CARDIOVASCULAR JOURNAL OF AFRICA • Vol 23, No 1, February 2012
24
AFRICA
and leading to chromosomal alterations, protein nitration, lipid
peroxidation, subsequent cellular dysfunction and cell death.
10
Quantification of apolipoproteins A and B provide a measure
of the total number of anti-atherogenic and pro-atherogenic
particles in the plasma. Apo-B-100 molecules present in lipo-
proteins lead to their entrapment in the arterial wall. Apo-B-100
are also taken up by macrophages in the arterial wall in native or
oxidised form and orchestrate an inflammatory response in the
arterial wall that promotes atherogenesis.
11
Our study attempted to evaluate the interrelationship between
dyslipidaemia, oxidative stress and inflammation in the aetio-
pathogenesis of atherosclerosis in angiographically proven CAD
patents. This was accomplished by evaluation of the levels of the
markers of dyslipidaemia, oxidative stress and inflammation;
namely, apolipoprotein B (Apo B), NO and ferritin, respectively,
in the study group.
Methods
This study was conducted in the Department of Biochemistry
in collaboration with the Department of Cardiology, Govind
Ballabh Pant Hospital, New Delhi, India. A total of 753 patients
who underwent coronary angiography were included in the study
and after initial screening for exclusion criteria, 476 patients
were finally enrolled.
Subjects were excluded from the study if they presented with
congenital heart disease, valvular heart disease, cardiomyopathy
and cardiogenic shock or were taking any nitrate preparation.
Patients suffering from known liver, thyroid or renal disease, or
malignancy, and those with acute viral infection within the previ-
ous four weeks were excluded. Patients with a history of recent
use of oral contraceptives, anticonvulsants and retinoic acid were
also excluded.
The number of significantly stenosed coronary arteries and
lesions determined the severity of the coronary artery disease.
Angiograms were assessed by the cardiologist, which enabled
sub-classification of patients into four groups: G0
=
no stenosis
in any coronary vessel, G1
=
one vessel stenosed, G2
=
two
vessels stenosed, with more than 50% stenosis, G3
=
all three
major vessels stenosed, with more than 50% stenosis.
Data on cardiovascular risk factors such as dyslipidaemia,
diabetes mellitus, hypertension, smoking (currently or recently
stopped) and medical treatment of all subjects were recorded.
Ethical committee clearance was obtained before the commence-
ment of the study. Informed consent was obtained from each
patient according to the guidelines of the ethics committee.
Analytical measurements
After overnight fasting and prior to coronary angiography, blood
samples were drawn in a plain vacutainer under sterile conditions.
The serum was separated and frozen at –50°C until further analy-
sis. Serum ferritin was assayed using a solid-phase enzyme immu-
noassay based on the sandwich principle. The kit used for ferritin
estimation was obtained from Syntron Bioresearch, Inc, USA.
Nitric oxide is a very unstable compound, therefore its level in
the serum was determined indirectly by the measurement of its
stable decomposition product, nitrite and nitrate, using the Griess
reaction.
12
This involves formation of a chromophore during the
reaction of nitrite with sulphanilamide and N-(-naphthyl) ethyl-
enediamine (Griess reagent) to produce a purple azo compound,
which was measured photometerically at 543 nm.
Apolipoprotein B-100 levels were estimated using an immu-
noturbidimetry kit (Randox Laboratories Ltd, Antrium, UK) on
an Olympus AU400 autoanalyser (Olympus, Germany). Total
cholesterol, TG and HDL-C concentrations were quantified on
an Olympus AU400 autoanalyser using standard kits. LDL-C
was calculated using Friedwald’s formula:
TC – (HDL-C
+
TG/5).
13
The calculation of small dense LDL was done using the formula
of Hattori
et al
.
14
Statistical analysis
Quantitative values of continuous variables were expressed as
mean
±
standard deviation. ANOVA was used to compare differ-
ent parameters in the four groups. Pearson’s correlation was
applied to test for associations between the continuous variables.
The receiver operating characteristics (ROC) curves were plot-
ted for NO, ferritin and apolipoprotein B and the area under the
curve was calculated. Cut-off points were determined from the
ROC curves and the specificity, sensitivity, positive predictive
value, negative predictive value, odds ratio and confidence inter-
vals were calculated. A two-tailed
p
-value
<
0.05 was accepted
as statistically significant for all the results. Statistical analysis
was carried out using SPSS for windows 12.0 software (SPSS
Inc, Chicago, IL, USA).
The positive predictive value, precision rate or post-test prob-
ability of disease is the proportion of patients with positive test
results who are correctly diagnosed. The negative predictive
value is the proportion of patients with negative test results who
are correctly diagnosed.
The likelihood ratio incorporates both the sensitivity and
specificity of the test and provides a direct estimate of how
much a test result will change the odds of having a disease.
The likelihood ratio for a positive result (LR
+
) indicates how
much the odds of the disease increase when a test is positive.
The likelihood ratio for a negative result (LR−) indicates how
much the odds of the disease decrease when a test is negative.
LR
+
=
true positives/false positives and LR−
=
false negatives/
true negatives.
A likelihood ratio of
>
1 indicates that the test result is asso-
ciated with the disease. A likelihood ratio
<
1 indicates that the
result is associated with absence of the disease. Tests where the
likelihood ratios lie close to 1 have little practical significance as
the post-test probability (odds) is little different from the pre-test
probability. When the positive likelihood ratio is
>
5 or the nega-
tive likelihood ratio is
<
0.2 (or 1/5) then it can be applied to the
pre-test probability of a patient having the disease, in order to
estimate a post-test probability of the disease state.
The odds ratio is a measure of effect size, describing the
strength of association or non-independence between two binary
data values.
Results
Table 1 shows the demographics of the study population: 135
patients had single-vessel, 174 had double-vessel and 114
patients had triple-vessel stenosis. Fifty-three patients were
categorised as without any stenosis. Risk-factor analysis showed
that about 73 patients with triple-vessel disease were diabetic
