1 

 

 

 

 

CARDIOVASCULAR DISEASE AND ITS ASSOCIATED RISK FACTORS IN SOUTH  

AFRICAN CHRONIC KIDNEY DISEASE PATIENTS 

 

 

 

 

 

DR HON-CHUN HSU 
 

 

 

 

 

 

 

 

A thesis submitted to the Faculty of Health Sciences,  

University of the Witwatersrand, Johannesburg,  

for the degree Doctor of Philosophy 

 

 

 

 

Johannesburg, South Africa 

2022 

 

 



2 

 

 

 

Declaration 

This is to certify that this thesis is my own work and has not been submitted before for any degree 

or examination in this or any other University. 

I have worked closely with my supervisors Professor Patrick Dessein and Professor Gavin Norton.  

I recruited the patients in my practice and obtained their written informed consent.  I conducted 

all clinical assessments and evaluated the blood results. 

Ms Chanel Robinson who belongs to a research team at the School of Physiology assisted me 

with the applanation tonometry using Sphygmocor software and echocardiography.  

Professor Patrick Dessein assisted me with the data analysis, interpretation of results and drafting 

of manuscripts.  Professor Gavin Norton and Professor Angela Woodiwiss advised on the evalu-

ation of diastolic function and gave valuable intellectual input. 

I hereby certify that the studies contained in this thesis have been approved by the Committee for 

Research in Human Subjects, University of the Witwatersrand, Johannesburg. The ethics  

approval number is M15-08-43. 

 

Signed on the 26th of February 2022. 

Dr Hon-Chun Hsu (Student) 

  

…………………………………………… 

 

 

Prof Patrick H. Dessein (Supervisor 1)                      Prof Gavin R. Norton (Supervisor 2) 

                                                                                   

……………………………………………                      ………………………………………… 

 



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Table of Contents 
                                                                                            Page 

Declaration………………………………………………………………… 2 

Publications arising from this work…………………………………… 4 

Abstract…………………………………………………………………….. 5 

Abbreviations……………………………………………………………… 8  

Acknowledgements………………………………………………………. 9 

Introduction………………………………………………………………... 10 

Study/Paper 1……………………………………………………………… 22 

Study/Paper 2……………………………………………………………… 51 

Study/Paper 3……………………………………………………………… 85 

Study/Paper 4……………………………………………………………… 121 

Summary of the results, implications and conclusions…………… 146 

Ethics approval………………………………………………………….... 160 

 

 

 

 

 

 

 

 

 

 

 

 

 



4 

 

 

Publications and presentations arising from this work 

 

1. Hsu H-C, Robinson C, Woodiwiss AJ, Norton GR, Dessein PH. Cardiovascular risk factors and 

disease in black compared to other Africans with chronic kidney disease. Int J Nephrol 2021 

Feb19;2021:8876363. doi: 10.1155/2021/8876363. eCollection 2021.PMID: 33680512  

2. Hsu H-C, Norton GR, Robinson C, Woodiwiss AJ, Dessein PH. Potential determinants of the 

E/e‘ ratio in non-dialysis compared to dialysis patients. Nephrology 2021;26:988-998.  

3. Hsu H-C, Norton GR, Peters F, Robinson C, Dlongolo N, Solomon A, Teckie G, Woodiwiss 

AJ, Dessein PH. Association of post transplant anaemia and persistent hyperparathyroidism 

with diastolic function in stable kidney transplant recipients. Int J Nephrol Renovasc Dis 

2021;14:1-13. 

4. Hsu H-C, Robinson C, Norton GR, Woodiwiss AJ, Dessein PH. The optimal haemoglobin tar-

get in dialysis patients may be determined by its opposing effects on arterial stiffness and 

pressure pulsatility. Int J Nephrol Cardiovasc Dis 2020;13:385-395.  

 

Potential determinants of diastolic function at different stages of chronic kidney disease.  Joint 

paper delivered as a plenary talk at the Second International Webinar on Nephrology, Urol-

ogy and Kidney Failure held on September 17, 2021 (Online Meeting). 

 

Towards preventing heart failure with preserved ejection fraction in non-dialysis and dialysis pa-

tients, and stable kidney transplant recipients.  Joint paper to be delivered as a Keynote Presen-

tation at the World Nephrology Congress in Barcelona, Spain (recently postponed due to 

COVID-19). 

 

 
 

 



5 

 

 

Abstract 
 
The markedly increased mortality in chronic kidney disease (CKD) patients is mostly due to an 

enhanced risk of cardiovascular disease (CVD).  The most documented CKD induced cardiovas-

cular abnormalities include impaired diastolic function that underlies heart failure with preserved 

ejection fraction and arteriosclerosis leading to impaired aortic function.  CKD is highly prevalent 

in South Africa.  The extent to which CKD enhances CVD risk among black Africans remains 

largely unknown. 

This thesis comprises a series of investigations that evaluated CVD and its risk factors in black 

compared to other Africans (first study), examined potential determinants of diastolic function in 

predialysis and dialysis patients (second study) as well as stable kidney transplant recipients 

(third study), and tested the hypothesis that the optimal haemoglobin target in dialysis patients 

may be determined by its contrasting effects on arterial stiffness and pressure pulsatility (fourth 

study). 

In the first study, we evaluated cardiovascular risk factors, aortic function by applanation tonom-

etry using SphygmoCor software, cardiac function by echocardiography, atherosclerosis extent 

by carotid ultrasound and cardiovascular event rates in 115 consecutive predialysis (n=67) and 

dialysis patients (n=48) including 46 black and 69 other (32 Asian, 28 white and 9 mixed race) 

participants.  Data were analysed in multivariable regression models. Overall, black compared to 

other African CKD patients had less frequent carotid artery plaque (30.4% versus 58.8%; OR 

(95% CI)=0.38 (0.16-0.91) despite an increased cardiovascular risk factor burden.  In receiver 

operator characteristic curve analysis, the Framingham score performed well in identifying non-

black but not black CKD patients with carotid plaque (area under the curve (AUC) (95% CI)=0.818 

(0.714-0.921) and AUC (95% CI)=0.556 (0.375-0.921), respectively).  Black compared to other 

African predialysis patients experienced larger Framingham scores and more adverse non-tradi-

tional cardiovascular risk factors, impaired arterial and diastolic function but similar cardiovascular 

event rates (OR (95% CI)=0.93 (0.22 to 3.87)).  Among dialysis patients, black compared to other 

Africans had an overall similar traditional and non-traditional cardiovascular risk factor burden, 

similar arterial and diastolic function and reduced cardiovascular event rates (OR (95% CI)=0.22 

(0.05 to 0.88)).  

 

For the second study, we assessed cardiovascular risk factors, arterial function, N-terminal natri-

uretic peptide (NT-proBNP) levels as a marker of volume overload, and diastolic function in 103 

(62 non-dialysis and 41 dialysis) patients.  In established confounder adjusted analysis, dialysis 

status impacted the pulse wave velocity-E/e’ relationship (interaction p=0.01) but not the NT-

proBNP level-E/e’ association (interaction p=0.1).  Upon entering arterial function measures and 

NT-proBNP levels simultaneously in regression models, arterial function measures were associ-

ated with E/e’ (p=0.008 to 0.04) in non-dialysis patients whereas NT-proBNP levels were related 



6 

 

 

to E/e’ in dialysis patients (p=0.009 to 0.04).  Bivariate associations were found between diabetes 

(p<0.0001) and E/e’ in non-dialysis patients, and haemoglobin concentrations and E/e’ (p=0.02) 

in those on dialysis.  Upon adjustment for diabetes in non-dialysis patients, only central pulse 

pressure remained associated with E/e’ (p=0.02); when haemoglobin concentrations were ad-

justed for in dialysis patients, NT-proBNP levels were no longer associated with E/e’ (p=0.2).  In 

separate models, haemoglobin levels were associated with E/e’ independent of left ventricular 

mass index and preload and afterload measures (p=0.02 to 0.03).  

 

For the third study, we evaluated traditional and non-traditional cardiovascular risk factors, carotid 

artery atherosclerosis, arterial function and diastolic function in 43 kidney transplant recipients 

with a transplant duration of >6 months, no acute rejection and a glomerular filtration rate of >15 

ml/min/1.73m2.  The mean (SD; range) transplant duration was 12.3 (8.0; 0.5-33.8) years.  Post 

transplantation anaemia and persistent secondary hyperparathyroidism were identified in 27.9% 

and 30.8% of the patients, respectively; 67.5% of participants were overweight or obese.  In es-

tablished confounder adjusted analysis, haemoglobin (partial R=-0.394, p=0.01) and parathyroid 

hormone concentrations (partial R=0.382, p=0.02) were associated with E/e’.  In multivariable 

analysis, haemoglobin (partial R=-0.278, p=0.01) and parathyroid levels (partial R=0.324, p=0.04) 

were independently associated with E/e’.  Waist-height ratio (partial R=-0.526, p=0.001 and partial 

R=-0.355, p=0.03), waist circumference (partial R=-0.433, p=0.008 and partial R=-0.393, p=0.02) 

and body mass index (partial R=-0.332, p=0.04 and partial R=-0.489, p=0.002) were associated 

with both e’ and E/A, respectively, in established confounder adjusted analysis.  The haemoglo-

bin-E/e’ (partial R=-0.422, p=0.02), parathyroid hormone-E/e’ (partial R=0.434, p=0.03), waist-

height ratio-e’ (partial R=-0.497, p=0.007) and body mass index-E/A (partial R=-0.386, p=0.04) 

relationships remained consistent after additional adjustment for left ventricular mass index and 

cardiac preload and afterload measures. 

 

For the fourth study, cardiovascular risk factors and arterial function was assessed in 48 dialysis 

patients.  In established confounder and diabetes adjusted linear regression models, haemoglo-

bin levels were directly associated with arterial stiffness (partial R=0.366, p=0.03) and inversely 

with central systolic pressure (partial R=-0.344, p=0.04), central pulse pressure (partial R=-0.403, 

p=0.01), peripheral pulse pressure (partial R=-0.521, p=0.001) and forward wave pressure (partial 

R=-0.544, p=0.001).  The presence of heart failure and use of angiotensin converting enzyme 

inhibitors or angiotensin receptor blockers and erythropoietin stimulating agents did not materially 

alter these relationships upon further adjustment for the respective characteristics in the models, 

and in sensitivity analyses.  In receiver operator characteristic curve analysis, the optimal hae-

moglobin concentration cut-off values in predicting arterial stiffness and increased central pulse 

pressure were remarkably similar at 10.95 g/dl and 10.85 g/dl respectively, and with clinically 

useful sensitivities, specificities and positive and egative predictive values.  In logistic regression 



7 

 

 

models, a haemoglobin value of >10.9 mg/dl was associated with both arterial stiffness (>10 

m/sec; OR (95% CI) = 10.48 (1.57 – 70.08), p=0.02) and normal central pulse pressure (>50 

mmHg; OR (95% CI) = 7.55 (1.58 – 36.03), p=0.01). 

 

In conclusion, black compared to other African predialysis patients experience an increased tra-

ditional and non-traditional cardiovascular risk factor burden and more impaired arterial and dias-

tolic function.  Once on dialysis, black African patients sustain less frequent cardiovascular event 

rates, which may represent a survival bias.  The atherosclerotic burden is smaller in black com-

pared to other African CKD patients but the Framingham score is unreliable in identifying those 

with very high risk atherosclerosis, which is nevertheless present in ~30% of them. Cardiovascu-

lar risk factors that are independently associated with markers of diastolic function include im-

paired arterial function and diabetes in predialyis patients, volume overload and low haemoglobin 

concentrations in dialysis patients, and post transplantation anaemia and persistent secondary 

hyperparathyroidism in kidney disease transplant recipients.  The optimal haemoglobin target in 

dialysis patients may be determined by its contrasting effects on aortic stiffness and pressure 

pulsatility.  These findings have implications in our understanding of CVD risk and its manage-

ment among CKD patients.         

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



8 

 

 

Abbreviations 

 

AUC  Area under the curve 

CI  Confidence interval 

CKD  Chronic kidney disease 

CVD  Cardiovascular disease 

ESRD  End stage renal disease 

HFpEF  Heart Failure with preserved ejection fraction 

HFrEF  Heart failure with reduced ejection fraction 

NT-proBNP N-terminal natriuretic peptide 

OR  Odds ratio 

SD  Standard deviation 

ROC  Receiver operator curve 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  



9 

 

 

Acknowledgements 

Special thanks to Professor Patrick Dessein for inspiring me to pursue a PhD while in full time 

private practice. Your contagiousness, enthusiasm and guidance spurred enough confidence in 

me to complete this series of interesting studies.  To Professor Gavin Norton, I am grateful that 

you accepted me into the School of Physiology and for your detailed guidance during the design 

and draft of the study.  I would not have been able to complete this thesis without the patience 

and knowledge of my supervisors. 

