1. health and fitness
2. disease
3. heart disease

[
ASSOCIATION OF MEAN PLATELET VOLUME
AND ISCHAEMIC STROKE
By
[
Dr Renoy A. Henry MBBS
A dissertation submitted to
Rajiv Gandhi University of Health Sciences
Bangalore, Karnataka
in partial fulfillment of
the requirements for the degree of
MD in General Medicine
under the guidance of
Dr. Prem Pais MD
Department of Medicine
St. John’s Medical College and Hospital
Bangalore.
2009
DECLARATION
I, Dr. Renoy A. Henry, hereby declare that this dissertation entitled ―Association of
mean platelet volume and ischemic stroke‖ is a bona fide and genuine research
work carried out by me under the guidance of Dr.Prem Pais.
MD,
Professor,
Department of Medicine, St. John‘s Medical College and Hospital, Bangalore.
15th October 2009
Bangalore.
Dr. Renoy A. Henry, MBBS
CERTIFICATE
This is to certify that the dissertation entitled ―Association of mean platelet volume
and ischemic stroke‖ is a bona fide research work done by Dr. Renoy A. Henry
under my guidance in partial fulfillment of the requirement for the degree of MD in
General Medicine.
15th October 2009
Bangalore
Dr. Prem Pais, MD
Professor, Department of Medicine
St. John‘s Medical College Hospital
Sarjapur Road, Bangalore 560 034
GUIDE.
CERTIFICATE
This is to certify that the dissertation entitled ―Association of mean platelet volume
and ischemic stroke‖ is a bona fide research work done by Dr. Renoy A. Henry
under my guidance in partial fulfillment of the requirement for the degree of MD in
General Medicine.
15th October 2009
Bangalore
Dr.Arun Shet, MD
Associate Professor,
Department of Medical Oncology
St. John‘s Medical College
Sarjapur Road, Bangalore 560 034
CO-GUIDE
CERTIFICATE
This is to certify that the dissertation entitled ―Association of mean platelet volume
and ischemic stroke‖ is a bona fide research work done by Dr. Renoy A. Henry
MBBS, under the guidance of Dr. Prem Pais MD, Professor, Department of
Medicine, St. John‘s Medical College and Hospital, Bangalore.
Dr. S.D Tarey, MD
Dr. Prem Pais, MD
Professor and Head, Dept. of Medicine
St. John‘s Medical College and Hospital
Bangalore
Dean
St. John‘s Medical College and Hospital
Bangalore
15th October 2009
Bangalore.
15th October 2009
Bangalore.
COPYRIGHT
DECLARATION
I hereby declare that the Rajiv Gandhi University of Health Sciences, Karnataka shall
have the rights to preserve, use and disseminate this dissertation in print or electronic
format for academic/ research purpose.
15th October 2009
Bangalore.
Dr. Renoy A. Henry, MBBS
ACKNOWLEDGEMENT
I am grateful and indebted to:
Dr. Prem Pais and Dr. Arun Shet for their guidance, support and encouragement
throughout this project.
Dr. S.D.Tarey, Dr. Girija Singh and Dr. Chandra Mouli K S for all the
encouragement and support they have given me throughout my course.
Dr. A.K Roy, Dr. G.S.K Sarma, Dr. Thomas Mathew from the department of
neurology for their support.
Dr.Karuna Ramesh Kumar and Dr. Sitalakshmi and all the others from the
department of clinical pathology for their help with peripheral smears.
Dr. Amit K Mondal and his team for allowing me to use the lab facilities.
Dr Suresh K.P for his help with statistics.
Dr. Sushmitha Pearl Fernandez, Dr. Francy Pulickan, Dr. George Xavier, Dr.
Gangyreddy Shivashankarreddy , Dr. Saikat Kanjilal, Dr. Shruthi Kulkarni, Dr.
Rajesh Alanjangi my colleagues, for their support throughout.
My juniors and my interns for their valuable help.
All the participants in my study for their cooperation, without which this work
would not have been possible.
My family especially my wife, for everything.
15th October 2009
Bangalore.
Dr. Renoy A. Henry. MBBS.
LIST OF ABBREVIATIONS
ABBREVIATIONS
1) ACE
- ANGIOTENSIN CONVERTING ENZYME
2) ADP
- ADENOSINE DIPHOSPHATE
3) ATP
- ADENOSINE TRIPOSPHATE
4) ATP - 3 - ADULT TREATMENT PANEL - 3
5) BT
- BLEEDING TIME
6) b-TG
- b-THROMBOGLOBULIN
7) CNS
- CENTRAL NERVOUS SYSTEM
8) CT
- COMPUTED TOMOGRAPHY
9) DALY
- DISABILITY ADJUSTED LIFE YEAR
10) DNA
- DEOXY RIBONUCLEIC ACID
11) EDTA
- ETHYLENE DIAMINE TETRA ACETIC ACID
12) f L
- FEMTOLITRE
13) ICH
- INTRACEREBRAL HEMORRHAGE
14) IS
- ISCHEMIC STROKE
15) LACS
- LACUNAR SYNDROME
16) MK
- MEGAKARYOCYTE
17) MPHA
- MEGAKARYOCYTE PLATELET HAEMOSTATIC AXIS
18) MPV
- MEAN PLATELET VOLUME
19) MRI
- MAGNETIC RESONANCE IMAGING
20) mRS
- MODIFIED RANKIN'S SCALE
21) NCEP
- NATIONAL CHOLESTROL EDUCATION PROGRAM
22) NIHSS
- NATIONAL INSTITUTE OF HEALTH SCIENCES
23) OCSP
- OXFORDSHIRE COMMUNITY STROKE PROJECT
24) PACS
- PARTIAL ANTERIOR CIRCULATION SYNDROME
25) PAN
- POLYARTERITIS NODOSA
26) PCT
- PLATELET COUNT
27) PDW
- PLATELET DISTRIBUTION WIDTH
28) PLCR
- PLATELETS LARGE CELL RATIO
29) POCS
- POSTERIOR CIRCULATION SYNDROME
30) PROGRESS - PERINDOPRIL PROTECTION AGAINST RECURRENT
STROKE STUDY
31) SAH
- SUB ARACHNOID HEMORRHAGE
32) SCCS
- SURFACE CONNECTED CANALICULAR SYSTEM
33) SOP
- STANDARD OPERATING PROCEDURE
34) TACS
- TOTAL ANTERIOR CIRCULATION SYNDROME
35) TOAST - TRIAL OF ORG 10172 IN ACUTE STROKE TREATMENT
36) vWF
- VON WILLEBRAND FACTOR
37) WHR
- WAIST HIP RATIO
TABLE OF CONTENTS
Page No.
1. INTRODUCTION
15
2. OBJECTIVES
18
3. REVIEW OF LITERATURE
20
4. METHODOLOGY
53
5. RESULTS
62
6. DISCUSSION
88
7. CONCLUSIONS
101
8. SUMMARY
103
9. BIBLIOGRAPHY
107
10. ANNEXURE
113
NO
FIGURES
PAGES
1 Pre analytical data
63
2 Stroke log and reasons for exclusion
64
3 Age distribution
65
4 Gender distribution
66
5 Risk factor profile
67
6 Clinical profile
The Oxfordshire community stroke project classification of
7 stroke syndromes
68
69
8 Comparison of blood parameters in cases and controls
71
9 Infarct territory
73
10 Stroke- clinical severity score
74
11 Comparison of MPV in cases and controls
75
12 Comparison of platelet mass in cases and controls
Comparison of MPV (EDTA) in cases and controls to risk
13 factors
Comparison of MPV (citrate) in cases and controls to risk
14 factors
Comparison of MPV (EDTA/citrate) in cases and controls to
15 other risk factors
76
16
Infarct territory and MPV
The Oxfordshire community stroke project Classification of
17 stroke syndromes and correlation with MPV
77
78
80
81
82
18 Stroke- clinical severity score and MPV
Comparison of platelet mass in cases according to severity
19 score
83
20 Association of MPV quintiles (EDTA) and stroke severity
85
21 Association of MPV quintiles (citrate) and stroke severity
86
84
NO
TABLES
1 Stroke log and reasons for exclusion
2 Age distribution
3 Gender distribution
4 Risk factor profile
5 Clinical profile
The Oxfordshire community stroke project classification of
6 stroke syndromes
7 Comparison of blood parameters in cases and controls
8 Type of Infarct
9 Infarct territory
10 Stroke- clinical severity score
11 Comparison of MPV in cases and controls
12 Comparison of platelet mass in cases and controls
Comparison of MPV (edta) in cases and controls to risk
13 factors
Comparion of MPV (citrate) in cases and controls to risk
14 factors
Comparion of MPV (edta/citrate) in cases and controls to
15
other risk factors
16 Infarct territory and MPV
The Oxfordshire community stroke project Classification of
17
stroke syndromes and correlation with MPV
18 Stroke- clinical severity score and MPV
Comparison of platelet mass in cases according to severity
19 score
20 Association of MPV quintiles (edta) and stroke severity
21 Association of MPV quintiles (citrate) and stroke severity
22 Multivariate logistic regression analysis to predict stroke
Comparison of Demographic data of the current study with
23 western literature
Comparison of risk factor profile of current study with
24 western literature
Comparison of drug history of patients in the current study
25 with western literature
Comparison of platelet parameters of the current study with
26 western literature.
PAGES
64
65
66
67
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82
83
84
85
86
87
91
92
94
96
ABSTRACT
BACKGROUND
Cerebrovascular diseases include some of the most common and devastating
disorders. Mean platelet volume (MPV) is a physiological variable of haemostatic
importance. Large platelets are more reactive, produce more prothrombotic factors
and aggregate more easily. Ischemic stroke is thought to occur as a result of
thrombotic occlusion of a stenosed atherosclerotic blood vessel. Initially platelets
adhere to the damaged vessel, resulting in recruitment of further platelets, followed by
aggregation, formation of a platelet plug and finally thrombotic occlusion. Thus, the
detection of large platelets in patients with cerebrovascular diseases would lend
support to the idea that platelet volume influences thrombotic large vessel occlusion
leading to ischemic stroke. Though there have been quite a few studies which have
demonstrated an association between myocardial infarction and platelet size, very few
studies have looked at the association between platelet size and ischemic stroke.
Among them there has been discrepancy regarding the sample size, methodology used
and the final results. There are no documented studies in India comparing the
association of mean platelet volume with ischemic stroke. Hence we have studied
these variables using a precise methodology in an unselected group of stroke patients
and compared them with data from age- and sex-matched control subjects.
OBJECTIVES
PRIMARY
To determine whether an association exists between mean platelet volume
(MPV) and ischemic stroke.
SECONDARY
1. To determine whether an association exists between platelet mass and
ischemic stroke.
2. To determine whether an association exists between mean platelet volume and
severity of stroke.
METHODS
This was a prospective study carried out from Nov 1st 2008 to July 31st 2009 at
St. John‘s Medical College Hospital, Bangalore, a tertiary care referral centre. The
study was carried out among fifty patients diagnosed with an acute ischemic stroke
and presenting to the medical and neurological wards in the hospital within forty eight
hours of onset of symptoms and satisfying the inclusion and exclusion criteria.
Clinical severity was assessed using Modified Rankin‘s scale. Mean Platelet Volume
was measured using an automated analyzer in both EDTA and citrate samples. Fifty
age and sex matched controls were also recruited and their Mean Platelet Volumes
assessed.
RESULTS
Mean platelet volume was higher in acute stroke. MPV( citrate) has got a statistically
significant correlation with Ischemic stroke with a p value of 0.005 with an average
MPV in cases being 7.35±0.81 compared to controls who average 6.94±0.59.Though
MPV(EDTA) also shows a strong trend in cases and controls 7.86±0.82 and
7.58±0.70, the difference is not statistically significant(P = 0.074). The platelet count
is showing a slightly lower trend in cases with an average of 2.56±0.58 (1.43- 4.40)
when compared to the controls in which the average was 2.69±0.83 (1.605.40).However this trend is not statistically significant (P = 0.380). The platelet mass
being a product of platelet count and mean platelet volume is almost a constant. This
study did not find a statistically significant correlation between clinical severity of
stroke or sub types of stroke and mean platelet volume (P = 0.281).
CONCLUSIONS
This study has shown an elevation of MPV in acute phase of Ischemic stroke. Within
this relationship and adjusting for other significant variables in multivariate regression
analysis, it can be stated that an increase in MPV is independently associated with
stroke. The observations here suggest a role for larger platelets in the genesis of
cerebral thrombosis and are likely to represent changes occurring at thrombopoiesis.
Further research is required into the role of platelet volume in stroke pathology,
outcome, and, most importantly, in individuals at risk for stroke. A prospective study,
which could follow a cohort of subjects with a high mean platelet volume over a
period of time for occurrence of ischemic strokes could be planned.
KEY WORDS : Ischemic stroke; Stroke outcome; Platelets; Mean platelet volume.
1. INTRODUCTION
Cerebrovascular diseases include some of the most common and devastating
disorders. They cause ~200,000 deaths each year in the United States and are a major
cause of disability. The incidence of cerebrovascular diseases increases with age and
the number of strokes is projected to increase as the elderly population grows, with a
doubling in stroke deaths in the United States by 203010. The prevalence of stroke in
India was estimated as 203 per 100,000 population above 20 years, amounting to a
total of about 1 million cases. Stroke is one of the major cause of human morbidity
and mortality. It ranked as the sixth leading cause of disability-adjusted years (DALY;
one DALY is one of the lost year of healthy life) in 1990 and is projected to rank
fourth by the year 202013. Ischaemic stroke (IS) accounts for about 85% of cases,
primary intracerebral haemorrhage (ICH) for 10% and subarachnoid haemorrhage
(SAH) for the remaining 5%. 7.
Most cerebrovascular diseases manifest by the abrupt onset of a focal neurologic
deficit, as if the patient was "struck by the hand of God."10 Stroke is associated with
increased long term mortality, residual physical, cognitive, and behavioral
impairments, recurrence, and increased risk of other types of vascular events .12
Several factors are known to increase the liability to stroke, and it has been here that
large-scale public health measures have had a substantial influence. The most
important of these are hypertension, heart disease, atrial fibrillation, diabetes mellitus,
cigarette smoking, and hyperlipidemia.11. Platelet size is also found to be elevated in
individuals with hypertension and diabetes mellitus2, both conditions that predispose
to the development of vascular disease3.Since this is such a huge public health
problem, other risk factors and possible preventive measures need to be identified. It
is in this context that this study has its significance.
