1. Role of Left Ventricular Mass Index Versus Left Ventricular Relative Wall Thickness in Assessment of Left Ventricular Geometry in Non Cardioembolic Stroke Patients
IJCCR
Role of Left Ventricular Mass Index Versus Left Ventricular
Relative Wall Thickness in Assessment of Left Ventricular
Geometry in Non Cardioembolic Stroke Patients
Osama Sanad Arafa1, Hany Hassan Ebaid2, Wael Mohamed Tawfik3, *Marwa Adel Diab4
1,2,3,4Cardiology department, Faculty of Medicine, Benha university, Egypt.
In non-cardioembolic stroke patients, the cardiac manifestations of elevated blood pressure are
of particular interest. The value of LV geometry in the prediction of cardiovascular risk is
controversial. Many reports detected that left ventricular hypertrophy is independently associated
with risk of ischemic stroke. The primary objective of this study was to identify the frequency of
different patterns of altered left ventricular geometry in patients with non cardioembolic stroke,
and to assess whether a significant number of patients will miss the diagnosis of LV remodeling
if the left ventricular relative wall thickness(RWT) is not evaluated or reported. 100 patients were
referred within 48 hours after an acute non cardioembolic ischemic stroke for a transthoracic
echocardiogram. The echocardiographic findings were analyzed. Mean age was 61.86 ± 12.59
years, 45 % men. Concentric remodeling carried the highest frequency (43%), followed by normal
pattern (27%), concentric hypertrophy (22%), and eccentric hypertrophy (8%). The frequency of
abnormal left ventricular RWT (61.4%) was significantly higher than that of abnormal LVMI.
Key words: non cardioembolic stroke; Left ventricular relative wall thickness; Left ventricular mass index
INTRODUCTION
Left ventricular hypertrophy (LVH), or increased LV mass,
is considered a risk factor for cardiovascular diseases
(Kannel et al.,1970). It is strongly correlated with
cardiovascular morbidity and mortality(Kannel.,1983).
The risk increase is independent of other cardiovascular
risk factors, as arterial hypertension (Schillaci et al., 2000).
Moreover, LVH is also independently associated with
increasing incidence of ischemicstroke. This
associationwas confirmed with more sensitive
echocardiographic studies (Bikkina et al.,1994).
Measurement of LV mass was widely used to identify
changes in LV geomtry due to arterial hypertension.
However, cardiac damage can already be present in
patients with normal LV mass (Gaasch et al., 2011);
however recently, there is reports of increasing risk
correlated with abnormal
LV geometry beyond the simple LV mass increase (Eguchi
et al., 2007). From LV mass and relative wall thickness
(RWT), 3 abnormal geometric patterns identified—
concentric remodeling (abnormal relative wall thickness
[RWT] and normal LV massindex [LVMI]), concentric
hypertrophy (abnormal RWT and LVMI), and eccentric LV
hypertrophy (abnormal LVMI and normal RWT)( Eguchi et
al.,2007).
The risk of adverse events from cardiovascular causes
and stroke is lowest for patients with normal geometry, and
gradually increases in patients with concentric
remodelling, eccentric hypertrophy, and concentric
hypertrophy. Increased risk associated with RWT is
independent of LVMI (Bikkina et al.,1994).
*Corresponding Author: Marwa Adel Diab, Cardiology
department, Benha university hospital, Benha faculty of
medicine, Egypt, Postal code no. 13518. E-mail:
marwadiab1987@yahoo.com; Tel: 01006278046
International Journal of Cardiology and Cardiovascular Research
Vol. 4(2), pp. 079-084, November, 2018. © www.premierpublishers.org, ISSN: 3102-9869
Research Article

2. Role of Left Ventricular Mass Index Versus Left Ventricular Relative Wall Thickness in Assessment of Left Ventricular Geometry in Non Cardioembolic Stroke Patients
Arafa et al. 080
Aim of the work
We conducted this study to assess forms of LV
geometrical changes and the role of RWT measurement in
avoidance of undiagnosis of LV remodeling in patients with
non cardioembolic stroke.
Study population
This is a prospective observational single –center study
including 100 patients presented to Neurology department,
Damanhour medical national institute from January 2017
to March 2018 with non cardioembolic cerebrovascular
ischemic stroke. Non cardioembolic cerebrovascular
ischemic stroke detected in stroke patients with no obvious
cardiac origin of emboli, sources of cardiogenic emboli
were considered in the exclusion criteria. All patients were
scheduled to perform 2D transthoracic echocardiography
within 48 hours of hospitalization. Thestudy protocol was
approved by Benha faculty of medicine Health Research
Ethics Committee.