To my parents, thank you for always believing in me.  I owe all my accomplishments to your love 

and kindness. 

I am most grateful to all my patients who participated in this work.  They gave up their precious 

time to help others benefit from their suffering. This selfless sacrifice inspired me to be a better 

doctor. 

Lastly to my wife, thank you for taking such good care of our boys while I concentrated my efforts 

on this thesis. I could not have done it without you. 

 

 

 

 

 

 

 

 

 

 

 

 

 

  



10 

 

 

Introduction 

Chronic kidney disease (CKD) contributes substantially to morbidity and mortality (Global Burden 

of Disease (GBD) Chronic Kidney Disease Collaboration, 2020).  This is a worldwide phenome-

non.  The main risk factors for CKD are hypertension and diabetes.  Increased mortality in CKD 

is mostly due to a markedly enhanced risk of cardiovascular disease (CVD).  In this regard, a 

systematic analysis for the Global Burden of Disease, Injuries, and Risk Factors Study in 2017 

revealed a global chronic kidney disease prevalence of 9.1% (95% confidence interval 8.5 to 9.8) 

in 2017 with an increase of 29.3% (26.4 to 32.6) since 1990.  Globally, in 2017, 1.2 (1.2 to 1.3) 

million people died from CKD and the all-age mortality rate from CKD had increased by 41.4% 

(35.2 to 46.5) since 1990 (GBD Chronic Kidney Disease Collaboration, 2017).  In addition, 1.4 

(1.2-1.6) million cardiovascular disease related deaths were attributable to CKD. 

 

CKD and CVD risk in black compared to other Africans 

A recent sub-Saharan population study (George JA et al, 2019) reported an age-standardised 

population CKD prevalence of 10.7% (9.9 to 11.7).  CKD prevalence were larger in South African 

sites (14.0% (11.9 to 16.4)) than in West African sites (9.5% (8.3 to 10.8)).  Risk factors for CKD 

included older age, hypertension, diabetes and human immunodeficiency virus infection whereas 

male sex was protective.  Regional differences in CKD and its risk factors were attributed to dis-

parities in sociodemographic and epidemiological health transition stages. 

   

Available data on CVD risk among CKD patients originates mostly in studies that were performed 

in high-income populations.  Most patients with CKD reportedly die from CVD prior to developing 

kidney failure (Cozzolino M et al, 2018; Sarnak MJ et al, 2019).  Both adverse traditional cardio-

vascular risk factor profiles and kidney disease specific factors including anaemia, chronic volume 

overload, calcium-phosphate imbalance and oxidative stress mediate CVD in CKD patients.  CKD 

thereby causes cardiovascular changes that characteristically include advanced arteriosclerosis 

leading to impaired arterial function (Zanoli L et al, 2019) and left ventricular fibrosis that results 

in diastolic dysfunction and is often accompanied by hypertrophy (Wang X et al, 2019).  CKD also 



11 

 

 

enhances atherosclerosis (Sarnak MJ et al, 2019).  These changes result in an increased risk of 

heart failure, arrhythmias, sudden death, stroke and myocardial infarction.  The risk of cardiovas-

cular disease increases from 1.5 fold in patients with stage 2 CKD to 20 fold in those with end 

stage renal disease (ESRD) (Cozzolino M et al, 2018). 

 

Sub-Saharan Africa comprises low and middle income countries (Sub-Saharan Africa Population 

2020 (Demographics, Maps, Graphics); World Bank Country and Lending Groups: Country Clas-

sification).  Due to the rapid current urbanization and consequent epidemiological health transi-

tion, cardiovascular risk factor profiles and their impact on CVD as well as cardiovascular event 

phenotypes differ in low or middle compared to high income populations (Solomon A et al, 2014).  

Black South African persons currently experience smaller age-standardized mortality rates from 

ischemic heart disease than their non-black counterparts (Pillay-Van Wijk V et al, 2016).  By con-

trast, age-standardized mortality rates due to cerebrovascular and hypertensive heart disease 

are much larger in black compared to other South Africans (Pillay-Van Wijk V et al, 2016).       

 

Compared to their white counterparts, black Americans with pre-dialysis CKD patients experience 

an enhanced risk of developing ESRD and CVD mortality (Choi AI et al, 2008; Carnethon MR et 

al 2017).  However, survival is better in black compared to white Americans once they are on 

dialysis. 

 

The extent to which CKD impacts CVD risk among black Africans remains largely unknown.  In 

two retrospective cohort studies, sepsis was a more frequent cause of death than CVD among 

predominantly black African dialysis patients (Luyckx VA et al, 2009; Tamayo Isla RA et al, 2016).  

Black African dialysis patients may be less prone to coronary and aortic calcification (Freercks R 

et al, 2012).  However, carotid artery plaque was identified in 38.1% of 58 black and 26 non-black 

African dialysis patients (Amira OC et al, 2012).  A consistent shortcoming of these reported in-

vestigations is that the mean age of participants was as low as 36 to 42 years (Luyckx VA et al, 

2009; Tamayo Isla RA et al, 2016; Freercks R et al, 2012; Amira OC et al, 2012).     



12 

 

 

 

Given these limited reported data on CVD and its risk factors among Africans with CKD, we com-

pared cardiovascular risk factor profiles (Gunter S et al, 2018), large artery function including 

arterial stiffness, wave reflection and pressure pulsatility (Gunter S et al, 2018; Briet M et al, 2012; 

London GM, 2018), left ventricular systolic and diastolic function (Mokotedi L et al 2017), athero-

sclerosis extent and cardiovascular event rates between black and other African pre-dialysis and 

dialysis patients.  

 

Potential determinants of the E/e’ ratio in non-dialysis compared to dialysis patients 

As alluded to above, impaired left ventricular diastolic function comprises a most characteristic 

cardiovascular abnormality induced by CKD (Wang X et al, 2019).  Impaired diastolic function 

results from both reduced active and passive myocardial relaxation.  Active relaxation is mostly 

estimated by the echocardiographically determined ratio of early (E) to late (A) diastolic filling or 

mitral inflow velocity (E/A) and the early diastolic mitral annulus motion (e’).  Active relaxation 

involves high energy requiring rapid removal of cytosolic calcium into the sarcoplasmic reticulum, 

thin filament deactivation and cross-bridging kinetics.  Passive relaxation is typically assessed by 

the E/e’ ratio, which is a measure of left ventricular filling pressure.  Left ventricular fibrosis impairs 

passive relaxation.  E/A, e’ and E/e’ are indices that form part of currently recommended algo-

rithms in the identification of patients with diastolic dysfunction (Nagueh SF, 2016). 

 

Impaired diastolic function underlies the development of heart failure with preserved ejection frac-

tion (HFpEF), the prevalence of which increases with decreasing kidney function.  HFpEF is more 

prevalent and carries a worse prognosis than heart failure with reduced ejection fraction (HFrEF) 

in CKD patients (Kim MK et al, 2013; Ahmed A et al, 2007). 

 

Impaired diastolic function in CKD patients is mediated by increased preload due to volume over-

load and anaemia as well as increased afterload caused by arteriosclerosis mediated arterial 



13 

 

 

stiffness.  Arterial stiffness enhances the forward wave pressure and thereby wave reflection and 

pulse pressure (Wang X et al, 2019; Zanoli L et al, 2019). 

 

Left ventricular hypertrophy comprises another highly prevalent cardiovascular abnormality in 

CKD (Wang X, 2019; Zanoli L, 2019).  It is also due to increased preload and afterload and is a 

strong predictor of incident cardiovascular events.  However, the reported mechanistic link be-

tween impaired diastolic function and left ventricular hypertrophy has been questioned (Wang X 

et al, 2019). 

 

Circulating levels of N-terminal proBNP (NT-proBNP) are mostly used in the evaluation of patients 

with heart failure (Gutierrez MC et al, 2013).  In CKD, NT-proBNP is a marker of volume overload 

(Kim J-S et al, 2017). 

 

Previously reported cohort studies suggest that volume overload may be particularly important in 

the development of CVD among dialysis patients (Zoccalli C et al, 2017).  By contrast, increased 

afterload may comprise a predominant cardiovascular risk mechanism among pre-dialysis pa-

tients (Chirinos JA et al, 2014).  Additionally, anaemia is associated with volume overload (Hung 

S-C et al, 2015) as well as NT-proBNP concentrations in patients with HFpEF, whereas diabetes 

is strongly associated with impaired arterial function in CKD persons who are not on dialysis 

(Townsend RR, 2015).   

 

We therefore hypothesized that, in established confounder adjusted analysis, impaired arterial 

function indices are more strongly associated with E/e’ in non-dialysis compared to dialysis pa-

tients whereas NT-proBNP levels are more closely related to E/e’ in dialysis compared to non-

dialysis persons.  We further examined whether traditional and non-traditional or renal cardiovas-

cular risk factors including diabetes and haemoglobin levels, could explain the associations of 

arterial function measures and NT-proBNP levels with E/e’ in CKD patients. 

 



14 

 

 

Association of post transplantation anaemia and persistent secondary hyperparathyroid-

ism with diastolic function in stable kidney transplant recipients  

Kidney transplant recipients experience a markedly improved quality of life and reduced CVD risk 

when compared to those on ongoing dialysis (Devine PA et al, 2019).  Indeed, a functioning 

allograft can improve echocardiographically identified abnormalities.  Nevertheless, kidney trans-

plant recipients still experience a 3 to 5 fold increased risk of CVD and, in particular, non-athero-

sclerotic CVD (Lentine KL et al, 2005; Rigatto C et al, 2002).  Approximately 18% of kidney trans-

plant recipients still develop de novo heart failure within 3 years subsequent to transplantation 

(Lentine KL et al, 2005). 

 

Reportedly, half of patients undergoing kidney transplantation have impaired diastolic function 

(Himelman RB et al, 1988).  The determinants of diastolic function among stable kidney transplant 

recipients (transplant duration of >6 months, absence of acute rejection and glomerular filtration 

rate of >15 ml/min/1.37m2) (Ducloux D et al, 2000) await further elucidation.  In this regard, late 

post transplantation anaemia (Gafter-Gvili A et al, 2019) and persistent hyperparathyroidism 

(Santos RD et al, 2019) are present in 35% and 50% of kidney transplant recipients, respectively.   

 

Anaemia can cause not only increased preload and left ventricular mass but also tissue hypoxia 

with consequent myocardial fibrosis (Mistry N et al, 2018; Caramelo C et al, 2007; D’Amario D et 

al, 2019; Lopez B et al, 2008).  Secondary hyperparathyroidism can increase cardiac afterload 

by enhancing arteriosclerosis (Devine PA et al 2019) and induce cardiac hypertrophy and myo-

cardial fibrosis directly (Fujii H et al, 2018).  

 

In view of these reported findings, herein we hypothesized that post transplantation anaemia and 

persistent secondary hyperparathyroidism are potential determinants of diastolic function in sta-

ble kidney transplant recipients.   

 



15 

 

 

The optimal haemoglobin target in dialysis patients may be determined by its contrasting 

effects on arterial stiffness and pressure pulsatility 

The prevalence of anaemia in ESRD patients is ~90% (Alemu B et al, 2021).  It is caused by 

multiple factors including relative erythropoietin deficiency, iron deficiency, blood loss, reduced 

erythrocyte survival duration, inflammation, infection, underlying hematologic disease, hyperpara-

thyroidism, hemolysis and nutritional factors (Fishbane S et al, 2018). 

 

Upon treating severe anaemia with erythropoietin in dialysis patients, quality of life improves and 

the need for hospitalization and blood transfusion decreases when targeting a haemoglobin level 

of 11.0 g/dl (Jones M et al, 2004).  However, upon targeting a haemoglobin level of ~13 g/dl with 

erythropoietin, the risk of all-cause mortality, stroke, hypertension and vascular access throm-

bosis increases (Promminitikul A et al, 2007; Palmer SC et al, 2010).  Due to previously reported 

trial designs, the effects of a haemoglobin level of 11.5 to 13 g/dl on the vasculature remain cur-

rently unknown.  The reasons why total correction of anaemia is associated with adverse CVD 

events in dialysis patients are unclear.  Postulates include frequent underlying atherosclerotic 

disease, increased viscosity and platelet aggregation and increased peripheral vascular re-

sistance.  Notably in this regard, haemoglobin is a potent nitric oxide scavenger (Donadee C et 

al, 2011).  Nitric oxide reduces arterial stiffness and peripheral vascular resistance (Wilkinson IB 

et al 2004).  Given that CKD causes severe arteriosclerosis, it is therefore conceivable that in-

creases in the haemoglobin level could enhance arterial stiffening further whereas a reductions 

in the haemoglobin level may further increase pressure pulsatility in the present context.  Both 

arterial stiffness and pressure pulsatility increase CVD risk (Hashimoto J et al, 2010). 

