title of research: frequency and prognostic …

i

TITLE OF RESEARCH: FREQUENCY AND PROGNOSTIC SIGNIFICANCE OF

ABNORMAL ELECTROENCEPHALOGRAPHIC FINDINGS IN ACUTE STROKE

PATIENTS AT THE UNIVERSITY COLLEGE HOSPITAL, IBADAN.

NAME OF INVESTIGATOR: DR. LUQMAN, OPEOLUWA OGUNJIMI (MBChB)

<[email protected]> 07032683222

NAMES OF SUPERVISORS: PROF. A. OGUNNIYI (FMCP, FWACP)

PROF. M.O. OWOLABI (FMCP)

TRAINING INSTITUTION: UNIVERSITY COLLEGE HOSPITAL IBADAN, OYO

STATE

PURPOSE OF RESEARCH: PARTIAL FULFILMENT OF THE REQUIREMENTS

FOR THE AWARD OF THE FELLOWSHIP OF THE

MEDICAL COLLEGE OF PHYSICIANS

(NEUROLOGY)

DATE OF PASSING PART 1: NOVEMBER, 2012

MAY, 2017

ii

DECLARATION

I hereby declare that this research work is original unless otherwise acknowledged. The work has

neither been presented to any college for an award nor has it been submitted elsewhere for

publication.

------------------------------------ -----------------------------

DR L. O. OGUNJIMI DATE

iii

CERTIFICATION

We attest that the information herewith contained is true and original research carried out under

our supervision by Dr. L. O. OGUNJIMI in partial fulfillment of requirements for the award of the

Fellowship of the National Postgraduate Medical College of Nigeria in Internal Medicine

(Neurology).

______________________________ ______________________

Professor A. OGUNNIYI Date Professor of Medicine/ Consultant

Department of Medicine

University College Hospital

Ibadan

______________________________ ______________________

Professor. M.O. OWOLABI Date Consultant Neurologist

Department of Medicine

University College Hospital

Ibadan

iv

ATTESTATION

I certify that the research work was carried out by DR L.O. OGUNJIMI in the Department of

Medicine, University College Hospital, Ibadan, under the supervision of PROF. A. OGUNNIYI

and PROF. M.O. OWOLABI.

NAME: --------------------------------------------

SIGNATURE: ________________________________

DESIGNATION: HEAD OF DEPARTMENT

DATE: ____________________________________

v

ACKNOWLEDGEMENTS

My immense gratitude goes to the Creator, God Almighty for enabling me to execute this project.

To my mentor, father and teacher Prof A. Ogunniyi, I am grateful to you for the indispensable

support and professional guidance you gave me from the initiation into Neurology to the

completion of this research. The fatherly role you have played during my training has contributed

profoundly to my progress, only God Almighty can reward you and I will always remain grateful

to you sir.

I also wish to appreciate all my teachers including Dr. O.S.A. Oluwole, Prof. M.O. Owolabi, and

Dr Akinyemi for painstakingly teaching me Neurology, as well as all consultants in the Department

of Medicine for their contributions to my knowledge base and skills acquired. I also wish to

appreciate all my colleagues within and outside Neurology Unit (Dr. T. Lola Taiwo, Dr. S.O.

Ekanem, Dr. Temitope Farombi, Dr. P. Olowoyo and Dr. A. Makanjuola) for their support and

team spirit in learning and management of patients. To Dr. Joseph Yaria, I cannot but appreciate

you for your very presence in my time of need, for your patience and resourcefulness. To my

lovely and beautiful wife, Bisi, how could I have gone this far without you? I thank you for your

support, understanding and patience with me while I executed this research, you are my sunshine.

To my kids Wafeeqah and Faheezah, thank you for motivating daddy to complete this study and

for bearing with my absence during my training.

To all my well-wishers, thank you and God bless you!

vi

TABLE OF CONTENTS

Page

Title Page……………………..….……………………………………………………………….… i

Declaration Page………………………………………….………………………………………… ii

Certification Page….………………………………………….……………………………………. iii

Attestation Page……………………………………………………………………………………. iv

Acknowledgement………………………………………………………………………………….. v

Table of Contents……………………………………………..…………………………………… vi

List of Tables……………………………………………………………………………………… vii

List of Figures……………………………………………………………………………………... viii

List of Abbreviations……………………………………………………………………………… ix

Summary……………………………………………………………..…………………………….. x

CHAPTER ONE

Introduction………….…………………………….…….………….………………………………. 1

Rationale …………………………………………….……….………..…….................................... 3

Aim and Objectives…………………………………..…….……………………………………… 4

CHAPTER TWO

Literature Review…………………………………….……...……………………………………… 5

CHAPTER THREE

Methodology………………..……………………….…….………………....................................... 22

Data Collection And Analysis……………………….…………….……………………………….. 27

Ethical Consideration…………………………………….…..……….............................................. 27

CHAPTER FOUR

Results…………………………………………………………………….……………………….. 31

CHAPTER FIVE

Discussion……………………………………………………………………................................... 65

CHAPTER SIX

Conclusion…………………………………………………………………………………………. 76

Recommendation…………………………………………………………………………………… 76

Limitations of The Study……………………………………………….......................................... 77

References………………………………………………….…………...….................................... 78

Appendix I (Ethical Approval) ………………………….……………............................................ 89

Appendix II (Informed Consent) …………………………..…………............................................. 90

Appendix III (Study Questionnaire) ….……....…….……...……….……………………………... 92

Appendix IV (NIHSS)…………………………....…………………..……..……………………… 98

Appendix V (MRS)……………………………………………………………................................. 100

Appendix VI (SLS)……………………………………………………….………………................ 101

Appendix VII (Barthel Index) ……………………………………..….............................................. 102

Appendix VIII (Figures And Values) ………………………………..…………………………….. 103

Appendix IX (Positive Predictive Values, Negative Predictive Value, Sensitivity, Specificity)….. 106

vii

LIST OF TABLES

Pages

Table1: Socio-Demographic Characteristics of Participants……………………. 32

Table 2: Comparison of Baseline EEG Findings in Stroke Patients Controls………. 38

Table 3: Epileptiform Pattern in Cases and Controls………………………………. 39

Table 4: Clinical Characteristics Associated with Outcome of Stroke……………. 44

Table 5: Case Fatality Rate In Acute Stroke ……………………………………….. 45

Table 6: Relationship Between Special Patterns and Early Onset Seizures……….. 64

viii

LIST OF FIGURES

Pages

Figure 1A: Frequencies of The Risk Factors For Stroke…..………................................................................. 33

Figure 1B: Proportion of Stroke Type Among Particitpants……..................................................................... 34

Figure 2A: Ischaemic Stroke Phenotyping Using OCSP…………….……………………………………….. 36

Figure 2B: Ischaemic Stroke Phenotyping Using Trial of ORG 10172 In Acute Stroke Treatment (Toast)…. 36

Figure 3: Showing Background Rhythm Among Stroke Patients.………………..………………………….. 40

Figure 4: Showing Pattern of EEG Waves From Admission To 30 Days………..………………………….. 41

Figure 5: Showing Epileptiform Pattern Among Stroke Patients…………………………………………….. 42

Figure 6: Showing Effect of Slowing on Outcomes Among Ischaemic Stroke Patients………..…………… 47

Figure 7: Showing Effect of Slowing on Outcomes Among Haemorrhagic Stroke Patients .……………… 49

Figure 8: Showing Trend of Predictive Values of Slowing Among Stroke Patient……………………...….. 51

Figure 9: Showing Effect of Alpha Rhythm In Outcomes Among Ischaemic Stroke Patients ………..……. 53

Figure 10: Showing Effect of Alpha on Outcomes Among Haemorrhagic Stroke Patients ………………… 55

Figure 11: Showing Trend of Predictive Values Of Alpha Rhythm Among Stroke Patients……………..…. 57

Figure 12: Showing Effect of Beta on Outcomes Among Ischaemic Stroke Patients …………………….. 58

Figure 13: Effect of Outcomes Among Haemorrhagic Stroke Patients……………..………………………. 59

Figure 14: Trend of Predictive Values of Beta Rhythm Among Stroke Patients…………………..……....... 61

Figure 15: Showing Trend of Seizure from Presentation To 30 Days………………………………………. 62

Figure 16: Showing Relationship Between EEG Wave Pattern and Trend of Seizure from

Presentation To 14 Days............................................................................................................... 63

ix

LIST OF ABBREVIATIONS

ASPECTS – Alberta, Stroke Program Early Computerized Tomograph

ATP – Adenosine Triphosphate

BI – Barthel Index

CBF – Cerebral Blood Flow

CFR – Case Fatality Rate

CT - Computerized Tomography

DWI – Diffusion Weighted Imaging

EEG – Electroencephalography

GOS – Glasgow Outcome Scale

HDL – High-Density Lipoprotein

ICA – Internal Carotid Artery

IDF – International Diabetes Federation

LACI – Lacunar Infarct

LDL – Low-Density Lipoprotein

MCA – Middle Cerebral Artery

MRI - Magnetic resonance imaging

MRS – Modified Rankin Scale

NIHSS - National Institute of Health Stroke Scale

NMDA - N-methyl-D-aspartate receptor

NPV- Negative Predictive Value

OSCP – Oxfordshire Community Stroke Project

PACI – Partial Anterior Circulation Infarct

PCV – Packed Cell Volume

PET – Positron Emission Tomograph

PLED – Periodic Lateralizing Epileptiform Discharges

PPV- Positive Predictive Value

POCI – Posterior Circulation Infarct

RAWOD – Regional Attenuation Without Delta

SLS – Stroke Levity Score

TACI – Total Anterior Circulation Infarct

TOAST - Trial of ORG 10172 in Acute Stroke Treatment

UCH – University College Hospital

WHO – World Health Organization

x

SUMMARY

BACKGROUND:

Stroke is a leading cause of morbidity and mortality in adults in the productive ages that contribute

to the work force of the society. Prevention, early detection, continuous and emergent monitoring

of cerebral physiological activities and aggressive intervention to treat may reduce the

unacceptably high mortality rate of stroke in our environment. Electroencephalography’s (EEG)

close correlation with cerebral metabolism and its ability to detect brief transient alterations in

cortical function make are indicators to its possible usefulness. The aim of the study is to determine

the frequency and prognostic role of abnormal electroecenphalograhic patterns and its relationship

with early onset seizures in acute stroke

METHODOLOGY:

Adult patients with acute stroke who presented to the University College Hospital and who met

the inclusion criteria were recruited consecutively after obtaining written informed consent.

Cranial computerized tomography was done for all cases recruited within 72 hours of stroke onset.

Ischaemic stroke was defined by brain CT scan (normal brain CT scan or recent infarct in the

clinically relevant area on scan performed within 3 days or 72 hours of stroke onset). Trial of ORG

10172 in Acute Stroke Treatment (TOAST) classification was used in phenotyping of ischaemic

stroke into large vessel atherosclerosis, cardioembolic, lacunar and undetermined. Stroke severity

was determined using the National Institutes of Health Stroke Scale (NIHSS) and patients’

functional outcomes were assessed at 72hours, 14days and 30 days using Modified Rankin Scale

(MRS). EEG was obtained in all cases and repeated at 72 hours, 7 days, 14 days and 30 days.

Epileptiform patterns were defined as focal spikes, focal sharps, sharps with accompanying slow

waves and spikes with accompanying slow waves. Pearson chi square test was used to assess

association between stroke characteristics, stroke type, EEG characteristics and stroke severity.

xi

The positive predictive and negative predictive values of EEG in determining stroke outcome were

calculated.

RESULTS: One Hundred and sixty participants were recruited into this study comprising eighty

consecutive stroke patients and eighty controls which were adequately matched for age and sex.

The cases recruited were 39 males (48.8%) and 41 females (51.2%) with mean age was 57.6 ±

14.6, while controls had equal numbers of male and females with mean age of 54.9 ± 12.6.

Background alpha rhythms and beta rhythm were more common in controls than in cases, while

delta rhythm and theta rhythm were seen more in cases than controls. Among the stroke patients,

alpha and beta background rhythm were on increase, while delta and theta rhythm decreased in the

course of 30-day monitoring. Among ischeamic stroke patients that had good outcome, presence

of slowing was on decline from 87.1% at presentation to 66.7% at 30days but there was only

marginal decline from 83.3% to 71.4% among ischeamic stroke cases with poor outcome. Alpha

rhythm was seen more in those with good outcome (Ischaemic 29.6%, haemorrhagic 37.5%)

compared to those with poor outcome (Ischaemic 14.3%, haemorrhagic 37.5%) at day 30

respectively. Beta rhythm was seen more in those with poor outcome (Ischaemic 42.5%,

haemorrhagic 25%) compared to those with good outcome (Ischaemic 33.3%, haemorrhagic

20%)at day 30 respectively. The positive predictive value (PPV) of slowing decreased marginally,

while that of alpha wave decreased by 50% from presentation till 30days. The PPV of Beta wave

increased from 0.14% to 0.17 % (Ischaemic), 0.33% to 0.4% (haemorrhagic) thus, predictive of

poor outcome. The negative predictive value of slowing, alpha wave and beta wave was on linear

increase from presentation to 30days. Epileptiform discharges were observed only in 31.6% of

cases at presentation, 32.9% at 72hrs, 62.7% at 7days, 57.9% after 14 days and in 44.4% at day

30.

xii

CONCLUSION: Alpha and beta rhythm increased while delta and theta rhythm decreased in the

course of 30-day monitoring. The PPV of alpha wave and slowing was maximal at presentation

and decreased within 30days. The PPV of beta wave increased marginally, thus predictive of poor

outcome. The NPV of alpha wave and beta wave in predicting poor outcome was increased from

presentation to 30days. The presence of alpha rhythm excluded poor outcome and predicted good

outcome while beta rhythm predicted poor outcome but did not exclude good outcome. The

proportion of epileptiform activities seen on EEG were more than the cases of seizures in this

study.