Inclusion criteria:
 Patients of both genders with age more than 18 years
with
acute non cardioembolic ischemic stroke.
 Patients with adequate imaging quality by
transthoracic echocardiography.
 Patients with sinus rhythm.
Exclusion Criteria:
We excluded patients with:
 Mitral stenosis, aortic stenosis and any congenital
heart disease.
 Atrial fibrillation.
 Multiple infarcts on computed tomography (CT) or
magnetic resonance imaging (MRI) because this was
probably due to an embolic insult, and suggested
showering, the source could not be ascertained.
 Prior myocardial infarction (MI) or Coronary Artery
Bypass Graft surgery (CABG), because the formulae
used for LVMI or RWT evaluation would not apply due
to the lack of homogeneity of wall thickness.
 Poor echocardiographic windows which would make
echocardiographic measurements unreliable.
 Hemorrhagic stroke.
Diagnostic Evaluation
All patients included in the study were subjected to detailed
history and clinical examination with special emphasis on
risk factors for ischemic stroke as hypertension, diabetes
mellitus, dyslipidemia, obesity and smoking. Hypertension
was defined as elevation of arterial systolic blood pressure
≥ 140 mmHg and/or diastolic blood pressure ≥ 90 mmHg
on two or more properly measured seated blood pressure
readings on two or more office visits or patients who were
taking anti-hypertensive medications (Bryan et al., 2018).
Diabetes mellitus was defined as 8 hours fasting plasma
glucose ≥ 126 mg/dl, 2-h plasma glucose ≥ 200 mg/dl
during an oral glucose tolerance test (OGTT), symptoms
of diabetes mellitus and casual plasma glucose ≥ 200
mg/dl or patients who were taking anti-diabetic
medications (American Diabetes Association.,2014).
Dyslipidemia was defined as total cholesterol > 200 mg/dl,
TG >150 mg/dl (Neil et al.,2013). Obesity was defined
according to WHO criteria as a body mass index >30
kg/m2.Initial brain CT was obtained at admission, if
inconclusive, diagnosis was confirmed by another CT or
Magnetic resonance imaging 24-48 hours later (Jauch et
al., 2013).
Echocardiographic Evaluation
Transthoracic echocardiography was performed within 48
hours after stroke using Phillips HD 11 XE ultrasound,
equipped with 4MHz transducer. In end diastole, the
septum walls thickness (SWTd), posterior LV wall
thickness (PWTd), and the diameter of the left ventricle
(LVIDd) measured using M-mode. Left ventricular mass
index LVMI calculated using the following equations:
LV mass= 0.8 (1.04 [LVID+PWTd+SWTd]3 –[LVID]3)x 0.6g
LVMI=LVM/body surface area.
Body surface area(BSA) calculated using Mosteller
formula (Adam et al.,2013):
BSA(m2)= square root of (height (cm) x weight (kg)/3600).
Relative wall thickness RWT calculated by dividing the
sum of SWTd and PWTd by the LVIDd (Roberto et
al.,2015).
RWT of 0.22 to 0.42 is regarded as normal.
The reference ranges used to define normal left ventricular
thickness are:
RWT (male and female)=>0.42.
LVMI (male) <115 g/m2.
LVMI (female) <95 g/m2.
Four LV geometric patterns will be identified on the basis
of LV mass index and RWT: normal geometry (normal LV
mass index, normal RWT), concentric remodeling (normal
LV mass index, abnormal RWT), eccentric hypertrophy
(abnormal LV mass index, normal RWT) and concentric
hypertrophy (abnormal LV mas index, abnormal RWT).
(Roberto et al.,2015).
Statistics
Data were analyzed by IBM-SPSS Version 16 statistical
software. The frequency ofdifferent types of LV wall
abnormality was assessed using the descriptive statistics.
To assess the association of the risk factors with LV
remodeling. The significance of the difference between
abnormal RWT and LVMI was assessed using Chi square
test.