Platelets play a crucial role in the pathogenesis of atherosclerotic complications,
contributing to thrombus formation.14 Platelets are anucleate cells and are
heterogeneous regarding their size, density and haemostatic potential. Platelet size
(mean platelet volume, MPV) is a marker and possibly determinant of platelet
function, large platelets being potentially more reactive. For example, large platelets
contain more dense granules, undergo greater in vitro aggregation in response to
agonists such as ADP and collagen, and release more serotonin and bthromboglobulin (b-TG). . In normal individuals the platelet count is inversely
proportional to MPV; platelet mass (the product of MPV and platelet count) is a near
constant. Although platelets are incapable of de novo protein synthesis they are very
active metabolically and respond rapidly to vascular injury or trauma by undergoing a
series of reactions (adhesion, release of granule contents, shape change and
aggregation), which ultimately result in the formation of a platelet–fibrin plug. Thus
there is evidence that platelet function is accentuated in acute ischaemic stroke. 7
Though there have been quite a few studies which have demonstrated an association
between myocardial infarction and platelet size, very few studies has looked at the
association between platelet size and ischemic stroke. Among them, there has been
discrepancy regarding the sample size, methodology used and the final result. There
are no documented studies in India comparing the association of mean Platelet
volume with ischemic stroke; hence an attempt has been made to study the association
if any between mean platelet volume and stroke in an Indian population.
2. OBJECTIVES
2. OBJECTIVES
2.1 PRIMARY
To determine whether an association exists between mean platelet volume
(MPV) and ischemic stroke.
2.2 SECONDARY
3. To determine whether an association exists between platelet mass and
ischemic stroke.
4. To determine whether an association exists between mean platelet volume and
severity of stroke.
3. REVIEW OF
LITERATURE
3. REVIEW OF LITERATURE
3.1 STROKE
3.1.1 HISTORY
More than 2,400 years ago the father of medicine, Hippocrates, recognized and
described stroke as the sudden onset of paralysis. In ancient times stroke was called
apoplexy, a general term that physicians applied to anyone suddenly struck down with
paralysis. Because many conditions can lead to sudden paralysis, the term apoplexy
did not indicate a specific diagnosis or cause. Physicians knew very little about the
cause of stroke and the only established therapy was to feed and care for the patient
until the attack ran its course.15
The first person to investigate the pathological signs of apoplexy was Johann Jacob
Wepfer. Born in Schaffhausen, Switzerland, in 1620, Wepfer studied medicine and
was the first to identify postmortem signs of bleeding in the brains of patients who
died of apoplexy. From autopsy studies he gained knowledge of the carotid and
vertebral arteries that supply the brain with blood. He also was the first person to
suggest that apoplexy, in addition to being caused by bleeding in the brain, could be
caused by a blockage of one of the main arteries supplying blood to the brain; thus
stroke became known as a cerebrovascular disease ("cerebro" refers to a part of the
brain; "vascular" refers to the blood vessels and arteries).15
Studies with animals have shown that brain injury occurs within minutes of an arterial
occlusion and can become irreversible within as little as an hour. In humans, brain
damage begins from the moment the occlusion starts and often continues for days
afterward. Scientists now know that there is a very short window of opportunity for
treatment of the most common form of stroke. Because of this, the significance of
prevention needs to be highlighted and new risk factors and primary preventive
strategies need to be identified.
3.1.2 EPIDEMIOLOGY
3.1.2a INCIDENCE AND PREVALENCE WORLDWIDE
Cerebrovascular diseases cause ~200,000 deaths each year in the United States and
are a major cause of disability. The incidence of cerebrovascular diseases increases
with age, and the number of strokes is projected to increase as the elderly population
grows, with a doubling in stroke deaths in the United States by 203010.
Epidemiology of stroke in a white population of 1 million.12
3.1.2b INDIAN SCENARIO
The prevalence of stroke in India was estimated as 203 per 100,000 population above
20 years, amounting to a total of about 1 million cases. The male to female ratio was
1.7. Around 12% of all stroke occurred in population below 40 years. The estimation
of stroke mortality was seriously limited by the method of classification of cause of
death in the country. The best estimate derived was 102,000 deaths; which
represented 1.2 % of total deaths in the country.13
3.1.3 PATHOPHYSIOLOGY
Acute occlusion of an intracranial vessel causes reduction in blood flow to the brain
region it supplies. The magnitude of flow reduction is a function of collateral blood
flow and this depends on individual vascular anatomy and the site of occlusion. A fall
in cerebral blood flow to zero causes death of brain tissue within 4–10 min; values
<16–18 mL/100 g tissue per min cause infarction within an hour; and values <20
mL/100 g tissue per min cause ischemia without infarction unless prolonged for
several hours or days. If blood flow is restored prior to a significant amount of cell
death, the patient may experience only transient symptoms, i.e., a TIA. Tissue
surrounding the core region of infarction is ischemic but reversibly dysfunctional and
is referred to as the ischemic penumbra. The ischemic penumbra will eventually
infarct if no change in flow occurs, and hence saving the ischemic penumbra is the
goal of revascularization therapies10.
Focal cerebral infarction occurs via two distinct pathways (1) a necrotic pathway in
which cellular cytoskeletal breakdown is rapid, due principally to energy failure of the
cell; and (2) an apoptotic pathway in which cells become programmed to die.
Ischemia produces necrosis by starving neurons of glucose, which in turn results in
failure of mitochondria to produce ATP. Without ATP, membrane ion pumps stop
functioning and neurons depolarize, allowing intracellular calcium to rise. Cellular
depolarization also causes glutamate release from synaptic terminals; excess
extracellular glutamate produces neurotoxicity by activating postsynaptic glutamate
receptors that increase neuronal calcium influx. Free radicals are produced by
membrane lipid degradation and mitochondrial dysfunction. Free radicals cause
catalytic destruction of membranes and likely damage other vital functions of cells.
Lesser degrees of ischemia, as are seen within the ischemic penumbra, favor apoptotic
cellular death causing cells to die days to weeks later10.
3.1.4 ETIOLOGY 10
Common Causes
Uncommon Causes
Thrombosis
Lacunar stroke (small
vessel)
Large vessel
thrombosis
Dehydration
Embolic occlusion
Artery-to-artery
Carotid bifurcation
Aortic arch
Arterial dissection
Cardioembolic
Atrial fibrillation
Mural thrombus
Myocardial infarction
Dilated
cardiomyopathy
Valvular lesions
Mitral stenosis
Mechanical valve
Bacterial endocarditis
Paradoxical embolus
Atrial septal defect
Patent foramen ovale
Atrial septal aneurysm
Spontaneous echo
contrast
Hypercoagulable disorders
Protein C deficiency
Protein S deficiency
Antithrombin III deficiency
Antiphospholipid syndrome
Factor V Leiden mutation
Prothrombin G20210 mutation
Systemic malignancy
Sickle cell anemia
β-Thalassemia
Polycythemia vera
Systemic lupus erythematosus
Homocysteinemia
Thrombotic thrombocytopenic purpura
Disseminated intravascular coagulation
Dysproteinemias
Nephrotic syndrome
Inflammatory bowel disease
Oral contraceptives
Venous sinous thrombosis
Fibromuscular dysplasia
Vasculitis
Systemic vasculitis (PAN, Wegener's,
Takayasu's, giant cell arteritis)
Primary CNS vasculitis
Meningitis (syphilis, tuberculosis, fungal,
bacterial, zoster)
Cardiogenic
Mitral valve calcification
Atrial myxoma
Intracardiac tumor
Marantic endocarditis
Libman-Sacks endocarditis
Subarachnoid hemorrhage vasospasm
Drugs: cocaine, amphetamine
Moyamoya disease
Eclampsia
3.1.5 RISK FACTORS10
Number Needed to Treat
Risk Factor
Relative Relative Risk
Risk
Reduction with
Treatment
Primary
Prevention
Secondary
Prevention
Hypertension
2–5
38%
100–300
50–100
Atrial fibrillation
1.8–2.9
68%warfarin, 21%
aspirin
20–83
13
Diabetes
1.8–6
No proven effect
Smoking
1.8
50% at 1 year,
baseline risk at 5
years post cessation
Hyperlipidemia
1.8–2.6
16–30%
560
230
Asymptomatic
carotid stenosis
2.0
53%
85
N/A
Symptomatic carotid
stenosis (70–99%)
65% at 2 years
N/A
12
Symptomatic carotid
stenosis (50–69%)
29% at 5 years
N/A
77
3.1.6 DEFINITIONS
TIA is defined as when all neurologic signs and symptoms resolve within 24 h
regardless of whether there is imaging evidence of new permanent brain injury.10,12
A Stroke has occurred if the neurologic signs and symptoms last for >24 h.10,12
3.1.7 CLASSIFICATION
The Oxfordshire Community Stroke Project12 classification of stroke syndromes,
based on easily observed clinical features, has good positive and negative predictive
values against brain imaging once the stroke lesion is complete, and before any of the
signs have resolved.
1) Lacunar syndromes (LACS):
– no visual field defect
– no new disturbance of higher cortical or brainstem function
– pure motor hemiparesis, or pure sensory deficit of one side of the body, or sensory
motor hemiparesis, or ataxic hemiparesis(dysarthria clumsy hand syndrome or
ipsilateral ataxia with crural hemiparesis)
– at least two of the three areas (face, arm, leg) should be involved, and the limb
should be involved in its entirety.
2) Posterior circulation syndromes (POCS)
any one of:
– cranial nerve impairment
– unilateral or bilateral motor or sensory deficit
– disorder of conjugate eye movement
– cerebellar dysfunction
– homonymous hemianopia
– cortical blindness.
3) Total anterior circulation syndromes (TACS):
– hemiplegia and homonymous hemianopia contralateral to the lesion, and
– either aphasia or visuospatial disturbance
– sensory deficit contralateral to the lesion.
4) Partial anterior circulation syndromes(PACS):
– one or more of unilateral motor or sensory deficit, aphasia or visuospatial neglect
(combined or not with homonymous hemianopia)
– motor or sensory deficit may be less extensive than in lacunar syndromes (for
example, hand alone).
3.2 PLATELETS
Platelets are small anucleate cells that play a critical role in haemostasis and
thrombosis16. Platelets were described by Addison in 1841 as ―extremely minute
granules‖ in clotting blood and were termed platelets by Bizzozero, who observed
their adhesive qualities as ―increased stickiness when a vascular wall is damaged‖.
They are formed from the cytoplasm of megakaryocytes and have a characteristic
discoid shape. Platelets are released from the ends of megakaryocytes as oval discs
with average size of 2 μm. Younger platelets have greater functional ability. Each
megakaryocyte forms 103platelets and 1011 platelets are replenished daily17.
3.2.1 PLATELET FORMATION
3.2.1a MEGAKARYOCYTE DEVELOPMENT.
Megakaryocytes are rare myeloid cells(constituting less than 1% of these cells) that
reside primarily in the bone marrow but are also found in the lung and peripheral
blood. In early development, before the marrow cavities have enlarged sufficiently to
support blood cell development, megakaryopoiesis occurs within the fetal liver and
yolk sac. Megakaryocytes arise from pluripotent stem cell that develop into 2 types of
precursors, burst-forming cells and colony-forming cells, both of which express the
CD34 antigen64. Thrombopoietin (TPO), the primary regulator of thrombopoiesis, is
currently the only known cytokine required for megakaryocytes to maintain a constant
platelet mass. TPO is thought to act in conjunction with other factors, including IL-3,
IL-6, and IL-11, although these cytokines are not essential for megakaryocyte
maturation64.
3.2.1b THE FLOW MODEL OF PLATELET FORMATION.
Despite the identification of platelets over 120 years ago, there is still little consensus
on many of the mechanisms involved in platelet biogenesis. However, recent evidence
supports a modified flow model of platelet assembly. In this model, platelets are
assembled along essential intermediate pseudopodial extensions, called proplatelets,
generated by the outflow and evagination of the extensive internal membrane system
of the mature megakaryocyte. In 1906, Wright introduced the initial concept that
platelets arise from megakaryocyte64 extensions when he described the detachment of
platelets from megakaryocyte pseudopods. Almost a century later, studies on
megakaryocytes producing platelets in vitro have revealed the details of platelet
assembly and have led us back to the classical proplatelet theory of platelet release in
which platelets fragment from the ends of megakaryocyte extensions.64
The assembly of platelets from megakaryocytes involves an elaborate dance that
converts the cytoplasm into 100- to 500-μm-long branched proplatelets on which the
individual platelets develop. The proplatelet and platelet formation process generally
commences from a single site on the megakaryocyte where 1 or more broad
pseudopodia form. Over a period of 4–10 hours, the pseudopodial processes continue
to elongate and become tapered into proplatelets with an average diameter of 2–4 μm.
Proplatelets64are randomly decorated with multiple bulges or swellings, each similar
in size to a platelet, which gives them the appearance of beads connected by thin
cytoplasmic strings . The generation of additional proplatelets continues at or near the
original site of proplatelet formation and spreads in a wavelike fashion throughout the
remainder of the cell until the megakaryocyte cytoplasm is entirely transformed into
an extensive and complex network of interconnected proplatelets. The multilobed
nucleus of the megakaryocyte cell body is compressed into a central mass with little
cytoplasm and is eventually extruded and degraded. Platelet-sized swellings also
develop at the proplatelet ends and are the primary sites of platelet assembly and
release, as opposed to the swellings along the length of the proplatelet shaft . The
precise events involved in platelet release from proplatelet ends have not been
identified. 64
Anatomy of a proplatelet. Differential interference contrast image of proplatelets on
a mouse megakaryocyte in vitro. Some of the hallmark features of proplatelets,
including the tip, swellings, shafts, and a branch point, are indicated. Scale bar, 5
mm.64
3.2.2 PLATELET LIFE SPAN
Normally, platelets circulate in blood with an average lifespan of 7-10 days.
Platelets are lost from circulation by two mechanisms: either by senescence or by
random removal in endothelial supportive functions of a fixed fraction of platelets
amounting to 7.1x109/l/day. Senescent platelets are removed primarily by
macrophages in the spleen, although the larger blood flow through the liver allows
severely damaged platelets to be removed more quickly by hepatic macrophages17. It
is assumed that when aging, platelets contain decreased levels of sialic acid and they
accumulate surface IgG18.
3.2.3 LIGHT MICROSCOPY
Light microscopy of Wright-stained smears reveals platelets are small, anucleate
fragments with occasional reddish granules, measuring approximately 2μm in
diameter with a volume of approximately 8fl19,20 and exhibiting considerable variation
in size and shape.