1

CHAPTER ONE

1.0 INTRODUCTION

Stroke can be defined as rapidly developing signs of focal or global disturbance of cerebral or

intracranial neuronal function with symptoms lasting for more than 24 hours or leading to the death

of the patient with no apparent cause other than that of vascular origin.1 The classic definition is

mainly clinical and does not account for advances in science and technology thus the Stroke

Council of the American Heart Association/American Stroke Association convened a writing

group to develop an expert consensus document for an updated definition of stroke for the 21st

century.2 Based on this, Central Nervous System infarction is now defined as brain, spinal cord,

or retinal cell death attributable to ischemia, based on neuropathological, neuroimaging, and/or

clinical evidence of permanent injury.2

Silent central nervous system infarction defined as imaging or neuropathological evidence of CNS

infarction, without a history of acute neurological dysfunction attributable to the lesion but

ischaemic stroke specifically refers to central nervous system infarction accompanied by overt

symptoms.2

Stroke caused by intracerebral haemorrhage is defined as rapidly developing clinical signs of

neurological dysfunction attributable to a focal collection of blood within the brain parenchyma or

ventricular system that is not caused by trauma, while silent cerebral is regarded as a focal

collection of chronic blood products within the brain parenchyma, subarachnoid space, or

ventricular system on neuroimaging or neuropathological examination that is not caused by trauma

and without a history of acute neurological dysfunction attributable to the lesion.2

Definition of stroke caused by subarachnoid haemorrhage is that of rapidly developing signs of

neurological dysfunction and/or headache because of bleeding into the subarachnoid space (the

space between

2

the arachnoid membrane and the pia mater of the brain or spinal cord), which is not caused by

trauma.2

Definition of stroke caused by cerebral venous thrombosis is that of infarction or in the brain,

spinal cord, or retina because of thrombosis of a cerebral venous structure. Symptoms or signs

caused by reversible edema without infarction or do not qualify as stroke.2

Stroke is the leading cause of neurological disability in adults and also a leading cause of morbidity

and mortality in adults in the productive ages that contribute to the work force of the society.3–5

The outcome following stroke is influenced by several factors such as subtype, severity of stroke,

the predisposing factor(s), associated factors, presence of complications, access to specialist care,

and availability of stroke care facility.6,7

Neuroimaging is mandatory for the avoidance of stroke misdiagnosis and for distinguishing it from

TIAs and stroke mimics (subdural hematoma, brain abscess, and brain tumor).2,8

Computerized Tomography (CT) is very sensitive for identifying acute and is considered the gold

standard; gradient echo and T2 susceptibility-weighted MRI are as sensitive as CT for detection of

acute blood and are more sensitive for identification of prior .9,10

There is evidence that electroencephalography (emergency and continuous) adds value to early

diagnosis, outcome prediction, patient selection for treatment, clinical management, and seizure

detection in acute ischaemic stroke and also vasospasm prediction and detection in subarachnoid

haemorrhage .11–13 Because of its sensitivity to metabolic and ionic disturbances related to

ischemia, electroencephalography potentially is a useful tool for acute stroke detection, monitoring

of the affected tissue and prognosis.14

Iranmanesh in a study done at Taiwan, showed that electroencephalography abnormality was

positively correlated with poor prognosis in patients with ischaemic stroke.15

3

Detection of seizures, confirmation of diagnosis, intraoperative monitoring, prognosis and level of

consciousness are areas of proven usefulness of electroencephalography in the evaluation of acute

stroke.12,13,15–17 Electroencephalography can be altered in response to the presence of seizures or

periodic discharges, changes in intracranial pressure or in the setting of systemic illness, sedatives,

narcotics, temperatures and glucose level.13,18

Several scales have proven reliability and validity in stroke trials, including the National Institutes

of Health Stroke Scale (NIHSS), Modified Rankin scale (MRS), Barthel Index (BI), Glasgow

outcome scale (GOS), and stroke levity scale.19–22 The Stroke Levity Scale showed significant

correlation to the NIHSS, Modified Rankin Scale and Health-Related Quality of Life in Stroke

Patients (HRQOLISP) questionnaire.22

1.1 RATIONALE

Stroke is increasingly contributing to the burden of disease worldwide and becoming a major cause

of death and morbidity in African population.23 Electroencephalography close correlation with

cerebral metabolism and its ability to detect brief transient alterations in cortical functions are

indicators of its possible usefulness. The use of emergency EEG in acute stroke can reveal a

distinctive EEG pattern that may be useful in prediction of functional outcome in acute

stroke.11,12,24 Electroencephalography has been shown to be a reliable marker of the decline in

neuronal integrity associated with a decline in blood flow.14,16 Moreover, there is a paucity of

published data on role of electroencephalography in acute stroke patients in our environment. This

study will be the first of its kind in Nigeria and add to the existing literature on stroke in the country

and globally.

4

1.2 AIM AND OBJECTIVES

1.2.1 General Objective

To determine the frequency and prognostic role of abnormal electroecenphalograhic patterns in

acute stroke at UCH, Ibadan.

1.2.2 Specific Objectives

1. To determine predictive value of electroencephalography wave patterns in acute

ischaemic stroke

2. To determine predictive value of electroencephalography wave patterns in acute

haemorrhagic stroke

3. To determine any relationship between early onset seizures and

electroencephalographic wave patterns in acute stroke.

5

CHAPTER TWO

2.0 LITERATURE REVIEW

2.1 Burden of Stroke

Worldwide, stroke remains a major cause of death, despite advances in its management.23,25,26

_ENREF_38The global estimates of disease burden indicate that over the next two decades,

cerebrovascular disease will continue to rank amongst the top four leading causes of death, even

in low-income countries.1,22,25

Previous reports detailed an increasing incidence but these were hospital-based studies, they could

be inaccurate and probably represent the tip of the iceberg.4,27,28 The current prevalence of stroke

in Africa is 114 to 1000 per 100 000 while the 30-day case fatality rate is as high as 40%.23,28,29

2.2 Prevalence

An earlier door to door rural community-based study of neurological disorders in south-western

Nigeria, conducted by Osuntokun et al at Aiyete, Igboora three decades ago, had stroke prevalence

of 58 per 100 000 reported. A study by same group at Udo, reported prevalence of 68/ 100

000.23,30,31 In a similar door-to-door survey done on a random sample of 60 820 rural Ethiopians,

stroke prevalence was 15 per 100 000 among people aged 28—85 years (crude prevalence 15 per

100 000).23

The largest study of the prevalence of disabling hemiplegic stroke in sub-Saharan Africa was done

in 1994 in the rural Hai district of Tanzania with crude prevalence of 127/100,000 while the age-

standardized (to the Segi world population) prevalence of disability resulting from stroke was 154

per 100 000 in men and 114 per 100 000 in women over 15 years of age.32,33

6

In 2001, the Southern Africa Stroke Prevention Initiative (SASPI) team did a stroke prevalence

study in Agincourt, a rural region in South Africa and reported stroke prevalence rate of 300 per

100,000 in people over the age of 15 years.34

More recently, Danesi et al reported an overall crude prevalence rate of 1.14/1000 in an urban

mixed income community in Lagos Nigeria and concluded that stroke prevalence rates in urban

Nigeria are lower than those in most developed countries, though the lower rates may be related

to lower incidence and higher stroke mortality in developing countries.35 The prevalence of stroke

is less than half that found in high-income regions with age-standardized rates of 114—315 per

100 000 for women and 154—281 per 100 000 for men, but disabling stroke prevalence may be at

least as high as in high-income areas.23 Without community-based incidence studies with follow-

up, determining whether the low prevalence results from low incidence or high case fatality or

both is impossible.

2.3 Incidence

2.3.1 Community-based incidence

Data from Ibadan Stroke Registry, from April 1973 to March 1975 described as first in Africa

reported an incidence rate of 26 per 100,000(13 per 100,000 in females and 25 per 100,000 in

males) and this was the first serious attempt at a community-based incidence study from sub-

Saharan Africa by Osuntokun and colleagues.23,25,36 The Tanzania Stroke Incidence Project (TSIP)

recorded crude incidences in Hai and Dar-es-Salam district of Tanzania as 94.5/100,000 and

107.9/100,000 respectively, the reported age standardized incidence rates to World Health

Organization world population were 108.6 and 315.9/100,000 respectively.

In a recent prospective community-based epidemiological stroke study by Danesi et al in Lagos,

Nigeria, an incidence rate of 25.2 per 100, 000 ( 28.3 per 100 000 in males and 21.3 per 100 000

in females) was reported.37

7

2.3.2 Hospital-based incidence

Most studies of stroke in sub-Saharan Africa are hospital-based. Typically, these studies

documented the proportion of patients admitted to medical and neurology services who had had

strokes38. Hospital admissions for acute stroke were monitored over a twelve-month period by

Rosman in Pretoria, South Africa. Out of a population at risk of 114931, there were 116 cases,

giving an overall incidence of 101 per 100,000 population per year over age twenty23.

Data from all four general hospitals in Harare, Zimbabwe, with a population of 887 768 black

Zimbabweans reported the crude stroke incidence to be 31 per 100 000 per year and when

standardised to the world population, the incidence was 68 per 100 00038.

The frequencies in Nigeria hospital populations varied from 0.9% to 4.0% and stroke accounted

for 0.5% to 45% of neurological admissions.5

The phenomenal increase in the incidence of stroke in Nigerian Africans and in other developing

countries has been described as “the Epidemiologic Transition” from infectious and nutritional

disease burden to diseases related to hypertension, high-fat diets, cigarette smoking, and sedentary

lifestyle6,39.

2.4 RISK FACTORS

Risk factors are divided into those that are modifiable and nonmodifiable.40 Non modifiable risk

factors for stroke include age, sex, race or ethnicity, and heredity.23 Men have greater stroke

incidence than women, although the absolute number of women having a stroke each year is

greater because women live longer than men.41,42 At older ages, the difference in the relative risk

between men and women diminishes.41 Hereditary factors contribute to stroke risk, although

teasing apart risk due to genetic mutations from risk due to shared familial exposures remains

challenging.43 While certain single gene disorders are associated with ischaemic and haemorrhagic

strokes as either a primary phenomenon or as part of a spectrum of illness, most genetic disorders

8

are a relatively rare cause of stroke.41 Phosphodiesterase 4D gene (PDE4D),5-lipoxygenase

activating protein (ALOX5AP) Chromosome 9p21, located near the genes CDKN2A and

CDKN2B, Chromosome 5 (Iceland) were related to ischaemic stroke type only.43,44

Cavernous haemangioma is linked to KRITI gene mutation, NOTCH 3 gene mutation in

CADASIL (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and

Leucoencephalopathy), while APOE lipoprotein mapped to chromosome19 is linked to cerebral

amyloid angiopathy.44

An international study of risk factors for stroke (INTERSTROKE study), revealed that

approximately 90% of strokes could be explained by 10 risk factors: hypertension, diabetes,

cardiac causes, current smoking, abdominal obesity, hyperlipidemia, physical inactivity, alcohol

consumption, diet, and psychosocial stress and depression.29,40,45 Hypertension is the single most

important modifiable, treatable risk factor for all types of stroke.29,45 The risk of first stroke

increases by more than 50% for an increase in diastolic BP of 10mmHg above 90mmHg.46

Structural hypertensive remodeling leads to narrowing and thickening in resistance vessels through

processes of lipohyalinosis and segmental arterial disorganization.29 Development of

microaneurysms in the deep hemispheric tissue, impaired perfusion resulting in white matter

diseases, lengthy cerebral vasodilation with formation of cerebral oedema and rise in intracranial

pressure associated with acute BP rise are the processes by which hypertension can cause and

worsen stroke. Several surveys have demonstrated a very low prevalence of hypertension

awareness and control in Africa.29,47–49 Observational studies have shown an increased risk of

stroke associated with all degrees of hypertension, isolated systolic hypertension, and diastolic

blood pressure.40,41,45 Recent analyses have shown that the variability in blood pressure

measurements, both from visit to visit and even among separate measurements taken within a

single visit, is associated with increased risk of stroke.27

9

Diabetes has been identified as an independent risk factor for thromboembolic stroke in previous

studies.41 Patients with impaired fasting glucose also have double risk of brain infarction than

people who are nondiabetic.50 Even among those without frank diabetes, insulin resistance appears

to predict risk of first stroke.50 Diabetes causes an increased susceptibility to atherosclerosis and

increased prevalence of atherogenic risk factors such as hypertension, obesity and abnormal

lipids.41,50

According to International Diabetes Federation (IDF), the current estimated prevalence rate of type 2

diabetes in Africa is about 2.8%.29 Currently, there are 10.4 million individuals with diabetes in sub-

Saharan Africa, representing 4.2% of the global population with diabetes.29

There is a significant relationship between total and low density lipoprotein cholesterol and a

protective influence of high density lipoprotein, cholesterol in stroke.41,50 Dyslipidemia has

emerged as an important risk factor in Africa. For example, Norman and colleagues found that

high cholesterol levels (≥ 3.8 mmol/l) accounted for 59% of ischaemic heart disease and 29% of

ischaemic stroke burden in adults aged 30 years and over.51 The prevalence of dyslipidemia,

especially cholesterol has been shown to vary across regions in Africa.51 In a study of healthy

workers in Nigeria, 5% of the study population had hypercholesterolaemia, 23% elevated total

serum cholesterol levels, 51% elevated low-density lipoprotein (LDL) cholesterol levels and 60%

low high-density lipoprotein (HDL) cholesterol levels, with females recording better overall lipid

profiles.50 The effects of lipids probably differ for haemorrhagic and ischaemic strokes, and even

among ischaemic subtypes.41,50 There is a positive relationship between total and low density

lipoprotein cholesterol and a protective influence of high density lipoprotein cholesterol on

extracranial carotid atherosclerosis.41,50

10

Cardiac diseases are a well-recognized cause of embolic cerebral infarction. Certain cardiac

diseases, such as atrial fibrillation (AF), recent myocardial infarction, significant left ventricular

dysfunction with mural thrombus, and valvular heart disease, are proven causes of stroke.41

Others, including patent foramen ovale (PFO), mitral valve strands, aortic arch atheroma, and left

ventricular hypertrophy, have more equivocal epidemiologic evidence.41 Patent foramen ovale has

been recognized as a potential cause of stroke for a long time.45 Many studies have shown

increased prevalence of PFO in patients with cryptogenic stroke compared with controls and those

with strokes of other known causes.41,45

A J-shaped association curve was suggested for the relation of alcohol consumption and ischaemic

stroke while heavy consumption of alcohol increases the risk for brain .41,52–54 Alcohol relationship

with stroke is dose dependent.29 In a meta-analysis of 25 ischaemic stroke studies, 11 intracerebral

and subarachnoid haemorrhage studies. It was demonstrated that light and moderate consumption

of alcohol was associated with lower risk of ischaemic stroke while high and heavy drinking was

associated with high risk.54 Furthermore, in the haemorrhagic stroke subtype light, moderate and

high alcohol consumption were associated with increased risk of intracerebral haemorrhage .54

Reynolds et al demonstrated that consumption of 60grammes of alcohol per day was associated

with increased relative risk of total stroke, while consumption of less than 12grammes or between

12grammes to 24grammes of alcohol per day was associated with a reduced relative risk of

ischaemic stroke.55 A study by Casolla and colleagues demonstrated that heavy alcohol intake

defined as consumption of more than 300grammes in a week was associated with occurrence of

intracerebral haemorrhage at a young age.56

11

2.5 Case fatality

Bamford and associates in a prospective community based study as part of the Oxfordshire

Community Stroke Project reported a case fatality rate (CFR) of 19%.57 The 30 day case fatality

rate for patients with cerebral infarction was 10% (57 of 545), primary intracerebral haemorrhage

was 52% (34 of 66), subarachnoid haemorrhage was 45% (15 of 33) and for those of uncertain

pathological type 74% (23 of 31).57,58 Rosman found a higher case fatality in patients with cerebral

(58%) than in those with ischaemic stroke (22%) but patients who died before they had a CT scan

were assumed to have had an intracerebral haemorrhage, which would have increased the

estimate.59

Community-based case fatality study are rare in sub- Saharan Africa but data from the Ibadan

stroke registry reported a 3-week case fatality of 35% for all stroke and highest for intracerebral

and subarachnoid haemorrhage at 61% and 62% respectively.36 Stroke types, other than

subarachnoid haemorrhage, must have been diagnosed unreliably without CT scanning.