3. Role of Left Ventricular Mass Index Versus Left Ventricular Relative Wall Thickness in Assessment of Left Ventricular Geometry in Non Cardioembolic Stroke Patients
Int. J. Cardiol. Cardiovasc. Res. 081
RESULTS
The mean age was 61.86 ±12.59 years, incidence of
cerebral infarction increased with advancing age where 71
% of the patients were ≤60 years and 29 % of the patients
were < 60 years. The sex distribution was as follows: 45
males (45%) and 55 females (55%) [table1]. Twenty-five
patients were obese (25%) (13 of them were males
(28.9%) and 12 females (21.8%)), 57 had HTN (57%) (29
were males (64.4%) and 28 females (58.9%)), 57 had DM
(57%) (25 were males (55.6%) and 32 females (58.2%),
43 had Hypercholesterolemia (43%) (24 were males
(55.8%) and 19 females (44%) [table2]. The frequencies of
different patterns of LV remodeling weredistributed as
follows: concentric remodeling carried the highest
frequency (43%), followed by normal pattern (27%),
concentric hypertrophy (22%), and eccentric hypertrophy
(8%).The frequency of abnormal RWT was higher than
that of abnormal LVMI. (table 3).
Table 1: Descriptive analysis of the four studied groups according to demographic data
Total
(n = 100)
Concenteric
hypertrophy (n = 22)
Concenteric
remodeling (n = 43)
Eccenteric
hypertrophy (n = 8)
Normal geometry
(n = 27)
No. % No. % No. % No. % No. %
Sex
Male 45 45.0 8 36.4 22 51.2 3 37.5 12 44.4
Female 5 55.0 14 63.6 21 48.8 5 62.5 15 55.6
P 0.357 0.282 0.727 0.946
Age (years)
<60 29 29.0 7 31.8 14 32.6 1 12.5 7 25.9
≤60 71 71.0 15 68.2 29 67.4 7 87.5 20 74.1
P 0.742 0.496 FEp=0.432 0.680
Min. – Max. 25.0 – 86.0 35.0 – 76.0 25.0 – 80.0 50.0 – 72.0 35.0 – 86.0
Mean ± SD. 61.86 ± 12.59 61.73 ± 12.11 59.77 ± 13.71 65.0 ± 7.35 64.37 ± 12.23
Median 65.0 65.0 60.0 67.50 65.0
BMI (kg/m2
)
Non obese 75(75.0%) 19(86.4%) 32(74.4%) 7(87.5%) 17(63.0%)
obese 25(25.0%) 3(13.6%) 11(25.6%) 1(12.5%) 10(37.0%)
Min. – Max. 21.90 – 37.20 23.70 – 35.40 22.30 – 37.20 23.70 – 34.0 21.90 – 36.0
Mean ± SD. 28.44 ± 3.22 27.50 ± 2.66 28.54 ± 3.37 27.76 ± 3.02 29.24 ± 3.36
Median 28.50 26.65 28.70 27.50 29.
p: p value for Chi square test
Table 2: Relation between sex and different parameters (n=100)
Total
Sex

 pMale Female
No. % No. % No. %
Obesity 25 25.0 13 28.9 12 21.8 0.660 0.417
HTN 57 57.0 29 64.4 28 50.9 1.850 0.174
DM 57 57.0 25 55.6 32 58.2 0.070 0.792
Cholesterol(>200 Abnormal) 43 43.0 24 55.8 19 44.0 3.564 0.059
2: Chi square test
p: p value for comparing between the two categories
*: Statistically significant at p ≤ 0.05
Table 3: RWT and LVMI Cross-tabulation
RWT
LVMI
χ2
pNormal Abnormal (F>95, M>115)
No. % No. %
≤0.42 Normal 27 38.6 8 26.7
1.308 0.253
>0.42 Abnormal 43 61.4 22 73.3
2: Chi square test
p: p value for comparing between the two categories
36 patients (36%) had small (lacunar) infarctions with higher incidence in concentric hypertrophy (45.5%) and concentric
remodeling)39.5%) patients[table4]. However, no statistically significant relationship found between stroke size and
different lV geometric patterns.