 

We therefore assessed the independent relationships of haemoglobin levels with arterial function 

measures including pulse wave velocity, wave reflection and pressure pulsatility in a cohort of 

dialysis patients. 

 

 



16 

 

 

References 
 

Ahmed A, Rich MW, Sanders PW et al. Chronic kidney disease associated mortality in diastolic 

versus systolic heart failure: A propensity matched study. Am J Cardiol 2007;99:393-8. 

 

Alemu B, Techane T, Dinegde NG, Tsige Y. Prevalence of anemia and its associated factors 

among chronic kidney disease patients attending selected public hospitals of Addis Ababa, Ethi-

opia: institutional-based cross-sectional study. Int J Nephrol Renovasc Dis 2021;14:67-75. 

 

Amira OC, Naicker S, Manga P et al. Adiponectin and atherosclerosis risk factors in African he-

modialysis patients: a population at low risk for atherosclerotic cardiovascular disease. Hemodi-

alysis Int 2012;16:59-68. 

 

Briet M, Boutouyrie P, Laurent S, London GM. Arterial stiffness and pulse pressure in CKD and 

ESRD. Kidney Int 2012;82:388-400. 

 

Caramelo C, Justo S, Gil P. Anemia in heart failure: pathophysiology, pathogenesis, treatment, 

and incognitae. Rev Esp Cardiol 2007;60:848-860. 

 

Carnethon MR, Pu J, Howard G et al. Cardiovascular health in African Americans: A scientific 

statement from the American Heart Association. Circulation 2017;136:e393-e423. 

 

Chirinos JA, Khan A, Bansai N et al. Arterial stiffness, central pressures and incident hospitalized 

heart failure in the Chronic Renal Insufficiency Cohort (CRIC). Circ Heart Fail 2014;7(5):709-16. 

 

Choi AI Rodriguez RA, Bacchetti P, Bertenthal D, Hernandez GT, O’Hare AM. White/black racial 

differences in risk of end-stage renal disease and death. Am J Med 2009;122:672-8. 

 



17 

 

 

Cozzolino M, Mangano M, Stucchi A et al. Cardiovascular disease in dialysis patients. Nephrol 

Dial Tranplant 2018;33 Suppl 3:iii28-iii34. 

 

D’Amario D, Migliaro S, Borovac JA, Restivo A, Vergallo R, Galli M, et al. Microvascular dysfunc-

tion in heart failure with preserved ejection fraction. Front Physiol 2019;10:1347. doi: 

10.3389/fphys.2019.01347. eCollection 2019. 

 

Devine PA, Courtney AE, Maxwell AP. Cardiovascular risk in renal transplant recipients. J Neph-

rol 2019;32:389-399. 

 

Ducloux D, Motte G, Challier R, Gibey R, Chalopin J-M. Serum homocysteine total and cardio-

vascular disease occurrence in chronic, stable renal transplant recipients: a prospective study. J 

Am Soc Nephrol 2000;11:134-137. 

 

Freercks F, Swanepoel C, Carrara H, Moosa S, Lachman A, Rayner B. Vascular Calcification in 

South African dialysis patients: ethnic variation, prevalence, detection and haemodynamic corre-

lates. Nephrology 2012;17:607-615. 

 

Fujii H. Association between parathyroid hormone and cardiovascular disease. Ther Apher Dial 

2018;22:236-241. 

 

Gafter-Gvili A, Gafter U. Posttransplantation anemia in kidney transplant recipients. Acta Haema-

tol 2019;142:37-43. 

 

GBD Chronic Kidney Disease Collaboration. Global, regional, and national burden of chronic kid-

ney disease, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. 

Lancet 2020;395:709-33. 

 



18 

 

 

George JA, Brandenburg J-T, Fabian J. Kidney damage and associated risk factors in rural and 

urban sub-Saharan Africa (AWI-Gen): a cross-sectional population study. Lancet 2019;7:e1632-

43. 

 

Gunter S, Robinson C, Woodiwiss AJ et al. Arterial wave reflection and subclinical atherosclerosis 

in rheumatoid arthritis. Clin Exp Rheumatol 2018;36:412-420. 

 

Gutierrez MC, Moore PG, Liu H. Goal-directed therapy in intraoperative fluid and hemodynamic 

management. J Biomed Res 2013;27(5):357-65. 

 

Hashimoto J, Ito S. Pulse pressure amplification, arterial stiffness, and peripheral wave reflection 

determine pulsatile flow waveform of the femoral artery. Hypertension 2010;56:926-33. 

 

Kidney Disease: Improving. Global Outcomes (KDIGO) Anemia Work Group. KDIGO clinical 

practice guideline for anemia in chronic kidney disease. Kidney Int (Suppl) 2012;2:279-335.  

 

Kim J-S, Yang J-W, Yoo JS, Choi S Ok, Han B-G. Association between E/e’ ratio and fluid over-

load in patients with predialysis chronic kidney disease. PLoS One 2017:13;12(9):e0184764. 

doi: 10.1371/journal.pone.0184764. eCollection 2017. 

 

Kim MK , Kim B, Lee JY et al. Tissue Doppler-derived E/e' ratio as a parameter for assessing 

diastolic heart failure and as a predictor of mortality in patients with chronic kidney disease. Ko-

rean J Intern Med 2013;28:35-44. 

 

Lentine KL, Schnitzler MA, Abbott KC et al. De novo congestive heart failure after kidney trans-

plantation: a common concition with poor prognostic implications. Am J Kidney Dis 2005;46:720-

733. 

 

https://www.ncbi.nlm.nih.gov/pubmed/29185969
https://www.ncbi.nlm.nih.gov/pubmed/29185969
https://pubmed.ncbi.nlm.nih.gov/?sort=date&term=Kim+MK&cauthor_id=23345995
https://pubmed.ncbi.nlm.nih.gov/?sort=date&term=Kim+B&cauthor_id=23345995
https://pubmed.ncbi.nlm.nih.gov/?sort=date&term=Lee+JY&cauthor_id=23345995


19 

 

 

London GM. Arterial stiffness in chronic kidney disease and end-stage renal disease. Blood  

Purif 2018;45:154-158.  

 

Lopez B, Gonzalez A, Hermida N, Laviades C, Diez J. Myocardial fibrosis in chronic kidney  

disease: potential benefits of torasemide. Kidney Int 2008;Suppl 111:S19-S23. 

 

Luyckx VL, Yip A, Sofianou L, Jhangri GS, Mueller TF, Naicker S. Cardiac function in an African 

dialysis population with a low prevalence of pre-existing cardiovascular disease. Ren Fail 

2009;31:211-220. 

 

Mistry N, Mazer CD, Sled JG et al. Red blood cell antibody-induced anemia causes differential 

degrees of tissue hypoxia in kidney and brain. Am J Physiol Reg Integr Comp Physiol 

2018;314:R611-R622. 

 

Mokotedi L, Gunter S, Robinson C et al. The Impact of different classification criteria sets on the 

estimated prevalence and associated risk factors of diastolic dysfunction in rheumatoid arthritis. 

Int J Rheumatol 2017;2017:2323410. 

 
Nagueh SF, Smiseth OA, Appleton CP et al. Recommendations for the evaluation of ventricular 

diastolic function by echocardiography: An update from the American Society of Echocardiog-

raphy and the European Association of Cardiovascular Imaging. J Am Soc Echocardiogr 

2016;29:277-314. 

 

Pillay-van Wyk V, Msemburi W, Laubscher R et al. Mortality trends and differentials in South 

Africa from 1997 to 2012: second National Burden of Disease Study. Lancet 2016;4:e642-e653. 

 

Phrommintikul A, Haas SJ, Elsik M, Krum H. Mortality and target haemoglobin concentrations in 

anaemic patients with chronic kidney disease treated with erythropoietin: a meta-analysis. Lancet 

2007:369:381-388. 

https://www.ncbi.nlm.nih.gov/pubmed/29348754
https://www.ncbi.nlm.nih.gov/pubmed/29348754


20 

 

 

 

 

Rigatto C, Parfrey P, Foley R, Negrijn C, Tribula C, Jeffrey J. Congestive heart failure in renal 

transplant recipients: risk factors, outcomes, and relationships with ischemic heart disease. J Am 

Soc Nephrol 2002;13:1084-1090. 

 

Santos RD, Rossi A, Coyne D, Maw TT. Management of post-transplant hyperparathyroidism and 

bone disease. Drugs 2019;79:501-513.  

 

Sarnak MJ, Amann K, Bangalore A et al. Chronic kidney disease and coronary artery disease. 

JACC State-of-the-Art Review. J Am Coll Cardiol 2019;74:1828-38. 

 

Solomon A, Tsang L, Woodiwiss AJ, Millen AME, Norton GR, Dessein PH. Cardiovascular dis-

ease risk amongst African black patients with rheumatoid arthritis: the need for population specific 

stratification. Biomed Res Int 2014;2014, article ID 826095; 

http://dx.doi.org/10.1155/2014/826095. 

 

Sub-Saharan Africa Population 2020 (demographics, maps, graphics): World Population Review. 

Http://worldpopulationreview.com/continents/sub-saharan-africa-population/ (Accessed 13 Sep-

tember 2020).  

 

Tamayo Isla RA, Ameh OI, Mapiye D et al. Baseline predictors of mortality among predominantly 

rural-dwelling end-stage renal disease patients on chronic dialysis therapies in Limpopo, South 

Africa. PLoS One 2016;11:e0156642, 2016. doi: 10.1371/journal.pone.0156642. eCollection 

2016. 

 

Townsend RR. Arterial stiffness and chronic kidney disease: lessons from the Chronic Renal In-

sufficiency Cohort study. Curr Opin Nephrol Hypertens 2015;24(1):47-53. 

http://dx.doi.org/10.1155/2014/826095


21 

 

 

 

Zoccali C, Moissl U, Chazot C et al. Chronic fluid overload and mortality in ESRD. J Am Soc 

Nephrol 2017;28(8):2491-7. 

 

Zanoli L, Lentini P, Briet M et al. Arterial stiffness in the heart disease of CKD. J Am Soc Nephrol 

2019;30:918-28. 

 

Wang X, Shapiro JI. Evolving concepts in the pathogenesis of uraemic cardiomyopathy. Nat Rev 

2019;15:159-74. 

 

Wilkinson IB, Franklin SS, Cockcroft JR. Nitric oxide and the regulation of arterial stiffness. Hy-

pertension 2004;44:112-116. 

 

World Bank Country and Lending Groups: Country Classification, https://data-

helpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending 

groups (Accessed 13 September 2020)   

 

 

 

 

 

 

 

 

    

 

 

 



22 

 

 

Study/Paper 1 

Study/Paper 1 shows that black compared to other African predialysis patients experience an 

increased traditional and non-traditional cardiovascular risk factor burden and more impaired ar-

terial and diastolic function.  Once on dialysis, black African patients sustain less frequent cardi-

ovascular event rates, which may represent a survival bias.  The atherosclerotic burden is smaller 

in black compared to other African CKD patients but the Framingham score is unreliable in iden-

tifying those with very high risk atherosclerosis, which is nevertheless present in ~30% of them. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



23 

 

 

Research Article 

Cardiovascular risk factor profiles and disease in black compared to other Africans with 

chronic kidney disease 

 

Hon-Chun Hsu1,2, Chanel Robinson1, Angela J. Woodiwiss1, Gavin R. Norton1, Patrick H.  

Dessein1,2,3,4  

 

1Cardiovascular Pathophysiology and Genomics Research Unit, School of Physiology, Faculty 

of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa 

2Nephrology Unit, Milpark Hospital, Johannesburg, South Africa 

3Internal Medicine Department, Faculty of Health Sciences, University of the Witwatersrand,  

Johannesburg, South Africa 

4Free University and University Hospital, Brussels, Belgium 

 

ORCID identifiers: Hon-Chun Hsu: https://orcid .org/0000-0003-4180-1552; Chanel Robinson: 

https://orcid .org/0000-0002-9385-2709; Angela J. Woodiwiss: https://orcid.org/0000-0001-

2555-4125; Gavin R. Norton: https://orcid .org/0000-0001-6416-6104; Patrick H. Dessein: 

https://orcid .org/0000-0002-9357-4630 

 
Correspondence should be addressed to Patrick H Dessein; patrick.dessein22@gmail.com 
 
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

https://orcid.org/0000-0001-2555-4125
https://orcid.org/0000-0001-2555-4125


24 

 

 

Abstract 

Background and objectives. The extent to which chronic kidney disease (CKD) impacts cardio-

vascular disease (CVD) in black Africans is uncertain.  We compared cardiovascular risk factors 

and CVD between black and other African CKD patients.   