Furthermore, the investigators had great difficulty with follow-up and at 3 months only 76 of 318

patients could be traced36.

A hospital-based study without cranial computed tomograghy done in the Gambia with long-term

follow-up over 4 years to determine case fatality, time to death, and likely causes of death reported

case fatality of 27% and 44% at 1 month and 6 months respectively, and 75% of patients had died

by the final follow-up.60 At the end of follow-up, the cause of death in all patients were the initial

stroke in 61%, further stroke in 7%, infection in 12%, and another vascular cause (hypertensive

encephalopathy) in only one patient. Remarkably, only four patients were lost to follow-up60. A

similar hospital based study among comatose stroke patients in Nigeria by Obiako et-al revealed

intracerebral haemorrhage (78.8%) and large cerebral infarction (21.2%) as the subtypes seen with

12

respective case fatalities of 69.7% and 13.6% at 4 weeks6 Stroke constituted 1.8% of all deaths at

t emergency unit and the case fatality was 9% at 24 hours, 28% at 7 days, 40% at 30 days, and

46% at 6 months in a 10 year review in southwest Nigeria4.

A comparison of hospital and community based case fatality rate data between developing

countries like ours and developed nations revealed about 3 to 8 times increase in the case fatality

in developing nations compared to developed nation rate of 12% and 19% for first-ever stroke

within the first 7 days and at 1 month, respectively6.

2.6 Diagnosis

Therapeutic decisions regarding management of stroke require accurate diagnosis of stroke types

and exclusion of mimics61. Categorization of stroke into ischaemic or haemorrhagic stroke can be

done in accordance with neuroimaging, WHO stroke criteria, and other weighted scoring scale62.

Imaging techniques, already alluded to, continue to enhance the diagnosis of stroke patients; CT

scanning demonstrates and accurately localizes even small , haemorrhagic infarcts, subarachnoid

blood, clots in and around aneurysms, regions of infarct necrosis and arteriovenous

malformations63. Magnetic resonance imaging (MRI) also demonstrates these lesions and in

addition reveals flow voids in vessels, hemosiderin and iron pigment, and the alterations resulting

from ischaemic necrosis and gliosis. MRI is particularly advantageous in demonstrating small

lacunar lesions deep in the hemispheres and abnormalities in the brainstem (a region obscured by

adjacent bone in CT scans)63,64.

In the absence of CT scan, weighted clinical scoring systems may be used for improved diagnostic

gain62. The diagnostic accuracy of the WHO criteria for the acute stroke syndrome is higher than

that of the Siriraj stroke score62 Siriraj Stroke Scale had sensitivity of 50% for and 58% for

infarction with an overall accuracy of 54.2% while WHO criteria for the acute stroke syndrome

had sensitivity of 73% for and 69% for infarction with an overall accuracy of 71%.62

13

Evaluation of acute cerebral ischemia with non -contrast CT may be a difficult task as often only

subtle changes may be present. These early ischaemic changes on cranial CT have been the topic

of much debate in the medical literature, particularly as they relate to selection of patients for

intravenous tissue plasminogen activator65.

In recent years, the Alberta Stroke Program Early Computed Tomography Score (ASPECTS) has

been adopted by many centres to describe the extent and location of ischaemic changes on

computerized tomography64,66. Obscuration of the lentiform nucleus; loss of insular ribbon; loss

of differentiation between cortical gray and subcortical white matter; focal swelling; hyperdense

middle cerebral artery or dot signs are signs of early Ischaemic changes.64–66 Hyperdense artery

sign can be categorized as proximal hyperdense middle cerebral artery sign and distal hyperdense

middle cerebral artery sign (dot sign) on non-contrast CT according to the site of occlusion.67,68

The hyperdense middle cerebral artery sign is defined as an MCA denser than its counterpart and

it is a well-recognized indicator of proximal thromboembolism within the MCA (M1 segment).67,69

The distal hyperdense MCA sign represents a thromboembolus within a segmental branch of the

MCA located within the Sylvian fissure (M2 segment).68,69 _ENREF_78 It is defined as the

hyperdensity of an arterial structure seen as a dot in the sylvian fissure relative to the contralateral

side or to other vessels within the sylvian fissure.67,69

2.7 Cerebral Blood Flow Changes and Electroencephalography

The difference in tissue outcome following arterial occlusion is based on the concept that cerebral

blood flow thresholds exist, below which neuronal integrity and functions are differentially

affected.18,70 There are three potential mechanisms of ischaemic stroke: thrombosis, embolism and

hypoperfusion (haemodynamic failure),while these are inter-related, each mechanism can produce

distinct clinical syndromes71.

14

The effect of a localized blood vessel occlusion will depend on the following factors: the area of

brain supplied by the vessel, the nature of the occlusion, the time that the occlusion lasts, its degree

and anatomy of collateral circulation.72,73

Neuronal cell death occurs as a result of two main mechanisms: necrosis and apoptosis. Necrosis

occurs predominantly in the hyperacute stage within the ischaemic core. It occurs mainly as a

consequence of disruption of cellular homeostasis due to energy failure and is accompanied by

cellular swelling, membrane lysis, inflammation, vascular damage, and oedema formation.18,71,74

Apoptosis is the main mechanism of neuronal injury in the penumbra where, because of the

milder degree of ischemia, sufficient energy is produced to allow for expression of new proteins

that mediate cell death through an ordered and tightly controlled set of changes in gene expression

and protein activity.71,75

Studies of CBF and cerebral rate of oxygen metabolism (CMRO2) using Xenon computed

tomography and positron emission tomography (PET) in ischaemic stroke have demonstrated that

regional electroencephalography changes also reflect the coupling of cerebral blood flow and

metabolism.16 During recovery from stroke, partial dissociation from cerebral blood flow and

oxygen content occur and under these circumstances, the electroencephalography more closely

reflects cerebral metabolism than does the cerebral blood flow, making it potentially more

valuable as a measure of neuronal function13.

The brain accounts for only 2% of body weight, it uses 20% of cardiac output when the body is at

rest and constant supply of ATP is essential for neuronal integrity and this process is much more

efficient in the presence of oxygen. Although ATP can be formed by anaerobic glycolysis, the

energy yielded by this pathway is small and it also leads to the accumulation of lactic acid.76 The

15

brain needs and uses approximately 500 mL oxygen and 100 mg glucose each minute, hence the

need for a rich supply of oxygenated blood containing glucose.16

Cerebral blood flow (CBF) is normally approximately 50 - 55mL/minute for each 100 g of brain;

while neuronal functionality is maintained at flow rate 23mL/100g/min. Adequate compensation

can be made even if blood flow is reduced to approximately 20–25 mL per 100 g/minute by

autoregulatory mechanism.70,73,77

When CBF falls below 18 – 20ml /100 g/min, oxygen extraction starts to fall and changes are

detected on electroencephalography which becomes reduced in amplitude. At levels below 10 -

12mL/100 g/minute, cell membrane functions are severely disrupted. The threshold for

maintaining morphological neuronal integrity is 6 – 8ml/100g/min below which neuronal death is

irreversible.77

Infarction may not occur for hours at this degree of flow limitation and some electrical activity

(mostly delta frequencies) may be seen, but as the cerebral blood flow continues to decrease toward

the infarction threshold (10–12 ml/100 g/min and below), the EEG becomes isoelectric and

cellular damage becomes irreversible74,77. A CBF of 6 to 8 mL/100 g/min causes marked ATP

depletion, increase in extracellular K, increase in intracellular calcium, and cellular acidosis,

leading invariably to histologic signs of necrosis.75

Calcium influx is further enhanced by impairment in the energy-dependent reuptake of excitatory

amino acids, especially glutamate, and by release of excitatory amino acids into the extracellular

space. An increase in extracellular glutamate leads to increased calcium influx, through increased

stimulation of the NMDA or non-NMDA.73

16

At the same time, sodium and chloride enter the neuron which create osmotic gradients, leading to

oedema, which is predominantly cytotoxic and can further diminish perfusion in regions

surrounding the core.70,72,75

The accumulation of intracellular calcium leads to a series of events at both the cytoplasmic and

nuclear levels that result in cell death through several mechanisms: activation of enzymes that

degrade cytoskeletal proteins; activation of lipoxygenase, cyclooxygenase, xanthine oxidase and

nitric oxide synthase with resultant accumulation of highly cytotoxic oxygen free radicals.18,71,75,78

2.8 Concept of Ischaemic Penumbra

Ischaemic core corresponds to cerebral blood flow values of less than 7 mL/100g/min to 12

mL/100 g/min..70 Ischaemic penumbra corresponds to a high CBF limit of 17 - 22 mL/100 g/min

and a low CBF limit of 7 to 12 mL/100 g/min18,70. Salvaging this tissue by restoring its flow to

non-ischaemic levels is the aim of acute stroke therapy.63,70,75,79

Oligemia represents from the normal range down to around 22 mL/100 mg/min.16

Advanced MRI techniques, particularly perfusion and diffusion-weighted imaging, have been the

cornerstone of the concept of Ischaemic penumbra.64,80

Restriction of acute stroke therapy aimed at vessel recanalization to 3 hours from onset of

symptoms for IV thrombolysis and 4.5 hours for intra-arterial thrombolysis is based on the concept

that the ischaemic penumbra has a short lifespan, being rapidly incorporated into the core within

hours of the ictus tolerance to hypoxia by 25 to 30 percent.81,82

These biochemical, cellular, and CBF findings enable one to conceptualize manoeuvres for

restoring blood flow within the marginally hypoperfused zone and salvaging brain tissue,

particularly under conditions of partial ischemia.70,76,78

17

2.9 Stroke Scales

The NIHSS has been repeatedly validated as a tool for assessing stroke severity and as an excellent

predictor of patient outcomes whereas the Barthel index is useful for planning rehabilitative

strategies.19,81

Due to the NIHSS’s focus on cortical function, patients with cortical stroke tend to have worse

baseline scores. Approximately 98% of humans have verbal processing taking place in the left

hemisphere, indicating that the NIHSS places more value on deficits in the left hemisphere19,81.

The modified Rankin scale ( MRS) and the Glasgow outcome scale (GOS) provide summary

measures of outcome and might be most relevant to clinicians and patients considering early

intervention82. The MRS, a clinician-reported measure of global disability, is widely applied for

evaluating stroke patient outcomes and as an end point in randomized clinical trials90.

The Stroke Levity Scale (SLS) is a concise, valid, and reliable stroke impairment scale that can be

used routinely to monitor outcome.22 It is the summation of the best motor power in dominant

hand/upper limb, best motor power in the weaker lower limb, mobility score minus score of one

in those with aphasia.22 It takes less than 2 minutes to administer the SLS in contrast to 8 min for

the NIHSS22 The NIHSS neurologic scale appears more sensitive than the Barthel Index or

modified Rankin scale allowing smaller sample sizes or greater statistical power. The Barthel

Index (BI) and the Modified Rankin Scale (MRS) are commonly used scales that measure

disability or dependence in activities of daily living in stroke victim82.

2.10 Factors Affecting Prognosis and Outcome in Stroke

High blood glucose on admission predicts an increased risk of mortality and poor outcome in

patients with and without diabetes83. Admission hyperglycaemia is a significant predictor of short-

term case fatality but not poor functional outcome in first ever acute ischaemic stroke in

18

Nigerians.83 Fever is associated with increased morbidity, mortality and unfavourable outcome7,9.

The incidence of fever after basal ganglionic and lobar ICH is high, especially in patients with

intraventricular haemorrhage 9. Fever occurs in 25% to 50% of patients after acute ischaemic

stroke and is more common with more severe deficits.9 Although mortality appears to be lower

and long-term outcomes better for those patients who are hypothermic on admission, the effect of

maintained or induced hypothermia on outcome after acute ischaemic stroke is questionable.9 A

major risk to consider is that such hypothermia might suppress or mask a fever caused by

infection.9

A few studies have examined the role of iron in patients with intracerebral haemorrhage and

reported that high serum ferritin levels are associated with poor outcome after intracerebral

haemorrhage and correlate with the peri-hematoma oedema9.Age above 39 years, male gender,

systemic hypertension, early onset of coma after stroke, aspiration pneumonia, recurrent seizures,

hyperglycemia, and sepsis have been found to be associated with poor stroke outcome6,84.

2.11 EEG CHANGES IN ACUTE STROKE

Pyramidal neurons found in layers III, V, and VI are exquisitely sensitive to conditions of low

oxygen, such as ischemia, thus leading to many of the abnormal changes in the patterns seen on

EEG which are closely tied to cerebral blood flow16 The basic repertoire of EEG changes in

ischemia was delineated as decreased beta-range fast activities; increased slowing in theta and

delta ranges; loss of normal background rhythms such as the alpha rhythm and decreased overall

amplitude13. Marked focal slowing and attenuation of background activity occur with an

intracerebral haemorrhage .16 If there is a shift across the midline or compromise of the midline

structures, intermittent rhythmic delta activity may also be present.85 After controlling for age and

Hunt & Hess grade in subarachnoid haemorrhage on admission, poor outcome was associated with

the presence of periodic lateralized epileptiform discharges (PLEDS), absent EEG reactivity,

19

generalized periodic epileptiform discharges bilateral independent PLED or non-convulsive status

epilepticus.86

Brain function is represented on EEG by oscillations of certain frequencies. Slower frequencies

(typically delta [0.5–3 Hz] or theta [4–7 Hz]) are generated by the thalamus and by cells in layers

II-VI of the cortex while faster frequencies (or alpha, typically 8–12 Hz) derive from cells in layers

IV and V of the cortex16. All frequencies are modulated by the reticular activating system, which

correspond to the observation of reactivity on the EEG.16

Cerebral blood flow is normally approximately 55mL/minute for each 100g of brain, oxygen

consumption is about 3.5 mL/ 100 g of brain/min (49 mL/min for the whole brain) in an adult

which is approximately 20% of the total body resting oxygen consumption.16 EEG would slow

down when mean CBF falls below 23 mL/100 g/min, while at values below 15 mL/100 g/min the

EEG would become flat.16,70. The threshold for maintaining morphological integrity of the neuron

is 6- 8ml/100g/min, when the value goes below this, neurons die irreversibly because of excessive

ATP depletion.70,71 From carotid endarterectomy and cerebral-blood-flow studies,

electroencephalography has been shown to be a reliable marker of the decline in neuronal integrity

associated with a decline in blood flow14,16.

