Literature DB >> 26870086

Predictor of cardiovascular risks in end stage renal failure patients on maintenance dialysis.

Christopher Thiam Seong Lim1, Xian Hui Yap2, Kuet Jun Chung3, Mohamad Azrul Khalid4, Norhayati Yayha5, Latiffah A Latiff6, Bak Leong Goh7.   

Abstract

OBJECTIVE: Cardiovascular disease (CVD) is the main cause of morbidity and premature mortality in end stage renal failure patients (ESRD) receiving dialysis. The aim of our study was to evaluate the impact of various risk factors in this group of high CVD risk patients in local population.
METHODS: We carried out a cross-sectional retrospective study in a single hospital. A total of 136 ESRF patients, consisted of 43 haemodialysis (HD) and 93 continuous ambulatory peritoneal dialysis (CAPD) patients, were recruited and followed up for 36 months duration. Midweek clinical and laboratory data were collected. The occurrence of existing and new CVD events was recorded.
RESULTS: Multiple Logistic Regression showed pre-existing cardiovascular event (odds ratio, 4.124; 95% confidence interval [CI], 0.990 to 17.187), elevated total cholesterol level (odds ratio, 0.550; 95% CI, 0.315 to 0.963), elevated serum phosphate level (odds ratio, 5.862; 95% CI, 1.041 to 33.024) and elevated random blood glucose level (odds ratio, 1.193; 95% CI, 1.012 to 1.406) were significantly associated with occurrence of CVD events.
CONCLUSIONS: History of cardiovascular event before the initiation of dialysis, elevated level of serum phosphate and random blood glucose levels are the risk factors of CVD whereas paradoxically a high total cholesterol level has CVD protective effect towards the ESRF patients.

Entities:  

Keywords:  CVD risk; End Stage Renal Failure (ESRF); Haemodialysis; Peritoneal dialysis

Year:  2015        PMID: 26870086      PMCID: PMC4744271          DOI: 10.12669/pjms.316.8039

Source DB:  PubMed          Journal:  Pak J Med Sci        ISSN: 1681-715X            Impact factor:   1.088


INTRODUCTION

CKD is an independent risk factor cardiovascular morbidity and mortality (CVD), even after adjustment for traditional and non-traditional risk factors. CVD events like cerebrovascular accident (CVA), ischeamic heart disease (IHD), congestive cardiac failure (CCF) and peripheral vascular disease (PVD) are much higher in CKD population.1 Traditional risk factors like hypertension, diabetes, hyperlipideamia and male gender cannot explain the abnormally high incidence of CVD in ESRF patients. The mortality rate for dialysis patients is abnormally high, up 10 to 30 times higher than the matched population.1 Several theories have been proposed over the last decade over the role of traditional and non-traditional contributing factors in accelerating CVD in ESRF population. However all these studies were done abroad with considerable different ethnic origin. In this study, we have undertaken a local study to evaluate whether we could predict the CVD risk for our local ESRF patients by using the routine parameters that are easily available in our day to day clinical practice. We hope by identifying these factors, we can institute strategy that will lessen the CVD risks in ESRF patients.

METHODS

This was a retrospective, cross-sectional, single center study. Incident ESRF patients undergoing Haemodialysis (HD) and Chronic Ambulatory Peritoneal Dialysis (CAPD) at Serdang Hospital from April 2006 until April 2009 were recruited by means of universal sampling. ESRF patients were defined as those having Glomerular Filtration Rate (GFR) < 15ml/min and have been started on dialysis for three months duration. The renal replacement therapy is of either haemodialysis or peritoneal dialysis. ESRF patients who had changed their dialysis modalities, either from HD to CAPD or vice versa or new ESRF of less than three months were excluded and those who had renal transplantation done were excluded. Data were collected by three trained researchers that reviewed the hospital electronic medical records of the recruited ESRF patients. The collected data that were entered into a proforma which capture data like socio-demographic factors, baseline medical history, essential routine laboratory parameters and the occurrence of new CV events. This study was non-interventional and did not influence the nature of treatment received by the subjects. Institutional review board (IRB) approval was obtained and either the patients or patients’ closest available next-of-kin were approached in all cases for informed consent using IRB-approved informed consent form. This was an investigator- initiated study. Data was analysed using SPSS version 18.0. The normality of continuous data was tested using Kolmogorov-Smirnov test. χ² test was used to test for the association of categorical data and p value ≤0.05 was considered significant. For continuous data which was not normally distributed, Mann-Whitney U test was used to test for the association. For dichotomous outcomes such as the CV events, Multiple Logistic Regression was used to determine the absolute risk on incidence.