4. Role of Left Ventricular Mass Index Versus Left Ventricular Relative Wall Thickness in Assessment of Left Ventricular Geometry in Non Cardioembolic Stroke Patients
Arafa et al. 082
Table 4: Relation between different LV patterns and stroke size
Stroke size
Total
(n = 100)
Concenteric
hypertrophy
(n = 22)
Concenteric
remodeling
(n = 43)
Eccenteric
hypertrophy
(n = 8)
Normal geometry
(n = 27)
No. % No. % χ2
p No. % χ2
p No. % FE
p No. % χ2
p
Small 36 36.0 10 45.5 0.407 17 39.5 0.688 2 25.0 0.710 7 25.9 0.326
Moderate 35 35.0 10 45.5 0.358 11 25.6 0.269 5 62.5 0.143 9 33.3 0.872
Large 29 29.0 2 9.1 0.052 15 34.9 0.485 1 12.5 0.439 11 40.4 0.244
χ2
p 0.066 0.215 MCp=0.271 0.243
2
p: p value for Chi square test
MCp: p value for Monte Carlo
FEp: p value for Fisher Exact
DISCUSSION
The value of LV geometry in the prediction of
cardiovascular risk is controversial. Moreover, its role as a
risk factor for ischemic stroke has been minimally
investigated. It is established that abnormal LV geometry
is associated with an increased ischemic stroke risk and
that RWT adds information not contained in LV mass
(Harold et al., 2007). Although RWT per se did not
increase stroke risk to a significant extent, it did so after
adjustment for LV mass. This suggests that LV geometry
may be associated with stroke in ways not necessarily
related to LV mass. Determination of RWT may be useful
for further stroke risk stratification, especially among
patients with LVH (Di Tullio et al., 2003) .
Hashem et al.(2015) reported that frequencies of different
patterns of LV remodeling were distributed as follows:
concentric remodeling carried the highestfrequency
(49.2%), followed by concentric hypertrophy(30.7%),
normal pattern (15.5%), and eccentric hypertrophy(4.1%)
Di Tullio et al. (2003) detected that normal pattern carried
the highest frequency (43%) ,followed byeccentric
hypertrophy (33%) , concentric hypertrophy (13%) and
concentric remodeling(11%).On the other hand, Wang et
al.(2014) reported that concentric hypertrophy carried the
highest frequency(28.54%) ,followed by concentric
remodeling (25.57%), normal geometry (23.97%), and
eccentric hypertrophy (21.92% ).
As regards association between risk factors and the
different LV patterns, Hypertension was the most common
risk factor (67%) of patients in our study. There was a
significant relation between concentric hypertrophy and
both DM and hypercholesterolemia. Concentric
remodeling was associated with both HTN and DM [table
4a,ab] .Hashem et al.(2015) reported that concentric
remodeling was associated with DM and concentric
hypertrophy had significant relation with HTN.
In the present study, incidence of cerebral infarction
increased with advancing age where 71 % of the patients
were ≤60 years and 29 % of the patients were < 60 years.
This agree with previous studies Grau et al. (2001)
reported that ischemic stroke increased with advancing
age where 5.7% of the patients were < 45 years and
94.3% of the patients were ≥ 45 years ; Marwat et al.
(2009) detected that incidence of cerebral infarction
increased with advancing age where 2.3% in the age
group 40–50, 27.2% in the age group 51–60, and 47.7%
in the age group older than 60 years ; Soliman et al. (2018)
where 85.6% of the patients were between 46 and
90 years and 14.4% of the patients were ≤ 45 years.
No significant difference was found between males and
females in incidence of different types of LV patterns
(p=0.691) in our study that disagree with findings of
previous studies Wang et al.(2014) that reported that
eccentric hypertrophy and concentric remodeling had
higher incidence in females (95% CI 1.13 – 2.54% , 1.03 –
2.30 % respectively) ; Hashem et al. (2015) that detected
that concentric hypertrophy and concentric remodeling
had higher incidence in males (95% CI 0.23–0.61 % ,
1.31–3.24 % respectively).This disagreement may be due
to less number of patients included in our study compared
to these studies.
No correlation found between obesity and LV geometric
patterns that agree with previous studies Wang et al.
(2014) and Hashem et al. (2015) and disagree with
previous studies Ervin et al. (2007) that reported that CH
and EH patients had the highest incidence of obesity ;
Angela et al. (2008) that detected that excess adiposity
promoted concentric remodeling (p= 0.02) and concentric
hypertrophy (p < 0.04) rather than eccentric changes (p=
0.91) ; Linda et al. (2004) ; Evrim et al. (2010) that showed
that obesity was associated with concentric LV remodeling
(p < 0.05) .
As regards relation between cerebral infarction size and
LV patterns ,our study detected that 36 patients (36%) had
lacunar infarctions with higher incidence in concentric
hypertrophy and concentric remodeling patients .Di Tullio
et al.(2003) reported that increased RWT tended to be
more frequently associated with lacunar infarcts as
concentric LVH tended to have more lacunar strokes
followed by concentric remodeling whereas Antonio et
al.(2013) detected that lacunar stroke had a higher LVMI
than non-lacunar stroke patients.