2.12 PREDICTIVE VALUE OF EEG CHANGES IN ACUTE STROKE

Recognition of changes in background EEG pattern provide valuable prognostic information and

also improves prediction of functional outcome in patient with a severe neurological deficit in

acute stage of cerebral ischemia and critically ill patients.12,86–88 While patterns like lack of delta

or the presence of faster frequencies within 24 hours, intermittent theta and/or delta activity on the

side of the infarction correlate with a good outcome12,17,24,89. The presence of unilateral prominent

continuous polymorphic delta slowing, decreased alpha, Regional Attenuation Without Delta

(RAWOD), slowing or depression of the alpha or beta activity and periodic lateralized epileptiform

20

discharges (PLEDs) add significantly to clinical prediction of poor outcome11,24,89. A study of

emergency EEG in 48 patiens with acute ischaemic event by Jordan and colleagues, revealed a

distinctive EEG pattern of regional attenuation of all frequencies without supervening delta in 18

subjects with infarcts in the ICA/MCA distribution.11

RAWOD can identify patients with massive acute stroke earlier than CT or MRI11,24. It was

submitted that RAWOD was specific for people with large infarct.24 There was no false positive

as all patients with RAWOD had severe clinical deficit but over 50% of the participant with

ischaemic stroke did not show RAWOD.24 Furthermore, comparison of RAWOD patients

presenting less than 3 hours after symptom onset and 3 to 24 hours after symptom onset, revealed

that 40.9 % of patients who presented less than 3 hours had RAWOD.24 All patients with RAWOD

had extremely severe clinical deficits, with a mean NIHSS score of 31.24 RAWOD are maximal

and persist in the frontal, central, parietal, and temporal derivations, which predominantly reflect

the ICA/MCA vascular distributions but relative sparing of activity in the occipital derivations,

which predominantly reflects the posterior cerebral vascular distribution.24

Sixty one of one hundred and thirty patients studied by Garcia-Morales et al had Periodic

Lateralizing Epileptic Discharge (PLED) which were associated with an acute process and

occurred early during the course of the illness in all patients studied and were usually associated

with structural lesions, with stroke being the main aetiology89. Also, epileptiform electrical activity

occurs in 10%to 20% of stroke which are associated with seizures and the focus is usually

demonstrable on an electroencephalogram86,90–92. Seizures occur more commonly with

haemorrhagic stroke than with ischaemic stroke and patients with a disabling cortical infarct or a

cortical are more likely to have seizures after stroke; those with late-onset seizures are at greater

risk of epilepsy.91–93

21

Diffusion-weighted magnetic resonance images (DWI MRI) are capable of detecting changes in

cerebral blood flow within 11 to 30 minutes64,94,95. In contrast, electroencephalography detects

changes at the same CBF within seconds and allows for continuous monitoring of these changes

over time16,18. This can be crucial for detecting evolving ischaemic changes when the cranial CT

is negative during early infarction, or when there is a mismatch between DWI MRI and the clinical

examination95_ENREF_29.

22

CHAPTER THREE

METHODOLOGY

3.1 Study Site

This study was carried out in the medical wards of the University College Hospital (UCH), Ibadan,

Oyo state.

3.2 Study Design

This study utilized a case control design involving acute stroke patients and apparently healthy

subjects.

3.3 Period of Study

The study was conducted over a period of months between 24/4/2013 and 23/4/2015

3.4 Study Population

All consenting patients admitted to medical wards in UCH who were diagnosed with acute stroke

were recruited to participate in the study.

3.5 Cases

3.5.1 Inclusion Criteria

1. History, physical examination and neuroimaging (CT and/or MRI) confirmation of stroke

2. Presentation within 3 days of ictus

3.5.2 Exclusion Criteria for Cases

1. Background history of seizure disorders

2. Stroke presentation > 3days of stroke onset

3. Concurrent primary cerebral disorder e.g. Pre-existing Parkinson’s disease, Brain tumour,

subdural haematoma.

4. Inability to provide an informed consent and no surrogate available

5. Patient on sedatives

23

3.6 CONTROL

3.6.1 Inclusion Criteria

1. The healthy subject matched for age and sex.

2. No background history of seizure disorder.

3. No background history of brain tumor.

4. No background history of use of psychoactive substances

3.6.2 Exclusion Criteria

1. Background history of seizure disorders

2. Previous history of stroke

3. Concurrent primary cerebral disorder e.g. Pre-existing Parkinson’s disease, Brain tumour,

subdural haematoma.

3.7 Sample Size Determination

Using Peacock formula for case control studies:

N = 2 (Zα + Z1-β)2 [P1 (1- P1) + P2 (1- P2)]

(P1 – P2)2

Where,

N = minimum sample size for cases or controls

Zα = Standard normal deviate at 5% level of significance = 1.96

Z1-β = Standard normal deviate corresponding to a power of 80% = 0.84

P1 = Prevalence of abnormal EEG in patients with stroke = 50%

P2 = Prevalence of abnormal EEG in normal subjects = 10%

24

Therefore;

N = 2(1.96 + 0.84)2[0.5 (1-0.5) +0.1 (1- 0.1)]

(0.5 – 0.1)2

N = 66.6

The minimum sample size required is 67 each for the cases and controls, 134 patients should be

recruited for the cases and controls. With an attrition rate of 10% (13 patients), a total of 160 (80

cases and controls) were recruited for the study.

3.8 Assessment of Subjects

A stroke register was opened in University College Hospital Ibadan to record all cases of stroke

seen during the period of study, irrespective of the outcome.

Using a questionnaire, baseline information was obtained from the study participants covering

demographic characteristics (name, sex, age, number of years of completed education, contact

address, telephone number, marital status, socio-economic status), medical history relating to the

stroke- (previous stroke, temporal profile, risk factors, and other co-morbidities), waist and hip

circumference ratio, smoking, alcohol use, past and current medications including psychoactive

substances. Blood samples were taken to assess complete blood count, blood glucose, lipid profile,

retroviral status, genotype, electrolyte urea and creatinine.

3.9 Neuroimaging Studies

Cranial computerized tomography was done for all cases recruited into the study. Ischaemic stroke

was defined by brain CT scan (normal brain CT scan or recent infarct in the clinically relevant

area on scan performed within 3 days or 72 hours of stroke onset). Pre-contrast images were

acquired and immediately reviewed. For haemorrhagic stroke, no contrast was given and the

procedure would be concluded. However, for ischaemic stroke, 40mls of Ultravist (an iodine-based

25

contrast medium) was injected intravenously fast and post-contrast images were immediately

acquired.

Calculation of the volume of bleed and infarct on head CT was performed using the ABC/2

method.96–99 The dimensions of the hematoma are measured in centimeters to create a volume in

cubic centimeters (cm3).97,98 A is the greatest haemorrhage diameter by CT, B is the diameter 90

degrees to A, and C is the approximate number of CT slices with haemorrhage multiplied by the

slice thickness.99 First, the longest axis measured (in centimeters) is labeled A, then a

perpendicular to line A is drawn and labeled B; then, the number of slices on which contiguous

blood noted were multiplied by the slice thickness and labeled C. The slice thickness on standard

head CT protocols is 0.5 cm.

3.10 Stroke severity and outcome

Stroke severity on admission was assessed using the NIHSS and was repeated at 72hours, 7days,

14days and 30days after stroke. (APPENDIX III). The scores range between (0), no stroke to

(42), the most severe stroke. Mild stroke was defined as stroke with NIHSS scores 1-4 while

moderate stroke was defined as stroke with NIHSS scores of 5-15. Moderate to severe stroke was

defined as stroke with NIHSS scores of 16-20 and NIHSS scores of 21-42 constituted severe

stroke. Functional outcome was assessed using the MRS at presentation, at two weeks and 30 days

after stroke (APPENDIX 1V). These assessments were done by the candidate using the Modified

Rankin scale forms. Participants with MRS 1, 2 and 3 were taken as having good outcome while

those with MRS 4,5,6 were taken as having poor outcome.

3.11 Management Protocol

All patients received standard management in accordance with the management guidelines of the

neurology unit of the hospital which was adopted from various international management

guidelines.2,8,9,100,101 The patients had isotonic fluid infusion and regular physiotherapy, with early

26

ambulation where possible. All patients with elevated blood pressure had antihypertensives

administered if there were compelling indications such as acute left ventricular failure, myocardial

ischemia / infarction, rapid decline in renal function or dissecting aortic aneurysm. Unconscious

patients were frequently turned in bed to prevent pressure sores while those with hemiplegia

received prophylactic subcutaneous heparin to prevent deep venous thrombosis. Antiplatelets and

anticoagulation were avoided in those with haemorrhagic stroke. The patients were followed up

until 30 days post stroke onset.

3.12 Electroencephalography

Using the international 10-20 electrode placement, electroencephalography was obtained in all

cases and controls using a Phoenix digital 16 channel electroencephalography machine by a trained

technologist under the my supervision and report the supervising consultant. These recordings

were taken daily in the first seven days, repeated at two weeks and 30days and each recording took

20 – 30 minutes. Hyperventilation which is one of the activation procedures was not done because

it could induce hypocarbia and cerebral vasoconstriction which would worsen the condition in

acute stroke. Pulse oximetry was done before and after the procedure and SPO2 of recruited patients

ranged from 94% to 100% to allow for proper oxygenation. The reports were interpreted by the

investigator, vetted by the supervising consultant and artefactual results were repeated. The

controls had electroencephalography done at presentation in order to compare the pattern found in

controls and cases. Standard sensitivity recording was set at 100uv/cm for all patients, however,

this was adjusted as required and reduced to 70uv/cm, 30uv/cm, 15uv/cm to increase the

amplitude. Filter was set at 70Hz as standard but reduced to 30Hz and 15Hz as required to reduce

the effect of interference.

27

3.13 Data Analysis

Data obtained from participants were entered in Microsoft Excel for cleaning and transferred to

the Statistical Package for Social Science version 22 for analysis. Baseline socio-demographic and

clinical characteristics of participants were obtained and continuous variables were presented as

means (standard deviation) while categorical variables were presented as frequencies

(percentages). Pearson chi square test was used to assess association between stroke characteristics

and stroke type, EEG characteristics and stroke severity. Pearson chi square test was used to assess

if there was any difference in the frequency of diabetes, dyslipidemia, ischaemic stroke, and

between those with poor outcome and good outcome. The independent student t-test was used to

determine association between age, systolic blood pressure, diastolic blood pressure, temperature,

EEG variable and stroke size. p-value <0.05 was deemed significant. Sensitivity, specificity,

positive predictive and negative predictive value of EEG in determining stroke outcome for

ischaemic and haemorrhagic stroke were also calculated. (APPENDIX IX) Stroke and EEG

characteristics were presented as frequencies (proportions) and case fatality rate was also

calculated. Stroke severity was dichotomized using NIHSS. (APPENDIX 111)

3.14 Ethical Consideration

3.14.1 Ethical Clearance

This was obtained from the Joint University of Ibadan/University College Hospital Institutional

Review Board (IRB).

3.14.2 Confidentiality of Data

Personal details obtained from participants including information and data were treated with

utmost confidentiality.

28

3.14.3 Beneficence

Electroencephalogram was done at no cost to the patients after due consultation with hospital

management. Permission was obtained from the patients or their relations to use the patients’ brain

CT scan or MRI for this study. Brain CT scan is part of routine investigation of patients with

stroke. Patients were allowed to have access to their results if they so desired by participating.

3.14.4 Non-maleficence

All procedures carried out on patients were done with extreme care and concern to ensure that

patients suffered no harm.

3.14.5 Voluntary participation

Subjects for this study were fully informed on the research protocol after which they were required

to give written informed consent. No patient was forced or cajoled to carry out investigations. The

consent was translated to the local language for those who did not understand English language.

For the 19 non Yorubas (13 cases and 6 controls), the services of interpreters were employed.

Participants were free to decline participation or withdraw from the study at any time without

reprisal or loss of benefit.

3.9 Operational Definition

3.9.1 Dyslipidaemia

Dyslipidaemia was defined as LDL ≥ 100mg/dl or HDL ≤ 50mg\dl in women and 40mg\dl in men

or Triglyceride ≥ 150mg/dl or Total cholesterol ≥200mg/dl according to NCEP – ATP 111

guidelines.102,103

3.9.2 Smoking

Smoking was defined as use of cigarette and duration defined in pack year. Pack year was

calculated by multiplying the number of packs of cigarettes smoked per day by the number

29

of years the person has smoked. 1 pack year was defined as smoking 20 sticks of cigarettes per

day for one year or 40 sticks of cigarettes per day for half a year.

3.9.3 Diabetes mellitus

Diabetes mellitus was defined as FPG ≥ 126 mg/dl or random plasma glucose ≥ 200 mg/dl

3.9.4 Hypertension

Hypertension was defined as previous blood pressure ≥ 140/90 taken at different time, previous

history of hypertension, current use of antihypertensive.

3.9.5 Stroke phenotyping

Toast classification was used in phenotyping of stroke into large vessel atherosclerosis,

cardioembolic, lacunar, undetermined.104 Large-vessel atherosclerosis was defined as clinical

evidence of involvement of the cortex (aphasia,neglect,hemianopsia,restricted weaknesses),

subcortical region, cerebellum, or brainstem and imaging evidence of CT showing evidence of

cortical, subcortical, cerebellar, or brainstem infarction >1.5cm in diameter.104

Cardioembolism stroke was defined as clinical evidence of cortical, subcortical, cerebellar, or

brainstem dysfunction and imaging evidence of CT imaging evidence or cortical, subcortical,

cerebellar or brainstem infarction >1.5cm in diameter with electrocardiography and

echocardiography supporting cardiac sources for embolus. Small-vessel occlusion was defined as

an evidence of a lacunar syndrome (pure motor hemiparesis, pure sensory syndrome, mixed

sensorimotor syndrome, ataxic hemiparesis, clumsy hand dysarthria syndrome) with no clinical

evidence of cortical involvement (aphasia, neglect hemianopia, restricted motor syndrome), and

imaging evidence of CT that were normal or show a small subcortical or brainstem infarct < 1.5cm

in diameter, and results of echocardiography not suggesting large vessel atherosclerosis or

cardioembolic sources of stroke.104

30

Stroke of undetermined origin was defined as incidents in whom the cause of stroke cannot be

determined with any degree of confidence. This includes patients in whom there was no obvious

source of stroke, patients in whom an incomplete or cursory evaluation was done, and patients

with two or more potential causes of stroke.104

3.9.6 Epileptiform pattern

Epileptiform pattern was defined as presence of either focal spikes, focal sharps, sharps with

accompanying slow waves or spikes with accompanying slow waves on each EEG recorded at

presentation, 7days, 14days and 30days.105

Sharps were defined as transient, clearly distinguishable from background activity, with pointed

peaks and duration of 70-200 milliseconds. Spikes were defined as transient, clearly

distinguishable from background activity, with pointed peaks and duration of 20-70

milliseconds.105 Fast waves were defined as Alpha waves with frequencies of 8 – 13 per second

and Beta waves at frequencies greater than 13 per second.106 Slow waves were defined as Theta

waves with frequencies between 4 – 7 waves per second and Delta waves at frequencies less than

4 waves per second.105,106

3.9.6 Early onset post stroke seizures

Early onset seizure was defined as presence of seizures within 14 days of stroke onset.107,108

31

CHAPTER FOUR

4.0 RESULT

4.1: BASELINE SOCIODEMOGRAPHIC CHARACTERISTICS

One Hundred and sixty participants were recruited into this study comprising eighty consecutive

stroke patients and eighty controls which were adequately matched for age and sex. As shown in

table 1 below, the mean age of cases was 57.6 ± 14.6 and control was 54.9 ± 12.6. For the cases,

there 39 males (48.8%) and 41 females (51.2%). In the control group, there were equal number of

males 40 (50%) and females 40 (50%). There were more cases with no formal education when

compared with controls and this was statistically significant. More controls were single, divorced

or widowed when compared with cases, however, there were more married patients than controls

in this study (p=0.003).