 

Methods.  Cardiovascular risk factors, aortic and cardiac function, atherosclerosis extent and car-

diovascular event rates were assessed in 115 consecutive pre-dialysis (n=67) and dialysis pa-

tients (n=48) including 46 black and 69 other (32 Asian, 28 white and 9 mixed race) participants.  

Data were analysed in multivariable regression models.   

 

Results. Overall, black compared to other African CKD patients had less frequent carotid artery 

plaque (OR (95% CI)=0.38 (0.16-0.91) despite an increased cardiovascular risk factor burden.  In 

receiver operator characteristic curve analysis, the Framingham score performed well in identify-

ing non-black but not black CKD patients with carotid plaque (area under the curve (AUC) (95% 

CI)=0.818 (0.714-0.921) and AUC (95% CI)=0.556 (0.375-0.921), respectively).  Black compared 

to other African pre-dialysis patients experienced larger Framingham scores and more adverse 

non-traditional cardiovascular risk factors, impaired arterial and diastolic function but similar car-

diovascular event rates (OR (95% CI)=0.93 (0.22 to 3.87)).  Among dialysis patients, black com-

pared to other Africans had an overall similar traditional and non-traditional cardiovascular risk 

factor burden, similar arterial and diastolic function but increased systolic function (partial 

R=0.356, p=0.01 and partial R=0.315, p=0.03 for ejection fraction and systolic volume, respec-

tively) and reduced cardiovascular event rates (OR (95% CI)=0.22 (0.05 to 0.88)).   

 

Conclusion.  Black compared to other African CKD patients have less frequent very high risk 

atherosclerosis and experience weaker cardiovascular risk factor-atherosclerotic CVD relation-

ships.  These disparities may be due to differences in epidemiological health transition stages.  

Among dialysis patients, black compared to other Africans have less cardiovascular events, which 

may represent a selection bias as previously documented in black American.   

 

 

 

 

 

 

 

 

 

 



25 

 

 

1. Introduction  

The global prevalence of chronic kidney disease (CKD) was recently estimated at 9.1% [1], 

whereas that in sub-Saharan Africa was 10.7% and ranged from 6.6% to 14% in west compared 

to South African sites [2].  Most patients with CKD are more likely to die from cardiovascular 

disease (CVD) than develop kidney failure [3,4].  CVD in CKD is mediated by adverse traditional 

cardiovascular risk factor profiles and renal disease specific factors including calcium-phosphate 

imbalance, anaemia, chronic volume overload and oxidative stress [3,4].  The risk of cardiovas-

cular disease increases from 1.5 fold in patients with stage 2 CKD to 20 fold in those with end 

stage renal disease (ESRD) [3].  

   Presently available evidence on the effects of CKD on CVD originates in studies that were 

mostly performed in high income countries.  Sub-Saharan Africa is a large continent that consists 

of low and middle income countries [5,6].  The sub-Saharan African black population is currently 

undergoing rapid urbanization and, consequently, an epidemiological health transition [7].  Cardi-

ovascular risk factor profiles and their impact on CVD as well as cardiovascular event phenotypes 

differ in low or middle compared to high income populations [7].  Black South African persons 

currently experience smaller age-standardized mortality rates from ischemic heart disease than 

their non-black counterparts [8].  By contrast, age-standardized mortality rates due to cerebro-

vascular and hypertensive heart disease are much larger in black compared to other South Afri-

cans [8]. Compared to their white counterparts, black Americans with pre-dialysis chronic kidney  

disease experience an enhanced risk of CVD mortality [9].  This disparity further increases with 

CKD severity [9].  However, survival is better in black compared to white Americans once they 

are on dialysis [9]. 

   The extent to which CKD impacts CVD risk among black Africans is less well established.  The 

respective evidence derives from investigations that included only patients on dialysis [10-13].  In 

two retrospective cohort studies, sepsis was a more frequent cause of death than CVD among 

predominantly black African dialysis patients [10,12].  Another study revealed a markedly low 

prevalence of coronary and aortic calcification in black African dialysis patients [11].  Yet, Amira 

and colleagues [13] identified carotid artery plaque in 38.1% of 58 black and 26 non-black African 

dialysis patients.  Notably, the mean age of participants in these studies was as low as 36 to 42 

years [10-13].  In the present study, we compared cardiovascular risk factor profiles [14], large 

artery function including arterial stiffness, wave reflection and pressure pulsatility [14-16], left ven-

tricular systolic and diastolic function [17], atherosclerosis extent and cardiovascular event rates 

between black and other African pre-dialysis and dialysis patients.                          

 

 

 

 



26 

 

 

2. Patients and Methods 

2.1. Patients. One hundred and fifteen consecutive pre-dialysis or dialysis patients that included 

46 black and 69 other (32 Asian, 28 white and 9 mixed race) participants, were recruited at the 

Milpark Hospital in Johannesburg, South Africa.  Pre-dialysis patients had a Chronic Kidney Dis-

ease Epidemiology Collaboration estimated glomerular filtration rate (eGFR) [18] of <60 

ml/min.1.73m2 upon enrolment.  Patients with infection or/and active cancer were excluded.  The 

study was approved by the University of the Witwatersrand Human (Medical) Research Ethics 

Committee (protocol number: M15-08-43) in Johannesburg, South Africa and performed accord-

ing to the 2013 revised Helsinki Declaration.  Each patient gave written informed consent. 

   

2.2. Methods. Baseline recorded characteristics comprised demographic features, CKD staging, 

lifestyle factors and anthropometric parameters. Dialysis patients were investigated on the day 

prior to undergoing the respective procedure.  Each of these patients was dialysed thrice weekly.       

 

2.2.1. Cardiovascular risk factors and their treatment.  Traditional and non-traditional or kidney 

disease related cardiovascular risk factors and their treatment were recorded using previously 

reported methods [14] and as given in the Supplementary material (methods).  The overall major 

traditional cardiovascular risk factor burden was estimated by calculating the Framingham score 

[19].  For this study, a high phosphate concentration was identified in patients with a phosphate 

level of >1.42 mmol/l or/and when a phosphate lowering agent (calcium carbonate or sevelamer 

in 48 and 1 (black dialysis patient) cases, respectively) was used.   

 

2.2.2. Arterial function.  Central hemodynamic characteristics were determined using a high-fidel-

ity SPC-301 micromanometer (Millar instument, Inc., Houston, Texas), interfaced with a computer 

utilizing SphygmoCor software, version 9.0 (AtCor Medical Pty. Ltd., West Ryde, New South 

Wales, Australia).  We evaluated arterial stiffness as estimated by aortic pulse wave velocity, 

wave reflection as represented by the augmentation index, reflected wave pressure and reflection 

magnitude, and pressure pulsatility measures including central systolic and pulse pressure, pe-

ripheral pulse pressure, pressure amplification and forward wave pressure as previously reported 

[14] and given in the Supplementary material (methods).  

 

2.2.3. Left ventricular structure and function.  Echocardiography was performed as recommended 

by the American Society of Echocardiography convention [17] and using a Philips CX50 POC 

Compact CompactXtreme Ultrasound System (Philips Medical Systems (Pty) Ltd, USA) equipped 

with a 1.8-4.2 MHz probe that allowed for M-mode, 2-D, pulsed and tissue Doppler measure-

ments.  We assessed left ventricular structure as represented by mass and hypertrophy, systolic 

function as estimated by ejection fraction and systolic volume, and diastolic function parameters 



27 

 

 

comprising the early (E)/late (atrial) diastolic wave (A) ratio, the peak mitral annulus motion during 

early diastole (e’) and E/e’ ratio, as previously described [17] and given in the Supplementary 

material (methods).   

 

2.2.4. Carotid atherosclerosis.  Carotid artery ultrasound was performed using a Philips CX50 

POC Compact CompactXtreme Ultrasound System (Philips Medical Systems (Pty) Ltd, USA) at-

tached to a linear array 4.0-12.0 MHz probe.  The software provided for semi-automated border 

detection gives markedly reproducible data as previously described [14].  Images of at least 1cm 

length of the distal common carotid arteries were obtained.  The optimal angle of incidence was 

used, defined as the longitudinal angle of approach where both branches of the internal and ex-

ternal carotid artery were visualized simultaneously. The carotid intima-media thickness (c-IMT) 

was defined as the mean of the left and right common carotid artery thickness.  Plaque in the 

extracranial carotid tree was defined according to the Mannheim consensus criteria [20].  Carotid 

ultrasound measurements were made by the same observer that performed the arterial function 

and echocardiographic evaluations (CR).  The intra-observer variability of ultrasound measure-

ments is low in our setting [14].  

 

2.2.5. Cardiovascular event rates.  Cardiovascular event rates included ischemic heart disease 

(acute myocardial infarction, percutaneous transluminal coronary angioplasty and/or coronary ar-

tery bypass surgery), heart failure and/or cerebrovascular and/or peripheral arterial disease that 

was confirmed by a cardiologist, neurologist and vascular surgeon, respectively.  

 

2.2.6. Data analysis.  Data were analysed using the IBM SPSS statistics program (version 23.0 

IBM, USA) and significance was set at p ≤0.05.  Significance was consistently analysed with two-

sided tests.  Results are expressed as mean (SD) or median (interquartile range, IQR) for contin-

uous variables and percentages for categorical variables.  Non-normally distributed characteris-

tics were logarithmically transformed prior to entering them in multivariable regression models.    

   We compared traditional and non-traditional cardiovascular risk factor profiles, arterial function 

parameters, left ventricular structure and function variables, atherosclerosis markers and cardio-

vascular event rates between black and other African chronic kidney disease patients in age and 

sex adjusted multivariable regression models.  Other established potential confounders or medi-

ators of arterial function [14] were consistently adjusted for in additional models.  We subse-

quently performed sensitivity analyses among pre-dialysis as well as dialysis patients.  Differ-

ences among the 4 investigated groups that included black and other African pre-dialysis and 

black and other African dialysis patients were assessed by ANOVA, Kruskall-Wallis and chi-quare 

test for continuous normally distributed, continuous non-normally distributed and categorical var-

iables, respectively.  The performance of the Framingham score in identifying black and other 



28 

 

 

African chronic kidney disease patients with very high CVD risk as represented by carotid plaque 

presence was determined in receiver operator characteristic (ROC) curve analysis.    

 

3. Results 

3.1. Baseline patient characteristics.  As given in Table 1, mean age was 5.6 years smaller in 

black compared to other CKD African patients (p=0.03).  Sex and lifestyle factors did not differ in 

black compared to other African participants.  In age and sex adjusted analysis, black patients 

were more frequently on dialysis (OR (95%CI)=3.18 (1.41 to 7.08)).  Body weight and height were 

each smaller in black compared to other African patients.  These difference reached significance 

for weight (p=0.02) only.  Other anthropometric measures were similar in the two groups. 

 

3.2. Traditional and non-traditional cardiovascular risk factors in black compared to other African 

patients with CKD.  Cardiovascular risk factor profiles are presented in Table 2.  In age and sex 

adjusted analysis, hypertension and diabetes were more prevalent in black compared to other 

African CKD patients.  The use of insulin, diuretics and calcium channel blockers was more fre-

quent whereas that of lipid lowering agents was less prevalent in black compared to other African 

patients.  Systolic blood pressure, heart rate and the Framingham score were each larger in black 

compared to other African patients. 

   With regard to non-traditional cardiovascular risk factors, black patients had more frequently 

high phosphate concentrations, smaller calcium and haemoglobin levels and larger parathyroid 

and ferritin concentrations compared to other African participants.  Black patients also more often 

received erythropoietin stimulating agent and intravenous iron therapy.  In an additional logistic 

regression model in which diuretic agent use was adjusted for, black population origin remained 

associated with low calcium levels (partial R=-0.192, p=0.04).  Black patients used erythropoietin 

stimulating agents and intravenous iron more often than their other African counterparts.          

 

3.3. Arterial function in black compared to other African patients with CKD. As given in Table 3, 

in age and sex adjusted analysis, pressure pulsatility as represented by central systolic and pulse 

pressure, peripheral pulse pressure and forward wave pressure were each larger in black com-

pared to other African CKD patients (model 1 in Table 3).  Upon additional adjustment for other 

established confounders or mediators, these disparities persisted except for as relates to the for-

ward wave pressure.  