Figure : Microscopic appearance of platelets in Leishman stained smear (X 1000)
3.2.4 ELECTRON MICROSCOPY AND SUB-CELLULAR FEATURES
Platelets exist in two distinct forms, resting and activated, with the resting state
marked by baseline metabolic activity and the activated form resulting from agonist
stimulation (i.e., response to thrombin) because platelets change their structure during
the ―resting-to activated‖ transition. In describing detailed platelet anatomy, most
information is derived from transmission electron microscopy, and platelet structure is
classified into four general areas: the platelet surface, membrane structures,
cytoskeleton (sol-gel zone), and granules21.
3.2.5 PLATELET SURFACE
Plasma Membrane: The platelet plasma membrane separates intra- from extracellular
regions and, in thin sections, exhibits a typical 20 nm thick trilaminar
structure22whose overall appearance does not differ from that of other blood cells23.
However this ―unit membrane‖ of platelets is exceptionally complex in composition,
distribution, and function, incorporating a number of glycoproteins and lipids into its
phospholipid bi-layer and integrating a variety of extra and intra-platelet events such
as permeability, agonist stimulation, and platelet adhesion, activation/secretion, and
aggregation24.
Glycocalyx: A fuzzy layer of lipids, sugars, and proteins. 15-20 nm thick, coats the
outside surface of the platelet plasma membrane, including surface connected
canalicular system SCCS), and interacts with both the plasma and the cellular
components of the blood and blood vessels. Termed the platelet glycocalyx25, the
layer provides a transfer point for plasma proteins such as fibrinogen as they are taken
up into secretory granules by endocytosis26. The glycocalyx contains glycoproteins,
glycolipids, mucopolysaccharides, and absorbed plasma proteins27, 28 and produces a
net negative surface charge mainly due to sialic acid residues on certain protein such
as gpIb29. This charge is thought to minimize attachment of circulating platelets to
each other and to vessels30.
3.2.6 PLATELET MEMBRANOUS SYSTEMS
Platelets have features of muscle-related cells in terms of their high content of
their actin and their contractile response during activation. Similar muscle like
qualities found in the two membranous systems of platelets, the SCCS and the dense
tubular system, which resemble transverse tubules and sarcotubules, respectively
23
Ultra structure of unstained human platelets. Membranous organelles, including
the surface-connected canalicular system (SCCS), and dense tubular system (DTS),
and cytoplasmic organelles, including mitochondria (M), α-granules (G), dense bodies
(DB), coated vesicles (CV), microtubules (MT) and glycogen (GLY) are visualized at
the ultra structure level.23
3.2.7 PLATELET CYTOSKELETON
Both the shape of platelets and their ability to contract and spread depend on a
cytoplasmic frame work of monomers, filaments, and tubules that constitute the
cytoskeleton32.The cytoskeleton can direct platelet shape change, send out
extracellular extensions, collect and then extrude secretory granules, and affect
surface activity. These varied functions are performed by three distinct structures:
first, the membrane skeleton, which buttresses the inner side of the plasma membrane;
second, the mass of actin and intermediate filaments, which fills the cytoplasm
(cytoplasmic actin filaments; also termed the sol-gel zone); and third, the
circumferential microtubule band, which encircles the substance of the platelet to
produce the resting disclike form32, 33.
3.2.8 PLATELET GRANULES AND ORGANELLES
3.2.8a PLATELET GRANULES
Normal platelet function appears to require some amplification or accentuation of
any given stimulus to obtain an appropriate response. Accordingly, platelets possess
secretory granules and mechanisms that serve this purpose by releasing additional
stimulatory materials, previously sequestered within the resting platelet. Two main
secretory granules, the α-granules and the dense bodies , appear to be the main
effectors with their highly reactive and readily available contents [i.e. adenosine
diphosphate (ADP) and fibrinogen]
34
. Platelet granule secretion begins with a
dramatic increase in platelet metabolic activity, set off by a wave of calcium release
and marked by increased adenosine phosphate (ATP) production 35, 36.
Contents of three different granule subpopulations of platelets.37
3.2.8b ORGANELLES : MICROPEROXISOMES, COATED VESICLES,
MITOCHONDRIA, AND GLYCOGEN
Microperoxisomes are rare, small (90 nm in diameter) granules, demonstrable with
alkaline diaminobenzidine due to their catalase activity38. The structure may
participate in the synthesis of platelet-activating factor, but its ultimate fate within the
platelet cytoplasm is unknown39. Coated vesicles are 70 to 90 nm in diameter platelet
organelles, distinguished by their electron dense bristle coat. The polyhedral surface
coat is composed of clathrin, and special staining reveals that the same coat that is in
the plasma and SCCS membrane is found on the coated pits and vesicles
themselves40. Mitochondria in platelets are similar, with the exception of their smaller
size, to those in other all types. There are approximately seven per human platelet,
and they serve as the site for the actions of the respiratory chain and the citric acid
cycle41. Glycogen is found in small particles or in masses of closely associated
particles, playing an essential role in platelet metabolism42.
3.2.9 PLATELET FUNCTION
The functions of platelets include adhesion, shape change and spreading, aggregation,
secretion, procoagulant activity, and clot retraction.
ADHESION: The initiating event following vascular damage is platelet adhesion to
exposed subendothelial matrix proteins. The platelet glycoprotein receptors which
mediate adhesion are dependent on the rate of shear. Adhesion applies also to
recruitment of circulating platelets into the thrombus43.
SHAPE CHANGE AND SPREADING: Upon activation, platelets become spherical
and extend pseudopodia to enable them to attach to other platelets and to the vessel
wall. The transition to a sphere increases their optical density is termed ‗shape
change‘, although this term should be used with caution unless supported by scanning
electron microscopy, as an increase in density can also be brought about in other
ways. Shape change is mediated by phosphorylation of myosin light chains, either as
a consequence of elevation in intracellular Ca2+ ions, which activate myosin light
chain kinase, or through inhibition of myosin light chain phosphatase, which is
regulated downstream of Rho kinase43.
AGGREGATION: Aggregation is used to describe cross-linking of platelets through
binding of fibrinogen, or other bivalent or multivalent ligands such as vWF to the
integrin αIIbβ3 on adjacent cells43.
SECRETION: The three types of granules contain a distinct set of contents that play
varying roles in haemostasis. A deficiency in dense or α-granules is the basis of a
heterogenous group of secretory disorders that are associated with excessive
bleeding43.
PROCOAGULANT ACTIVITY: A critical function of platelet activation is to
provide a negatively charged phospholipid surface for the assembly of two
multiprotein complexes that form a vital part of the coagulation cascade, namely the
tenase and prothrombinase complexes. The formation of the negatively charged lipid
surface on activated platelets is commonly described as antiphospholipid exposure or
procoagulant activity. It is formed by the movement of phosphatidyl serine from the
inner to the outer leaflet of the platelet membrane43.
PLATELET-DERIVED MICROPARTICLES: Platelet-derived microparticles are
generated during platelet activation and are usually seen together with an increase in
procoagulant activity. The formation of platelet microparticles also requires Ca2+
entry and is readily seen in response to stimulation by Ca2+ ionophore but requires
high agonist concentrations and favourable conditions for them to be formed upon
receptor activation43.
CLOT RETRACTION: It has been known for more than two centuries that blood
clots retract over a time course of minutes to hours, a process that is termed clot
retraction. This event helps platelet rich thrombi to withstand the high shear forces
found in small arterioles and in other vessels. Clot retraction can be readily measured
in thrombin-stimulated platelet-rich plasma by taking aliquots of the volume of
plasma over time after addition of thrombin. Thrombin rapidly generates a blood clot
that fills an aggregometer tube but which gradually reduces to almost 20% of its
original volume over a course of 60 minutes43.
3.2.10 PLATELET INDICES
The quantification of platelet count in peripheral blood is a well recognized tool.
Similar to RBC, several indices have been derived from platelets, with the most
commonly used being the mean platelet volume (MPV) and platelet distribution width
(PDW). Recent advances in automated blood cell analysers have made it possible to
measure various platelet parameters such as PDW, MPV, PCT and P-LCR, which
provide some important information but are not yet accepted for routine clinical use44.
3.3 MEAN PLATELET VOLUME (MPV)
Measurement of peripheral blood platelet counts tells us little about platelet related
haemostatic function unless the platelet count is particularly low. However, most
haematology analysers measure another platelet parameter, the mean platelet volume
which can give useful clinical and patho-physiological information about patients and
vascular diseases.8
3.3.1 PHYSIOLOGY OF PLATELET SIZE
MPV appears to be a marker, or even a determinant, of platelet function. Large
platelets are more reactive than small platelets in vitro. They preferentially and more
rapidly aggregate to platelet agonist including ADP, collagen and adrenaline produce
more prothrombotic and vasoactive factors including arachidonic acid metabolites
(eg. Thromboxane A2), serotonin, β thromboglobulin and ATP, contains more dense
granules, and have higher LDH activity.8 .They are associated with a decreased
bleeding time (BT; a measure of in vivo haemostatic function).7
MPV correlates with platelet aggregation, whether measured in platelet rich plasma or
whole blood, populations of subjects or in some disease states, eg. Diabetes mellitus.
Large platelets also express increased levels of adhesion molecules. eg. P- selectin,
GPIIb/IIIa although the surface density of these glycoproteins is usually constant
independent of platelet volume. 8
3.3.2 THE MEGAKARYOCYTE-PLATELET-HAEMOSTATIC AXIS
Platelets are anucleate cells and, as such, have little or no protein synthetic capacity.
Platelets are heterogeneous regarding their size, density and haemostatic potential. It
used to be thought that platelet size decreased with age, but more recent evidence
suggests that MPV and other platelet parameters and, therefore, platelet protein
content and reactivity, are determined primarily at or before thrombopoiesis by the
platelet precursor cell, the MK. MK‘s are unique amongst mammalian cells in that
they are polyploid. That is to say they can redouble their chromosomal DNA content
without subsequent full mitotic cell division, a process termed endomitosis. MK‘s
undergo varying numbers of endomitotic cycles to produce a population of cells
whose ploidy ranges from 4N to 128N (where 2N represents the normal diploid state),
with 16N being the modal ploidy in the majority of mammals studied thus far. Each
MK produces about 1000 to 2000 platelets, probably by cytoplasmic fragmentation of
MKs in the pulmonary circulation7.
Measurements of platelet and MK parameters in man suggest that they are so closely
linked that they can be considered a single system: the megakaryocyte-platelet
haemostatic axis (MPHA). For example, in normal individuals the platelet count is
inversely proportional to MPV; platelet mass (the product of MPV and platelet count)
is a near constant; platelet mass correlates with BT; and BT is inversely proportional
to MK ploidy and size. When acute platelet destruction occurs in the absence of
platelet production MPV increases but MK ploidy remains unchanged; when platelet
production is increased alone MK ploidy is increased; and when platelet destruction
and production co-exist there is an increase in both MPV and MK ploidy. Thus, it
would appear that MPV and MK ploidy can change together or independently of each
other in response to varying haemostatic demands. This has led to the postulation that
regulation of MPV and MK ploidy (and therefore platelet count) is under separate
hormonal control. Variations in MPV are a result of a change in the rate of platelet
destruction, whereas altered MK ploidy, and concomitant changes in MK size and
cytoplasmic volume are associated with a change in the rate of platelet production. 7
3.3.3 MEASUREMENT OF PLATELET VOLUME
The optimal method for measuring platelet volume utilises changes in either electrical
impedance (as used in Coulter haematology analysers) or light diffraction (as used by
Technicon) when a platelet passes through a narrow aperture. Alternative and less
satisfactory methods include semi-quantitative measurement of diameter on platelet
smears, or using flow cytometry8.
In the Coulter series, cells held in fluid suspension are flown through a small aperture,
thereby creating a change in voltage proportional to particle size. A raw histogram is
generated, and a log-normal curve is fitted to the data. Platelet count is derived from
this together with the MPV, which is calculated by numerical integration 1. Similarly,
the Sysmex measures parameters with cells in fluid suspension, although in addition
the cells are hydro dynamically focused, ensuring that cells travel in a straight line
through the aperture. This prevents cells flowing through at the edge of the aperture
and causing spurious changes in the electrical field. It also differs from Coulter in that
the upper and lower discriminators are both mobile1. The distribution curve obtained
is thus the actual data and not a fitted curve. MPV is calculated from the curve by a
formula (MPV (fL)=Pct (%)x1000÷Plt (x103/μL)). In contrast,Technicon instruments
use laser-optic technology to measure the size and granularity of cells in suspension.
A beam of light is passed through cells, and the amount of forward scatter is
proportional to size of particles, whereas side scatter equates to density or granularity.
A platelet histogram is derived from the data, and MPV is calculated as the mode.
Differences of up to 40% have been found when Coulter and Technicon results have
been compared.1
Complete blood count specimens are usually anticoagulated in EDTA which causes
platelet to swell in a time dependent manner. Most of the increase in MPV occurs
during the first 1.5 hr but the process continues over the next 24 hrs. EDTA is thought
to increase intracellular cyclic AMP and change plasma membrane permeability1.
This situation is further complicated since analysers utilising light diffraction measure
particle size by assessing optical density. These analysers record a decreasing MPV
with time since platelet swelling results in a lower optical density. As a result, studies
reporting raw MPV measurements made in EDTA are of questionable clinical or
research value unless MPV is assessed at a consistent time following phlebotomy, or
once the swelling has ceased at 24 hrs. In contrast MPV measured in high
concentration sodium citrate does not change with time8 and hence considered as the
gold standard.
3.3.4 NORMAL VALUES FOR MPV
The normal range for platelet volume has yet to be adequately determined, but studies
measuring MPV in sodium citrate in normal subjects suggest a approximately normal
range of 4.5 – 8.5 fl with a mean of 6.5 fl8. The day to day variation in MPV is small
(CV =2.1%) compared with platelet count.(CV = 6.1%)8.
3.3.5 MPV AND STROKE
In some pathologic conditions the MPHA is chronically or acutely perturbed resulting
in the production of hyper functional platelets which may be involved in subsequent
vascular disease or an acute thrombotic event such as stroke. There is evidence that
platelet function is accentuated in acute ischaemic stroke7. Therefore, a fundamental
issue is whether this increase in platelet reactivity precedes the stroke, and plays a part
in initiating the event, or represents a reactive change to it. The development of
atherosclerosis involves local platelet adhesion, but whether widespread systemic
activation of platelets is present is open to question. The study of MK‘s and platelets
in the acute stage (within 36 hrs of onset) of stroke would yield valuable information
on this subject. MPV measured at this stage may well reflect (at least in part) the
potential reactivity of platelets prior to the stroke. However, the dynamics of platelet
consumption and production in the acute phase of stroke are not yet understood well
enough to rule out the possibility that MPV is being modified to some extent by the
acute destruction of platelets and subsequent change in the fragmentation of MK
cytoplasm. If MK parameters could be shown to be abnormal shortly following the
stroke this would strongly suggest that the MPHA was chronically perturbed prior to
the stroke7. Increased platelet function, and in some cases, a shift in MK indices in a
prothrombotic direction has been shown in stroke risk factors such as hypertension,
hypercholesterolaemia, diabetes mellitus and smoking, and in vascular conditions
associated with stroke, such as atherosclerosis, MI and peripheral vascular disease.