32

Table 1: Socio-demographic characteristics of participants

CASES CONTROLS X2 p-VALUE

N = 80 N = 80

Age (Mean, SD) 57.6 (14.6) 54.8 (12.4) 1.29 0.198

Gender (N, %)

Male 40 (50.0%) 40 (50.0%) 0.01 0.936

Female 40 (50.0%) 40 (50.0%)

Education (N, %)

No formal education 18 (22.5) 2 (2.5)

Primary 10 (16.9) 13 (16.7) 20.81 <0.001*

Secondary 32 (27.1) 37 (47.4)

Tertiary 20 (33.9) 28 (35.9)

Marital Status (N, %)

Single 49 (70.0) 58 (82.9) 0.003*

Married 21 (30.0) 12 (17.14)

Divorced 3 (3.75) 4 (5.0)

Widow 7 (8.75) 6 (7.5)

*Statistically Significant

33

4.2 RISK FACTORS FOR STROKE

In this study, of the cases recruited, 83.3%, 25%, 21.3%,20%,15.3%, 2.5% had hypertension,

diabetes mellitus, dyslipidemia, alcohol consumption, cardio-embolic source and smoking

respectively.

Figure 1a: Showing the frequencies of Risk Factors for Stroke

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

80.00%

90.00%

Hypertension Dyslipidaemia Diabetesmellitus

Alcohol Cardio-embolic Smoking

34

4.3 CLASSIFICATION OF STROKE

The highest proportion of cases (61.0%) had Ischaemic stroke, 36.0% suffered from Intracerebral

haemorrhage and 3.0% had sub-arachnoid haemorrhage. These are shown in Figure 1b below

FIGURE 1b: Proportion of Stroke type among cases

61%

36%

3%

Percentage

Infarct

ICH

Sub-arachnoid Haemorrhage

35

4.4 ISCHAEMIC STROKE PHENOTYPING

Using Oxfordshire Community Stroke Project (OCSP) classification of ischaemic strokes, Partial

Anterior Circulation Infarct (PACI) and Lacunar Infarct (LACI) were more common with

proportions of 44.9% and 42.96% respectively. TACI and POCI had equal proportions of 6.1%

each as shown in Figure 2A. Based on the Trial of Org 10172 in Acute Stroke Treatment (TOAST)

system of classification as shown in Figure 2B, 37.7% of cases with ischaemic stroke had small

vessel disease, followed by 35.9% under the large vessel category, 20.8% had cardio-embolic,

5.7% were of undetermined aetiology.

36

FIGURE 2A: ISCHAEMIC STROKE PHENOTYPING USING OCSP

TACI – Total Anterior Circulation Infarct PACI – Partial Anterior Circulation Infarct

POCI – Posterior Circulation Infarct LACI – Lacunar Infarct

OCSP – Oxfordshire Community Stroke Project

0

5

10

15

20

25

30

35

40

45

50

TACI PACI POCI LACI

PER

CEN

TAG

ES

CLASSIFICATIONS OF STROKE SUBTYPES

0

5

10

15

20

25

30

35

40

LARGE VESSEL SMALL VESSEL CARDIO-EMBOLIC

UNDETERMINED

PER

CEN

TAG

ES

37

FIGURE 2B: ISCHAEMIC STROKE PHENOTYPING USING TRIAL OF ORG 10172 IN

ACUTE STROKE TREATMENT (TOAST)

4.5 BASELINE EEG FINDINGS IN CASES AND CONTROLS

As shown in Table 3, 22.8%, 21.5%,24.1%, 12.7% and 18.9% of cases had frequencies at < 4Hz

(delta), 4-7 Hz(theta), 8-12Hz(alpha), > 12Hz (beta) and intermixed frequency respectively. In the

control arm, 5.0%, 3.8%, 66.3, 17.5 and 7.5% had < 4Hz (delta), 4-7Hz(theta), 8-12Hz(alpha), >

12Hz (beta) and intermixed frequency respectively.

While fast frequencies were seen in 83.8% of controls, it was observed in 36.7% of cases. A

statistically higher proportion of cases had slow frequencies compared to controls (63.3%

versus16.2%; p = 0.001).

38

TABLE 2: COMPARISON OF BASELINE EEG FINDINGS IN STROKE PATIENTS

WITH CONTROLS

A – BACKGROUND RHYTHM

Background Frequency Cases (n=80)

N (%)

Controls (n=80)

N (%)

p-value

DELTA

THETA

ALPHA

BETA

INTERMIXED

(<4HZ)

(4- 7HZ)

(8- 12HZ)

(> 12HZ)

-

18(22.8)

17(21.5)

19(24.1)

10(12.7)

15(18.9)

4(5.0)

3(3.8)

53(66.3)

14(17.5)

6(7.5)

0.008*

Intermixed (Alpha + Delta) as observed in cases 3(5.7)

Intermixed (Delta + Theta) as observed in cases 12(17.1)

Intermixed (Delta + Theta) as observed in controls6(12.9)

B- FREQUENCY OF BACKGROUND RHYTHM IN CASES AND CONTROLS

Frequency Cases (n=80)

N (%)

Controls (n=80)

N (%)

p-value

Slow

Fast

51(63.3)

29(36.7)

13(16.2)

67(83.8)

0.001*

39

4.6: EPILEPTIFORM PATTERNS IN CASES AND CONTROLS

As shown in Table 3, a statistically higher proportion of cases had epileptiform patterns compared

to controls (31.6% versus 11.2%; p = 0.041)

TABLE 3- SHOWING EPILEPTIFORM PATTERN IN CASES AND CONTROLS

Epileptiform Cases (n=80)

N (%)

Controls (n=80)

N (%)

p-value

Present

Absent

25(31.6)

54(68.4)

9(11.2)

71(88.8)

0.041*

40

4.7: PATTERN OF CHANGE IN THE BACKGROUND RHYTHM AMONG STROKE PATIENTS

As shown in Figure 3, background pattern showed increasing alpha and decreasing abnormal rhythms from

presentation till 30days.

FIGURE 3: SHOWING BACKGROUND RHYTHM AMONG STROKE PATIENTS

0

10

20

30

40

50

60

70

80

AtPresentation

72 hrs 7 days 14 days 30 days

PER

CEN

TGES

Alpha

Abnormal

41

4.8: PATTERN OF ELECTROENCEPHALOGRAPHIC WAVES FROM ADMISSION TO

30 DAYS.

At presentation, 61.9% of stroke patients had slow waves and the proportion reduced to 12.5% by

the 30th day. Beta waves were also observed in 12.7% of cases at presentation and 12.5% of cases

showed beta waves at day 30. Twenty four percent of cases had alpha waves at presentation and

this increased to 31.2% by day 30.

FIGURE 4: SHOWING PATTERN OF EEG WAVES FROM ADMISSION TO 30DAYS

0

10

20

30

40

50

60

70

AtPresentation

72 hrs 7 days 14 days 30 days

PER

CEN

TAG

ES

Beta

Alpha

Slow Waves

42

4.9: TIME TREND IN THE PATTERN OF EPILEPTIFORM DISCHARGES AMONG

STROKE PATIENTS

Epileptiform discharges were seen in 31.6%, 32.9%, 62.7%, 57.9% and 44.4% of cases at

presentation, 72hours, 7days, 14days and 30days respectively.

FIGURE 5: SHOWING EPILEPTIFORM PATTERN AMONG STROKE PATIENTS

0

10

20

30

40

50

60

70

80

At Presentation 72 hrs 7 days 14 days 30 days

PER

CEN

TAG

ES

Absent

Present

43

4.10: CLINICAL CHARACTERISTICS ASSOCIATED WITH OUTCOME OF STROKE

From Table 4, With respect to location, 6.25% of patients with stroke in the cortical region had

good outcome while only 2.5% had poor outcome. Forty five percent of cases with stroke in the

subcortical region had good outcome while 36.25% had poor outcome. Of cases with strokes in

the cortical-subcortical region, 7.5% had good outcome while 1.3% had poor outcome. NIHSS <

20 was associated with good outcome and this was statistically significant (p-value= 0.001). The

mean systolic blood pressure on admission of patient with poor outcome was 177.3±36.9 compared

to a mean of 158.2 ±22.7 in those with good outcome. The mean diastolic blood pressure on

admission was 102.9±22.3 in cases with poor outcome compare to a mean of 94.2±13.3 in cases

with good outcome.

44

TABLE4: SHOWING CLINICAL CHARACTERISTICS ASSOCIATED WITH OUTCOME OF

STROKE

POOR OUTCOME GOOD OUTCOME X2 P-VALUE

n=33 n= 47

Age, years (Mean± SD) (57.6 ±16.5) (57.6 ±13.1) 0.01 0.991

Diabetes N,( %) 9 (27.3) 8 (18.2) 0.34 0.410

Dyslipidemia N( %) 9 (27.3) 11 (24.4) 1.51 0.469

Admission Systolic BP, mmHg (177.3±36.9) (158.2 ±22.7) -2.79 0.007*

(mean±S.D)

Admission Diastolic BP, mmHg (102.9 ±22.3) (94.2 ±13.3) -2.11 0.038*

(mean±S.D)

MAP (mean, SD) 131.4 (23.4) 105.1 (19.9) 5.9 <0.001*

**Temperature0c(Mean ± SD) (37.6 ±0.9) (37.1 ±0.6) -2.82 0.006*

PCV, % (Mean ±SD) (37.6± 5.9) (37.7 ±4.5) -3.04 0.983

Seizures N,( %) 11 (33.3) 16 (34.0) 0.038 0.846

GCS N( %)

3 – 7 14(42.4) 8 (17.0) 19.74 <0.001

8 – 12 13(39.4) 16 (34.0)

13 – 15 6(18.2) 23 (49.0)

Stroke volume, cm3 (Mean± SD (6.5± 4.4) (8.7±6.1) -1.48 0.143

Location N( %) 3.22 0.020*

Cortical 2 (2.5) 5 (6.25)

Subcortical 29(36.25) 36(45.0)

Cortical-Subcortical 2 (2.5) 6(7.5)

Stroke Severity (NIHSS < 20) 7 (21.2) 41(87.2) 40.40 0.001*

Stroke severity (NIHSS > 20) 26(78.8) 6(12.8)

**(Highest temperature within 24hours of admission)

45

4.11. CASE FATALITY RATE IN ACUTE STROKE

The case fatality rate among cases recruited was 5% at 72hours, 16.3 at day 7, 26.3% after 14days and

43.8% at day 30 as shown in Table 5.

TABLE 5: CASE FATALITY RATE IN ACUTE STROKE

72hrs 7days 14days 30days

Alive 76 67 59 45

Dead 4 13 21 35

Case fatality rate (%) (5.0) (16.3) (26.3) (43.8)

46

4.12: EFFECT OF SLOWING ON OUTCOMES AMONG ISCHAEMIC STROKE

PATIENTS

The presence of slowing was seen in 71.4% and 66.7% of patient with good outcome at day 14

and day 30 respectively. While 28.6%and 33.3% of the had no slowing at 14days and 30days

among cases with good outcome.

Among cases with poor outcome, 83.3% had slowing at day14 and 71.4% at day30, while 16.7%

at day14 and 28.6% at day 30 had no slowing.

47

FIGURE 6: SHOWING EFFECT OF SLOWING ON OUTCOMES AMONG ISCHAEMIC STROKE PATIENTS

0

20

40

60

80

100

Poor outcome Good outcome

DAY 14

slowing

No slowing

Sensitivity 83.3%, Specificity 28.6%, PPV : 0.33% NPV: 0.80%

0

20

40

60

80


DAY 30

slowing

No slowing


48

4.13: EFFECT OF SLOWING ON OUTCOMES AMONG HAEMORRAGHIC STROKE

PATIENTS

The percentage of cases with slowing was on decline from presentation till day 30 in both group

with good outcome and poor outcome. The percentage of cases without slowing increased from

13.3% at day14 and 46.7% at day 30 among haemorrhagic stroke patients with good outcome.

However, the percentage of cases without slowing increased from 45.5% at day14 and 62.5% at

day 30 among haemorrhagic stroke patients with poor outcome.

49

FIGURE 7: SHOWING EFFECT OF SLOWING ON OUTCOMES AMONG HAEMORRAGHIC STROKE PATIENTS

0

20

40

60

80

100


DAY 14

slowing

No slowing


0

10

20

30

40

50

60

70


DAY 30 SLOWING

NO SLOWING


50

4.14: TRENDS OF PREDICTIVE VALUE OF SLOWING IN PREDICTING POOR

OUTCOME AMONG STROKE PATIENTS.

Among ischaemic stroke patients, the positive predictive value of slowing decreased from 0.36 at

presentation to 0.33 at day 14 and 0.22 at day 30. The negative predictive value of slowing

increased from 0.57 at presentation to 0.8 at day 14 and 0.82 at day 30.

The positive predictive values among haemorrhagic stroke were 0.46 at presentation,0.32 at day

14 and 0.27 at day 30. The negative predictive values were 0.4, 0.29 and 0.58 at presentation, day

14 and day 30 respectively.

51

FIGURE 8: SHOWING TREND OF PREDICTIVE VALUES OF SLOWING AMONG STROKE PATIENTS.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

PRESENTATION DAY 14 DAY30

ISCHAEMIC STROKE

PPV NPV

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7


HAEMORRAGHIC

PPV NPV

52

4:15: EFFECT OF ALPHA RHYTHM ON OUTCOMES AMONG ISCHAEMIC

STROKE PATIENTS

At day 14, there was no alpha rhythm among patients with poor outcome while 28.6% of patients

with good outcome had alpha rhythm.

Similarly, at day 30, while 14.3% of patients with poor outcome had alpha rhythm, 29.6% of

patients with good outcome had alpha rhythm.

53

FIGURE 9: SHOWING EFFECT OF ALPHA RHYTHM ON OUTCOMES AMONG ISCHAEMIC STROKE PATIENTS

0

20

40

60

80

100


DAY 14 ALPHA WAVE

OTHER WAVES

Sensitivity 0%, Specificity 71.4%, PPV : 0.0% NPV: 0.63%

0

20

40

60

80

100


DAY 30 ALPHA WAVE

OTHER WAVES


54

4.16: EFFECT OF ALPHA ON OUTCOMES AMONG HAEMORRHAGIC STROKE

PATIENTS

At day 14, 9.1% of patients with poor outcome had alpha rhythm while 53.3% of patients with

good outcome had alpha rhythm. At day 30, 37.5% of patients with poor outcome had alpha

rhythm, while 53.3% of rhythm with good outcome had alpha rhythm.