 

3.4. Left ventricular structure and function in black compared to other African patients with chronic 

kidney disease.  Cardiac structure and function measures in black and other African CKD patients 

are shown in Table 4.  In age and sex adjusted analysis, black African patients experienced a 

larger E/e’ ratio and smaller e’.   

 



29 

 

 

3.5. Atherosclerosis and cardiovascular event rates in black compared to other African patients 

with chronic kidney disease. As given in Table 5, in age and sex adjusted analysis, carotid artery 

plaque prevalence was smaller in black compared to other African CKD patients.  The frequency 

of cardiovascular events and carotid intima-media thickness were also smaller in black compared 

to other African patients but none of these differences reached significance.  

 

3.6. Sensitivity analyses 

3.6.1. Baseline characteristics in black compared to other African pre-dialysis and dialysis pa-

tients.  Baseline demographic characteristics, lifestyle factors and anthropometric features did not 

differ significantly in black compared to other pre-dialysis as well as dialysis patients, as shown 

in Table 1. 

 

3.6.2. Traditional and non-traditional cardiovascular risk factors in black compared to other African 

pre-dialysis and dialysis patients.  Table 2 gives the traditional and non-traditional cardiovascular 

risk factors in black compared to other African pre-dialysis and dialysis patients.  Among pre-

dialysis patients, all black African patients were hypertensive as compared to 81.3% of their other 

African counterparts.  Black patients also had a larger systolic blood pressure and used diuretics, 

calcium channel blockers and alpha blockers more frequently.  Diabetes was more prevalent, 

haemoglobin A1c concentrations were larger and insulin was used more frequently in black com-

pared to other African patients.  The Framingham score was larger in black compared to other 

African patients.  With regard to non-traditional cardiovascular risk factors, the prevalence of high 

phosphate levels and parathyroid concentrations were larger and vitamin D levels were smaller 

in black compared to other African patients.   

   Among dialysis patients, beta blockers were used less frequently and heart rate was larger in 

black compared to other African patients.  With regard to non-traditional cardiovascular risk fac-

tors, the calcium x phosphate product was smaller in black compared to other African patients. 

 

3.6.3. Arterial function in black compared to other African pre-dialysis and dialysis patients.   

Arterial function in black compared to other African pre-dialysis and dialysis patients are shown 

in Table 3.  Among pre-dialysis patients, arterial wave reflection markers and, except for the for-

ward wave pressure, pressure pulsatility parameters were larger in black compared to other Afri-

can patients.  Except for as relates to augmentation index and reflection magnitude, each of these 

disparities remained significant in regression models in which, besides age and sex, other estab-

lished potential confounders or mediators were additionally adjusted for.   

   Among dialysis patients, arterial stiffness, wave reflection as well as pressure pulsatility 

measures did not differ significantly in black compared to other African patients. 

 



30 

 

 

3.6.4. Left ventricular structure and function in black compared to other African pre-dialysis and 

dialysis patients.  Table 4 gives the left ventricular structure and function in black compared to 

other African pre-dialysis and dialysis patients.  Among pre-dialysis patients, the E/e’ ratio was 

larger and the e’ was smaller in black compared to other African patients.  The association of 

black population origin with E/e’ ratio was unaltered upon additional adjustment for left ventricular 

hypertrophy (partial R=0.307, p=0.01) or hypertension (partial R=0.278, p=0.02) but was no 

longer present after diabetes was adjusted for (partial R=0.089, p=0.5). 

   Among dialysis patients, ejection fraction and stroke volume were larger in black compared to 

other African patients.  These associations were materially unaltered upon additional adjustment 

for haemoglobin levels (partial R=0.356, p=0.01 and partial R=0.276, p=0.07).  

 

3.6.5. Carotid atherosclerosis and cardiovascular event rates in black compared to other African 

pre-dialysis and dialysis patients.  Among pre-dialysis patients, carotid atherosclerosis extent and 

cardiovascular event rates did not differ significantly in black compared to other African patients, 

as shown in Table 5.   

   Among dialysis patients, black compared to other African study participants were less likely to 

have experienced any cardiovascular event. 

 

3.6.6. Differences among black and other African pre-dialysis and black and other African dialysis 

patients.  Differences among the 4 investigated groups that included black and other African pre-

dialysis and black and other African dialysis patients were confirmed upon inter-group compari-

sons.  This was the case for body weight as a baseline characteristic (Table1), a substantial 

proportion of the traditional and non-traditional cardiovascular risk factors and their treatment 

(Table 2), pressure pulsatility measures (Table 3), E/e’ (Table 4) and carotid artery plaque and 

intima-media thickness as well as ischemic heart disease (Table 5).         

 

3.7. Association of cardiovascular risk factors with atherosclerosis in black compared with other 

African chronic kidney disease.  The above mentioned results indicate that the cardiovascular 

disease risk factor burden was larger in black compared to other African chronic kidney disease 

patients.  Despite this disparity, the atherosclerosis extent as estimated by carotid plaque preva-

lence was smaller in black compared to other African patients.  In this regard, in interaction anal-

ysis, black population origin impacted the Framingham score – plaque prevalence relationship 

(OR (95% CI)=0.914 (0.862 to 0.970), interaction p=0.003).  As given in Table 6, stratified analysis 

revealed that traditional cardiovascular risk factors were not related to carotid plaque in black 

African patients whereas age, sex, dyslipidemia and the Framingham score were associated with 

atherosclerosis among other Africans.   The performance of the Framingham score in identifying 

black and other African chronic kidney disease patients with carotid plaque in ROC curve analysis 



31 

 

 

is shown in Figure 1.  The area under the curve (AUC) (95% CI) for the association of the Fram-

ingham score with plaque was 0.556 (0.375 to 0.737) (p=0.6) in black compared to 0.818 (0.714 

to 0.921) (p<0.0001) in other Africans.   

   

Non-traditional cardiovascular risk factors were not associated with carotid plaque (data not 

shown).   

 

4. Discussion 

To our knowledge, this is the first study that compared the traditional and non-traditional cardio-

vascular risk factor burden and subclinical and established CVD between black and other pre-

dialysis and dialysis African patients that were seen at the same centre.  The main novel findings 

produced by our investigation were as follows: (1) overall, black compared to other African CKD 

patients experienced a larger traditional cardiovascular risk factor burden as estimated by the 

Framingham score, more adverse non-traditional cardiovascular risk factors, impaired arterial and 

diastolic function but less frequent very high risk atherosclerosis as represented by carotid artery 

plaque presence and numerically though not significantly smaller cardiovascular event rates; (2) 

black compared to other African pre-dialysis patients experienced a larger traditional cardiovas-

cular risk factor burden, more adverse non-traditional cardiovascular risk factors, impaired arterial 

function and diastolic dysfunction but similar cardiovascular event rates, (3) among dialysis pa-

tients, black compared to other Africans had an overall similar traditional and non-traditional car-

diovascular risk factor burden, similar arterial and diastolic function but increased systolic function 

and reduced cardiovascular event rates, and (4) in ROC curve analysis among all participants, 

the Framingham score was strongly associated with carotid artery plaque in non-black but not 

black African CKD patients.     

   We found that, as applies to American black pre-dialysis CKD patients [9], the prevalence of 

hypertension and diabetes were larger in black compared to other African study participants 

(100% versus 81.3% and 68.4% versus 16.7%, respectively).  These differences translated into 

an overall increased major traditional cardiovascular risk factor burden.  Moreover, hypertension 

was more severe in black pre-dialysis CKD patients in that despite the use of more intensive 

antihypertensive therapy, their systolic blood pressure was larger than in their non-black counter-

parts.   Additionally, black African CKD patients had more frequent high phosphate levels, larger 

parathyroid hormone concentrations and lower vitamin D levels.  

   Severe arteriosclerosis is a characteristic vascular feature of CKD that results in impaired large 

artery function [21].  Increased arterial stiffness, wave reflection and pressure pulsatility in black 

persons were well documented in general population studies [22-24].  These central artery char-

acteristics contribute to heart failure, arrhythmias, sudden death, stroke and myocardial infarction 

in CKD [15,16].   In this study, black African pre-dialysis CKD patients experienced increased 



32 

 

 

wave reflection and pressure pulsatility.  Increased wave reflection contributes to enhanced pres-

sure pulsatility, which is strongly associated with CVD and disease progression in CKD patients 

[21,25-27].  Effective management of impaired central artery function associates with improved 

survival in CKD [21].  Our results therefore argue for comprehensive cardiovascular risk factor 

management among black African pre-dialysis CKD patients.    

   We measured E/A ratio and e’ as markers of left ventricular relaxation and E/e’ ratio as an index 

of left ventricular filling pressure.  The E/e’ ratio and e’ predict incident cardiac and cardiovascular 

events more strongly than the E/A ratio [28].  In this study, the E/e’ ratio was larger and the e’ 

smaller in black compared other African pre-dialysis CKD patients.  Hypertension and diabetes 

are both important determinants of diastolic dysfunction in the general population [29].  In multi-

variate analysis, we found that diabetes but not hypertension explained the association of black 

population origin with impaired diastolic function among pre-dialysis CKD patients.    In contrast 

to black African pre-dialysis patients, those on dialysis experienced similar cardiovascular risk 

factor profiles and arterial and left ventricular diastolic function to those recorded in other Africans.  

In this regard, Bellasi and colleagues [30] previously reported disparities in cardiovascular risk 

factors but similar arterial function in black compared to white American dialysis patients.  More 

noticeably, we found that cardiovascular event rates were significantly reduced by 78% (OR (95% 

CI)=0.22 (0.05 to 0.88)) in black compared to other African dialysis patients.  This is remarkably 

similar to what was reported among black American dialysis patients [9,30].  The likelihood of 

progressing from chronic kidney disease to end-stage renal disease is greater in African Ameri-

cans than whites.  However, once on dialysis, survival is better among African Americans com-

pared with whites.  In 2008, the mortality rate for patients on dialysis was 16% in African Ameri-

cans compared with 24% in whites.  This disparity may be due to black pre-dialysis CKD patients 

being sicker and therefore more likely to die, a phenomenon that would be expected to result in 

a selection of healthier persons that survive by the time they start dialysis [30].  This notion is 

supported by the DOPPS-1 report in which comorbidities, concurrent therapies and nutritional 

variables explained the reduced mortality rates in black compared to white dialysis patients [31].  

The authors concluded that minority group dialysis patients should not be expected to survive 

longer than their white counterparts with similar characteristics.  Interestingly, we also found that 

left ventricular function as estimated by the ejection fraction and stroke volume was more pre-

served in black compared to other African dialysis patients. 

   Besides the decreased cardiovascular event rates in black compared to other African dialysis 

patients, the most striking finding in this study was that, among all study participants, despite the 

more adverse cardiovascular risk factor profiles, impaired arterial function and left ventricular di-

astolic dysfunction, the atherosclerosis extent as represented by plaque presence was overall 

smaller in black compared to other African CKD patients (OR (95% CI)=0.38 (0.16 to 0.91)).  Ad-

ditionally, in black compared to other African pre-dialysis patients, despite more adverse cardio-

vascular risk factor profiles, cardiovascular event rates were not increased (OR (95% CI)=0.93 



33 

 

 

(0.0.22 to 3.87)).  These results suggest that cardiovascular risk factors may be less strongly 

associated with atherosclerotic CVD in black compared to other African CKD patients.  Indeed, 

black population origin impacted the Framingham score-plaque prevalence relationship (interac-

tion p=0.003).  In stratified analysis, the Framingham score was associated with carotid plaque in 

non-black but not black African CKD patients.  ROC curve analysis confirmed that the Framing-

ham score performed well in identifying very high risk atherosclerosis in non-black but not black 

African CKD patients (AUC (95% CI)= 0.818 (0.714 to 0.921) and AUC (95% CI)=0.556 (0.375 to 

0.921)), respectively.  We recently reported the same finding in black African patients with rheu-

matoid arthritis [32-34].  This may be attributable to a shorter lifetime exposure to cardiovascular 

risk factors as part of recent urbanization and an earlier epidemiological transition stage [32].  

More importantly, this finding indicates that cardiovascular risk equations such as the Framing-

ham score should not be relied upon in cardiovascular risk stratification among black African CKD 

patients [33,34].              

   The major limitations of the present study are the relatively small number of patients included, 

particularly in subgroups, its cross-sectional design and that all included participants were en-

rolled at a single centre.  Strengths are that we performed a detailed assessment of not only 

cardiovascular risk factor profiles but also large artery and cardiac function as well as subclinical 

atherosclerosis and that recorded data were compared between black and other African CKD 

patients. 

