Introduction study determined the ECG patterns in a cohort

Introduction

Metabolic syndrome is increasing globally, Nigeria inclusive
with obesity and increasing sedentary lifestyle being the main epidemic drivers.(1, 2) Prevalence as much as 40% for
this condition has been reported in some Western country while in Nigeria it is
about 30%.(3, 4)  

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 Each of the components
produces complications which impose various electrocardiographic (ECG) changes.
Previous studies in other population have reported metabolic syndrome to have
high prevalence of ECG abnormalities.(5-7) These are associated with adverse
cardiovascular outcomes among this population group. There is paucity of
studies in Nigeria examining these features among metabolic syndrome patients.

The study determined the ECG patterns in a cohort of patient
aged above 18years in Ibadan who had metabolic syndrome and accessed the
predictors of the abnormalities seen.

Methods

A total of 615 patients with cardiovascular risks presenting
to the outpatient unit of cardiology department, University College Hospital,
Ibadan for the first time was recruited into the Cardiovascular Risk Prediction
Registry (CRP). Basic demographic & clinical profiles and ECG findings were
determined and those found to have metabolic syndrome based on the definition below
were selected for this study.

Definition
of metabolic syndrome

Metabolic syndrome was defined based on International
Diabetic Federation (IDF) criteria using waist circumference (?94cm (men),
?80cm (female),or two or more  of the
following i.  Fasting triglyceride
>150g/dL, or specific treatment for this lipid abnormality, ii HDL
cholesterol > 40mg/dL(men), >50mg/dL(women) or specific treatment for
this lipid abnormality  iii. Blood
pressure >130mmHg (systolic), >90mmHg (diastolic) or on antihypertensive
treatment. iv. ?100mg/dL or previously diagnosed diabetes mellitus.

Assessment
of anthropometric measurement

Weight and height were taken by trained research staff.
Weight was taken after the participants have removed clothing to the barest
minimum and the height without shoes or head gear. The weight was measured to
the nearest 0.1 kg while height was to the nearest 0.5cm. Waist circumference was taken midpoint
of the distance of last palpable rib and the top of the iliac crest using an
anthropometric measuring tape while hip circumference was at the widest portion
of the buttocks using the same tape.

The basic, clinical and ECG profiles of those with metabolic
syndrome were compared with those with metabolic syndrome.

Assessment of blood pressure

 

Electrocardiography

All participants for this study had resting  ECG using a
commercially availableDA1  CONTEC® Workstation Model CONTEC
EC8000G, ECG machine (Made in China) at 25 mm/s and 1mV/cm calibration. The
entire ECG tracing used were inspected visually by the technicians in the team
to detect technical errors, missing leads, and inadequate quality of tracings.
Defective ones are repeated before extraction of data.

Various parameters such as heart rate, PR interval, QRS
duration, QTc interval, P wave axis, QRS axis, T wave axis were extracted. These
are in addition to standard determination of rhythm & conduction
abnormalities, chamber enlargement and right or left ventricular hypertrophy.
Cornell product was
determined by (RaVL + SV3) + 8mm for women x QRS duration ? 2440 mm while
Sokolow-Lyon voltage was determined by sum of the amplitudes of S wave in V1 and
R wave in V5 or V6 ?3.5 mV.

Data management and statistical analysis

The data was extracted from the
case reporting form and stored safe and secure location using excel spreadsheet
and data base pass worded and access  only be 
available to the research team.

The qualitative data were summarized
as frequency and percentage. Quantitative variables would be summarized as
means, standard deviations and percentages. Categorical data were analyzed
using chi square with Yates correction  and confidence interval determined.        

Multiple linear regression would
be used to model for the influence of socio demographic and clinical variables
of the participants on various ECG findings.

The data was analyzed using Statistical
Package for Social Sciences (SPSS), version 16.0 (Spss Inc, Chicago, IL, USA).

 

Ethical considerations

Ethical approval was granted for
the study by UI/UCH ethical committee and all patients that participated in the
study gave informed consent.