55

FIGURE 10: SHOWING EFFECT OF ALPHA ON OUTCOMES AMONG HAEMORRHAGIC STROKE PATIENTS

0

20

40

60

80

100


DAY 14 ALPHA WAVE

OTHER WAVES


0

20

40

60

80


DAY 30 ALPHA WAVEOTHER WAVES


56

4.17: TRENDS OF PREDICTIVE VALUE OF ALPHA RHYTHM IN PREDICTING

OUTCOME AMONG STROKE PATIENTS

The positive predictive value of alpha rhythm among ischaemic stroke patients were 0.2 at

presentation, 0 at day 14 and 0.11 at day 30. The negative predictive values were 0.53 at

presentation, 0.63 at day 14 and 0.76 at day 30 respectively.

Among haemorrhagic stroke patient, the positive predictive values were 0.43 at presentation, 0.11

at day 14 and 0.27 at day 30. The negative predictive values of were 0.5 at presentation,0.41 at day

14 and 0.58 at day 30.

57

FIGURE 11: SHOWING TREND OF PREDICTIVE VALUES OF ALPHA RHYTHM AMONG STROKE PATIENTS.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8


ISCHAEMIC STROKE

PPV NPV

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7


HAEMORRAGHIC STROKE

PPV NPV

58

4.18: EFFECT OF BETA ON OUTCOMES AMONG ISCHAEMIC STROKE PATIENTS

At day 30, 42.5% of patient with poor outcome had beta rhythm while 33.3% of patient with good

outcome had beta rhythm. The specificity was 80.6%, 82.1%, 66.7% at presentation, day 14, day

30 respectively.

FIGURE 12: SHOWING EFFECT OF BETA ON OUTCOMES AMONG ISCHAEMIC STROKE PATIENTS

0

10

20

30

40

50

60

70

80

90


DAY 14 BETA WAVEOTHER WAVES


0

20

40

60

80




59

4.19: EFFECT OF BETA RHYTHM ON OUTCOMES AMONG HAEMORRHAGIC

STROKE PATIENTS.

At day 14, 9% of patients who had poor outcome had beta rhythm, while 20% of patients who had

good outcome had beta rhythm. At day 30, 25% of patients with poor outcome had beta rhythm,

while 20% of those with good outcome had beta rhythm. The specificity was 80% at day14 and

day 30.

FIGURE 13: SHOWING EFFECT OF BETA ON OUTCOMES AMONG HAEMORRHAGIC STROKE PATIENTS.

0

20

40

60

80

100



Sensitivity 9%, Specificity 80%, PPV : 0.25% NPV: 0.55%

0

10

20

30

40

50

60

70

80


DAY 30 BETA WAVE

OTHER WAVES

Sensitivity 25%, Specificity 80%, PPV : 0.40% NPV: 0.67%

60

4.20: TRENDS OF PREDICTIVE VALUE OF BETA RHYTHM IN ACUTE STROKE

The positive predictive value of beta rhythm in predicting poor outcome was 0.14 at presentation,

0.29 at day14 and 0.17 at day 30. The negative predictive value however increased from 0.6 at

presentation to 0.7 at day 14 and 0.81 at day 30. In cases with haemorrhagic stroke the positive

predictive was 0.33 at presentation, 0.25 at day 14 and 0.4 at day 30. The negative predictive value

also increased from 0.5 at presentation to 0.55 at day 14 and 0.67 at day 30.

61

FIGURE 14: SHOWING TREND OF PREDICTIVE VALUES OF BETA RHYTHM

AMONG STROKE PATIENTS.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9


ISCHAEMIC STROKE

PPV NPV

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8


HAEMORRAGHIC STROKE

PPV NPV

62

4.21: SEIZURE TREND IN ACUTE STROKE

Of cases recruited into the study, 66% had no seizures, 24% had early onset seizures were, 10%

had late onset seizures at as shown in Figure 15

FIGURE 15: SHOWING TREND OF SEIZURES FROM PRESENTATION TO 30 DAYS

seizure Absent66%

Early onset seizures

24%

late onset seizures

10%

seizure Absent

Early onset seizures

late onset seizures

63

4.22: RELATIONSHIP BETWEEN EEG WAVE PATTERNS AND SEIZURE TREND

There is a reduction in presence of slowing, alpha rhythm, PLED, RAWOD, while beta rhythm was

increased among patient with early onset seizures from presentation to 14 days.

FIGURE 16: SHOWING RELATIONSHIP BETWEEN EEG WAVE PATTERNS AND

TREND OF SEIZURES FROM PRESENTATION TO 14 DAYS

0

10

20

30

40

50

60

slowing Alpha Rhythm Beta PLED RAWOD

SEIZURES AT PRESENTATIONn =11

0

10

20

30

40

50

60

70

Slowing Alpha Beta PLED RAWOD

SEIZURES WITHIN 14 DAYSn= 19

64

4.23: RELATIONSHIP BETWEEN PLED AND RAWOOD AND EARLY ONSET SEIZURES

There was a significant association between PLED and presence of early onset seizures at

presentation as shown Table 6.

TABLE 6: SHOWING RELATIONSHIP BETWEEN SPECIAL PATTERN AND EARLY ONSET SEIZURES

ABSENT (n=53) PRESENT (n = 19) p value

AT PRESENTATION

PLED 2(3.8) 4(21.1) 0.049*

RAWOD 5 (9.4) 5(26.3) 0.679

14TH DAY EEG SLOWING

PLED 1 (1.9) 2(10.5) 0.105

RAWOD 3(5.7) 4 (5.0) 0.1I0

*Significant

65

CHAPTER FIVE

5.0 DISCUSSION

5.1 SOCIO-DEMOGRAPHIC CHARACTERISTICS OF THE STUDY POPULATION

This study investigated the frequency and prognostic significance of abnormal

electroencephalographic findings in acute stroke patients at the University College Hospital,

Ibadan. A total of 160 participants were recruited into the study comprising 80 cases (stroke

patients) and 80 controls (subjects) with mean age cases at 57.6 years. This implies that stroke

affected middle age group mainly and thus has negative effect on the vibrant group workforce of

the country.

More cases had no formal education when compared with controls and this attained statistical

significance. This may result in poor compliance with instructions relating to medication and

healthy diet habit among cases. Stroke incidence was inversely correlated with years of educations

in a three year population study conducted in Brazil.109 There are previous evidences supporting

higher stroke mortality rates and physical functional limitations among individuals with a low level

of education and by extension low socioeconomic status.110,111 Years of education, age and sex of

patient, have all been linked with educational related differences in stroke incidence.112 Primary

prevention is key in reducing the burden of diseases in countries with minimal resources like

Nigeria.113 To achieve this, high level of education is of utmost importance. It is not surprising that

the participants with no formal educational among cases were more compared to controls in this

present study.

In this study, more of the controls were married compared to cases with higher frequencies of

singles, divorces and widows. The importance of caregivers cannot be underestimated as they help

to improve health seeking behavior in stroke patient. In a study by Malyutina et al, it was observed

that higher education was associated with reduced mortality from all causes, cardiovascular disease

66

and coronary heart disease in both gender.111 Adjustment for coronary risk factor and marital status

substantially reduced relative risk in men and women. The authors also noted that unmarried men

had higher mortality from all causes, cardiovascular and coronary heart disease than married

subjects.111 Even though association between marital status and cardiovascular disease was

inconsistent in the above study. These findings are somewhat similar to the findings obtained in

this present study. Perceptual, social, and behavioral factors contribute to delay in seeking medical

care in acute stroke beyond demographic and clinical variables.114

5.2 RISK FACTORS FOR STROKE

In this present study, 83.8%, 25%, 21.3%, 20% and 2.5% had history of hypertension,

dyslipidemias, diabetes mellitus, alcohol consumption and current smoking respectively. Previous

hypertension or blood pressure greater 140/90mmHg, regular physical activity, apolipoprotein

ratio, diet, waist hip ratio, psychosocial factor cardiac diseases, current smoking, alcohol

consumption, and diabetes mellitus were all associated with stroke in recent INTERSTROKE

study.40 While hypertension was more associated with haemorrhagic stroke than ischaemic,

current smoking, apolipoproteins and cardiac causes were more associated with ischaemic stroke.40

Only 2.5% of cases are current smokers, however, previous study by Bonita, showed that stroke

risks are at 18% in current smokers, 6% in former smokers and 12% in environmental tobacco

exposure.115 Smoking has been proposed to reduce blood vessel distensibility.41 Of all risk factors,

hypertension remains the highest and the leading risk factor for stroke in all types of stroke and

across all age groups.40

67

5.3 STROKE CLASSIFICATION AND PHENOTYPING

Data from Ibadan Stroke Registry between April, 1973 to March 1975 showed that of a total of

318 stroke patients who were entered into the register, 11% had subarachnoid haemorrhage, 16%

cerebral haemorrhage, 49% cerebral infarction while 24% were ill-defined.36

In a more recent study in the south western region of Nigeria (Ogun State) which spanned 10years,

of the 708 stroke patients reviewed, cerebral infarction contributed 49%, while 45% of cases had

intra cerebral haemorrhage and 6% had subarachnoid haemorrhage.4 However, in this present

study, the number of cases who had intracerebral hemorrhage were 36%, 61% had infarct and 3%

subarachnoid bleed. The discrepancies in these results could be due to the differences in diagnostic

criteria used. While the first study classified stroke using WHO criteria and autopsy records in

those cases, the current study recruited only cases that were accurately phenotyped by

neuroimaging.

In the INTERSTROKE study which involved a total of 3,000 cases cutting across Africa, South

America, Asia, North America, 22% of the cases had haemorrhagic stroke while ischaemic stroke

constituted 78%.40 However, coning down to the 323 cases recruited in Africa, 34% had

haemorrhagic stroke while 66% had ischaemic stroke.40 These proportions are quite similar to the

findings obtained in this present study.

Using the Oxfordshire Community Stroke Project Classification (OCSP), this present study

showed that partial anterior circulation infarct and lacunar infarct were more common with

proportions of 27.5% and 26.3% respectively.57 TACI and POCI had 3.8% each.57 These findings

are different from the African subtypes reported in the INTERSTROKE study which had PACI

and TACI as 47% and 19% respectively. The LACI proportion reported in the INTERSTROKE

68

study was smaller than reported in this study. The reason for this disparity could be the difference

in sample size. Across all continents, PACI is the commonest form of ischaemic sub-type of

stroke.54 In Africa it was 47%, S East Asia 57%, South America 33% and high income countries

52%. This trend is comparable to the findings in this study where the proportion of PACI was

higher than other subtypes. However, the PACI value on this study is relatively smaller than that

reported by INTERSTROKE study. The probable reason could be as a result of the smaller sample

size considered in this study.

The proportion reported for cases with small vessel disease in this present study is similar to the

finding by Kolominsky et al who conducted a population based study between 1994 and 1998

involving 583 residents in Germany. The group reported that 25.8% had small artery occlusion,

15.3% had large artery atherosclerosis and 30.2% had cardioembolism.116 Comparing the findings

from this study with that obtained from INTERSTROKE study, small vessel accounted for 44%

of cases, large vessel 19%, cardioembolic 9% and undetermined 22%. Whereas in this present

study, 37.74% of cases with ischaemic stroke had small vessel disease, 35.85% had the large vessel

category, 20.75% had cardio-embolic stroke, 5.72% were of undetermined aetiology. Apart from

the sample size which may account for the significant differences, there is need to ensure other

ancillary investigation in acute management of stroke.

5.4 CASE FATALITY RATE AND FUNCTIONAL OUTCOME IN ACUTE STROKE

The case fatality rate among cases recruited into this study was 5% at 72hours, 16.3% at day 7,

26.3% after 14days and 43.8% at day 30. A previous study aimed at determining the prognosis

and outcome of acute stroke conducted in the University College Hospital by Obiako et al revealed

an overall case fatality rate of 83.3% among stroke patients that were comatose which is eight

times higher than 12% and 19% case fatality rate of people with first ever stroke at 14days and

69

30days.6 The case fatality rate observed in this study (43.8% at 30days and 16.3% at 7 days) is still

relatively higher than that reported in developed countries. In a retrospective study in southwestern

Nigeria, Ogun et al reported a case fatality rate of 28% at 7days and 40% at 30days.4 The case

fatality rate increase by 27.5% between 7days and 30days in this study is of great concern but

value of 43.8 % is relatively similar 40% case fatality rate which has been described as high

previous review to estimate burden of stroke.48 Hospital-based studies have demonstrated a one

month case fatality rate between 27% and 46% in Africa.23,29,117. In the hospital based

INTERSTROKE study, one month stroke case fatality rate was 22% compared to 4% in high

income countries.40 An earlier study in Ibadan community reported a case fatality rate of 35% at

3weeks, and a similar community- based study in Tanzania reported a 28-ssday case fatality rate

of 28.7% and 84.3% at 3years.36.

Low level of education, poor access to imaging facilities, few available facilities for investigation

and treatment and poor documentation are some of the reasons identified for the increased case

fatality in Africa.29,118

5.5 FREQUENCY OF BACKGROUND RHYTHM, SLOWING AND EPILEPTIFORM

DISCHARGE AMONG STROKE PATIENTS.

The comparison of EEG tracing among cases and controls at presentation showed significant

differences between frequency, background, symmetry and epileptiform activities. Background

alpha rhythms and beta rhythm were more common in controls than in cases, while delta rhythm

and theta rhythm were seen more in cases than controls. Fast frequencies were seen in 83.8% of

controls and were observed in only 36.3% of cases. Epileptiform patterns were about 3 times

commoner in cases than controls at presentation. In a similar study, where EEG was performed

70

within 24 hours of admission, focal discharges were seen in 10% of cases of which 6% had

PLED119 whereas, in this present study, 15.2% had focal discharges of which 7.5% had PLED.

These findings underscore the need for EEG monitoring in order to detect purely electrographic

seizures in acute stroke. In a study to determine usefulness of EEG in patients with seizures in

acute phase of stroke, EEG revealed focal slow waves in 90% of which 22.5% were accompanied

by interictal epileptiform discharges.120 However, this present study revealed EEG slowing in

descending order from 61.9% of cases at presentation, 62.4% at 72hours, 51.2% at day 7, 35% by

the 14th day and 12.5% at day 30.

Epileptiform discharges was observed only in 31.6% of cases at presentation, 32.9% at 72hrs,

62.7% at 7days, 57.9% after 14days and in 44.4% at day 30.