 

5. Conclusion 

Overall, black compared to other African CKD patients currently experience less frequent severe 

atherosclerosis despite an increased cardiovascular risk factor burden.  The Framingham score 

is useful in atherosclerotic CVD risk stratification among non-black but not black African CKD 

patients.  Among pre-dialysis patients, black compared to other Africans have more adverse tra-

ditional and non-traditional cardiovascular risk factor profiles, impaired arterial function and dias-

tolic dysfunction but similar cardiovascular event rates.  These disparities may originate in differ-

ences in epidemiological transition stages.  Black compared to other African dialysis patients have 

smaller cardiovascular event rates, which may represent a selection bias as previously docu-

mented in black Americans.   

 

Supplementary material 

Methods: Methods used in cardiovascular risk factor and arterial and left ventricular systolic and 

diastolic function recording. 

 

Figure legend 

FIGURE 1: Performance of the Framingham score in identifying non-black (A) and black (B) CKD 

patients with carotid artery plaque. 



34 

 

 

Data availability 

The data used in this study can be obtained from the corresponding author.  

 

Ethical approval 

The study was approved by the University of the Witwatersrand Human (Medical) research Ethics 

Committee (protocol number: M15-08-43) in Johannesburg, South Africa. 

 

Consent 

Each patient gave written informed consent. 

 

Conflicts of interest 

The authors declare no conflict of interest.  

 

Authors’ contributions 

Conception and design of the study: H-C.H., P.H.D. 

Arterial function evaluation and echocardiography: C.R.  

Analysis of the data: H-C.H., P.H.D. 

Interpretation of the data: H-C.H., P.H.D., C.R., G.R.N., A.J.W. 

Drafting of the manuscript: H-C.H., P.H.D. 

Revising the article: H-C.H., P.H.D., C.R., G.R.N., A.J.W. 

Providing intellectual content of critical importance to the work described: H-C.H., P.H.D., C.R., 

G.R.N., A.J.W. 

Final approval of the version to be published: H-C.H., P.H.D., C.R., G.R.N., A.J.W. 

 

Acknowledgement 

We thank Ms Noluntu Dlongolo for revising the manuscript. This study was supported by the 

South African National Research Foundation. 

 

  



35 

 

 

References 

[1]  GBD Chronic Kidney Disease Collaboration. “Global, regional, and national burden of 

chronic kidney disease, 1990-2017: a systematic analysis for the Global Burden of Disease 

Study: 2017,” Lancet, vol. 395, no. 10225, pp. 709-733, 2020. 

[2]     J.A. George, J-T. Brandenburg, J. Fabian et al., “Kidney damage and associated risk factors 

in rural and urban sub-Saharan Africa (AWI-Gen): a cross-sectional population study,” Lan-

cet Glob Health, vol. 7, no. 12, pp. e1632-1643, 2019. 

[3] M. Cozzolino, M. Mangano, A. Stucchi et al., “Cardiovascular disease in dialysis pa-

tients,”Nephrol Dial Tranplant, vol. 33, suppl_3, pp. iii28-iii34, 2018.  

[4] M.J. Sarnak, K. Amann, S Bangalore et al., “Chronic kidney disease and coronary artery 

disease: JACC State-of-the-Art Review,” J Am Coll Cardiol, vol. 74, no. 14, pp. 1823-1838, 

2019.  

[5]  “Sub-Saharan Africa Population 2020 (demographics, maps, graphics): World Population 

Review,” http://worldpopulationreview.com/continents/sub-saharan-africa-population/   

         (Accessed 13 September 2020)   

[6]  “World Bank Country and Lending Groups: Country Classification,” https://data-

helpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-

groups  (Accessed 13 September 2020)   

[7]  A. Solomon, L. Tsang, A.J. Woodiwiss, A.M.E. Millen, G.R. Norton, P.H. Dessein, Cardio-

vascular disease risk amongst African black patients with rheumatoid arthritis: the need for 

population specific stratification. Biomed Res Int 2014;2014, article ID 826095; 

http://dx.doi.org/10.1155/2014/826095.  

[8]  V. Pillay-van Wyk, W. Msemburi, R. Laubscher et al., “Mortality trends and differentials in 

South Africa from 1997 to 2012: second National Burden of Disease Study,” Lancet, vol. 4, 

no. 9, pp. e642-e653, 2016. 

[9] M.R. Carnethon, J. Pu, G. Howard et al., “Cardiovascular health in African Americans: A 

scientific statement from the American Heart Association,” Circulation, vol. 136, no. 21, pp. 

e393-e423, 2017.  

[10] V.L. Luyckx, A. Yip, L. Sofianou, G.S. Jhangri, T.F. Mueller, S. Naicker, “Cardiac function 

in an African dialysis population with a low prevalence of pre-existing cardiovascular dis-

ease,” Ren Fail, vol. 31, no. 3, pp. 211-220, 2009. 

[11] R. Freercks, C. Swanepoel, H. Carrara, S. Moosa, A. Lachman, B. Rayner, “Vascular cal-

cification in South African dialysis patients: ethnic variation, prevalence, detection and hae-

modynamic correlates,” Nephrology, vol. 17, no. 7, pp. 607-615, 2012.  

[12] R.A. Tamayo Isla, O.I. Ameh, D. Mapiye et al. “Baseline predictors of mortality among pre-

dominantly rural-dwelling end-stage renal disease patients on chronic dialysis therapies in 

Limpopo, South Africa,” PLoS One, vol. 11, no. 6, pp. e0156642, 2016. doi: 10.1371/jour-

nal.pone.0156642. eCollection 2016. 



36 

 

 

[13] O.C. Amira, S. Naicker, P. Manga et al., “Adiponectin and atherosclerosis risk factors in 

African hemodialysis patients: a population at low risk for atherosclerotic cardiovascular 

disease,” Hemodialysis Int, vol. 16, no. 1, pp. 59-68, 2012.  

[14]  S. Gunter, C. Robinson, A.J. Woodiwiss et al., “Arterial wave reflection and subclinical ath-

erosclerosis in rheumatoid arthritis,” Clin Exp Rheumatol, vol. 36, no. 3, pp. 412-420, 2018.  

[15]  M. Briet, P. Boutouyrie, S. Laurent, G.M. London, “Arterial stiffness and pulse pressure in 

CKD and ESRD,” Kidney Int, vol. 82, no. 4, pp. 388-400, 2012. 

[16] G.M. London, “Arterial stiffness in chronic kidney disease and end-stage renal disease,” 

Blood Purif, vol. 45, no. 1-3, pp. 154-158, 2018. 

[17] L. Mokotedi, S. Gunter, C. Robinson et al., “The Impact of different classification criteria 

sets on the estimated prevalence and associated risk factors of diastolic dysfunction in 

rheumatoid arthritis,” Int J Rheumatol 2017;2017:2323410.  

[18] A.S. Levey, L.A. Stevens, C.H. Schmid et al., “A new equation to estimate glomerular           

filtration rate,” Ann Intern Med, vol. 150, no. 9, pp.604-612, 2009.  

[19] R.B.Sr. D’Agostino, R.S. Vasan, M.J. Pencina et al., “General cardiovascular risk profile for 

use in primary care: the Framingham Heart Study,” Circulation, vol. 117, no. 6, pp. 743-753, 

2008.  

[20] P.J. Touboul, M.G. Hennerici, S. Meairs et al., “Mannheim carotid intima-media thickness 

consensus (2004-2006). An update on behalf of the Advisory Board of the 3rd and 4th Watch-

ing the Risk Symposium, 13th and 15th European Stroke Conferences, Mannheim, Ger-

many, 2004, and Brussels, Belgium, 2006,” Cerebrovasc Dis, vol. 23, no. 1, pp. 75-80, 

2007. 

[21] L. Zanoli, P. Lentini, M. Briet et al., “Arterial stiffness in the heart of CKD,” J Am Soc Nephrol, 

vol. 30, no. 6, pp. 918-928, 2019.  

[22] M. Maritz, C.M.T. Fourie, J.M. van Rooyen, I.M. Kruger, A.E. Schutte, “A health profile          

associated with excessive alcohol use independently predicts aortic stiffness over 10 years 

in black South Africans,” J Hypertens, vol. 35, no. 11, pp. 2268-2275, 2017. 

[23] J.A. Chirinos, J.G. Kips, M.J. Roman et al., “Ethnic differences in arterial wave reflections 

and normative equations for augmentation index,” Hypertension vol. 57, no. 6, pp. 1108-

1116, 2011. 

[24] T. Coutinho, S.T. Turner, T.H. Mosley, I.J. Kullo, “Biomarkers associated with pulse pres-

sure in African-Americans and non-hispanic whites,” Am J Hypertens, vol. 25, no. 2, pp. 

145-151, 2012.  

[25] R.R. Townsend, J.A. Chirinos, A. Parsa A et al. “Central pulse pressure in chronic kidney 

disease: A CRIC ancillary study,” Hypertension, vol. 56, no. 3, pp. 518-524, 2010.  

[26] A.A. House, C. Wanner, M.J. Sarnak et al., “Heart failure in chronic kidney disease: conclu-

sions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Confer-

ence,” Kidney Int, vol. 95, no. 6, pp. 1304-1317, 2019.  

https://www.ncbi.nlm.nih.gov/pubmed/29185969
https://www.ncbi.nlm.nih.gov/pubmed/29185969
https://www.ncbi.nlm.nih.gov/pubmed/29348754
https://www.ncbi.nlm.nih.gov/pubmed/29348754
https://www.ncbi.nlm.nih.gov/pubmed/29348754


37 

 

 

[27] L. Di Lullo, A. Gorini, D. Russo, A. Santoboni, C. Ronco, “Left ventricular hypertrophy in 

chronic kidney disease patients: from pathophysiology to treatment,” Cardiorenal Med, vol. 

5, no. 4, pp. 254-266, 2015.  

[28] T. Kuznetsova, L. Thijs, J. Knez, S.L. Herbot, Z Zhang, J.A. Staessen, “Prognostic value of 

left ventricular diastolic dysfunction in a general population,” J Am Heart Assoc, vol. 3, no. 

3, pp. e000789, 2014. doi: 10.1161/JAHA.114.000789. 

[29] C. Russo, Z. Jin, S. Homma et al., “Effect of diabetes and hypertension on left ventricular 

diastolic function in a high-risk population without evidence of heart disease,” Eur J Heart 

Fail, vol. 12, no 5, pp. 454-461, 2010. 

[30] A. Bellasi A, Veledar E, Ferramosca E, Ratti C, Block G, Raggi P. “Markers of vascular 

disease do not differ in black and white hemodialysis patients despite different risk profile,” 

Atherosclerosis, vol. 197, no. 1, pp242-249, 2008.  

 [31] B.M. Robinson, M.M. Joffe, R.L. Pisoni, F.K. Port, H.I. Feldman, “Revisiting survival differ-

ences by race and ethnicity among hemodialysis patients: the dialysis outcomes and prac-

tice patterns study,” J Am Soc Nephrol, vol. 17, no. 10, pp. 2910-2918, 2006.    

 [32] A. Solomon, A.J. Woodiwiss, A.T. Abdool-Carrim, B.A. Stevens, G.R. Norton, P.H. Dessein, 

“The carotid artery atherosclerosis burden and its relation to cardiovascular risk factors in 

black and white Africans with established rheumatoid arthritis: a cross-sectional study,” J 

Rheumatol, vol. 39, no. 9, pp. 1798-1806, 2012. 

[33] P.H. Dessein, A. Corrales, R. Lopez-Mejias et al., “The Framingham Score and the Sys-

tematic Coronary Risk Evaluation at Low Cutoff Values Are Useful Surrogate Markers of 

High-risk Subclinical Atherosclerosis in patients with Rheumatoid Arthritis,” J Rheumatol, 

vol. 43, no. 3, pp. 486-494, 2016.   

[34] A. Solomon, Stanwix A.E., S. Castaneda et al., “Points to consider in cardiovascular          

disease risk management among patients with rheumatoid arthritis living in South Africa, 

an unequal middle income country,” BMC Rheumatol, vol. 16, no. 4, pp. 42. doi: 

10.1186/s41927-020-00139-2. eCollection 2020.PMID: 32550295. 