Thus it would seem probable that in patients with certain risk factor profiles systemic
platelet activation precedes the onset of stroke7.
There have been multiple studies looking at the correlation of MPV and Ischaemic
stroke.
O‘malley et al1 studied 58 stroke patients consecutively admitted to a geriatric
medical unit. Platelet variables were measured in the acute (<48 hours after stroke)
and chronic (>6 months) phases of cerebral ischemia and compared with control
variables. Control patients, admitted to the same unit were of similar age and sex and
without evidence of acute vascular events. Mean platelet volume was higher in acute
stroke (11.3 compared with 10.1 fL in control subjects; P<.001, Student's t test). In
addition, platelet count was reduced in stroke patients (255x109/L) compared with
control subjects (299x109/L; P<.01). Repeated measurements of mean platelet
volume and platelet count in available survivors showed no significant change from
the acute phase. Platelet changes did not relate to outcome measured at 6 months. In
conclusion, this study has shown an elevation of MPV and reduction of platelet count
in acute stroke that persist long after the acute event. Within this relationship and
adjusting for other significant confounding variables in univariate analysis, an
increase in MPV is independently associated with stroke. The observations here
suggest a role for larger platelets in the genesis of cerebral thrombosis and are likely
to represent changes occurring at thrombopoiesis1.
Philip Bath et al4in a sub study of the PROGRESS trial followed 3134 individuals
for an average of 3.9 years and assessed the association of MPV with the risk of
stroke. The Perindopril Protection Against Recurrent Stroke Study (PROGRESS)
recruited 6105 individuals with a history of cerebrovascular disease and
demonstrated that a blood pressure lowering regimen, involving an angiotensinconverting enzyme (ACE) inhibitor and diuretic, reduced the risks of stroke and
major vascular events. The mean age was 65 years; 71% male; average MPV, 10.0
fL. Three hundred eighty-three individuals had 402 stroke events, and 160 had
major coronary events. MPV was positively associated with the risk of stroke, with
an 11% increased relative risk (95% CI, 3% to 19%) of stroke per femtoliter greater
MPV. There was no clear association of MPV with the risk of major coronary
events (9% decreased relative risk; 95% CI, 23% to 7%). Perindopril did not alter
MPV. This study concluded that MPV is an independent predictor of the risk of
stroke among individuals with a history of stroke or transient ischemic attack. The
measurement of MPV may add useful prognostic information for clinicians
managing patients with a history of cerebrovascular disease.4
Greisenegger et al14performed a cross sectional study nested in a stroke registry of patients admitted to
Vienna, Austria. Patients with stroke or transient ischemic attack (TIA) who were
admitted to one of the participating centres between October 1998 and June 2001
were prospectively documented. During that period, 2400 patients with an acute
TIA/ischemic stroke were admitted to 1 of the participating centres. A total of 1078
patients from 3 centres in which MPV was not routinely determined were excluded.
Of the remaining 1322 patients, MPV was determined on admission in 846 cases
(64%), whereas in the other 476 patients (36%), MPV was not determined on
admission. The Modified Rankin Scale (mRS) was available in 776 (92%) of those
patients with an MPV value on admission. By multivariate logistic regression
modelling, they determined the influence of MPV on stroke severity, adjusting for
potential confounding factors. Patients within the highest quintile of MPV had a
significantly higher risk of suffering a severe stroke, defined as modified Rankin
Scale score of 3 to 6, compared with patients within the lowest quintile (odds ratio
= 2.6; 95% confidence interval, 1.6 to 4.1; P<0.001). This association remained
significant after adjustment for possible confounding factors (odds ratio = 2.2; 95%
confidence interval, 1.2 to 4.0; P<0.013).In conclusion an elevated MPV is
associated with a worse outcome for acute ischemic cerebrovascular events
independent of other clinical parameters14.
Antonio Muscari et al45 studied one hundred and thirty-seven patients with ischemic
stroke, aged 75.4±11.0 (SD) years, and classified them according to several criteria
National Institutes of Health Stroke Scale (NIHSS) score, maximum lesion
diameter on CT scan, Oxfordshire Community Stroke Projects (OCSP) and Trial of
ORG 10172 in Acute Stroke Treatment (TOAST) categories. Platelet parameters
were determined 1.2 days after the onset of symptoms, and after 3.0 further days.
The initial MPV was higher in non-lacunar than lacunar strokes (8.30±1.10 vs.
7.95±0.79 fl, P=0.04), and correlated with the sampling delay with respect to the
onset of symptoms, especially in the strokes with lesions N=4 cm (r=0.39,
P=0.009), NIHSS N=11 (r=0.35, P=0.02) and of cardioembolic origin (r=0.35,
P=0.01). Subsequently a late MPV increment was observed in the remaining
categories: from 8.20 to 8.38 fl (P=0.02) in the strokes with lesions < 4 cm, from
8.11 to 8.31 fl (P=0.01) in the presence of an NIHSS<11 and from 8.20 to 8.61 fl
(P=0.03) when the occlusion of a large artery was involved. This study has
examined for the first time the spontaneous variability of MPV during the acute
phase of ischemic stroke and has shown, in contrast with what was previously
thought that this parameter is not stable. In fact MPV increases early in the strokes
characterized by greater neurological impairment, and later in the less compromised
categories. This may reflect the release in the circulation of more reactive platelets
in response to mediators coming from the peripheral ischemic sites. Platelet volume
is not stable during the acute phase in non-lacunar ischemic strokes, as it increases
early in the most severe forms, and later in the remaining subtypes. The release of
large and more reactive platelets may contribute to the thrombophilic state
associated with ischemic events.45
Butterworth and Bath46 studied MPV and Platelet count in 167 hospitalized patients
with stroke within 48 h of symptom onset, and 65 age, gender and race matched
controls. Stroke was clinically and radiologically sub-typed. MPV was significantly
higher in patients with ischaemic stroke than the control group: mean (SD) 7.35
(1.05) vs 7.09 (0.74) fl, 2P = 0.04; this difference could be explained by MPV being
higher in patients with cortical stroke: 7.46 (1.00) fl, 2P = 0.039, but not lacunar
infarction: 7.14 (1.16) fl, 2P = 1.0. No difference was seen in PC between
ischaemic patients and controls: 231×109 /l vs 236×109/l, 2P = 0.63. MPV did not
change at 3 months post-stroke in surviving patients with ischaemic stroke: 7.39
(1.03) fl vs 7.34 (0.97) fl, 2P = 0.53. Patients who were dead or dependent at 3
months had a significantly higher baseline MPV and a tendency to a lower PC than
those who returned to independence. MPV and PC were not altered in patients with
primary intracerebral haemorrhage. No differences in red cell volume were
observed. Platelet volume is elevated in acute ischaemic stroke, a finding that
persists at 3 months post-stroke and is limited to patients with cortical infarction.
Thrombomegaly is a risk factor for a poor outcome after ischaemic stroke.46
Slaven Pikija et al47 included consecutive acute ischemic stroke patients referred to
their institution i.e. Department of Neurology, County Hospital Varazdin,Croatia
over a predefined 5-month period. Patients were included in the present analysis
when the following criteria were met: (1) Admission/MPV determination within 36
h since the stroke onset. (2) CT scan performed no later than 84 h since the
symptom onset
with visible fresh ischemic lesions. (3) Patients were free of malignancy or severe
infectious/inflammatory diseases. (4) Consent was obtained (patients/relatives) for
using medical data for research purposes. All CT scans were done using a Siemens
Somatom Emotion Duo® apparatus and were evaluated by the same investigator
unaware of other patients‘ particulars. All infratentorial and supratentorial surfaces
were summed up separately and were multiplied by the respective slice
thicknesses(3 and 8mm) to yield respective lesion volumes47. The sum of the
infratentorial and supratentorial volumes gave the overall approximate infarct
volume (in cm3). Blood samples (for hematology) were analyzed using Abbott
Cell-Dyn® 3700 hematology analyzer (EDTA, <2 h between venipuncture and
analysis, stored at room temperature, in order to minimize platelet swelling).
Modified Rankin scale (mRS, 0 = no symptoms at all, 6 = death) was implemented
7 days and 3 months after the stroke by the same rater. MPV (within 30 h since
stroke onset), infarct volume (13–83 h since stroke onset) and clinical outcomes
were evaluated in 81 consecutive patients (32 men, age 52–91 years, 10 small artery
occlusion,10 large artery atherosclerosis, 29 cardioembolic, 32 multiple
probable/possible etiology). Higher MPV was independently associated with larger
infarct volume [estimate 0.259, 95% confidence interval (CI) 0.004–0.513, P =
0.046], greater risk of death/dependence 7 days post-stroke [relative risk (RR) =
1.077, 95% CI 1.005–1.115, P = 0.036], and greater risk of death/dependence 3
months post-stroke (RR = 1.077, 95% CI 1.001–1.158, P = 0.048)47. Considered
covariates: stroke etiology, CT scan timing, platelet count and other hematological
parameters, demographic variables, history of cerebrovascular, cardiac or
cardiovascular diseases, diabetes, serum chemistry, previous antiplatelet and statin
use and treatments delivered after the index event. Thus data support the view about
MPV as a determinant of severity/outcome of the acute ischemic stroke47.
Negative correlation has been found in study by Tohji et al.6 They studied 22
patients with cerebral thrombosis (age 43-83, mean±SD 64.0±12.9 years) and 29
controls (age 43-81, mean±SD 55.3±9.5 years). The patients were studied serially,
during the acute (<7 days), subacute (2-3 weeks), and chronic (4-5 weeks) periods
after the stroke. The controls were healthy individuals who had not received any
drug. During the acute and subacute periods, platelet aggregation, platelet count,
plateletcrit, and mean platelet volume were significantly less in the patients than in
the controls (p<0.05-0.01) while the adenosine triphosphate release rate per volume
of platelets was significantly greater (p <0.05). During the acute period, infarct size
showed a significant positive correlation with platelet aggregation (r=0.59, p<0.01)
and adenosine triphosphate release rate (r=0.70, /p <0.001) but a negative
correlation with platelet count (r= — 0.44, p< 0.05). The results suggest that
platelet aggregation is reduced during the acute period due to the consumption of
platelets during thrombogenesis but that the remaining individual platelets are
hyperactive.6 Platelet consumption during the acute period increases with infarct
size. During the chronic period, platelet crit and mean platelet volume were
significantly less in the patients than in the controls (p<0.01) while the adenosine
triphosphate release rate was significantly greater (p<0.01), suggesting sustained
platelet consumption and chronically enhanced secretion of individual platelets6.
D‘Erasmo et al5 found a significantly lower platelet count in patients with ischaemic
stroke.
3.3.6 MPV AND ANTIPLATELET DRUGS
Platelet aggregation is an essential step in physiological hemostasis and is involved
in vascular pathology such as atherosclerosis, arterial thromboembolism, unstable
angina pectoris, myocardial infarction, transitory ischemic attacks of the brain and
stroke.48 The inhibition of platelet aggregation, e.g. by aspirin, has become an
important treatment for unstable angina pectoris and transitory ischemic attacks and
the secondary prevention of myocardial infarction and stroke . Aspirin inhibits
platelet aggregation through an irreversible inhibition of the cyclooxygenase. It is
not known whether this impairment of platelet function has an influence on the
feedback control system of platelet production and hence on platelet count and
platelet volume. Stephan Erhart et al48 studied the influence of aspirin on platelet
count, volume and total platelet mass in vitro and in a randomized double-blind,
placebo-controlled study in 20 healthy young male volunteers in vivo. The PC was
unaffected by increasing concentrations of aspirin in vitro over 4 h, indicating that
there was no platelet destruction by aspirin even with the high concentration of 250
µg/ml, which is well above concentrations reached in vivo usually. The platelet
volume was unaffected by aspirin and remained constant over time. In vivo studies
showed that repeated blood sampling during a 7-day treatment with 250 mg aspirin
daily showed an increased platelet count (7.3% on day 1, 3.0% on day 2, 6.8% on
day 4 and 9.3% on day 7; p < 0.01) and total platelet mass (7.2, 5.0, 8.6 and 11.5%
on days 1, 2, 4 and 7,respectively, p < 0.01). An increased PC and mass were also
observed in the placebo group on day 4. Because of this observation the study was
repeated with a minimal volume taken only on day 4. Surprisingly both aspirin and
placebo had not effect under these conditions. Therefore, they stated that aspirin
treatment together with repeated small bleeding increased PC and mass, but not
aspirin treatment by itself. Aspirin treatment without repeated blood withdrawal had
no effect. These data indicate that aspirin may affect the circulating platelet mass
under certain conditions48.
3.3.7 MPV AND AGE
It used to be thought that the platelet size decreased with age, but more recent
evidence suggests that MPV and other platelet parameters and therefore platelet
protein content and reactivity, are determined primarily at or before thrombopoesis
by the platelet precursor cell, the MK. 9
3.3.8 MPV AND GENDER
Gender-dependent differences in platelet count have been demonstrated in few
studies. In women platelet count is higher than in men, which seems to reflect
different hormonal profiles or a compensatory mechanism associated with
menstrual blood loss. Anna M. Butkiewicz et al
49
conducted a study on healthy
blood donors divided into groups: F — 60 women and M — 65 men. Platelet count
and mean platelet volume were determined on a haematological analyser Advia
120, Bayer. Higher platelet count was noted in the group of women
252.35 ± 41.25 × 109/l as compared to men 221.87 ± 37.63 × 109/l (p = 0.0002). At
the same time women had lower thrombopoietin concentration 156.50 ± 57.18
pg/ml compared to men 180.46 ± 60.98 pg/ml, (p = 0.03). No statistically
significant differences were found in the mean platelet volume, though there was a
slight increase in females49.
3.3.9 MPV AND HYPERTENSION
Mean platelet volume (MPV), a determinant of platelet function, is a newly
emerging risk factor for atherothrombosis. Coban E et al50 selected 36 essential
hypertensive patients, 36 white coat hypertensive subjects and 36 normotensive
control subjects matched for age, gender, and body mass index. MPV was very
significantly higher in essential hypertensives and white coat hypertensives than in
normotensives (P < 0.00); it was also higher in essential hypertensives than in white
coat hypertensives (P < 0.05). Platelet counts were not different among the study
groups (P > 0.05). MPV was positively correlated with ambulatory diastolic blood
pressure in essential hypertension and white coat hypertension groups (P < 0.05)50.