The findings from the study above and this present study with regards to epileptiform discharges

at presentation further support the need of EEG monitoring in the acute phase of stroke.120

Neuromonitoring is an important field for the recognition of occurrence of non-convulsive

seizures, the development of quantitative measures to detect regional ischemia, and the

appreciation of electroencephalography phenotypes that is of prognostic value.16,121

Generally, focal epileptiform discharges are the initial EEG abnormality seen in acute stroke.122,123

In this present study, focal abnormalities were reported in 15.2% of cases at presentation which

increased with repeat to EEG ,17.56% at 72hours, 50.75% at day 7, 47.37% at 14days and 35.6%

at day 30. The rate of epilepsy increases with time after stroke and the yield of EEG improves

with repeat and long term studies in detecting epileptiform activity in adults.124 During acute

stroke, intracellular calcium accumulation may lead to depolarization of the transmembrane

potential and calcium mediated effect which may lower seizure threshold.125

The alpha and beta background rhythm were on increase, while delta and theta rhythm were

decreasing in course of 30days. This could be due to improved perfusion with recovery in phase

71

of acute stroke and EEG changes are closely related to cerebral blood flow.16 When normal

cerebral blood flow declines to values like 25-35ml/100g/min, faster frequencies (alpha and beta)

will be lost, then as the CBF decreases to approximately 17-18 ml/100 g/min, slower frequencies

(delta and theta) gradually increase.16 This represents a crucial ischaemic threshold at which

neurons begin to lose their transmembrane gradients, leading to cell death (infarction). However

as the cerebral blood flow continues to decrease toward the infarction threshold (10-12 ml/100

g/min and below), the EEG becomes silent and cellular damage becomes irreversible.16 Again with

improved perfusion and reperfusion fast frequency gradually returns as demonstrated in this

study126. Summarily, the frequency of epileptiform activity, alpha, beta, alpha delta ratio increased

with time, while delta, theta decreased on EEG tracing within 30day duration.

5.6 PREDICIVE VALUE OF EEG WAVE PATTERN IN ISCHAEMIC AND

HAEMORRHAGIC STROKE

The EEG has been shown to improve prediction of functional outcome in patient with severe

neurological deficit in acute stroke.12 In a previous study to evaluate prognostic value of EEG in

ischaemic stroke, Iranmanesh showed significant positive correlation between mild to severe EEG

abnormalities and poor prognosis.15 In this current study, the PPV, which is strength of truly

predicting poor outcome in acute stroke was on decline for slowing. In another study by Su et al

to find out abnormal pattern on EEG in massive cerebral hemispheric infarction and their

correlation with poor outcome dominant alpha without reactivity, RAWOOD, burst suppression,

epileptiform activity and generalized suppression were correlated with poor outcome.127 Overall

there is a decline in PPV of alpha rhythm from presentation till 30days which means that the true

strength of alpha rhythm in predicting poor outcome was maximal at presentation and decreased.

72

The negative predictive value alpha wave in predicting poor outcome was on linear increase from

presentation to 30days meaning that presence alpha rather excluded poor outcome. Beta wave is

however weakly predictive of poor outcome in this current study.

In a study to assess value of clinical and EEG (findings classified into those predicting poor

outcome and good outcome) in acute stroke showed that while EEG (findings predicting good

outcome) predicted good outcome in 6 out of 7 patients (PPV,0.86), while EEG findings predicting

poor outcome predicted correctly poor outcome in 11 out of 13 patients (PPV, 0.85).12 In a

prospective study of patient with sub-arachnoid haemorrhage who had continuous EEG, Claassen

et al showed that periodic epileptiform discharges, electrographic status epilepticus and absent of

EEG reactivity were associated with poor outcome.86 The EEG is a are very useful in prediction

and diagnosis of post subarachnoid haemorrhage ischaemic due to vasospasm.16,86,128,129 Pattern

of prognostic significance in delayed vasospasm include presence of frontally predominant

biphasic delta waves, focal polymorphic delta and presence of unreactive delta.128 In this present

study, seizures was associated poor outcome but epileptiform patterns like sharps, spikes, PLED

were associated with poor outcome. In a similar study to determine prognostic significance of

interictal and periodic epileptiform patterns during acute stroke, the presence of any of the two

was associated poor prognosis with odd ratio of 2.27.130 The use of emergency EEG in acute

ischaemic

stroke can reveal a distinctive EEG pattern that adds value to the selection of patients for

thrombolytic and cerebral oedema treatment.

5.9 CLINICAL CHARACTERISTICS OF CEREBRAL ISCHEMIA AND

INTRACEREBRAL HAEMORRHAGE

As demonstrated in this present study, the median stroke size and interquartile range for

intracerebral hemorrhage was higher than in ischaemic stroke. Acute stroke size has been

73

correlated with modified Rankin scale (MRS) showing that the higher the size, the worse the

functional outcome in stroke.131 Higher values of NIHSS greater than 20 was associated with poor

outcome in 78.8% of cases with poor outcome, while NIHSS less than 20 was associated with

good outcome in 87.2% of cases with good outcome. Mortality was higher in patients with NIHSS

scores of 20 and above in a study to determine the relationship between NIHSS score to 90-day

mortality in Lagos, southwestern Nigeria by Dawodu et al.132 It was however observed that if

initial NIHSS score remained static or worsened, prognosis was worse. Among such patients, all

those with initial NIHSS score of 20 and above died, compared with those with NIHSS score of

less than 20 who had mortality of 70%. Bruno et al showed that the proportion of NIHSS score

change predicted functional outcome in acute stroke.20 Elevated blood pressure is common in acute

ICH, often with markedly elevated levels, and is associated with poor outcomes.133 This is similar

to what was found in this study that higher systolic and diastolic blood pressure were associated

with poor outcome while lower blood pressure was associated with good outcome. Similarly, other

studies like the Antihypertensive Treatment of Acute Cerebral Hemorrhage (ATACH) trial and

Intensive Blood Pressure Reduction in Acute Cerebral Trial (INTERACT) have demonstrated that

systolic BP reduction to 140 mmHg is well tolerated and associated with attenuation of hematoma

expansion.133,134

5.10 POST STROKE SEIZURES

Stroke is the most common cause of seizure and epilepsy in the elderly population.125,135 Post‐

stroke seizure and post‐stroke epilepsy are common causes of hospital admissions, either as a

presenting feature or as a complication after a stroke.136,137 It is described as a late onset seizure,

when it occurs after two weeks of stroke onset. The prevalence of post stroke seizure varies

between 4 – 67%.91,92,123,124 A review of available data to assess related risk factors and predict

74

early- and late-onset seizure after first ever stroke revealed independent risk factors for early- onset

seizure were large lesions, subarachnoid haemorrhage, initial hyponatremia, and cortical

involvement.138 The independent risk factors for late-onset seizures were cortical involvement and

large lesions.138 A review of Oxfordshire stroke project revealed that 20.7% patients suffered a

seizure at stroke onset.92 In the Cincinnati study, overall incidence of acute seizures after stroke

was 3.1%, with a higher incidence seen in younger patients with haemorrhagic stroke.139 The

OCSP revealed that 11.5% of patients with stroke were at risk of developing post‐stroke seizures

within five years.92,140

Hauser and colleagues reported the incidence of epilepsy and all unprovoked seizures from 1935

through 1984 and found that cerebrovascular disease accounted for 11% of cases.136 Camilo

reported estimates of the rate of early post ischaemic stroke seizures to range from 2% to 33% in

acute stroke.140 In this study, at presentation, seizure was present in 11.25% of cases, however, by

day 30, 32.5% of our cases had seizures. Around 45% of early onset post‐stroke seizures have been

said to occur within the first 24 hours. Late onset seizure has a peak within 6 to 12 months after

the stroke and has a higher recurrence rate of up to 90% in both ischaemic and haemorrhagic

stroke. Early onset seizures after stroke were rather common and did not affect outcome and did

not recur even when not treated with anti-epileptics. Late onset seizures were less common but

were associated with recurrent seizures.141 Finding of 11.25% of seizure at presentation and 23.8%

at 14 days suggests relatively common early onset seizure in this study. Also, presence of seizure

did not significantly affect outcome at 30 days but epileptiform discharges like sharps, spike,

PLED were associated with poor outcome regardless of stroke severity.

PLEDs are usually seen in the context of destructive structural lesions of the cortex, more

frequently in acute ischaemic stroke or herpes simplex encephalitis, and their prognostic

75

significance is linked to the underlying etiology.142–144 In this present study, PLED was seen in

7.5% of the population. PLED association with recent seizures are transient manifestations of

increased neuronal excitability, irrespective of the underlying etiology.142 In general, the presence

of periodic EEG patterns in critically ill adult patients mostly carries a poor prognosis possibly

linked to the underlying etiology. Periodic lateralized epileptiform discharges of cortical origin

were found to have more morphologic variability and longer duration than PLEDs of subcortical

origin in a study to assess neuroimaging and neurophysiological of the entity.142,145

Again, the proportion of epileptiform activities seen were more than the cases of seizures in this

study. This brings forth possibility of electrographic seizures and subclinical seizures and its

attending consequences if not detected and treated in stroke patient. An emerging application for

continuous EEG is to detect new or worsening brain ischemia in patients at high risk, especially

those with subarachnoid haemorrhage.146 Post‐stroke epilepsy could pose a clinical dilemma in

terms of diagnosis and its management is controversial, especially with use of prophylactic anti-

epilepsy.120,147

76

CHAPTER SIX

6.0 CONCLUSION AND RECOMMENDATIONS

6.1 CONCLUSION

EEG is highly sensitive in detecting changes in physiological activities of the brain in acute stroke

because of its close correlation with cerebral blood flow. The study showed increase in background

alpha and beta rhythm, but delta and theta rhythm were decrease in the course of 30-day

monitoring. The PPV of alpha rhythm and slowing in both ischaemic and haemorrhagic stroke

were maximal at presentation and decreased within 30 days. However, that of Beta rhythm

increased marginally and was predictive of poor outcome. The NPV of alpha rhythm and beta

rhythm in predicting poor outcome was increased from presentation to 30 days.

The proportion of epileptiform activities seen on EEG were more than the cases of seizures in this

study. This brings forth possibility of electrographic and subclinical seizures and it’s attending

consequence in acute stroke. Clinical characteristics that were associated with poor outcome

include: location of the stroke, increased temperature, NIHSS >20, increased systolic and diastolic

blood pressure.

6.1 RECOMMENDATIONS

1. Changes in EEG wave patterns are reliable marker of the decline in neuronal integrity

associated with a decline in blood flow.

2. EEG monitoring is useful in detecting subclinical and purely electrographic seizures in

acute stroke.

3. There are EEG wave patterns on Emergency and continuous EEG monitoring that may be

useful in predicting functional outcome in acute stroke.

77

6.2 LIMITATIONS OF THE STUDY

1. Quantitative EEG was not available for use during this study.

2. The study was conducted in patient with acute stroke, thus the predictive value of the EEG

wave patterns at more than 30 days could not be determined.

3. The relationship between the late - onset seizures and EEG wave pattern could not be

ascertained because the study was conducted in patient with acute stroke.

4. The BMI was not calculated because special instrument needed to calculate the weight and

height of unconscious patients was not available.

78

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APPENDIX 1

(ETHICAL APPROVAL)

89

APPENDIX 11

INFORMED CONSENT

90

IRB Research approval number: ________________

My name is ………………………, I am a staff of the ……………………., University College

Hospital (UCH), Ibadan. I am carrying out a study on patients with stroke at the UCH to explore

the prognostic role of electroencephalography in acute stroke.

During this exercise, I will need to ask you some questions and carry out physical examination.

This examination will include electroencephalography which involves tiny non-metallic materials

to measure electrical activity of the brain, checking for swallowing difficulty involve touching

back of your throat with a wooden spatula, giving you 10mls of water to drink and attaching pulse

oximeter to your index finger. These procedures will not cause you any harm. Your blood sample

will be taken and sent for random blood glucose, full blood count, genotype, retroviral screening

and blood electrolytes. The process of taking the specimen will not cause any harm but a slight

pain during the introduction of the needle.

These investigations will be at no cost to the patients or their relatives. I also require your

permission to use your brain CT or MRI for the purpose of this study.

All the information obtained will be treated with absolute confidentiality. Appropriate therapy will

be instituted as necessary.

You are free to take part in this study. If you decide not to participate in this study, you will not be

treated differently from any other patients attending this hospital. You have a right to withdraw

from this study anytime you choose. (This will be explained in the vernacular to those who do not

understand English).

Statement of person obtaining informed consent:

I have fully explained this research to ____________________________________and have

given sufficient information, including about risks and benefits, to make an informed decision.

Name: ..................................................... Signature/Date.............................................

91

Statement of person giving consent:

I have read the description of the research or have had it translated into a language I understand.

I have also discussed the doctor to my satisfaction. I understand that my participation is voluntary.

I know enough about the purpose, methods, risks and benefits of the research study to judge that I

want to take part in it. I understand that I may freely stop being part of this study at any time. I

have received a copy of this consent form and additional information sheet to keep for myself.

Name: ................................................. Signature/Date......................................

Witness’s Signature (If Applicable):....................................................................

Witness’s Name (if applicable):...............................................................................

This research has been approved by the Health Research Ethics Committee of the University of

Ibadan and the Chairman of this committee can be contacted at Biode Building, 2nd Floor,

RoomT10, IMRAT, College of Medicine, University of Ibadan. E-mail: [email protected].

In addition, if you have any question about your participation in this research, you can contact the

principal investigator Dr. Luqman Opeoluwa Ogunjimi, College of Medicine, University college

Hospital, Ibadan. Phone number: 07032683222

E-mail: [email protected]

PLEASE KEEP A COPY OF THE SIGNED INFORMED CONSENT

APPENDIX II1:

STUDY QUESTIONNAIRE (To be completed by the investigator)

92

SECTION A:

Please tick the corresponding number provided where applicable

(1) Serial Number: ________________

(2) Hospital Number: __________________________

(3) Name: Surname Other Names:

(4) Age at last Birthday (in Years):_________________

(5) Gender: ( ) Male ( ) Female

(6) Ethnicity: ( ) Hausa ( ) Igbo ( ) Yoruba ( ) Others Specify_______________

(7) Handedness: ( ) Right ( ) Left

(8) Highest Level of Education: ( ) Primary ( ) Secondary ( )Tertiary ( ) Postgraduate.