 

 

 

 



38 

 

 

TABLE 1: Baseline characteristics in black compared to other African chronic kidney disease patients overall, and in sensitivity analysis among pre-dialysis and dialysis patients 

____________________________________________________________________________________________________________________________________________________________ 

                           Chronic kidney disease patients 

                          ___________________________________________________________________________________________________________________________________________ 

                          All patients                                                                     Pre-dialysis patients                                                 Dialysis patients   Inter-group 

                                   comparisona 

                        _________________________________             _________________________________          _________________________________ ___________

             

                          Black African Other African  p                    Black African      Other African    p               Black African   Other African   p p              

Characteristic     (n=46)            (n=69)                                    (n=19)                  (n=48)                                          (n=27)                (n=21)                                  

____________________________________________________________________________________________________________________________________________________________ 

Demographics 

  Age (years)  54.3 (14.6) 59.9 (13.3) 0.03 55.7 (14.2) 60.3 (13.6) 0.2 53.3 (15.0) 59.1 (13.0) 0.2 0.1   

  Female sex 18 (39.1) 25 (36.2) 1.0 6 (31.6) 15 (31.3) 0.8 12 (44.4) 10 (47.6) 0.8 0.5  

CKD stage 

  Pre-dialysis 19 (41.3) 48 (69.6) 0.005 - - - - - - -  

  Dialysis 27 (58.7) 21 (30.4) 0.005 - - - - - - -  

Lifestyle 

  Current smoker 2 (4.4) 1 (1.5) 0.4 2 (10.5) 1 (2.1) 0.2 0 (0) 0 (0) - - 

  Ex-smoker 2 (4.4) 6 (8.7) 0.3 0 (0) 4 (8.3) 1.0 2 (7.4) 2 (9.5) 0.5 0.6 

  Alcohol 1 (2.2) 1 (1.5) 0.8 0 (0) 1 (2.1) 1.0 1 (3.7) 0 (0)   - 0.7 

  Exercise 19 (41.3) 23 (33.3) 0.4 6 (31.6) 11 (22.9) 0.5 13 (48.2) 12 (57.1) 0.4 0.06  

Anthropometry 

  Weight (kg) 74.5 (13.0) 81.1 (16.8) 0.02 76.3 (13.6) 83.1 (16.5) 0.07 73.1 (12.7) 76.7 (17.1) 0.5 0.04 

  Height (cm) 167.8 (9.8) 170.5 (10.4) 0.09 170.0 (7.9) 171.3 (9.7)  0.5 166.2 (10.7) 168.6 (11.3) 0.2 0.2 

  Waist (cm) 96.5 (13.1) 102.0 (15.3) 0.1 97.1 (10.4) 101.4 (14.8) 0.3 96.1 (14.9) 103.3 (16.7) 0.3 0.2 



39 

 

 

  Neck (cm) 38.6 (3.8) 39.7 (4.5) 0.2 38.7 (4.7) 39.5 (5.5) 0.7 38.4 (3.1) 40.1 (5.1) 0.3 0.5 

  BMI (kg/m2) 26.6 (5.3) 27.9 (5.6) 0.2 26.5 (5.2) 28.3 (5.5) 0.2 26.7 (5.5) 27.0 (5.8) 0.8 0.4 

  Waist-hip ratio 0.98 (0.11) 0.97 (0.10) 0.2 0.97 (0.14) 0.97 (0.11) 0.6 0.99 (0.09) 0.97 (0.09) 0.3 0.8 

  Waist-height ratio 0.58 (0.09) 0.59 (0.09) 0.5 0.57 (0.07) 0.59 (0.09) 0.5 0.58 (0.11) 0.61 (0.11) 0.7 0.5 

____________________________________________________________________________________________________________________________________________________________ 

Data are expressed as mean (SD) or number (percent) and were analysed in age and sex adjusted linear of logistic regression models as appropriate.  aFor differences among black and  
other African pre-dialysis patients and black and other African dialysis patients.  Significant differences are shown in bold.  Abbreviations: CKD: chronic kidney disease; BMI: body mass index. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



40 

 

 

TABLE 2: Traditional and non-traditional cardiovascular risk factors and their treatment in black compared to other African chronic kidney disease patients overall, and in sensitivity analysis among pre-dialysis and dialysis patients  

__________________________________________________________________________________________________________________________________________________________________________________________ 

                                          Chronic kidney disease patients 

                                      __________________________________________________________________________________________________________________________________________________________ 

                                      All patients                                                                                      Pre-dialysis patients                                                        Dialysis patients                                                                         Inter-group 

                                                                                                                                                                                                                                                                                                                                                                            comparisonb 

                                      ______________________________________________   ______________________________________________   ______________________________________________  __________ 

                                     Black African           Other African          Modela                   Black African           Other African        Modela        Black African        Other African        Modela                    p 

Characteristic            (n=46)                      (n=69)                                                        (n=19)                      (n=48)                                              (n=27)                     (n=21) 

__________________________________________________________________________________________________________________________________________________________________________________________ 

Traditional CV risk factors and  

their treatment    

 Categorical variables    OR (95% CI)   OR (95% CI)   OR (95% CI) 

  Hypertension 45 (97.8) 59 (85.5) 9.05 (1.08-75.59) 19 (100) 39 (81.3)           -  26 (96.3) 20 (95.2) 1.51 (0.08-28.03) 0.04 

  Dyslipidemia 30 (71.4) 53 (85.5) 0.41 (0.15-1.12)  12 (70.6) 41 (91.1) 0.25 (0.06-1.10) 18 (72.0) 12 (70.6) 0.89 (0.21-3.72) 0.1 

  Diabetes 21 (45.7) 19 (27.5) 3.10 (1.30-7.40) 13 (68.4) 8 (16.7) 13.28 (5.51-50.27) 8 (29.6) 11 (52.4) 0.51 (0.13-2.01) <0.0001 

  Antihypertensive treatment 45 (97.8) 59 (85.5) 9.05 (1.08-75.59) 19 (100) 39 (81.3)                 -  26 (96.3) 20 (95.2) 1.51 (0.08-28.03) 0.04 

   ACEI/ARB 36 (81.8) 54 (79.4) 1.07 (0.40-2.87) 15 (83.3) 38 (79.2) 1.41 (0.33-6.03) 21 (80.1) 16 (80.0) 0.70 (0.14-3.47) 1.0 

   Beta blocker 21 (47.7) 30 (44.4) 1.22 (0.51-2.45) 9 (50.0) 16 (33.3) 2.31 (0.72-7.26) 12 (46.2) 14 (70.0) 0.20 (0.05-0.88) 0.04 

   Diuretic  20 (44.4) 19 (27.5) 2.56 (1.11-5.94) 11 (61.1) 13 (27.1) 5.52 (1.59-19.17) 9 (33.3) 6 (28.6) 1.34 (0.36-5.05) 0.07 

   Calcium channel blocker 26 (57.8) 23 (33.8) 2.70 (1.22-6.00) 10 (52.6) 11 (22.9) 3.69 (1.18-11.50) 16 (61.5) 12 (60.0) 1.14 (0.33-3.91) 0.002 

   Alpha blocker 11 (25.6) 13 (19.1) 1.73 (0.67-4.48) 7 (38.9) 8 (16.7) 5.48 (1.31-22.87) 4 (16.0) 5 (25.0) 0.53 (0.11-2.45) 0.2 

  Lipid lowering therapy  21 (47.7) 51 (75.0) 0.33 (0.14-0.75) 9 (50.0) 37 (77.1) 0.32 (0.09-1.08) 12 (46.2) 14 (70.0) 0.31 (0.08-1.12) 0.03 

   Statin  21 (47.7) 51 (75.0) 0.33 (0.14-0.75) 9 (50.0) 37 (77.1) 0.32 (0.09-1.08) 12 (46.2) 14 (70.0) 0.31 (0.08-1.12) 0.03 

   Ezetimibe  4 (9.1) 7 (10.4) 0.96 (0.26-3.61) 2 (11.1) 5 (10.4) 1.26 (0.21-7.59) 2 (7.7) 2 (10.5) 0.72 (0.09-5.95) 1.0 

  Insulin 14 (31.1) 12 (17.4) 2.60 (1.03-6.61) 9 (47.4) 5 (10.4) 7.67 (2.07-28.41) 5 (19.2) 7 (33.3) 0.67 (0.16-2.89) 0.007 

  OGLA 8 (17.8) 6 (8.7) 3.37 (0.98-11.61) 4 (21.1) 4 (8.3) 3.26 (0.64-16.56) 4 (15.4) 2 (9.5) 3.24 (0.40-26.49) 0.5  

Continuous variables   Partial R   p    Partial R  p    Partial R  p 

 Systolic blood pressure 148 (24) 137 (18) 0.271          0.004 145 (25) 135 (16) 0.265        0.03 150 (24) 141 (21) 0.185       0.2 0.02  

 Diastolic blood pressure (mmHg) 84 (13) 82 (10) 0.032  0.7 80 (10) 82 (8) -0.150        0.2 86 (13) 82 (15) 0.083       0.6 0.2 

 Mean blood pressure (mmHg) 105 (14) 100 (11) 0.175 0.06 101 (13) 100 (9) 0.093       0.5  107 (14) 102 (14) 0.155       0.3 0.07 

 Total cholesterol (mmol/l) 4.3 (1.2) 4.2 (1.2) 0.005 1.0 4.2 (1.2) 4.2 (1.1) -0.006       1.0 4.3 (1.2) 4.3 (1.3) -0.001     1.0 1.0 

 LDL-cholesterol (mmol/l) 2.3 (0.9) 2.4 (1.0) -0.047 0.6 2.2 (0.7) 2.3 (0.9) -0.094        0.5 2.4 (1.0) 2.5 (1.1) -0.038      0.8 0.8 



41 

 

 

 HDL cholesterol (mmol/l 1.14 (0.43) 1.14 (0.42) -0.007 0.9 1.03 (0.37) 1.12 (0.42) -0.087 0.5 1.22 (0.45) 1.18 (0.41) 0.058  0.7 0.5 

 Non-HDL cholesterol (mmol/l) 3.1 (1.1) 3.1 (1.0) -0.017  0.8 3.2 (1.3) 3.1 (1.0) 0.025 0.9 3.1 (1.1) 3.3 (1.1) -0.086 0.6 0.9 

 Triglycerides (mmol/l) 1.3 (0.9-1.8) 1.5 (1.1-2.1) -0.080 0.4 1.5 (1.1-1.9) 1.4 (1.1-2.2) 0.033 0.8 1.4 (0.8-1.8) 1.6 (1.2-1.8) -0.127 0.4 0.4 

 Cholesterol-HDL cholesterol ratio     3.8 (2.7-5.2) 3.8 (3.1-4.8) -0.022  0.6 3.7 (3.1-5.4) 3.8 (3.1-4.9) 0.073 0.6 3.8 (2.6-5.1) 3.9 (3.1-4.8) -0.122 0.4 0.9 

 Triglycerides-HDL cholesterol ratio   1.2 (0.7-2.0) 1.4 (0.9-2.1) -0.050 0.8 1.7 (1.2-2.3) 1.5 (1.0-2.1) 0.102 0.4 1.0 (0.6-2.0) 1.3 (0.9-2.4) -0.111 0.5 0.2 

 Haemoglobin A1c (%) 5.6 (5.1-7.0) 5.5 (5.2-6.3) 0.106  0.3 6.9 (5.7-8.3) 5.6 (5.3-6.2) 0.429  <0.0001 5.4 (4.9-5.7) 5.4 (4.9-7.3) -0.094 0.5 0.004 

 Framingham score 23.4 (21.7) 22.6 (16.5) 0.223 0.01 27.9 (23.3) 21.8 (16.3) 0.327  0.008 20.2 (20.2) 24.3 (14.0) 0.046  0.8 0.5 

 Heart rate (beats per minute) 79 (14) 72 (14) 0.196 0.04 76 (15) 72 (15) 0.067  0.6 81 (13) 72 (12) 0.350  0.02 0.05 

 Antihypertensives (n) 2.5 (1.1) 2.0 (1.2) 0.215 0.02 2.8 (1.2) 2.0 (1.2) 0.388  0.001 2.3 (1.1) 2.5 (1.1) -0.149 0.3 0.008 

Non-traditional CV risk factors 

and their treatment 

 Categorical variables   OR (95% CI)    OR (95% CI)    OR (95% CI) 

  High phosphate 34 (77.3) 31 (44.9) 3.99 (1.67-9.54) 9 (52.9) 12 (25.0) 3.31 (1.01-10.89) 25 (92.6) 19 (90.5) 1.20 (0.15-9.92) <0.0001 

  Phosphate binder 22 (52.4) 25 (37.3) 1.71 (0.77-3.81) 4 (23.5) 8 (16.7) 1.55 (0.39-6.10) 18 (72.0) 17 (89.5) 0.27 (0.05-1.52) <0.0001 