5. Role of Left Ventricular Mass Index Versus Left Ventricular Relative Wall Thickness in Assessment of Left Ventricular Geometry in Non Cardioembolic Stroke Patients
Int. J. Cardiol. Cardiovasc. Res. 083
Table 5a: The association of risk factors with the different types of lv remodeling
N HTN OR (CI 95%) DM OR (CI 95%) BMI OR (CI 95%)
Concenteric hypertrophy 22 0.825 (0.307 – 2.222) 3.230 (1.084 – 9.621) 0.402 (0.108 – 1.495)
p 0.704 0.030* 0.163
Concenteric remodeling 43 0.396*(0.175–0.895) 0.396 (0.175 – 0.895) 1.056 (0.424 – 2.630)
p 0.026* 0.025* 0.907
Eccenteric hypertrophy 8 1.525 (0.291 – 8.000) 1.282 (0.289 – 5.686) 0.405 (0.047 – 3.462)
p 1.000 1.000 0.675
Normal geometry 27 0.980 (0.384 – 2.501) 1.135 (0.463 – 2.781) 2.275 (0.866 – 5.974)
p 0.966 0.781 0.091
OR: Odds ratio CI: Confidence interval
Table 5b: The association of risk factors with the different types of lv remodeling
N
Smoking
OR (CI 95%)
Cholesterol
OR (CI 95%)
Age (years)
OR (CI 95%)
Concenteric hypertrophy 22 0.670 (0.235 – 1.906) 0.338 (0.127 – 0.903) 0.842 (0.302 – 2.343)
p 0.451 0.027* 0.742
Concenteric remodeling 43 1.538 (0.668 – 3.543) 1.802 (0.798 – 4.069) 0.740 (0.310 – 1.763)
P 0.310 0.154 0.496
Eccenteric hypertrophy 8 1.181 ( 0.265 – 5.266) 1.282 (0.289 – 5.686) 3.062 (0.360 – 26.077)
P 1.000 1.000 0.306
Normal geometry 27 0.761 (0.293 – 1.978) 1.135 (0.463 – 2.781) 1.232 (0.456 – 3.335)
P 0.575 0.781 0.681
OR: Odds ratio CI: Confidence interval
As regards relation between the stroke subtype and risk factors, our study detected higher incidence of all cardiovascular
risk factors in macroangiopathic stroke patients [table5] whereas Grau et al. (2001) reported that the prevalence of
smoking was higher in macroangiopathic stroke, on the other hand, hypertension, diabetes mellitus, hypercholesterolemia,
and obesity had higher incidence in the microangiopathic subtype. Farhad et al. (2015) detected that macroangiopathic
stroke had higher incidence of DM and dyslipidemia whereas microangiopathic subtype was more associated with
smoking.
Table 5: Relation between stroke subtype and risk factors
Male ِ≤ِِ ِِ 60 years HTN DM Smoking Obesity Hypercholesterolemia LVH
No. % No. % No. % No. % No. % No. % No. % No. %
Stroke subtype
Microangiopathic
16 35.6 28 39.4 13 30.2 15 34.9 26 39.4 8 32.0 18 41.9 29 39.7
Macroangiopathic
29 64.4 43 60.6 30 69.8 28 65.1 40 60.6 17 68.0 25 58.1 44 60.3
2
p: p value for Chi square test
Study Limitations
It is single-center non randomized study. This is small
sized study included only 100 patients with non-
cardioembolic stroke.
The study was mainly conducted to evaluate the
prevalence of RWT in this group. Echocardiographic
criteria used to define LV hypertrophy
in available studies are not uniform and vary substantially.
Therefore, comparison with other studies is limited.
CONCLUSION
In this group of consecutive patients with non-
cardioembolic stroke, abnormal LV geometry detected by
RWT is very frequent. As abnormal RWT was often found
with normal LVMI, abnormal left ventricular geometry
diagnosis may be missed if RWT is not assessed or
reported.
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Accepted 17 September 2018
Citation: Arafa OS, Ebaid HH, Tawfik WM, Diab MA
(2018). Role of Left Ventricular Mass Index Versus Left
Ventricular Relative Wall Thickness in Assessment of Left
Ventricular Geometry in Non Cardioembolic Stroke
Patients. International Journal of Cardiology and
Cardiovascular Research, 4(2): 079-084.
Copyright: © 2018 Arafa et al. This is an open-access
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