RESULTS

A total of 136 of dialysis patients were recruited into the study. Table-I shows the demographic, laboratory parameters and the new CV events. Majority of the patients were within the 65-74 age group. The most common cause of ESRF in our center was diabetic nephropathy. The co-morbidities documented were hypertension (96.5%), diabetes (66.2%), hyperlipidemia (58.1%) and pre-existing cardiovascular event (31.6%).
Table-I

Summary demographic, laboratory parameters, and cardiovascular events (n=136).

VariablesFrequency (%)MeanMedian ± IQR
Socio-demographic Factors
Age50.9655 ± 20
 15-3422 (16.2)
 35-5444 (32.4)
 55-7466 (33.1)
 ≥754 (2.9)
Gender
 Male68 (50.0)
 Female68 (50.0)
Race
 Malay70 (51.5)
 Chinese48 (35.3)
 Indian18 (13.2)
Causes of ESRD
 DM45 (33.1)
 DM + HPT32 (23.5)
 Unknown24 (17.6)
 HPT15 (11.1)
 GN2 (1.5)
 SLE1 (0.7)
Co-morbidities
 HPT130 (95.6)
 DM90 (66.2)
 Hyperlipidaemia79 (58.1)
 Pre-existing CV event43 (31.6)
Essential Laboratory Parameters
Lipid Profile
 Total Cholesterol (mmol/L)5.17 ± 1.70
 LDL (mmol/L)3.11 ± 1.47
 HDL (mmol/L)1.15 ± 0.40
 Triglyceride (mmol/L)1.86 ± 1.29
Serum Calcium (mmol/L)2.19 ± 0.31
Serum Phosphate (mmol/L)1.42 ± 0.53
Random Blood Glucose (mmol/L)8.18 ± 5.50
Haemoglobin (g/dL)10.40 ± 2.40
Cardiovascular Event
 CV event (overall)37 (27.2)
 CVA12(8.8)
 IHD7(5.1)
 CCF2(1.5)
 PVD16(11.8)

*DM: Diabetes Mellitus, HPT: Hypertension, GN: Glomerulonephritis, SLE: Systemic Lupus Erythematosus,

LDL: Low density lipoprotein, HDL: High density lipoprotein, CVA: Cerebral vascular accident,

IHD: Ischaemic heart disease, CCF: congestive cardiac failure, PVD: peripheral vascular disease.

Summary demographic, laboratory parameters, and cardiovascular events (n=136). *DM: Diabetes Mellitus, HPT: Hypertension, GN: Glomerulonephritis, SLE: Systemic Lupus Erythematosus, LDL: Low density lipoprotein, HDL: High density lipoprotein, CVA: Cerebral vascular accident, IHD: Ischaemic heart disease, CCF: congestive cardiac failure, PVD: peripheral vascular disease. In the bivariate analysis results, there were significant association between hypertensive nephrosclerosis (p=0.040), diabetes mellitus (p=0.050) and pre-existing CVD (p=0.024) with the occurrence of new CVD events (Table-II). As for laboratory tests, there were significant associations between LDL (p=0.043) and random blood glucose (p=0.014) level with the occurrence of new CVD events (Table-III).
Table-II

Bivariate analysis of baseline medical history with cardiovascular events.

Baseline Medical HistoryCV Eventsχ2 value/Fisher’s Exact Testp value
YesNo
n%n%
Causes of ESRD
UnknownYes1(4.2)23(95.8)[b]0.304
No15(13.4)97(86.6)
DMYes12(14.8)69(85.2)1.795[a]0.180
No4(7.3)51(92.7)
GNYes1(25.0)3(75.0)[b]0.397
No15(11.4)117(88.6)
SLEYes0(0)1(100.0)[b]1.000
No16(11.9)119(88.1)
Polycystic kidney diseaseYes0-0---
No16(11.8)120(88.2)
Obstructive nephropathyYes0(0)5(100.0)[b]1.000
No16(12.2)115(87.8)
HypertensionYes10(18.9)43(81.1)4.221[a]0.040*
No6(7.2)77(92.8)
OthersYes0(0)12(100.0)[b]0.359
No16(12.9)108(87.1)
Co-morbidities
HypetensionYes15(11.5)115(88.5)[b]0.535
No1(16.7)5(83.3)
Diabetes MellitusYes14(15.6)76(84.4)3.684[a]0.050*
No2(4.3)44(95.7)
HyperlipidaemiaYes11(13.9)68(86.1)0.847[a]0.357
No5(8.8)52(91.2)
Pre-existing CVYes34(79.1)9(20.9)5.089[a]0.024*
No86(92.5)7(7.5)

