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CARDIOVASCULAR JOURNAL OF AFRICA • Volume 26, No 3, May/June 2015
126
AFRICA
Methods
From 30 April to 24 August 2012, all consecutively appearing
patients with known CKD seen in tertiary care (University of
Kinshasa Hospital) and those with diabetes or hypertension
regularly followed in secondary care (General Hospital of
Kinshasa and Saint Joseph Hospital) were asked to participate in
this cross-sectional study. Inclusion criteria were: age
≥
18 years,
antihypertensive treatment for at least three months, and written
informed consent.
The sample was a convenient one. Self-reported alcohol use,
smoking habits, personal and family history of hypertension or
diabetes, family history of sickle cell anaemia (SCA) and measure
of adiposity [body mass index (BMI) and waist circumference
(WC)] were obtained for all patients. Excessive alcohol intake
was defined as regular intake of two or more glasses per day of
beer or equivalent for at least one year, knowing that one glass of
beer contains 10 g of alcohol.
14
Smoking was defined as regular
consumption of at least one cigarette per day for more than
five years or having stopped smoking for less than five years.
15
Overweight and obesity were defined as BMI
≥
25 and
≥
30 kg/
m², respectively.
16
Central obesity was defined as WC
>
94 cm in
men
>
80 cm in women.
17
Seated blood pressure (BP) was measured using an electronic
device Omron M3 on the left arm at the level of the heart
after five minutes’ rest. Three consecutive BP measurements at
two-minute intervals were made and the mean of the last two
readings was used for analysis. Pulse pressure (PP) was calculated
as systolic blood pressure (SBP) minus diastolic blood pressure
(DBP) and was considered increased when
>
60 mmHg.
18
Hypertension was defined as BP
≥
140/90 mmHg or current use
of antihypertensive, whatever the level of BP.
18
Heart rate was
counted for a full minute.
A 12-hour overnight fasting blood sample was collected
from each patient for measurement of haemoglobin (Hb), total
cholesterol (TC) and its sub-fractions [low-density lipoprotein
cholesterol (LDL-C), high-density lipoprotein cholesterol
(HDL-C)], triglycerides (TG), glucose, uric acid and creatinine
levels at the Laboratory of the National AIDS Control Program
(NACP). LDL-C was calculated using the Friedewald formula.
19
The metabolic syndrome (MetS) was defined according to 2009
consensus criteria.
17
Diabetes was defined as plasma glucose
>
7
mmol/l or current use of antidiabetic drugs, whatever the level
of blood glucose.
20
A uric acid level
>
416 µmol/l was defined as
hyperuricaemia.
21
Serum creatinine concentrations were analysed based on a
modified Jaffe reaction (picric acid) using an automated device
(Dimension
®
XPand
®
Plus, Siemens). Estimated glomerular
filtration rate (eGFR) was calculated using the modification
of diet in renal disease (MDRD) equation,
22
based on serum
creatinine levels calibrated as described elsewhere.
23
The Combur
9 test (Roche, France) was used on morning spot urine collections
to determine semi-quantitative proteinuria; positive proteinuria
was defined as Combur 9 test
≥
1+.
24
According to KDOQI,
25
reduced kidney function and CKD were defined as GFR
<
90
ml/min/1.73 m² and
<
60 ml/min/1.73 m², respectively.
Haemoglobin types were determined using isoelectro-
focalisation electrophoresis (Capillaris, France) at the laboratory
of Monkole Hospital in Kinshasa. This analytical method
results in elution of haemoglobin variants and determines the
proportion of these variants relative to the total haemoglobin
concentration.
26
It has been shown to be a reliable determinant
of the HbS concentration and allows for the determination of
HbS and HbC traits.
26
Statistical analysis
Data are expressed as mean
±
standard deviation (SD) or relative
frequency in percentages. Chi-square and Student’s
t
-tests
were used for comparing categorical and normally distributed
continuous variables, respectively. The Mann–Whitney test was
used for non-normally distributed continuous variables. Multiple
logistic regression analysis and the likelihood ratio method
were performed with CKD as the dependent variable for the
assessment of the strength and independence of association with
CKD risk factors, among them, SCT alone or in interaction with
hypertension or diabetes. Adjusted odds ratio (aOR) and their
95% confidence intervals (CI) were calculated for each variable.
All statistical analyses were performed with SPSS for Windows,
version 12.0 at the Division of Epidemiology and Biostatistics of
Kinshasa Public Health School, University of Kinshasa.
Results
A total of 359 patients with reduced kidney function (198 women
and 161 men) were recruited in this study. Clinical characteristics
of the study population as a whole and by renal functional status
are given in Table 1. Their mean age was 56
±
15 years; they had
on average a BMI of 26
±
5 kg/m², WC of 90
±
14 cm, SBP of
143
±
26 mmHg and DBP of 83
±
13 mmHg. A family history
of sickle cell disease (FH-SCD) was present in 6% of patients.
Average levels of TC, HDL-C, TG, glucose, uric acid, Hb and
eGFR were 5.32
±
2.22 mmol/l, 1.49
±
0.59 mmol/l, 1.31
±
0.65
mmol/l, 8.16
±
4.94 mmol/l, 360
±
159 mmol/l, 11
±
2.40 g/dl and
59
±
46 ml/min/1.73 m
2
, respectively (Table 2).
CKD was present in 188 patients (52%), of whom 40, 38 and
21% had CKD stage 3, 4 and 5, respectively (Tables 1, 2). The
main causes of CKD were diabetes (44%), hypertension (39%),
glomerulonephritis (14%) and other conditions (3%). Family
history of sickle cell disease was present in 7 and 6% of patients
with and without CKD, respectively; the difference was not
statistically significant (
p
>
0.05). Compared to patients without
CKD, those with CKD had on average higher levels of WC (92
±
16 vs 88
±
12 cm;
p
=
0.009), SBP (151
±
26 vs 136
±
24;
p
=
0.001), DBP (85
±
15 vs 81
±
13 mmHg;
p
=
0.001) and PP (66
±
21 vs 54
±
19 mmHg;
p
=
0.001). They also had higher levels of
TG (1.42
±
0.75 vs 1.22
±
0.54 mmol/l;
p
=
0.017) and uric acid
(442
±
165 vs 277
±
100 mmol/l;
p
=
0.001), and lower levels of
HDL-C (1.39
±
0.67 vs 1.58
±
0.46 mmol/l;
p
=
0.014), glucose
(7.5
±
5.16 vs 8.94
±
4.61) and Hb (10
±
2.20 vs 12
±
2.10 g/dl;
p
=
0.001). The proportion of subjects with proteinuria was also
higher in CKD patients (37 vs 24%;
p
=
0.001).
Table 3 summarises the distribution of CKD risk factors
in the study population as a whole and by renal functional
status. SCT was present in 19% of patients in the entire group,
and 23 and 18% of those with and without CKD, respectively;
the observed difference did not reach the level of statistical
significance. Patients with CKD also had higher rates of the
MetS (31 vs 24%;
p
=
0.001), anaemia (72 vs 42%;
p
=
0.001)
and elevated PP (60 vs 39%,
p
=
0.001). Clinical and biological
characteristics of CKD patients by Hb status are depicted in