Platelet size is also found to be elevated in individuals with hypertension and
diabetes mellitus2, both conditions that predispose to the development of vascular
disease3
3.3.10 MPV AND DIABETES MELLITUS
Zuberi B F et al51 conducted this cross-sectional study at Dow University of Health
Sciences, Karachi, Pakistan between the period of September 2006 and May 2007.
Sample size of 204 in each group was calculated using power (1-beta) of 90 percent
and level of significance (alpha) at five percent. Confirmed patients with DM, IFG
and non-diabetic controls were selected and allocated to respective groups. A total
of 612 patients were selected and allocated to three groups of 204 patients each,
referred to as DM group, IFG group and non-DM group. Fasting blood glucose,
platelet counts and MPV were done. Mean MPV in the DM group was 9.34 fl, in
the IFG Group was 8.98 fl, and in the non-DM group was 8.63 fl. Comparison of
MPV values for the three groups showed statistically significant intergroup and
intragroup differences, with a pvalue of 0.00.MPV was significantly increased in
the IFG group, as compared to the non-DM group, and it increased further when
compared to the DM and IFG groups51.
3.3.11 MPV AND METABOLIC SYNDROME
Giuseppe Lippi et al52 performed a retrospective analysis on the database of the
Laboratory Information System of the Clinical Chemistry Laboratory at the
University Hospital of Verona, Verona, Italy. Data for MPV, fasting glucose (FPG),
high-density lipoprotein cholesterol (HDL-C) and triglycerides (The last three
parameters being key biochemical markers of metabolic syndrome according to
Adult Treatment Panel [ATP] III criteria), were retrieved from all outpatients
consecutively referred by a general practitioner for routine blood testing.
Cumulative results for MPV, FPG, HDL and triglycerides were retrieved for 3337
outpatients >35 years of age over the 2 year period. The mean MPV of subjects
with all biochemical markers suggestive of the metabolic syndrome was slightly
higher but not significantly different from that of control subjects ie. 8.7fl (95% CI
7.7, 9.6) versus 8.6fl (95% CI 7.5, 9.6), respectively (p = 0.119)52.
3.3.12 MPV AND SMOKING
Tobacco smoking is one of the major factors accelerating atherosclerosis.
Deleterious effects of smoking are associated with generation of free radicals that
break down NO, which on the one hand enhances thromboxane synthesis (the
prothrombic action), but on the other reduces production of prostacyclin (the
antithrombic action), thus leading to clotting disorders, additionally enhanced by
increased production of fibrinogen and factor VII. Butkiewicz AM et al53 designed
a study to assess platelet parameters in smoking healthy subjects with reference to
sex. In the group of women, 27% were smokers, in the group of men – 49%. All the
subjects were tested for platelet count (PLT), mean platelet volume (MPV),
percentage of large platelets (LPLT), concentrations of -thromboglobulin, sP-selectin (soluble) and thrombopoietin, percentage of reticulated platelets (RP) and
absolute count of reticulated platelet. In neither of the sexes smoking had an effect
on the following parameters: mean platelet volume, percentage of large platelets,
concentration of thrombopoietin, absolute count of reticulated platelet and
concentration of –thromboglobulin53.
3.3.13 MPV AND ISHCEMIC HEART DISEASE
M M Khandekar, A S Khurana et al54 studied a total of 210 cases, 94 patients had
unstable angina (UA) or acute myocardial infarction (AMI) diagnosed on the basis
of history, characteristic electrocardiographic changes, and increased cardiac
enzyme activities. Seventy patients had stable coronary artery disease (stable CAD)
or were admitted for a coronary angiography or coronary artery bypass graft
procedure. The third group comprised 30 age and sex matched healthy controls with
no history of heart disease and a normal electrocardiogram. All PVI—mean platelet
volume (MPV), platelet distribution width (PDW), and platelet large cell ratio (PLCR)—were significantly raised in patients with AMI and UA (mean MPV, 10.43
(SD, 1.03) fL; mean PDW, 13.19 (SD, 2.34) fL; mean P-LCR, 29.4% (SD, 7.38%))
compared with those with stable CAD (mean MPV, 9.37 (SD, 0.99) fL; mean
PDW, 11.35 (SD, 1.95) fL; mean P-LCR, 22.55% (SD, 6.65%)) and the control
group (mean MPV, 9.2 (SD, 0.91) fL; mean PDW, 10.75 (SD, l.42) fL; mean PLCR, 20.65% (SD, 6.14%)).Larger platelets are haemostatically more active and
are a risk factor for developing coronary thrombosis, leading to myocardial
infarction. Patients with larger platelets can easily be identified during routine
haematological analysis and could possibly benefit from preventive treatment54.
4. MATERIALS AND
METHODS
4. MATERIALS AND METHODS
4.1 SETTING OF THE STUDY
The study was a prospective study and data was collected from Nov 1st 2008 to
July 31st 2009 at St. John‘s Medical College Hospital, Bangalore. St. John‘s Medical
College Hospital is a tertiary care referral centre. The study was carried out among
fifty patients diagnosed with an acute ischemic stroke and presenting to the hospital
within forty eight hours of onset of symptoms.Fifty age and sex matched controls
were also recruited. The study protocol was approved by the institutional review
board.
4.2 STUDY DESIGN
A case control study
Cases:
Definition of stroke: Focal neurological deficit lasting more than 24hrs with no
evidence of a non – vascular cause.
Inclusion criteria:
1. Gender:
Males/Females
2. Age Range:
18 years and above
3. Socioeconomic group: All socioeconomic groups were eligible
4. CT Scan to exclude hemorrhagic stroke.
Exclusion criteria:
1. Thrombocytopenia .
2.
Known cases of Hereditary disorders of large platelets.
3. Medications that can reduce the platelet count: hydroxyurea, antineoplastic
agents, and inhibitors of the platelet integrin αIIbβ3.
4. Haemorrhagic stroke.
5. Patients unable to communicate because of severe stroke, aphasia or dementia
without a valid surrogate respondent.
(A valid surrogate respondent is considered a spouse or first degree relative that is
living in the same home or is self- identified as aware of the participant‘s previous
medical history and current therapies)
6.
Patients presenting 48hrs after the onset of neurological symptoms.
7. Peripheral smear showing platelet aggregates.
Controls:
Controls were primarily hospital based. Each control was matched for sex and age
(+/- 5 years). There was at least one control for each case recruited.
Inclusion criteria
1. Relative of a patient from ward.
2. Unrelated Visitor of any patient.
3. Patients attending the hospital or outpatient clinic for other illness.
Exclusion criteria
1. Individuals with a previous history of stroke.
2. Thrombocytopenia
3. Peripheral smear showing platelet aggregates.
4.3 METHODS OF COLLECTION OF DATA
All stroke patients admitted to the hospital were screened during the time period
described above. Each of them was entered into a stroke log. Patients fulfilling the
criteria were enrolled into the study after obtaining an informed consent. Data was
collected by the principal investigator and recorded, as per the proforma . Each patient
was given a serial number and was formally included into the study as a case. Each
patient was assessed and a modified Rankin‘s Scale assigned to them. A Blood
sample was collected from the antecubital vein using a 5cc syringe and transferred to
an EDTA and citrate vacutainers. The samples were then taken to the laboratory
between 2hrs and 4hrs of collection and analyzed using the ABX pentra automated
analyzer using electrical impedance to measure the mean platelet volume. After the
analysis the same sample was taken to the central laboratory and a peripheral smear
was done to look for platelet aggregates. If platelet aggregates were found then such
cases were excluded from the study. The same procedure was adopted in controls for
taking the samples, and then transferred it to the vacutainers (EDTA and Citrate) and
analyzed using the automated analyzer (ABX pentra). Peripheral smears were done to
look for aggregates and if present were excluded.
4.4 SOP FOR CASES
Screen cases
1) Medical ward
2) Neurology
ward
+
Eligibility
Assessment
Inclusion /Exclusion
criteria
_
Informed consent
Assign serial no
Enter Pt in stroke
log
Enter Pt in the
stroke log.
Detailed history and
physical examination.
Mention
the reason
for
exclusion
Apply modified
Rankin‘s score
Diagnostic
Investigations
as per protocol
Take the same
sample for a
peripheral
smear study to
hospital
laboratory
Fill the case
report form
Take one EDTA
sample +one
CITRATE sample
Run the test for
MPV using
Abx Pentra
within 4 hrs in
2nd floor
college lab
Discard sample
and keep
peripheral
smear report
for further
reference.
4.5 PRINCIPLE BEHIND ESTIMATION OF MPV WITH ABX PENTRA
ANALYZER
The MPV (Mean platelet volume) is directly derived from the analysis of
the platelet distribution curve. The volume of each platelet is plotted in a
histogram and the mean of it is taken as shown in the figure.
4.6 MODIFIED RANKIN’S SCALE USED TO ASSESS CLINICAL SEVERITY
OF STROKE55, 56
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 affair 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): _______
4.7 INVESTIGATIONS USED FOR CASES AND CONTROLS
INVESTIGATIONS
1) Hemoglobin
2) Total Leukocyte
count /Differential
count
3) Mean Platelet
Volume
4) Platelet Count
5) Peripheral smear
6) Random blood
sugar
7) Lipid Profile
8) CT/MRI Brain
CASES
yes
yes
CONTROLS
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
yes
no
no
4.8 STATISTICAL METHODS
Sample size:
50 cases admitted in St. John‘s Medical College Hospital who gave informed consent
and who met the inclusion criteria were recruited. 50 age and sex matched controls
were also recruited from the hospital.
Data analysis:
The Statistical software namely SPSS 15.0, Stata 8.0, MedCalc 9.0.1 and Systat 11.0
were used for the analysis of the data and Microsoft word and Excel have been used
to generate graphs, tables etc.
Statistical Methods:
Descriptive statistical analysis has been carried out in the present study. Results on
continuous measurements are presented on Mean  SD (Min-Max) and results on
categorical measurements are presented in Number (%). Significance is assessed at 5
% level of significance. Analysis of variance (ANOVA) has been used to find the
significance of study parameters between three or more groups of patients, Student t
test (two tailed, independent)
has been used to find the significance of study
parameters on continuous scale between two groups . A Multivariate logistic
regression analysis has been carried out to find the risk factors associated with
stroke60, 61, 62, and 63.
1. Analysis of Variance: F test for K Population means61, 62
Objective: To test the hypothesis that K samples from K Populations with the same
mean.
Limitations: It is assumed that populations are normally distributed and have equal
variance. It is also assumed that samples are independent of each other.
Method. Let the jth sample contain nj elements (j=1, 2…K). Then the total number of
elements is
x. j  
N   nj
xij
nj
n1
S1 
2
  ( x1  x. j )
n1
2
i 1
S2 
2
NK
F=S22/S12
 nj ( x. j  x..)
i 1
K 1
Which follows F distribution (K-1, N-K)
2. Student t test (Two tailed, independent)63
t
Where s 2 
( x 1  x 2 )  ( 1   2 )
s 2 (1 / n1  1 / n2)
n1
n2
i 1
i 1
(n1  1) ( x1  x1) 2  (n2  1) ( x 2  x 2) 2
n1  n2  2
3. Significant figures
+ Suggestive significance (P value: 0.05<P<0.10)
* Moderately significant (P value:0.01<P  0.05)
** Strongly significant (P value: P0.01)
2
5. RESULTS
FIGURE 1: PRE ANALYTICAL TEST
Tests were conducted in normal volunteers prior to the actual study. The anti
coagulants EDTA and citrate, the time factor etc were compared for finding out their
independent influence on MPV.
9
CITRATE-MPV
8.5
8
7.5
7
Sample 1
Sample 2
Sample 3
Sample 4
Sample 5
6.5
1 hour
2 hours
3 hours
4 hours
8 hours
24 hours
48 hours
PRE-ANALYTICAL TEST
10
9.5
EDTA-MPV
9
8.5
8
7.5
Sample 1
Sample 2
Sample 3
Sample 4
Sample 5
7
1 hour
2 hours
3 hours
4 hours
8 hours
24 hours
48 hours
PRE-ANALYTICAL TEST
The MPV‘s have been plotted in the y axis and the time has been plotted on the x
axis.
DEMOGRAPHIC DATA
236 patients of strokes admitted to the medical and neurology wards were screened to
get 50 cases.
TABLE 1: STROKE LOG AND REASONS FOR EXCLUSION
No of cases screened
236
No of cases included
50
No of cases excluded
186
The reasons for exclusion are tabulated
Reason for exclusion
Late Presentation to Hospital(>48hrs)
Haemorrhagic stroke
Delay in recruiting
Platelet aggregates in peripheral smear
No informed consent
No
%
86
30
31
11
28
46.2
16.1
16.7
5.9
15.1
FIGURE 2: STROKE LOG AND REASONS FOR EXCLUSION
5.9%
Late Presentation to
Hospital(>48hrs)
15.1%
46.2%
16.7%
Haemorrhagic stroke
Delay in recruiting
16.1%
Platelet aggregates in
peripheral smear
No informed consent
TABLE 2: AGE DISTRIBUTION
The mean age for the cases was 58.10±13.67 when compared to 57.50±13.82 for the
controls. The maximum No of cases in this study were in the age group between 5160 which was followed by age group of 61-70.
Cases
Age in
years
21-30
31-40
41-50
51-60
61-70
71-80
>80
Total
Mean ± SD
Controls
No
%
No
%
2
4.0
2
4.0
4
8.0
4
8.0
6
12.0
6
12.0
18
36.0
18
36.0
13
26.0
13
26.0
6
12.0
6
12.0
1
2.0
1
2.0
50
100.0
50
100.0
58.10±13.67
57.50±13.82
Male
55.86±14.38
55.24±14.27
Female
64.46±9.12
63.92±9.78
P value
0.050*
Samples are age matched with P=0.828
0.049*
FIGURE 3: AGE DISTRIBUTION
50
45
Percentages
40
35
30
25
20
15
10
Cases
5
Controls
0
21-30
31-40
41-50
51-60
61-70
Age in years
71-80
>80
TABLE 3: GENDER DISTRIBUTION
74% of the cases and controls were males and 26% were females. Females
(64.46±9.12) with stroke were significantly older than males (55.86±14.38) with a p
value of 0.050*.