p≤0.05 is significant

χ2 Test

Fisher’s Exact Test.

Table-III

Bivariate analysis of laboratory parameters and cardiovascular events.

Lab ParametersCV EventMedian ± IQRMean RankZ valuep value
Total Cholesterol (mmol/L)Yes4.45 ± 1.6551.78-1.8070.071
No5.21 ± 1.6570.73
LDL (mmol/L)Yes2.51 ± 1.3149.81-0.2020.043*
No3.12 ± 1.5170.99
HDL (mmol/L)Yes1.17 ± 0.3776.16-0.8280.408
No1.12 ± 0.4167.48
TG (mmol/L)Yes1.94 ± 0.8165.91-0.2800.779
No1.84 ± 1.3168.85
Serum Calcium (mmol/L)Yes2.19 ± 0.2577.69-0.9930.321
No2.19 ± 0.3267.28
Serum Phosphate (mmol/L)Yes1.57 ± 0.5082.38-1.5000.408
No1.40 ± 0.5566.65
Random Blood Glucose (mmol/L)Yes9.46 ± 5.4791.25-2.4590.014*
No7.72 ± 5.2565.47
Haemoglobin (g/dL)Yes10.30 ± 1.7372.91-0.4760.634
No10.40 ± 2.7567.91

p≤0.05 is significant Mann-Whitney U test.

Bivariate analysis of baseline medical history with cardiovascular events. p≤0.05 is significant χ2 Test Fisher’s Exact Test. Bivariate analysis of laboratory parameters and cardiovascular events. p≤0.05 is significant Mann-Whitney U test. Statistical analysis via multiple logistic regression showed history of pre-existing CV event (p=0.050), serum phosphate level (p=0.045) and random blood glucose level (p=0.035) were associated with significant increased of developing new CVD (Table-IV). Interestingly a high total cholesterol level with associated with a significant fewer CV events (P=0.035). There is no correlation between CVD events and serum haemoglobin and calcium level. Other comorbidities and aetiology of ESRF do not seem to have any correlation either with CVD events.
Table-IV

Multivariate analysis.

VariablesBp valueExp (B)95.0% C.I. for Exp (B)
LowerUpper
Socio-demoraphic Factor
 Gender-0.4150.5840.6610.1492.920
Causes of ESRD
 Diabetes mellitus-0.8930.3780.4090.0562.981
 Hypertension1.2240.0683.4020.91312.685
Co-morbidities
 Hypertension-1.4870.3000.2260.0143.769
 Diabetes mellitus1.7040.1705.4980.48262.665
 Hyperlipidaemia-0.2270.7620.7970.1843.455
 Pre-existing CV event1.4170.050*4.1240.99017.187
Essential Lab Parameters
 Total cholesterol-0.5970.036*0.5500.3150.963
 Serum calcium2.1280.1598.3970.434162.481
 Serum phosphate1.7690.045*5.8621.04133.024
 Random blood glucose0.1770.035*1.1931.0121.406
 Haemoglobin0.1040.6241.1090.7331.679
Constant-9.4000.0160.000