(9) Level of Monthly Income (N): ( ) ≤ 20,000 ( ) 20,001- 50,000 ( ) 50,001- 100,000 ( ) 100,001-

200,000 ( ) 200,001-500,000 ( )>500,000

(10) Hypertension ( ) Yes ( ) No ( ) Don’t know Treatment ____________________

If yes, please specify the duration ________________________

(11) A. Diabetes Mellitus: ( ) Yes ( ) No ( ) Don’t know Treatment________________________

If yes, please specify the duration _______________________

B. Hyperlipidemia ( ) Yes ( ) No ( ) Don’t know

(12) Alcohol: ( )Yes ( ) No

If yes, please specify type (gram per week) _______________

(13) Smoking ( ) Yes ( ) No

If yes, please specify number of sticks per day (expressed as “pack years”) _________

(14) Background seizure ( ) Yes ( ) No

If Yes, since when_________________________

(15) Family History of Seizures ( ) Yes ( ) No

If yes, (a) Duration___________ (b) Medications ______________

(16) Date of Presentation: Day Month Year

(17) Date of Discharge:\Demise Day Month Year

SECTION B: PHYSICAL FINDINGS

(18) Glasgow Coma Scale Score: ( ) 14 – 15 ( ) 9 - 13 ( ) 3 – 8

93

(19) Dysphasia: ( ) Present ( ) Absent

If present, please specify type ______________________

(20) Dysarthria: ( ) Present ( ) Absent

(21) Cranial nerves: ( ) Normal ( ) Abnormal

(22) If abnormal, please specify ________________________________

(23) Motor weakness: ( ) Hemiparesis ( ) Quadriparesis ( ) Monoparesis ( ) Absent

(24) Coordination: ( ) Normal ( ) Abnormal

(25) Movement Disorder: ( ) Present ( ) Absent

If present, please specify ______________________________

(26) Pulse: _____________________________

(27) Admitting Blood Pressure: ( ) Systolic BP____________ ( )

Diastolic BP ____________

(28) Apex beat: ( ) Displaced ( ) Not displaced

(29) Heart Murmurs: ( ) Present ( ) Absent

If present, please specify _________________________________

(30) Respiratory rate ( ) Normal ( ) Abnormal

If abnormal please specify ________________________________

(31) Chest crackles ( ) Present ( ) Absent

(32) Bronchial breath sound ( ) Present ( ) Absent

(33) Highest Temperature in the last 24hrs ___________________

94

SECTION C: NEUROIMAGING

Date of Neuroimaging

CT/MRI : Yes No

Type of Scan: Without contrast With contrast

Normal findings? Yes No

Stroke type: CI ICH SAH

Subtype of Stroke:

A. OSCP Classification C. TOAST Classification

I. TACI Yes No I. Large vessel Yes No

II. PACI Yes No II. Small vessel/lacunar Yes No

III. POCI Yes No III. Cardioembolic Yes No

IV. LACI Yes No IV. Undetermined Yes No

V. Others: Dissection Yes No

B. ASCO Classification VI. Vasculitis Yes No

I. Atherosclerosis Yes No VII. CVST Yes No

II. Small vessel disease Yes No

III. Cardiac disease Yes No

Arterial Territory ACA MCA PCA

Vertebrobasilar PICA SCA

Ant choroidal Lenticulostriate Watershed

Watershed infarct

1. Cortical: ACA/MCA MCA/PCA

2. Deep: LSA perforators/MCA penetrating branches

OTHER FINDINGS

a. cerebral atrophy

Yes No

b. Periventricular/white matter changes Yes No

c. Aneurysm

d. Arteriovenous malformation

e. Lacunar

95

Location of Lesion

Right Hemisphere Left hemisphere

Size (cm) Volume Age

Size(cm) Volume Age

Cortical

Frontallobe

Temporallobe

Parietallobe

Occipotallobe

Subcortical

Thalamus

Pituitary gland

Internal capsule

Putamenal

Basalganglia (caudate nucleus

globuspallidum putamen)

Cerebellar

Brainstem

Midbrain

Pons

Medulla

Ventricle

Lateral ventricle

3rdventricule

4th ventricle

*Size: Largest dimension in any direction †Volume: Entire volume # Age: 1-Hyperacute; 2- Acute; 3- Subacute; 4- Chronic

*Size: 0-3 3.1-5.0 5.1-7.0 7.1-10.0 >10.0

†Volume: 0.0-3.0 3.1-5.0 5.1-7.0 7.1-10.0 >1

96

D: EEG FINDINGS

1. Voltage/Amplitude

2. Alert/Sleep recording

3. Background

4. Pattern

a. Slowing Diffuse Intermittent

b. PLED

c. BiPED

d. RAWOD

e. TIRDA

f. FIRDA

g. OIRDA

h. BECTS

i. Wicket

j. Sharps

k. Spikes

l. Arterfact

m. Phase reversal

n. Others_____________________________

5. Frequency/Rhythm

6. Symmetry

7. Activation procedures/Results

8. Medications

9. Location

a. Frontal

b. Temporal

c. Parietal

d. Occipital

e. Central

10. Conclusion /Remarks ---------------------------------------------------------------------------------

-----------------------------------------------------------------------------------------------------------

97

SECTION E: Laboratory Results

WBC differentials (%)

Neutrophils Lymphocyte Monocyte

Eosinophils Basophil

Sodium ________ meq/L OR ______ mmol/L MCV_______

Potassium _______ meq/L ______ mmol/L MCH_______

Total Cholesterol _____ mg/dL ______ mmol MCHC/L______

Triglycerides _______ mg/dL ______ mmol/L HbA, C_______

LDL-Cholesterol ______ mg/dL ______ mmol/L ESR________

LDL-C:HDL-C ratio ____ mg/dL ______ mmol/L

Random glucose at admission _____ mg/dL _____ mmol/L

Fasting glucose _____ mg/dL _____ mmol/L

2HPPG _____ mg/dL _____ mmol/L

Urea _____ mg/dL ______ mmol/L

Creatinine _____ mg/dL ______ mmol/L

Uric Acid

Proteinuria: Yes No If ‘Yes’, how much ?____________

Genotype: AA____ AS____ AC _____ SC ____ SS ____ Others ______________

Retroviral Screening: Yes___ No___ If positive, are you currently on medications? Yes____ No____

CD4 Count if known (if positive)___________

Date

INR PCV(%) WBC(/mm3) Platelets(x103/mm)

98

APPENDIX IV

National Institute of Health Stroke Scale (NIHSS)

Date and time DD-MM-YYYY HH:MM (24h) Score

1.a. Level of Consciousness 0: Alert

1: Not alert, but arousable with minimal stimulation

2: Not alert, requires repeated stimulation to attend

3: Coma

1.b. LOC questions (Ask patient the month and her/his age)

0: Answers both correctly

1: Answers one correctly

2: Both incorrect

1.c. LOC commands (Ask patient to open/close eyes & form/release fist)

0: Obeys both correctly

1: Obeys one correctly

2: Both incorrect

2. Best gaze (only horizontal eye movement)

0: Normal

1: Partial gaze palsy

2: Total gaze paresis or Forced deviation

3. Visual Field testing

0: No visual field loss

1: Partial hemianopia

2: Complete hemianopia

3: Bilateral hemianopia (blind including cortical blindness)

4. Facial Paresis (Ask patient to show teeth/ raise eyebrows & close eyes tightly)

0: Normal symmetrical movement

1: Minor paralysis (flattened nasolabial fold, asymmetry on smiling)

2: Partial paralysis (total or near total paralysis of lower face)

3: Complete paralysis of one or both sides (absence of facial movement in the upper and lower face)

5. Motor Function – Arm

0: Normal (extends arms 900 (or 450) for 10 seconds without drift)

1: Drift

2: Some effort against gravity

3: No effort against gravity

4: No movement

9: Untestable (Joint fused or limb amputated) (do not add score)

Right

Left

6. Motor Function - Leg

0: Normal (hold leg in 300 position for 5 sec without drift)

1: Drift

2: Some effort against gravity

3: No effort against gravity

4: No movement

9: Untestable (Joint fused or limb amputated) (do not add score)

Right

Left

7. Limb Ataxia 0: No ataxia

1: Present in one limb

2: Present in two limbs

8. Sensory (Use pinprick to test arms, legs, trunk and face- compare side to side)

0: Normal

1: Mild to moderate decrease in sensation

2: Severe to total sensory loss

9. Best Language (Ask patient to describe picture, name items, read sentences)

0: No aphasia

1: Mild to moderate aphasia

2: Severe aphasia

3: Mute

10. Dysarthria (Ask patient to read several words)

0: Normal articulation

1: Mild to moderate slurring of words

2: Near unintelligible or unable to speak

9: Intubated or other physical barrier (do not add score)

11. Extinction and inattention (Formerly Neglect) (Use visual or sensory double stimulation)

0: Normal

1: Inattention or extinction to bilateral simultaneous stimulation in one of the sensory modalities

99

2: Severe hemi-inattention or hemi-inattention to more than one modality

Total Score

100

APPENDIX V

Modified Rankin Scale (MRS)

MODIFIED RANKIN SCALE

Score Description

0

No symptoms at all

1

No significant disability despite symptoms; able to carry out all usual duties and

activities

2

Slight disability; unable to carry out all previous activities, but able to look after

own affairs without assistance

3

Moderate disability; requiring some help, but able to walk without assistance

4

Moderately severe disability; unable to walk without assistance and unable to

attend to own bodily needs without assistance

5

Severe disability; bedridden, incontinent and requiring constant nursing care and

attention

6

Dead

Total (0-6): ______

101

APPENDIX V1

STROKE LEVITY SCALE (SLS)

0

nil

1 flicker of

movement

2 active

1motion

when

gravity is

eliminated

3 active

motion

against

gravity

4 active motion

against moderate

resistance

5 normal

Best motor

power in

dominant

hand/upper limb

Best motor

power in weaker

lower limb

Speech disorder

(aphasia)

0-nil

1-present

Mobility 1-

bedbound 2-

chairbound

3-walks

with one

helper

4-walks

independently

with aids

(e.g.frame/tripod)

5-walks

unaided

MRC, Motor Research Council.

The score in the lower limb is determined as the maximum MRC power grade across the hip or

ankle joint (whichever is higher). This is tested recumbent with assessment of hip flexion and ankle

dorsiflexion. The power in the distal arm is tested by asking the patient to extend the wrist whilst

making a fist. Aphasia is present if the patient is unable to comprehend and obey commands during

assessment of items (i) and (ii) or unable to name a key.

Stroke Levity Scale = i + ii + iii + iv = maximum MRC power grade in the dexterous hand +

maximum MRS power in the affected lower limb + mobility score – 1 (if aphasia is present).

Minimum = 0, maximum = 15.

102

APPENDIX VI1

Barthel Index

A -

Date and time DD-MM-YYYY HH:MM (24h) Score

Bowels

0=Incontinent (or needs to be given enema)

5=Occasional accident (once/week)

10=Continent

Bladder

0=Incontinent, or catheterized and unable to manage

5=Occasional accident (max once per 24 h)

10=Continent (for more than 7 days)

Grooming

0=Needs help with personal care

5=Independent face/hair/teeth/shaving (implements provided)

Toilet use

0=Dependent

5=Needs some help, but can do something alone

10=Independent (on and off, dressing, wiping)

Feeding

0=Unable

5=Needs help cutting, spreading butter, etc.

10=Independent (food provided in reach)

Transfer

0=Unable, no sitting balance

5=Major help (one or two people, physical), can sit

10=Minor help (verbal or physical)

15=Independent

Mobility

0=Immobile

5=Wheelchair independent, including corners, etc.

10=Walks with help of one person (verbal or physical)

15=Independent (but may use any aid—e.g., stick)

Dressing

0=Dependent

5=Needs help, but can do about half unaided

10=Independent (including buttons, zips, laces, etc.)

Stairs

0=Unable

5=Needs help (verbal, physical, carrying aid)

10=Independent up and down

Bathing

0=Dependent

5=Independent (or in shower)

Total Score ( 0 – 100)

103

APPENDIX VII1: FIGURES AND VALUES

FIGURE 2A: ISCHAEMIC STROKE PHENOTYPING USING OCSP

Classification of Stroke subtypes %

TACI 6.12

PACI 44.89

POCI 6.12

LACI 42.87

B - FIGURE 2B: ISCHAEMIC STROKE PHENOTYPING USING TRIAL OF ORG 10172

IN ACUTE STROKE TREATMENT (TOAST)

Classification of Stroke subtypes %

Large Vessel 35.85

Small Vessel 37.74

Cardio-embolic 20.75

Undetermined 5.72

C- FIGURE 3: BACKGROUND RHYTHM AMONG STROKE PATIENTS

At Presentation 72hrs 7days 14days 30days

Alpha (%) 24.1 26.3 27.5 26.3 31.2

Abnormal (%) 74.6 68.7 56.2 45.0 25.0

D- FIGURE 4: PATTERN OF EEG WAVES FROM ADMISSION TO 30DAYS


Alpha (%) 24.1 26.3 27.5 26.3 31.2

Beta (%) 12.7 6.3 5.0 10.0 12.5

Slow waves(%) 61.9 62.4 51.2 35.0 12.5

E- FIGURE 5: EPILEPTIFORM PATTERN AMONG STROKE PATIENTS


Absent (%) 68.4 67.1 37.3 42.1 55.6

Present (%) 31.6 32.9 62.7 57.9 44.4

F- FIGURE 6: ASSOCIATION BETWEEN BACKGROND EEG WAVE

PATTERN AND OUTCOME IN ISCHAEMIC STROKE PATIENTS

(Others – Beta, Delta and Theta Waves)

Day 14 Day 30 Good Outcome Poor Outcome Good Outcome Poor Outcome

Slowing 71.4 83.3 66.7 71.4

No Slowing 28.6 16.7 33.3 28.6

p-value:0.095 p-value:0.039

104

G- FIGURE 7:ROLE OF SLOWING IN PREDICTING OUTCOME AMONG

HEAMORRHAGIC STROKE PATIENTS


Slowing 86.7 54.5 53.3 37.5

No slowing 13.3 45.5 46.7 62.5

p-value:0.047 p-value:0.005

H- FIGURE 8: TREND OF PREDICTIVE VALUES OF SLOWING AMONG STROKE

PATIENTS

At Presentation Day 14 Day 30 PPV NPV PPV NPV PPV NPV

Ischaemic 0.36 0.57 0.33 0.8 0.22 0.82

(Hae 0.46 0.4 0.32 0.29 0.27 0.58

morrhagic)

I- FIGURE 9: SHOWING ROLE OF ALPHA IN PREDICTING THE OUTCOME AMONG

ISCHAEMIC STROKE PATIENTS


Alpha 28.6 0 29.6 14.3

Others 71.4 100 70.4 85.7

J- FIGURE 10: SHOWING ROLE OF ALPHA IN PREDICTING OUTCOME

AMONG HAEMORRHAGIC STROKE PATIRNTS Day 14 Day 30

Good Outcome Poor Outcome Good Outcome Poor Outcome

Alpha 53.3 9.1 53.3 37.5

Others 46.7 90.9 46.7 62.5

K- FIGURE 11: TREND OF PREDICTIVE VALUES OF ALPHA AMONG STROKE

PATIENTS


Ischaemic 0.2 0.57 0 0.63 0.11 0.76

(Hae 0.43 0.5 0.11 0.41 0.27 0.58

morrhagic)

L- FIGURE 12: SHOWING ROLE OF BETA IN PREDICTING OUTCOME

AMONG ISCHAEMIC STROKE Day 14 Day 30


Beta 17.9 16.7 33.3 42.9

Others 82.1 83.3 66.7 57.1

105

M- FIGURE 13: ROLE OF BETA IN PREDICTING OUTCOME AMONG

HAEMORRHAGIC STROKE Day 14 Day 30


Beta 20 9 20 25

Others 80 91 80 75

FIGURE 14: SHOWING TREND OF PREDICTIVE VALUES OF BETA WAVE AMONG

STROKE PATIENTS


Ischaemic 0.14 0.6 0.29 0.7 0.17 0.81

(Hae 0.33 0.5 0.25 0.55 0.4 0.67

morrhagic)

106

APPENDIX IX

( Postive Predictive Value, Negative Predictive Value, Sensitivity, Specificity )

Contingency matrix and measures calculated based on it 2x2 contingency table for displaying

the outcome of predictions. Based on the table it is possible to calculate row and column wise

parameters, PPV and NVP, and sensitivity and specificity, respectively. Positive connotes

presence of specific EEG wave pattern or abnormality and negative connotes absence of

specific EEG wave pattern or abnormality. Accuracy is a measure that is calculated based

on all the four figures in the table.

title of research: frequency and prognostic …

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