Results

Dummy tables

Table 1:
Basic demographic and clinical profile of participants

 

Total

Men

Women

P value

Age(mean)

 

 

 

 

Ethnicity

 

 

 

 

Marital status(Married)

 

 

 

 

Educational background(None)

 

 

 

 

Occupation(Unemployed)

 

 

 

 

smoking

 

 

 

 

Alcohol

 

 

 

 

BMI(mean)

 

 

 

 

Weight (Kg)

 

 

 

 

Height(cm)

 

 

 

 

Waist circumference(cm)

 

 

 

 

WHtR

 

 

 

 

Systolic blood pressure(mean)

 

 

 

 

Diastolic blood pressure(mean)

 

 

 

 

 

 

 

metabolic syndrome

Without metabolic syndrome

P value

Heart rate

 

 

 

PR interval

 

 

 

QRS duration

 

 

 

QT interval

 

 

 

QTc interval

 

 

 

P wave axis

 

 

 

QRS axis

 

 

 

T wave axis

 

 

 

 

Table 2:
Various ECG abnomalities

 

metabolic syndrome

Without metabolic syndrome

P value

Presence of any ECG abnomalities

 

 

 

Sinus rhythm(Yes)

 

 

 

Sinus arrthymia(Yes)

 

 

 

Atrial fibrillation(Yes)

 

 

 

Atrial flutter

 

 

 

Presence of arrthymia

 

 

 

PVC

 

 

 

PVC and PSVC

 

 

 

Ventricular tachycardia

 

 

 

Supraventricular tachycardia

 

 

 

 

 

 

 

No conduction abnormalities

 

 

 

First degree AV block

 

 

 

Second degree AV block

 

 

 

Complete AV block

 

 

 

RBBB

 

 

 

LBBB

 

 

 

LAH

 

 

 

LPH

 

 

 

Bifascicular block

 

 

 

Trifascicular block

 

 

 

Indeterminate interventricular block

 

 

 

 

 

 

 

No chamber enlargement

 

 

 

Right atrial enlargement

 

 

 

Left atrial enlargement

 

 

 

Biatrial enlargement

 

 

 

LVH

 

 

 

LVH with strain

 

 

 

RV hypertrophy

 

 

 

 

Table 3: Assessment of gender difference of  ECG abnormalities in metabolic syndrome

 

Male with metabolic syndrome

Female with metabolic syndrome

P value

Presence of any ECG abnormalities

 

 

 

Sinus rhythm(Yes)

 

 

 

Sinus arrthymia(Yes)

 

 

 

Atrial fibrillation(Yes)

 

 

 

Atrial flutter

 

 

 

Presence of arrthymia

 

 

 

PVC

 

 

 

PVC and PSVC

 

 

 

Ventricular tachycardia

 

 

 

Supraventricular tachycardia

 

 

 

 

 

 

 

No conduction abnormalities

 

 

 

First degree AV block

 

 

 

Second degree AV block

 

 

 

Complete AV block

 

 

 

RBBB

 

 

 

LBBB

 

 

 

LAH

 

 

 

LPH

 

 

 

Bifascicular block

 

 

 

Trifascicular block

 

 

 

Indeterminate interventricular block

 

 

 

 

 

 

 

No chamber enlargement

 

 

 

Right atrial enlargement

 

 

 

Left atrial enlargement

 

 

 

Biatrial enlargement

 

 

 

LVH

 

 

 

LVH with strain

 

 

 

RV hypertrophy

 

 

 

 

 

Table 4:
Associations with different ECG abnomalities

 

 

All abnormalities

Rhythm abnormalities

Conduction abnormalities

Chamber enlargement/Wall abnomalities

 QT changes

Age

 

 

 

 

 

 

Gender

 

 

 

 

 

 

Smoking status

 

 

 

 

 

 

 

Non-smoker

 

 

 

 

 

 

Former smoker

 

 

 

 

 

 

Light smoker(10years

 

 

 

 

 

Family history of hypertension(Yes)

 

 

 

 

 

 

Family history of DM(Yes)

 

 

 

 

 

 

Family history of coronary heart disease(Yes)

 

 

 

 

 

 

Diagnosis of hypertension

 

 

 

 

 

 

Diagnosis of DM

 

 

 

 

 

 

Diagnosis of lipid abnormality

 

 

 

 

 

 

Albuminuria

 

 

 

 

 

 

Presence of urine protein

 

 

 

 

 

 

Urea(mean)

 

 

 

 

 

 

 

 

 

References

 DA1ECG
acquisition box  Model MGY-S3, Made in
Germany

 

CONTEC® Workstation Model CONTEC EC8000G,
Made in China