p≤0.05 is significant; Nagelkerke R Square=0.353

Multivariate analysis. p≤0.05 is significant; Nagelkerke R Square=0.353

DISCUSSION

There is abundance of data which demonstrated the association of ESRF and CVD.1 The overall prevalence of CVD in our center was 31.6% with incidence rate of 27.2%. The aetiology of ESRF appeared to have positive correlation with CVD where diabetic nephropathy and hypertensive nephrosclerosis has the worst outcome as shown in the bivariate analysis. In a large, prospective cohort study that included 12 550 adults, the development of type II diabetes was almost 2.5 times as likely in persons with hypertension than in their normotensive counterparts. This, in conjunction with considerable evidence of the increased prevalence of hypertension in diabetic persons, suggests that these 2 common chronic diseases frequently coexist. Moreover, each pathophysiological disease entity, although independent in its own natural history, serves to exacerbate the other.2 The bivariate analysis also demonstrated that an elevated random blood glucose level or low density lipoprotein (LDL) level significantly increased the cardiovascular risk. However further multivariate analysis demonstrated the inverse relationship with total cholesterol level and CVD. Our study supported the hypothesis whereby a lower plasma total cholesterol level in ESRF patient was associated with a significantly higher risk of death, possibility due to confounding protein-energy wasting or ‘time discrepancy of competing risks’ in which hypercholesterolaemia is beneficial only in the short term, while it worsens survival over a long-term interval.3 Cholesterol level reflects the nutritional status and well being of the ESRF patient a low cholesterol level is a results of malnutrition and on-going inflammation.4 The multivariate analysis again reconfirmed the increase cardiovascular risks with elevated random sugar level and phosphate level. In a recently published meta-analysis and systemic analysis, a high glycated haemoglobin level significantly increased the mortality risk in ESRF patient on dialysis. Poor glycemic control might result directly in macrovascular complications, possibly secondary to the generation of advanced glycation end products (AGEs), and hence shorten survival of these patients.5 In ESRD patients, as glomerular filtration rate decreases, there will be accumulation of inorganic phosphate which leads to stimulation of parathyroid hormone (PTH) in an attempt to restore the serum phosphorus and calcium homestasis. We found that hyperphosphatemia significantly increased risk of cardiovascular events by 5.8 times. Inadequate control of serum phosphorus contributed to elevated insoluble calcium-phosphorus (Ca x P) product, which lead to cardiovascular calcification, and accelerated CVD manifestation.6 In our study, there was no association between serum calcium level and occurrence of cardiovascular event in dialysis patients. The presence and extent of vascular calcifications rather than serum calcium were strong predictors of cardiovascular mortality.6 In our study, there were 31.6% dialysis patients who had pre-existing cardiovascular event prior to initiation of dialysis treatment. In both bivariate and multivariate analysis, pre-existing CVD was statistically associated with cardiovascular event. Those with pre-existing cardiovascular disease also has 4.1 times risk of developing further cardiovascular complications. The pre-existence of CVD appeared to be a strong predictor for CVD event. This finding concurred with the findings done in Canada by Kalantar-Zadeh.7 Majority of our patient has anaemia of chronic disease. Generally, patients with ESRD will develop anaemia mainly due to the inability of the kidneys to secrete enough erythropoietin to stimulate adequate hematopoiesis.8 Apart from erythropoietin deficiency, uremic-induced inhibitors of erythropoiesis, shortened erythrocyte survival, and disordered iron homeostasis all contribute to the development of anaemia. Recent work has identified hepcidin excess as a main contributor to the disordered iron homeostasis and anemia of CKD by impairing dietary iron absorption and iron mobilization from body stores.9 From both the bivariate and multivariate analysis, our study showed there was no association between haemoglobin level and cardiovascular event. Patients with ESRD and mild-to-moderate anaemia, the normalization of heamoglobin levels to 13.0 to 15.0 g/dL did not reduce cardiovascular events.10 We acknowledge that we have not studied all the potential risk factors but rather of those which are routinely available and easily carried out in our day to day practice. Our study is also limited by the sample size and it is a single center study which may not be accurate representation of the regional trend. Nevertheless this study reassured us that routine measurement and history taking is invaluable in determining the cardiovascular risk factors.
  10 in total

1.  Hypertension and antihypertensive therapy as risk factors for type 2 diabetes mellitus. Atherosclerosis Risk in Communities Study.