Cases
Controls
Gender
No
%
No
%
Male
37
74.0
37
74.0
Female
13
26.0
13
26.0
Total
50
100.0
50
100.0
Samples are gender matched with P=1.000
FIGURE 4: GENDER DISTRIBUTION
Female
26%
Female
26.0%
Male
74.0%
Cases
Male
74%
Controls
TABLE 4: RISK FACTOR PROFILE
Out of the many risk factors for stroke metabolic syndrome was the most prevalent in
this study group with a percentage of 74 among cases and 48 among controls with a
significant p value of .008. Hypertension came second with percentage of 52 among
cases and 34 among controls with a trend towards significance with a p value of .069.
DM and Angina /MI were placed third and fourth respectively and of which only
angina /MI had a significant correlation of .026.
Cases
(n=50)
Past History
Controls
(n=50)
P value
No
%
No
%
Previous Stroke
4
8.0
0
0.0
0.411
Hypertension
26
52.0
17
34.0
0.069+
DM
14
28.0
12
24.0
0.648
Smoking
7
14.0
4
8.0
0.338
Alcohol
4
8.0
4
8.0
1.000
Angina/MI
9
18.0
2
4.0
0.026*
AF
Metabolic
syndrome
1
2.0
0
0.0
1.000
37
74.0
24
48.0
0.008**
FIGURE 5: RISK FACTOR PROFILE
80
70
60
50
40
30
20
10
0
Cases
Controls
TABLE 5: CLINICAL PROFILE
Clinical Manifestations
No
%
Hemiplegia (motor), facial palsy
18
36
Hemiplegia (sensory+motor)
17
34
Hemiplegia,facial palsy,aphasia,homonymous
hemianopia
3
6
Monoplegia
4
8
Cerebellar signs
6
12
Acute Memory Loss
1
2
UMN Facial palsy
1
2
FIGURE 6: CLINICAL PROFILE
UMN Facial palsy
2%
Acute Memory Loss
2%
Cerebellar signs
12%
Monoplegia
8%
Hemiplegia,facial
palsy,Aphasia,Homonymous…
Hemiplegia(sensory+motor)
Hemiplegia(motor) , facial palsy
6%
34%
36%
0% 5% 10% 15% 20% 25% 30% 35% 40%
TABLE 6: THE OXFORDSHIRE COMMUNITY STROKE PROJECT
CLASSIFICATION OF STROKE SYNDROMES
This classification sub typed strokes on basis of clinical criteria. Predominant subtype
was Lacunar syndrome which summed up to 70% of the total cases. This was
followed by POCS and PACS with 12% each and then TACS which summed up to
6% of the cases.
Number
(n=50)
Stroke sub type
LACS (Lacunar syndromes)
35
POCS (Posterior circulation syndromes)
6
PACS (Partial anterior circulation syndromes)
6
TACS (Total anterior circulation syndromes)
3
FIGURE 7: THE OXFORDSHIRE COMMUNITY STROKE PROJECT
CLASSIFICATION OF STROKE SYNDROMES
POCS
12%
PACS
12%
TACS
6%
LACS
70%
Stroke sub type
TABLE 7: COMPARISON OF BLOOD PARAMETERS IN CASES AND
CONTROLS
There was a trend for lower platelet count in cases, but this was not significant ( p
value = .380) Thus the platelet counts in the cases averaged 2.56±0.58 (1.43-4.40)
when compared to the controls in whom the average was 2.69±0.83 (1.60-5.40).
Blood parameters
Cases
Controls
Significance
Hemoglobin (g/dl)
13.37±2.21
(7.10-18.60)
12.49±1.71
(8.30-16.00)
t=2.256;P=0.026*
9728.00±2966.96
(4300-15900.0)
9638.00±3168.39
(4200-18000)
t=0.145;P=0.884
Platelet count (%)
2.56±0.58
(1.43-4.40)
2.69±0.83
(1.60-5.40)
t=0.881;P=0.380
Neutrophil (%)
71.14±12.02
(39-89)
75.86±9.79
(48-96)
t=2.152;P=0.034*
Lymphocyte (%)
23.98±9.98
(7-44)
20.74±11.11
(3-70)
t=1.535;P=0.128
Eosinophil (%)
3.20±2.72
(1-16)
2.51±1.79
(1-10)
t=1.422;P=0.159
Monocyte (%)
2.70±1.19
(1-6)
2.56±1.23
(1-5)
t=0.496;P=0.621
Total count (%)
Results are presented as Mean ± SD (Min-Max)
FIGURE 8: COMPARISON OF BLOOD PARAMETERS IN CASES AND
CONTROLS
18
14000
16
12000
Total count
Hemoglobin
14
12
10
8
10000
8000
6000
6
4000
4
2000
2
0
0
Controls
Cases
4
90
3.5
80
3
70
Neutrophil
Platelet count
Cases
2.5
2
1.5
Controls
60
50
40
30
1
20
0.5
10
0
0
Cases
Cases
Controls
Controls
40
35
7
4
6
3.5
20
15
5
3
Eosinophil
25
Monocyte
Lymphocyte
30
4.5
2.5
2
1.5
10
5
0
4
3
1
2
0.5
1
0
Cases
Controls
Cases
Controls
0
Cases
Controls
TABLE 8: TYPE OF INFARCT (MRI FINDINGS)
The common patterns seen were parietal and temporo- parietal infarcts which
comprised of 12% each of the cases. This was followed by Corona radiata infarcts
which comprised of 10% of the cases.
Number
(n=50)
6
12.0
Temporo parietal Infarct
6
12.0
Corona Radiata Infarct
5
10.0
Fronto parietal Infarct
4
8.0
Ganglio Capsular Infarct
4
8.0
Parasagittal Infarct
3
6.0
Basal ganglia Infarct
2
4.0
Cerebellar Infarct
2
4.0
Internal capsule Infarct
2
4.0
Pontine Infarct
2
4.0
Temporo parietal & Corona Radiata
2
4.0
B/L Cerebellar Infarct
1
2.0
Basal ganglia & Corona radiata
1
2.0
Cortical Infarct
1
2.0
Fronto Temporal Infarct
1
2.0
Medial Frontal Infarct
1
2.0
Medullary Infarct
1
2.0
Parietal & Thalamic Infarct
1
2.0
Perisylvian Infarct
1
2.0
Posterior Limb of internal capsule
1
2.0
Temporal Infarct
1
2.0
Temporo parietal & Occipital
1
2.0
Thalamic Infarct
1
2.0
Type of Infarct
Parietal Infarct
%
TABLE 9: INFARCT TERRITORY
MCA territory was involved in 72% of the patients. This was followed by
involvement of the vertebra basilar artery (posterior circulation) with 14 % of the
cases. Involvement of ACA and MCA together comprised of 10% of the cases. Pure
ACA territory involvement was seen with 4% of cases.
ACA
Number
(n=50)
2
4.0
MCA
36
72.0
ACA+MCA
5
10.0
VBA
7
14.0
Territory
%
FIGURE 9: INFARCT TERRITORY
100
90
72
80
Percentages
70
60
50
40
30
10
20
14
4
10
0
ACA
MCA
ACA+MCA
Territory
VBA
TABLE 10: STROKE- CLINICAL SEVERITY SCORE
The clinical severity of stroke at presentation was determined by the Modified
Rankin‘s scale and severe disability was seen with 20% of the cases. 28% of the cases
had no significant disability.
Number
(n=50)
14
28.0
Score 2: Slight disability
9
18.0
Score 3: Moderate disability
6
12.0
Score 4: Moderately severe disability
11
22.0
Score 5: Severe disability
10
20.0
Modified Rankin’s Score
Score 1: No significant disability
%
FIGURE 10: STROKE- CLINICAL SEVERITY SCORE
50
45
Percentages
40
Score 1: No significant
disability
Score 2: Slight
disability
Score 3: Moderate
disability
Score 4: Moderately
severe disability
Score 5: Severe
disability
35
30
25
20
15
10
5
0
Score 1
Score 2
Score 3
Score 4
Modified Rankins Score
Score 5
TABLE 11: COMPARISON OF MPV IN CASES AND CONTROLS
MPV( citrate) has got a statistically significant correlation with Ischemic stroke with
a P value of 0.005 with an average MPV in cases being 7.35±0.81 compared to
controls who average 6.94±0.59.Though MPV(EDTA) also shows a strong trend in
cases and controls 7.86±0.82 and 7.86±0.82, the difference is not statistically
significant.
MPV (fL)
Cases
Controls
Significance
MPV(EDTA)
7.86±0.82
(6.50-10.00)
7.58±0.70
(5.90-9.00)
t=1.834;P=0.074+
MPV(CITRATE)
7.35±0.81
(6.10-9.60)
6.94±0.59
(5.80-8.20)
t=2.894;P=0.005**
Results are presented as Mean ± SD (Min-Max)
FIGURE 11: COMPARISON OF MPV IN CASES AND CONTROLS
10
9
9
8
MPV(CITRATE)
MPV(EDTA)
8
7
6
5
4
3
7
6
5
4
3
2
2
1
1
0
0
Cases
Controls
Cases
Controls
TABLE 12: COMPARISON OF PLATELET MASS IN CASES AND
CONTROLS
The platelet mass being a product of platelet count and mean platelet volume is almost
a constant. This is evident from the values in cases and controls in both EDTA
(20.09±4.60, 20.19±5.79) and citrate (18.85±4.67, 18.52±5.31) samples. However
there is no statistical correlation of platelet mass to Ischemic stroke.
Platelet Mass
Cases
Controls
Significance
PLATELET MASS (EDTA)
20.09±4.60
(10.87-31.68)
20.19±5.79
(11.52-42.12)
t=0.316;P=0.919
PLATELET MASS
(CITRATE)
18.85±4.67
(10.30-31.68)
18.52±5.31
(9.76-36.72)
t=0.330;P=0.742
Results are presented as Mean ± SD (Min-Max)
PLATELET MASS (CITRATE)
FIGURE 12: COMPARISON OF PLATELET MASS IN CASES AND
CONTROLS
PLATELET MASS (EDTA)
30
25
20
15
10
5
30
25
20
15
10
5
0
0
Cases
Controls
Cases
Controls
TABLE 13: COMPARISON OF MPV (EDTA) IN CASES AND CONTROLS
ACCORDING TO RISK FACTORS
The risk factors for stroke was compared with MPV(EDTA) to look for any positive
correlation however no statistically significant correlation was found, possibly
because of the small numbers.
Risk factors
Hypertension
DM
Smoking
Alcohol
Levels
Absent
Present
P value
Absent
Present
P value
Absent
Present
P value
Absent
Present
P value
Cases
8.11±0.93
7.77±0.78
0.230
7.73±0.83
8.08±0.79
0.138
7.81±0.82
8.14±0.78
0.328
7.83±0.80
7.32±0.99
0.357
Controls
7.53±0.72
7.67±0.67
0.508
7.57±0.73
7.61±0.64
0.665
7.58±0.69
7.55±0.88
0.935
7.55±0.72
7.90±0.33
0.343
P value
0.144
0.623
0.394
0.086+
0.156
0.278
0.087+
0.560
-
FIGURE 13: COMPARISON OF MPV (EDTA) IN CASES AND CONTROLS
ACCORDING TO RISK FACTORS
10
Cases
Controls
9
8
MPV (EDTA)
7
6
5
4
3
2
1
0
Absent
Present
Hypertension
Absent
DM
Present
Absent
Present
Smoking
Absent
Present
Alcohol
TABLE 14: COMPARION OF MPV (CITRATE) IN CASES AND CONTROLS
ACCORDING TO RISK FACTORS
Similarly the risk factors for stroke was compared with MPV(citrate) to look for any
positive correlation however no statistically significant correlation was found though
presence of diabetes had a slight correlation with high values of MPV.
Risk factors
Hypertension
DM
Smoking
Alcohol
Levels
Absent
Present
P value
Absent
Present
P value
Absent
Present
P value
Absent
Present
P value
Cases
7.64±0.82
7.26±0.79
0.161
7.26±0.82
7.51±0.78
0.309
7.30±0.79
7.69±0.89
0.248
7.32±0.78
7.75±1.08
0.314
Controls
6.91±0.57
7.02±0.62
0.584
6.96±0.61
6.90±0.54
0.769
6.95±0.61
6.85±0.37
0.742
6.95±0.61
6.95±0.23
0.983
P value
0.053*
0.256
0.078+
0.025*
0.022*
0.116
0.012*
0.200
-
FIGURE 14: COMPARION OF MPV (CITRATE) IN CASES AND
CONTROLS ACCORDING TO RISK FACTORS
Cases
Controls
10
9
MPV (CITRATE)
8
7
6
5
4
3
2
1
0
Absent
Present
Hypertension
Absent
DM
Present
Absent
Present
Smoking
Absent
Present
Alcohol
TABLE 15: COMPARISON OF MPV (EDTA/CITRATE) IN CASES AND
CONTROLS ACCORDING TO OTHER RISK FACTORS
MPV was compared to the other risk factors like age, gender, WHR, lipid profiles and
metabolic syndrome. A positive correlation was seen with female gender having
higher MPV than males. However a statistically significant correlation with a p value
of .004 was seen only in high triglyceride group.
Risk factors
Levels
MPV(EDTA)
<60
7.84±0.80
60 and
Age in years
7.88±0.85
above
P value
0.932
Male
7.72±0.74
Gender
Female
8.25±0.95
P value
0.047*
Normal
7.43±1.08
57, 58, 59.
