuminemia as a risk factor for progressive left-ventricular hypertrophy in hemodialysis patients. Am J Nephrol 2000;20:396-401.  Back to cited text no. 4
Amman K, Rychlik J, Mitenberger MG. Left ventricular hypertrophy in renal failure. Kidney Int 1998;54:78-85.  Back to cited text no. 5
Foley RN, Parfrey PS, Harnett JD, Kent GM, Murray DC, Barry PE. The prognostic importance of left ventricular geometry in uremic cardiomyopathy. J Am Soc Nephrol 1995;5:2024-31.  Back to cited text no. 6
Greaves SC, Gamble GD, Collins JF, Whalley GA, Sharpe DN. Determinants of left ventricular hypertrophy and systolic dysfunction in chronic renal failure. Am J Kidney Dis 1994;24:768-76.  Back to cited text no. 7
Almqvist EG, Bondeson AG, Bondeson L, Nissborg A, Smedgård P, Svensson SE. Cardiac dysfunction in mild primary hyperparathyroidism assessed by radionuclide angiography and echocardiography before and after parathyroidectomy. Surgery 2002;132:1126-32.  Back to cited text no. 8
Arodiwe EB. Left ventricular hypertrophy in renal failure a review. Niger J Clin Pract 2007;10:83-90.  Back to cited text no. 9
[PUBMED]  [Full text]  
Zoccali C, Benedetto FA, Mallamaci F, Tripepi G, Giacone G, Cataliotti A, et al. Prognostic impact of the indexation of left ventricular mass in patients undergoing dialysis. J Am Soc Nephrol 2001;12:2768-74.  Back to cited text no. 10
WHO Steps Manual. Available from: [Last accessed on 2019 Sep 01].  Back to cited text no. 11
Obesity: Preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser 2000;894:1-253.  Back to cited text no. 12
American Society of Hypertension. Recommendation for routine blood pressure measurement by indirect cuff sphygmomanometry. Am J Hypertens 1992;5:207-9.  Back to cited text no. 13
Nkrumah B, Nguah SB, Sarpong N, Dekker D, Idriss A, May J, et al. Hemoglobin estimation by the HemoCue® portable hemoglobin photometer in a resource poor setting. BMC Clin Pathol 2011;11:5.  Back to cited text no. 14
Fiske CH, Subba RY. The colorimetric determination of phosphorus. J Biol 1925;66:375-81.  Back to cited text no. 15
Baron DN, Joyce LB. Compleximetric determination of calcium in pathological and physiological specimens. J Clin Pathol 1959;12:143.  Back to cited text no. 16
Kumar D, Banerjee D. Methods of albumin estimation in clinical biochemistry: Past, present, and future. Clin Chim Acta 2017;469:150-60.  Back to cited text no. 17
Davis GA, Chandler MH. Comparison of creatinine clearance estimation method in patients with trauma. Am J Health Sys Pharm 1996;53:1028-32.  Back to cited text no. 18
Ferreira CE, França CN, Correr CJ, Zucker ML, Andriolo A, Scartezini M. Clinical correlation between a point-of-care testing system and laboratory automation for lipid profile. Clin Chim Acta 2015;446:263-6.  Back to cited text no. 19
Wen CP, Yang YC, Tsai MK, Wen SF. Urine dipstick to detect trace proteinuria: An underused tool for an underappreciated risk marker. Am J Kidney Dis 2011;58:1-3.  Back to cited text no. 20
Sahn DJ, DeMaria A, Kisslo J, Weyman A. Recommendations regarding quantitation in M-mode echocardiography: Results of a survey of echocardiographic measurements. Circulation 1978;58:1072-83.  Back to cited text no. 21
Lang RM, Badano LP, Mor-Avi V, Anderson A, Laura E, Frank A, et al. Recommendation for chamber quantification in adults; anupdate from the American Society of Echocardiography and European Association of Cardiovascular Imaging. J Am Soc Echocardiogr 2015;28:1-39.e14.  Back to cited text no. 22
Agaba EI, Wigwore CM, Agaba PA. Performance of CockroftGault and MDRD equation in adult Nigerians with chronic kidney disease. Int Urol Nephrol 2001;41:635-42.  Back to cited text no. 23
Kidney Disease Improving Global Outcomes. KIDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kid Int Suppl 2013;3:5-70.  Back to cited text no. 24
National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) Final Report. Circulation 2002;106:3143-421.  Back to cited text no. 25
Ulasi II, Arodiwe EB, Ijoma CK. Left ventricular hypertrophy in African black patients with chronic renal failure at first evaluation. Ethn Dis 2006;16:859-64.  Back to cited text no. 26
Tucker B, Fabbian F, Giles M, Thuraisingham RC, Raine AE, Baker LR. Left ventricular hypertrophy and ambulatory blood pressure monitoring in chronic renal failure. Nephrol Dial Transplant 1997;12:724-8.  Back to cited text no. 27
Bhuriya R, Li S, Chen S, McCullough P, Bakris G. Plasma parathyroid hormone level and prevalent cardiovascular disease in CKD Stages 3 and 4: Analysis from the Kidney Early Evaluation Program (KEEP). Am J Kidney Dis 2009;53:S3-10.  Back to cited text no. 28
Evenepoel P, Meijers B, Vianene L, Bammens B, Claes K, Kuypers D, et al. Fibroblast growth factor-23 in early chronic kidney disease: Additional support in favour of a phosphate eccentric paradigm for the pathogenesis of secondary hyperparathyroidism. Clin J Am Soc Nephrol 2010;5:1268-76.  Back to cited text no. 29
Faul C, Amaryl AP, Oskouei B, Ming-Chang H, Alexis S, Tamara I, et al. FGF23 indices of left ventricular hypertrophy. J Clin Invest 2011;12:4393-408.  Back to cited text no. 30
John S, Pin H, William F, Sunderman J. A biuret method for determination of protein in normal urine. Clin Chem 1968;12:1160-71.  Back to cited text no. 31
Matsuushita K, Kwak L, Sang Y, Ballew SH, Skali H, Skali AM, et al. Kidney disease measures and left ventricular structure and function: The atherosclerosis risk in community study. J Am Heart Assoc 2017;6:e006259.  Back to cited text no. 32
Alsagaff MY, Thaha M, Aminuddin M, Yogiarto RM, Yogiantoro M, Tomino Y. Asymmetric dimethylarginine: A novel cardiovascular risk factor in end-stage renal disease. J Int Med Res 2012;40:340-9.  Back to cited text no. 33


  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]


    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

  In this article
Article Tables

 Article Access Statistics
    PDF Downloaded35    
    Comments [Add]    

Recommend this journal