  Vitamin D replacement 27 (67.5) 31 (47.7) 2.27 (0.98-5.28) 9 (50.0) 14 (31.1) 1.96 (0.62-6.17) 18 (81.8) 17 (85.0) 1.06 (0.19-6.03) <0.0001 

  Erythropoietin stimulating agent       29 (63.0) 25 (36.2) 3.00 (1.36-6.62) 6 (31.6) 5 (10.4) 3.69 (0.95-14.35) 23 (85.2) 20 (95.2) 0.34 (0.03-3.81) <0.0001 

  Intravenous iron 26 (56.5) 24 (34.8) 2.50 (1.14-5.48) 5 (26.3) 5 (10.4) 3.07 (0.75-12.59) 21 (77.8) 19 (90.5) 0.44 (0.08-2.61) <0.0001 

  Sevelamer 1 (2.0) 0 (0)          -  0 (0) 0 (0)                 -  1 (4.0) 0 (0)                 - 

 Continuous variables   Partial R  p    Partial R  p    Partial R  p 

  Dialysis duration (months) 30 (12-48) 36 (12-48) -0.090  0.6    -     -       -    - 30 (12-36) 36 (12-42) -0.138 0.4 - 

  Phosphate (mmol/l) 1.2 (0.8-1.6) 1.2 (1.0-1.6) -0.022  0.8 1.3 (0.9-1.6) 1.2 (0.9-1.4) 0.076 0.6 1.3 (0.8-1.7) 1.6 (1.1-2.1) -0.268 0.07 0.04 

  Calcium (mmol/l) 2.3 (2.1-2.4) 2.3 (2.2-2.4) -0.205 0.03 2.2 (2.1-2.4) 2.3 (2.2-2.4) -0.120 0.4 2.2 (2.0-2.4) 2.3 (2.2-2.4) -0.254 0.09 0.2 

  Calcium x phosphate  2.5 (1.8-3.8) 2.8 (2.2-3.7) -0.100 0.3 3.0 (2.0-3.6) 2.9 (2.2-3.1) 0.010 0.9 2.9 (1.8-3.8) 3.7 (2.6-4.6) -0.364 0.01 0.02 

  Intact PTH (pg/ml) 287 (141-531) 84 (64-334) 0.270 0.007 232 (92-370) 70.0 (50-111) 0.426 0.001 369 (172-686) 621 (197-801) -0.149 0.4 <0.0001 

  Haemoglobin (g/dl) 10.7 (9.6 -12.5) 12.6 (10.7-14.2) -0.202  0.03 11.5 (10.0-14.9) 13.5 (10.6-15.1) -0.072 0.6 10.6 (9.5-11.9) 11.0 (10.7-12.5) -0.199 0.2 0.001 

  Transferrin saturation (%) 22.0 (17.4-29.0) 22.9 (17.5-30.2) -0.037 0.7 24.1 (13.7-30.6) 21.0 (17.0-29.0) -0.144  0.3 22.6 (20.0-30.0) 25.0 (18.5-28.9) -0.013 0.9 0.3 

  Ferritin (ng/ml) 325 (113-573) 166 (51-365) 0.203 0.03 191 (113-490) 115 (38-224) 0.198 0.1 364 (124-725) 361 (168-609) 0.029 0.8 0.001 

  Albumin (g/l) 36.8 (8.0) 38.6 (5.5) -0.157  0.1 35.3 (9.2) 38.9 (5.4) -0.235  0.06 37.8 (7.0) 38.0 (5.9) -0.025 0.9 0.2 

  Vitamin D (nmol/l) 19.0 (8.8) 19.8 (9.3) -0.050 0.6 15.5 (5.4) 20.9 (9.9) -0.269 0.03 21.4 (9.9) 17.4 (7.2) 0.204 0.2 0.07 

  Uric acid (mmol/l) 0.31 (0.24-0.40) 0.37 (0.28-0.46) -0.184 0.06 0.38 (0.32-0.48) 0.42 (0.35-50.8) -0.157 0.2 0.28 (0.21-0.32) 0.28 (0.17-0.34) 0.029 0.9 <0.0001 

  Hs-C-reactive protein (mg/l) 8.2 (2.6-28.1) 6.0 (2.0-15.5) 0.073 0.5 4.7 (1.3-22.3) 4.1 (2.0-15.1) -0.050 0.7 12.3 (4.1-32.1) 7.7 (1.9-25.4) 0.181  0.2 0.4 

__________________________________________________________________________________________________________________________________________________________________________________________ 

Data are expressed as mean (SD), median (interquartile range) or number (percentage). aAdjusted for age and sex; bfor differences among black and other African pre-dialysis and black and other African dialysis patients.   



42 

 

 

Significant associations are shown in bold.  Abbreviations: CV: cardiovascular; ACEI: angiotensin converting enzyme inhibitor; ARB: angiotensin receptor blocker; OGLA: oral glucose lowering agents; LDL: low density lipoprotein;  
HDL: high density lipoprotein; PTH: intact parathyroid hormone; hs: high sensitivity. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



43 

 

 

TABLE 3: Arterial function in black compared to other African chronic kidney disease patients overall, and in sensitivity analysis among pre-dialysis and dialysis patients 

____________________________________________________________________________________________________________________________________________________________________________________________________ 

                            Chronic kidney disease patients 

                            ______________________________________________________________________________________________________________________________________________________________________________________ 

                            All patients                                                                                                       Pre-dialysis patients                                                         Dialysis patients      Inter-group 

                    comparisona 

                            ______________________________________________________    ______________________________________________________     ____________________________________________________ ___________ 

Arterial               Black African     Other African   Model 1a         Model 2b             Black African     Other African  Model 1a Model 2b          Black African   Other African  Model 1a         Model 2b               p 

function               (n=46)                   (n=69)                                                    (n=19)                 (n=48)                                                                                 (n=27)     (n=21)      

____________________________________________________________________________________________________________________________________________________________________________________________________ 

                                                                                           Partial   p           Partial  p                                                                       Partial   p           Partial   p                                                                            Partial   p           Partial   p 

                                                                                             R                         R                                                                                      R                         R                                                                                           R                         R                                            

PWV (m/s) 12.0 (3.8) 11.4 (4.4) 0.126 0.2 0.031 0.8 12.2 (3.5) 10.9 (3.7) 0.230 0.09 0.210  0.1 11.9 (4.1) 12.2 (5.5) 0.016 0.9 -0.143 0.4 0.6 

Aix (%) 66.6 (16.4) 66.8 (16.7) 0.089 0.4 0.030 0.8 73.3 (18.0) 64.5 (15.7) 0.299 0.03 0.229 0.1 62.2 (14.0) 71.8 (18.2) -0.170 0.3 -0.223 0.2 0.08 

RWP (mmHg)    25.0 (13.8-29.0) 20.5 (15.0-25.0) 0.100 0.2 0.152 0.1 24.0 (14.0-29.0) 19.5 (13.5-23.0) 0.280 0.04 0.307  0.03 25.0 (13.0-29.0) 21.5 (15.8-30.5) 0.126 0.4 0.037 0.8 0.1 

Rm (%) 67.4 (16.8) 67.2 (16.6) 0.099 0.3 0.047 0.7 74.3 (18.4) 64.9 (15.6) 0.309 0.02 0.250 0.09 62.9 (14.4) 72.3 (18.2) -0.159 0.3 -0.213 0.2 0.08 

CSBP (mmHg) 136 (22) 127 (17) 0.265  0.006 0.225 0.02 132 (21) 125 (15) 0.251 0.04 0.361 0.005 139 (22) 132 (22) 0.208 0.2 0.074 0.7 0.03 

CPP (mmHg) 50 (19) 43 (13) 0.292 0.002 0.247 0.01 51 (20) 41 (11) 0.367 0.003 0.390 0.002 50 (18) 48 (17) 0.142 0.4 0.056 0.7 0.04 

PPP (mmHg) 64 (22) 54 (16) 0.283 0.002 0.240 0.01 65 (23) 53 (13) 0.358 0.003 0.405 0.001 64 (22) 59 (21) 0.148 0.3 0.113 0.5 0.03 

FWP (mmHg) 35.2 (12.1) 31.1 (9.5) 0.204 0.04 0.159 0.1 32.5 (12.9) 30.4 (19.2) 0.097 0.5 0.151 0.3 37.0 (11.5) 32.6 (10.2) 0.251 0.1 0.209 0.2 0.1 

____________________________________________________________________________________________________________________________________________________________________________________________________ 

Descriptive results are expressed as mean (SD) or median (interquartile range).  Significant associations are show in bold.  aAdjusted for age and sex; badditionally adjusted for height, weight, heart rate and mean arterial pressure; cfor differ-
ences among black and other African pre-dialysis and black and other African dialysis patients.  Abbreviations: PWV: pulse wave velocity; Aix: augmentation index; RWP: reflected wave pressure; Rm: reflection magnitude; CSBP: centralsystolic 
blood pressure; CPP: central pulse pressure; PPP: peripheral pulse pressure; FWP: forward wave pressure.   
 
 
 
 
 
 
 
 
 
 
 
 
 
 



44 

 

 

TABLE 4: Left ventricular structure and function in black compared to other African chronic kidney disease patients overall, and in sensitivity analysis among pre-dialysis and dialysis patients  

_____________________________________________________________________________________________________________________________________________________________________________________ 

 

                                          Chronic kidney disease patients 

                                      _____________________________________________________________________________________________________________________________________________________ 

                                      All patients                                                                              Pre-dialysis patients                                                      Dialysis patients                                                                         Inter-group 

                                                                                                                                                                                                                                                                                                                                                                           comparisonb 

                                      ________________________________________   ________________________________________   ________________________________________  __________ 

                                     Black African    Other African Modela                   Black African  Other African   Modela     Black African    Other African   Modela     p 

Characteristic            (n=46)              (n=69)                                                        (n=19)              (n=48)                                              (n=27)             (n=21) 

_____________________________________________________________________________________________________________________________________________________________________________________ 

Categorical variables   OR (95% CI)   OR (95% CI)   OR (95% CI) 

  LV hypertrophy  21 (45.7) 27 (39.1) 1.50 (0.65 to 3.48) 6 (31.6) 18 (37.5) 0.77 (0.22 to 2.75) 15 (55.6) 9(42.9) 1.78 (0.55 to 6.27) 0.3 

  LV concentric remodelling  15 (33.3) 18 (26.9) 1.36 (0.59 to 3.15) 7 (36.8) 13 (27.7) 1.53 (0.49 to 4.78) 8 (30.8) 5 (25.0) 1.35 (0.35 to 5.14) 0.9 

  Reduced ejection fraction 5 (11.1) 17 (25.3) 0.41 (0.14 to 1.26) 2 (10.5) 11 (23.9) 0.46 (0.07 to 2.62) 3 (11.5) 6 (30.0) 0.32 (0.07 to 1.52) 0.3 

Continuous variables    Partial R  p   Partial R  p   Partial R p 

  LV mass index (g/m2) 104.1 (50.9) 91.4 (38.6) 0.147         0.1 99.2 (38.2) 88.6 (38.2) 0.132         0.3 107.6 (58.8) 97.9 (39.6) 0.084    0.06 0.3 

  LV relative wall thickness 0.39 (0.12) 0.38 (0.12) 0.023         0.8 0.42 (0.13) 0.38 (0.10) 0.132 0.3 0.37 (0.10) 0.39 (0.15) -0.058 0.7 0.6 

  Ejection fraction (%) 65.9 (13.7) 61.2 (14.6) 0.159         0.1 65.7 (15.7) 63.3 (13.8) 0.071 0.6 66.1 (12.3) 56.4 (15.8) 0.356 0.01 0.1 

  Stroke volume (ml/beat) 74.1 (24.7) 66.9 (24.2) 0.150         0.1 67.6 (22.3) 69.2 (24.3) -0.025 0.9 78.9 (25.7) 61.6 (23.6) 0.315 0.03 0.1 

  E/A 1.10 (0.48) 1.01 (0.36) 0.053         0.6 1.19 (0.56) 1.06 (0.38) 0.093 0.5 1.04 (0.41) 0.91 (0.27) 0.135 0.4 0.2 

  E/e’ 11.5 (5.1) 9.7 (4.0) 0.254         0.007 11.3 (5.4) 8.8 (3.6) 0.307 0.01 11.7 (4.1) 11.7 (5.0) 0.070 0.7 0.02 

  Average e’ (cm/s) 8.2 (2.6) 8.7 (2.7) -0.201        0.03 8.4 (2.4) 9.1 (2.7) -0.246 0.