WHR
Abnormal
7.88±0.81
P value
0.361
Normal
7.99±0.97
HDL(mg/dl) Abnormal
7.83±0.79
P value
0.575
Normal
7.77±0.77
LDL (mg/dl) Abnormal
8.18±0.96
P value
0.141
Normal
8.10±0.83
Triglycerides
Abnormal
7.51±0.67
(mg/dl)
P value
0.012*
Normal
7.79±0.79
Total
cholesterol
Abnormal
8.06±0.89
(mg/dl)
P value
0.304
Absent
7.90±0.96
Metabolic
Present
7.84±0.78
syndrome
P value
0.803
Median age of cases studied is 59 years
MPV(CITRATE)
7.34±0.73
7.36±0.89
0.932
7.21±0.77
7.76±0.82
0.034*
7.00±0.82
7.38±0.88
0.441
7.41±0.96
7.34±0.78
0.810
7.32±0.79
7.48±0.90
0.560
7.63±0.83
6.99±0.62
0.004**
7.34±0.82
7.41±0.82
0.785
7.48±0.93
7.31±0.78
0.531
FIGURE 15: COMPARISON OF MPV (EDTA/CITRATE) IN CASES AND
CONTROLS ACCORDING TO OTHER RISK FACTORS
10
9
10
8
9
7
8
6
7
6
5
5
4
4
3
3
2
1
MPV(EDTA)
2
MPV(CITRATE)
1
MPV(EDTA)
0
MPV(CITRATE)
0
<60
60 and above
Male
Age in years
Female
Gender
10
10
9
9
8
8
7
7
6
6
5
5
4
4
3
3
2
2
MPV(EDTA)
1
MPV(EDTA)
1
MPV(CITRATE)
MPV(CITRATE)
0
0
Normal
Normal
Abnormal
Abnormal
HDL(mg/dl)
WHR
10
9
10
8
9
8
7
7
6
6
5
5
4
4
3
3
2
1
MPV(EDTA)
2
MPV(CITRATE)
1
0
MPV(EDTA)
MPV(CITRATE)
0
Normal
Abnormal
Normal
LDL (mg/dl)
Abnormal
Triglycerides (mg/dl)
10
10
9
9
8
8
7
7
6
6
5
5
4
4
3
3
2
2
MPV(EDTA)
1
MPV(EDTA)
1
MPV(CITRATE)
MPV(CITRATE)
0
0
Normal
Abnormal
Total cholesterol(mg/dl)
Normal
Abnormal
Metabolic syndrome
TABLE 16: INFARCT TERITORY AND MPV
The infarct territory and MPV (EDTA and Citrate) were compared to look for any
correlation, but no statistical significance was obtained.
Number
(n=50)
MPV
(EDTA)
MPV
(Citrate)
ACA
2
7.30±0.57
6.85±0.64
MCA
36
7.88±0.81
7.39±0.70
ACA+MCA
5
8.20±1.14
7.50±1.33
VBA
7
7.64±0.73
7.17±1.02
0.525
0.720
Territory
P value
FIGURE 16: INFARCT TERITORY AND MPV
MPV(EDTA)
10
MPV(CITRATE)
9
8
7
6
5
4
3
2
1
0
ACA
MCA
ACA+MCA
Territory
VBA
TABLE 17: THE OXFORDSHIRE COMMUNITY STROKE PROJECT
CLASSIFICATION OF STROKE SYNDROMES AND CORRELATION WITH
MPV.
There was no statistically significant difference in MPV in each of these clinical
subtypes of strokes.
Number
(n=50)
MPV(EDTA)
MPV(CITRATE)
LACS
35
7.83±0.90
7.34±0.84
POCS
6
7.78±0.66
7.40±0.98
PACS
6
7.78±0.59
7.12±0.59
TACS
3
8.47±0.21
7.87±0.31
F=0.579; P=0.632
F=0.563; P=0.642
Stroke sub type
Significance
FIGURE 17: THE OXFORDSHIRE COMMUNITY STROKE PROJECT
CLASSIFICATION OF STROKE SYNDROMES AND CORRELATION WITH
MPV.
10
9
9
8
MPV (EDTA)
MPV (CITRATE)
8
7
6
5
7
6
5
4
4
3
3
2
2
1
1
0
0
LACS
POCS
PACS
TACS
LACS
POCS
PACS
TACS
TABLE 18: STROKE- CLINICAL SEVERITY SCORE AND MPV
The association of MPV with severity of stroke was determined by comparing the
Modified Rankin‘s score with corresponding mean values of MPV in each group.
However no statistically significant correlation was obtained.
Modified Rankin’s
Score
Score 1: No significant
disability
Score 2: Slight
disability
Score 3: Moderate
disability
Score 4: Moderately
severe disability
Score 5: Severe
disability
Significance
Number
(n=50)
MPV(EDTA)
MPV(CITRATE)
14
8.00±0.69
7.44±0.58
9
8.00±1.06
7.81±0.97
6
7.18±0.67
6.70±0.66
11
7.80±0.89
7.51±1.02
10
8.00±0.68
7.49±0.69
P value
0.283
0.318
12
12
10
10
8
8
MPV (CITRATE)
MPV (EDTA)
FIGURE 18: STROKE- CLINICAL SEVERITY SCORE AND MPV
6
4
6
4
2
2
0
0
0
1
2
3
4
Modified Rankins Score
5
6
0
1
2
3
4
Modified Rankins Score
5
6
TABLE 19: COMPARISON OF PLATELET MASS IN CASES ACCORDING
TO SEVERITY SCORE
The association of Platelet mass with severity of stroke was determined by comparing
the Modified Rankin‘s score with corresponding mean values of platelet mass in each
group. However no statistically significant correlation was obtained.
Platelet
mass
PLATELET
MASS
(EDTA)
PLATELET
MASS
(CITRATE)
Severity of disease based on Modified Rankin’s Score
No
Moderately
Slight
Moderate
Severe
significant
severe
disability disability
disability
disability
disability
P
value
20.22±4.6
17.43±3.3
20.77±6.4
21.11±4.55
20.75±4.5
0.434
18.83±4.4
15.88±2.7 19.54±6.77
20.37±4.87
19.47±4.53 0.281
FIGURE 19: COMPARISON OF PLATELET MASS IN CASES ACCORDING
TO SEVERITY SCORE
30
PLATELET MASS (EDTA)
25
20
15
10
5
0
No significant
disability
Slight disability
Moderate
disability
Moderately
Severe disability
severe disability
Severity of disease based on Modified Rankins Score
PLATELET MASS (CITRATE)
30
25
20
15
10
5
0
No significant
disability
Slight disability
Moderate
disability
Moderately
Severe disability
severe disability
Severity of disease based on Modified Rankins Score
TABLE 20: ASSOCIATION OF MPV QUINTILES (EDTA) AND STROKE
SEVERITY
MPV was arranged into quintiles and compared with the stroke severity score which
was further subdivided into two groups. Group 1 with a score of 0-2 being less severe
and group 2 with a score of 3-6 being more severe. The p value obtained is .654 in
EDTA anticoagulated samples and has no statistical significance.
MPV (EDTA)
Quintiles
Stroke severity score
P value
Score: 0-2
Score: 3-6
6.50-7.20
5 (21.7%)
10 (37.1%)
7.21-7.60
3 (13.1%)
4 (14.8%)
7.61-7.86
5 (21.7%)
3 (11.1%)
7.87-8.60
8 (34.8%)
6 (22.2%)
8.61-10.00
4 (17.4%)
4 (14.8%)
23 (100.0%)
27 (100.0%)
Total
0.654
-
FIGURE 20: ASSOCIATION OF MPV QUINTILES (EDTA) AND STROKE
SEVERITY
50
45
40
Percentages
35
30
25
20
Stroke severity
score
15
10
Score: 0-2
5
Score: 3-6
0
6.50-7.20
7.21-7.60
7.61-7.86
7.87-8.60 8.61-10.00
MPV (EDTA) Quintiles
TABLE 21: ASSOCIATION OF MPV QUINTILES (Citrate) AND STROKE
SEVERITY
MPV was arranged into quintiles and compared with the stroke severity score which
was further subdivided into two groups .Group 1 with a score of 0-2 being less severe
and group 2 with a score of 3-6 being more severe. The p value obtained is 0.490 in
citrate anticoagulated samples and has no statistical significance.
MPV (Citrate)
Quintiles
Stroke severity score
P value
Score: 0-2
Score: 3-6
6.10-6.70
4 (17.4%)
8 (29.6%)
6.71-7.08
4 (17.4%)
4 (14.8%)
7.09-7.36
7 (30.4%)
3 (11.1%)
7.37-8.18
4 (17.4%)
7 (25.9%)
8.18-9.60
4 (17.4%)
5 (18.5%)
23 (100.0%)
27 (100.0%)
Total
0.490
-
FIGURE 21: ASSOCIATION OF MPV QUINTILES (Citrate) AND STROKE
SEVERITY
50
45
40
Percentages
35
30
25
20
Stroke severity
15
10
Score: 0-2
5
Score: 3-6
0
6.10-6.70 6.71-7.08 7.09-7.36 7.37-8.18 8.18-9.60
MPV (CITRATE) Quintiles
TABLE 22: MULTIVARIATE LOGISTIC REGRESSION ANALYSIS TO
PREDICT STROKE
It is demonstrated by multiple logistic regression analysis that MPV with a p value of
0.009 and an adjusted OR (Odds ratio) of 8.10, it is one of the most important risk
factors associated with stroke only second to hypertension which had a p value of
<0.001and adjusted OR of 10.10.
Logit
co-efficient
P value
Adj. OR
Age in years
-0.03
0.099+
0.97
Female
-0.02
0.977
0.98
H/O Hypertension
2.31
<0.001**
10.10
H/O DM
-0.12
0.833
0.89
Smoking
0.08
0.951
1.08
Alcohol
-0.10
0.944
0.91
MPV CITRATE
2.09
0.009**
8.10
MPV EDTA
-1.02
0.156
0.36
Variables
6. DISCUSSION
6.DISCUSSION
Previous studies have documented various platelet abnormalities in cerebrovascular
disease.eg, circulating platelet aggregates, platelet aggregation, and increased release
of platelet-specific α granule proteins, thereby indicating platelet activation. Others
have shown that platelet aggregation is not increased in the acute phase but occurs
several days after the event. This lack of detectable activation in the acute phase has
been attributed to platelet consumption during the event. However, the lack of
agreement between these studies may relate to specimen handling and different
methodology.
6.1 PRE ANALYTIC DATA
Normal volunteers were studied to find out the independent influence of the use of
anticoagulants either EDTA or citrate and the time delay on MPV values. Five
volunteers were selected and blood samples were taken in both EDTA and citrate.
Each of these samples were tested at different time intervals starting from one hour to
48 hrs as plotted in the graph.MPV in citrate was found to be about 1 fl lower than the
corresponding EDTA values. It was also seen that the maximum variation of MPV
happens in the first two hours and after four hours. MPV is relatively stable between
two to four hours and after 24 hours.
This is in tune with the other western literature which explains that the maximum
swelling of platelets happen in EDTA in the first two hours and stabilizes completely
after 24hrs. In the current study we have run the samples between 2 and 4 hrs when
they are relatively stable. Though citrate is the gold standard, samples were run in
EDTA as well. The reason for the same is that EDTA is the most common anti
coagulant used for routine complete blood counts and if a positive correlation of MPV
is found with stroke in EDTA as well then it can be used to screen individuals
prospectively.
6.2 DEMOGRAPHIC DATA
The study was a prospective study carried out from Nov 1st 2008 to July 31st 2009 at
St. John‘s Medical College Hospital, Bangalore. 236 patients of strokes admitted to
the medical and neurology wards were screened to get 50 cases.186 cases of stroke
were excluded. Delay in presenting to the hospital i.e. 48hrs from the onset of
symptoms (which was an inclusion criteria) comprised of 46% of the total exclusion.
Hemorrhagic stroke (16.1%), delay in recruiting (16.7%), absence of an informed
consent (15.1%) and platelet aggregates in peripheral smear (5.9%) were other causes
of exclusion.
The mean age for the cases was 58.10±13.67 when compared to 57.50±13.82 for the
controls. The maximum number of cases in this study were in the age group between
51-60 which was followed by age group of 61-70. The average age in males was
55.86±14.38
when compared to 55.24±14.27 in controls. The average age in females
was 64.46±9.12 when compared to 63.92±9.78 in controls. Females were older.
74% of the cases and controls recruited were males and 26% were females.
TABLE 23: COMPARISON OF DEMOGRAHIC DATA OF THE CURRENT
STUDY WITH WESTERN LITERATURE
Study
No of cases
recruited
Demographics
Age, y,
mean±SD
Pikija
et al
A.
Muscari
et al
Current
study
301
81
137
50
71.9 ±10.8
65 ±9
76
78
O'Malley
et al
Butterworth
et al
58
137
79.5±6.5
Bath
et al
58.1±13.6
Women
39 (67%)
55 (40%)
87(29%)
49(60.5%)
65(47.4%)
13(26%)
Men
19 (33%)
82 (60%)
214(71%)
32(39.5%)
72(52.6%)
37(74%)
Thus the mean age in our study was much lower (58.10±13.67) compared to the other
studies. There was a clear male preponderance in the cases of stroke recruited in this
study. Similar patterns were seen in all the other studies compared except for
O‘Malley et al and Pikija et al where a female preponderance was seen.
6 .3 RISK FACTORS FOR STROKE
Out of the many risk factors for stroke hypertension was the most prevalent in this
study group with a percentage of 52 among cases and 34 among controls. Diabetes
mellitus came second with percentage of 28 among cases and 24 among controls.
Similar trend was seen in the other studies as mentioned below with hypertension
being most prevalent risk factor. (84.7% in A. Muscari et al and 82.7% in Pikija et
al.). When compared to the other western studies the representation of previous
strokes as a risk factor was only 8%. Bath et al had 72% of previous strokes since this
study was a sub study which looked at the benefits of ACE inhibitors( perindopril) in
preventing a re stroke. Another important finding noted was the the relatively low
percentage of atrial fibrillation (2%) when compared to the western literature which
also reflects the age of the population studied. The mean age for cases in the current
study was 58.10±13.67 which is much lower than the other western studies compared.
It is a well known fact that atrial fibrillation is more common in the elderly. This
gives more authenticity since the causes for stroke in other cases are predominantly
thrombotic and this gives more importance to the results of MPV in this study group.
Diabetes mellitus had a representation of 28% of the cases which was higher when
compared to the other studies. Metabolic syndrome was the most prevalent in this
study group with a percentage of 74 among cases and 48 among controls with a
significant p value of .008.
TABLE 24: COMPARISON OF RISK FACTOR PROFILE OF CURRENT
STUDY WITH WESTERN LITERATURE
Study
No of cases
recruited
Risk factors
Previous
stroke/TIA
Hypertension
Atrial
fibrillation
Previous
myocardial
infarction
Angina
pectoris
Alcohol
Peripheral
vascular
disease
Current
smoking
Diabetes
O'Malley
et al
58
Butterworth
et al
Bath
et al
Pikija
et al
A. Muscari
etal
Current
study
81
137
50
137
301
19(33%)
17(29%)
-
217(72%)
-
23(28.4%)
67(82.7%)
116(84.7%)
15(26%)
-
-
26(32.1%)
44(32.1%)
1(2%)
15(26%)
-
24(8%)
3(3.70%)
17(12.4%)
4(8%)
16(28%)
10(17%)
-
-
-
-
5(10%)
4(8%)
7 (12%)
-
-
2(2.47%)
-
-
8 (14%)
5 (8.6%)
-
60(20%)
39(13%)
20(14.6%)
29(21.2%)
7(14%)
14(28%)
4 (4.9%)
15(18.5%)
4(8%)
26(52%)
MPV has been compared with the various risk factors for stroke. Multiple logistic
regression done of the baseline risk factors showed that hypertension was the most
common risk factor involved in stroke with a p value of <0.001and adjusted OR of
10.10.MPV was higher in patients with stroke and diabetes mellitus with a suggestive
significance (0.022) when compared to controls .MPV in female gender was higher
when compared to males with a p value of 0.034 in citrated samples. Other risk
factors compared were age, waist hip ratio, lipid parameters, metabolic syndrome, and
smoking and alcohol consumption.