Authors:  T W Gress; F J Nieto; E Shahar; M R Wofford; F L Brancati
Journal:  N Engl J Med       Date:  2000-03-30       Impact factor: 91.245

2.  Low cholesterol in dialysis patients--causal factor for mortality or an effect of confounding?

Authors:  Michal Chmielewski; Marion Verduijn; Christiane Drechsler; Bengt Lindholm; Peter Stenvinkel; Boleslaw Rutkowski; Elisabeth W Boeschoten; Raymond T Krediet; Friedo W Dekker
Journal:  Nephrol Dial Transplant       Date:  2011-02-28       Impact factor: 5.992

3.  Glycated hemoglobin and risk of death in diabetic patients treated with hemodialysis: a meta-analysis.

Authors:  Christopher J Hill; Alexander P Maxwell; Christopher R Cardwell; Barry I Freedman; Marcello Tonelli; Masanori Emoto; Masaaki Inaba; Yasuaki Hayashino; Shunichi Fukuhara; Tomonari Okada; Christiane Drechsler; Christoph Wanner; Anna Casula; Amanda I Adler; Claudia Lamina; Florian Kronenberg; Elani Streja; Kamyar Kalantar-Zadeh; Damian G Fogarty
Journal:  Am J Kidney Dis       Date:  2013-08-16       Impact factor: 8.860

Review 4.  Mechanisms of anemia in CKD.

Authors:  Jodie L Babitt; Herbert Y Lin
Journal:  J Am Soc Nephrol       Date:  2012-08-30       Impact factor: 10.121

5.  Atherosclerotic cardiovascular disease risks in chronic hemodialysis patients.

Authors:  A K Cheung; M J Sarnak; G Yan; J T Dwyer; R J Heyka; M V Rocco; B P Teehan; A S Levey
Journal:  Kidney Int       Date:  2000-07       Impact factor: 10.612

6.  Anemia and mortality in hemodialysis patients: accounting for morbidity and treatment variables updated over time.

Authors:  Bruce M Robinson; Marshall M Joffe; Jeffrey S Berns; Ronald L Pisoni; Friedrich K Port; Harold I Feldman
Journal:  Kidney Int       Date:  2005-11       Impact factor: 10.612

7.  Hepcidin--a potential novel biomarker for iron status in chronic kidney disease.

Authors:  Joshua Zaritsky; Brian Young; He-Jing Wang; Mark Westerman; Gordana Olbina; Elizabeta Nemeth; Tomas Ganz; Seth Rivera; Allen R Nissenson; Isidro B Salusky
Journal:  Clin J Am Soc Nephrol       Date:  2009-04-30       Impact factor: 8.237

8.  Traditional cardiovascular disease risk factors in dialysis patients compared with the general population: the CHOICE Study.

Authors:  J Craig Longenecker; Josef Coresh; Neil R Powe; Andrew S Levey; Nancy E Fink; Alice Martin; Michael J Klag
Journal:  J Am Soc Nephrol       Date:  2002-07       Impact factor: 10.121

9.  Association between cholesterol level and mortality in dialysis patients: role of inflammation and malnutrition.

Authors:  Yongmei Liu; Josef Coresh; Joseph A Eustace; J Craig Longenecker; Bernard Jaar; Nancy E Fink; Russell P Tracy; Neil R Powe; Michael J Klag
Journal:  JAMA       Date:  2004-01-28       Impact factor: 56.272

Review 10.  Reverse epidemiology of cardiovascular risk factors in maintenance dialysis patients.

Authors:  Kamyar Kalantar-Zadeh; Gladys Block; Michael H Humphreys; Joel D Kopple
Journal:  Kidney Int       Date:  2003-03       Impact factor: 10.612

  10 in total
  3 in total

1.  Prognostic Value of the Controlling Nutritional Status (CONUT) Score in Patients at Dialysis Initiation.

Authors:  Kimiaki Takagi; Hiroshi Takahashi; Tomomi Miura; Kasumi Yamagiwa; Kota Kawase; Yuka Muramatsu-Maekawa; Takuya Koie; Masashi Mizuno
Journal:  Nutrients       Date:  2022-05-31       Impact factor: 6.706

2.  Risk profiles of referred chronic kidney disease patients in a tertiary nephrology centre.

Authors:  Christopher Thiam Seong Lim; Raihan R; Mohd Zharif Fikri A S
Journal:  Pak J Med Sci       Date:  2016 Jan-Feb       Impact factor: 1.088

3.  Clinical course after parathyroidectomy in adults with end-stage renal disease on maintenance dialysis.

Authors:  Christopher Thiam Seong Lim; Thevandra Kalaiselvam; Normayah Kitan; Bak Leong Goh
Journal:  Clin Kidney J       Date:  2017-08-17
  3 in total

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