6.4 DRUG HISTORY
16% of the stroke patients recruited where on antiplatelets either because of previous
strokes or history of ischemic heart diseases. This was a cause for concern since
doubts were raised if concurrent usage of antiplatelets would influence the mean
platelet volume studied. However there has been previous studies with aspirin and
MPV and it showed no interference in vitro and in vivo. The same cannot be
affirmatively said about the other antiplatelet drugs. But in this study all the patients
were on 150 mg of aspirin and not on other antiplatelets. The other drugs used were
predominantly antihypertensives with 32% of the hypertensives on calcium antagonist
followed by β blockers and diuretics.
TABLE 25: COMPARISON OF DRUG HISTORY OF PATIENTS IN THE
CURRENT STUDY WITH WESTERN LITERATURE
Study
No of cases
recruited
Drug history
Antiplatelet
ß-Blocker
Diuretic
Nitrate
Digoxin
Calcium
antagonist
Statins
Anticoagulants
O'Malley
et al
Butterworth
et al
Bath
et al
58
137
301
19(33%)
3 (5%)
24(41%)
7 (12%)
11(19%)
-
211(70%)
-
4 (6.8%)
-
-
Pikija
et al
A. Muscari
etal
Current
study
81
137
50
59(43.1%)
-
8(16%)
10(20%)
6(12%)
3(6%)
1(2%)
-
16(32%)
8(16%)
-
33(40.7%)
6 (7.4%)
2 (2.5%)
6.5 PLATELET PARAMETERS AND STROKE
Platelet parameters assessed were MPV, Platelet mass, and platelet count. The main
parameter studied was MPV. MPV( citrate) has got a statistically significant
correlation with ischemic stroke with a p value of 0.005 with an average MPV in
cases being 7.35±0.81 compared to controls who average 6.94±0.59.Though
MPV(EDTA) also shows a difference in cases and controls 7.86±0.82 and 7.86±0.82,
the difference is not statistically significant.
MPV assessment using EDTA and Citrate has been done only in one other study i.e.
Butterworth et al and the values were 8.04 ±1.04 (7.69±0.83) for EDTA and 7.35
±1.05(7.09±0.74) for citrate. The values were comparable even though these studies
have been done in different populations. All the other studies have used EDTA as the
anticoagulant and there is no uniformity in the collection method, time of analysis,
transport of the specimen or the storage. O‘Malley study has performed the test after
24hrs of storage in room temperature. Most of the other studies have performed the
test after 2hrs. In this study the samples were analysed after 2 hrs of storage in room
temperature. The only study with a lower MPV in cases compared to controls is Tohji
et al. This study did not specify the time after venipuncture at which samples were
analysed or temperature at which it was stored.
In the current study the platelet count is showing a slightly lower trend in the cases
with an average of 2.56±0.58 (1.43-4.40) when compared to the controls in which the
average was 2.69±0.83 (1.60-5.40). This trend is however not statistically significant.
This pattern has been seen in all the other case control studies which included
O‘Malley et al, Butterworth et al and Tohji et al.
The platelet mass being a product of platelet count and mean platelet volume is almost
a constant. This is evident from the values in cases and controls in both EDTA
(20.09±4.60, 20.19±5.79) and citrate (18.85±4.67, 18.52±5.31) samples. However
there is no statistical correlation of platelet mass to Ischemic stroke. This has not been
looked upon in other western studies.
We have further demonstrated by multiple logistic regression analysis that MPV with
p value of 0.009 and an adjusted OR of 8.10, it is one of the most important risk
factors associated with stroke only second to hypertension which had a p value of
<0.001and adjusted OR of 10.10.
It has been suggested that MPV and platelet count are under independent hormonal
control, although control of platelet production remains obscure. Some have
suggested a role for interleukin-6, interleukin-3, thrombopoietin, and colonystimulating factors.It is, however, generally accepted that platelet volume and count
are determined at thrombopoiesis,8 and as in ischemic heart disease, these findings
may implicate primary changes occurring at the bone marrow (megakaryocyte) level.
Moreover, an increase in megakaryocyte size and ploidy (DNA content) coincides
with an increase in MPV. This direct association suggests the possibility that
activation of megakaryocytes, as heralded by an increase in MPV, is a feature of
ischemic stroke.
TABLE 26: COMPARISON OF PLATELET PARAMETERS OF THE
CURRENT STUDY WITH WESTERN LITERATURE.
Study
Mean platelet volume
(EDTA) , fL
Mean platelet
volume(citrate), fL
O‘Malley et al
11.3±0.85 (11.3±0.85)
Butterworth et al
8.04 ±1.04(7.69±0.83)
Bath et al
10.0 ±2.1
-
233 ±80
Pikija et al
9.09 (7.05–17.60)
-
197 (106–637)
A. Muscari et al
8.21±1.04
-
244.1±86.7
Tohji etal
9.80±0.79(10.72±0.63)
-
194±54 (247±59)
Current Study
7.86±0.82(7.58±0.70)
7.35 ±1.05(7.09±0.74)
7.35±0.81(6.94±0.59)
Platelet count,
x109/L
255 ±88 (299±80)
231 ±82( 236±54)
256±58 (269±83)
6.6 STROKE SUBTYPES AND MPV
6.6.1 CLINICAL SUBTYPES
The Oxfordshire community stroke project classification of stroke syndromes was
used to classify strokes into Lacunar and Non Lacunar Syndromes (PACS, POCS and
TACS). Two studies i.e. Butterworth et al and A. Muscari et al had found statistically
significant increase of MPV in Non Lacunar strokes when compared to Lacunar
strokes. However O‘ Malley et al did not find any such correlation. Similarly in this
study no statistically significant correlation has been established. This study confirms
that patients with ischaemic stroke have larger platelets a finding that is compatible
with other reports of accentuated platelet function in brain infarction, including
elevated blood and urine levels of b -thromboglobulin (b -TG) and TxA2. However,
we have not been able to establish that thrombomegaly is restricted to patients with
cortical ischaemic stroke. Cortical events are usually related to atherothromboembolic
events that occur in the heart, aorta, carotid arteries or large intracranial arteries are
likely to involve platelet activation. Conversely, many deep white matter lacunar
strokes are considered to be a consequence of small vessel lipohyalinosis, a disease
process not involving platelets46.
6.6.2 SUBTYPES BASED ON ISCHEMIC TERRITORY
MCA territory was involved in 72% of the patients. This was followed by
involvement of the vertebrobasilar artery (posterior circulation) in 14 % of the cases.
Involvement of ACA and MCA together comprised 10% of the cases. Pure ACA
territory involvement was seen with 4% of cases. The infarct territory and MPV
(EDTA and Citrate) were compared to look for any correlation. The p values obtained
were 0.525 for MPV- EDTA and 0.720 for MPV citrate. However these were not
statistically significant. Such studies have not been cited in western literature.
6.7 STROKE SEVERITY AND MPV
The clinical severity of stroke at presentation was determined by the modified
Rankin‘s scale and severe disability was seen with 20% of the cases. 28% of the cases
had no significant disability. Others included 18% with slight disability, 12% with
moderate disability and 22% with moderately severe disability. There were no deaths
recorded. The association of MPV with severity of stroke was determined by
comparing the modified Rankin‘s score with corresponding mean values of MPV in
each group. MPV – EDTA showed a p value of 0.283 and MPV –citrate showed a p
value of 0.318, both of which were statistically insignificant. O‘ Malley conducted
similar studies and divided the outcomes as independent (Rankin‘s grade 0 to 2),
dependent (Rankin‘s grade 3 to 5) and dead (Rankin‘s grade 6). However no
statistical significance with MPV was obtained. Butterworth et al studied patients
who were dead or dependent at 3 months, using the Lindley score, and they had a
significantly higher platelet volume, and a tendency to a lower platelet count, as
compared with those who fared well. However statistical significance was not found.
MPV was arranged into quintiles though the sample size was too small for such a
study and was compared with the stroke severity score which was further subdivided
into two groups. Group 1 with a score of 0-2 being less severe and group 2 with a
score of 3-6 being more severe. The p value obtained is 0.654 in EDTA and 0.490 in
citrate anticoagulated samples and has no statistical significance. Similar study was
conducted by Griesenegger et al and an increased MPV was associated with a worse
outcome in patients suffering an acute ischemic cerebrovascular event. Patients within
the highest quintile of MPV had a 2-fold risk of suffering a severe stroke compared
with patients within the lowest quintile. The association of high MPV with severe
stroke remained significant after adjustment for confounding factors. The p value was
0.002 in this particular study. In our study the cases were recruited from medical and
neurological wards and though there were intensive treatment units in each of these
departments, patients who needed ventilatory support were admitted to the intensive
care unit and such patients were not included .This would have lead to a bias since
seriously ill patients were not recruited.
There is indirect evidence that the changes in MPV and platelet count are likely to
have preceded the vascular event and are unlikely to be due to platelet consumption at
the infarct site. Because the average life span of the platelet is about 8 days, the
elevated MPV seen within the first 48 hours after stroke probably represents platelets
released before infarction.
Furthermore, it is unlikely that platelet consumption due to localized thrombosis
would affect peripheral venous estimations of platelet variables. The observation that
there was no difference in MPV between large cortical strokes and smaller lacunar
infarctions also lends support to this view. We suggest that large platelets may
promote the thrombotic event in a susceptible individual and that the increase in
MPV may have contributed to the development of the stroke rather than simply being
a consequence of the acute event itself. In conclusion, this study has shown an
elevation of MPV and reduction of platelet count in acute stroke. Within this
relationship and adjusting for other significant variables in multivariate regression
analysis, an increase in MPV is independently associated with stroke. The
observations here suggest a role for larger platelets in the genesis of cerebral
thrombosis and are likely to represent changes occurring at thrombopoiesis. Further
research is required into the role of platelet volume in stroke pathology, outcome, and,
most importantly, in individuals at risk for stroke.
6.7 LIMITATIONS OF THE STUDY
There are a few limitations to this study that need to be mentioned

There were only 50 patients and controls in the study. Sample size was
calculated and found adequate for such a study. But the sample size was
smaller than some of the western studies.

There was no follow up done of the cases due to the time constraint .If on
follow up a persistent increase of MPV was demonstrated it would have given
more strength to the hypothesis that the increase in MPV may have
contributed to the development of the stroke rather than simply being a
consequence of the acute event itself.

Seriously ill patients directly admitted to the intensive care unit have not been
included in the study due to difficulty in getting consent. This could have lead
to selection bias. This would have reflected on the correlation with MPV and
stroke severity.

One of the western study i.e. Pikija et al
47
had compared MPV and Infarct
volume on the CT scan of the brain as an index of severity of stroke. This
study was accepted only in April 2009 and became online in May 2009 which
was almost towards the end of sample collection for this study. However if
this parameter was compared it could have added another attribute to stroke
severity.

The controls have been matched only for age and sex and not for the other risk
factors which would have been ideal. However almost all the western
literature reviewed has also compared only age and sex matched controls.
7. CONCLUSIONS
7. CONCLUSIONS
1) This study has shown an elevation of MPV in acute phase of ischemic stroke.
Within this relationship and adjusting for other significant variables in
multivariate regression analysis, it can be stated that an increase in MPV is
independently associated with stroke. The observations here suggest a role for
larger platelets in the genesis of cerebral thrombosis and are likely to represent
changes occurring at thrombopoiesis. Further research is required into the role
of platelet volume in stroke pathology, outcome, and, most importantly, in
individuals at risk for stroke.
2) Platelet mass was found to be more or less a constant .i.e. this study has shown
not only an elevation of MPV but a slight reduction of platelet count in acute
phase of ischemic stroke though no statistical correlation was established.
3) This study did not find a statistically significant correlation between clinical
severity of stroke and mean platelet volume.
4)
In this study strokes were sub typed clinically and based on the vascular
territory on MRI. However no statistical correlation was obtained when MPV
was compared to the various subtypes of stroke.Thrombomegaly is restricted
not just to patients with cortical ischaemic stroke but also with lacunar
syndromes.
8. SUMMARY
SUMMARY
Cerebrovascular diseases include some of the most common and devastating
disorders. They cause ~200,000 deaths each year in the United States and are a major
cause of disability.The prevalence of stroke in India was estimated as 203 per 100,000
population above 20 years, amounting to a total of about 1 million cases. It ranked as
the sixth leading cause of disability-adjusted years (DALY; one DALY is one of the
lost year of healthy life) in 1990 and is projected to rank fourth by the year 2020 13.
The platelet plays a major role in the pathogenesis of vascular disease, and mean
platelet volume (MPV) is a physiological variable of hemostatic importance. Large
platelets are more reactive, produce more prothrombotic factors, 3and 4 and aggregate
more easily. They also contain more dense granules and release more serotonin and ßthromboglobulin than do small platelets. Platelets have no nuclei, and their
characteristics are determined by their progenitor cell, the bone marrow
megakaryocyte. Ischemic stroke is thought to occur as a result of thrombotic
occlusion of a stenosed atherosclerotic blood vessel. Initially platelets adhere to the
damaged vessel, resulting in recruitment of further platelets, followed by aggregation,
formation of a platelet plug and finally thrombotic occlusion. Thus, the detection of
large platelets in patients would lend support to the idea that platelet volume
influences thrombotic large vessel occlusion leading to ischemic stroke. Though there
have been quite a few studies which have demonstrated an association between
myocardial infarction and platelet size, very few studies has looked at the association
between platelet size and ischemic stroke. Among them there has been discrepancy
regarding the sample size, methodology used and the final results. There are no
documented studies in India comparing the association of mean Platelet volume with
Ischemic strokes. This was a prospective study and data collected from Nov 1st 2008
to July 31st 2009 at St. John‘s Medical College Hospital, Bangalore, a tertiary care
referral centre. The study was carried out among 50 patients diagnosed with an acute
ischemic stroke and presenting to the medical and neurological wards in the hospital
within forty eight hours of onset of symptoms and satisfying the inclusion and
exclusion criteria. The data was compared to 50 age and sex matched controls.
Key findings included:
1) The main parameter studied was MPV. MPV( citrate) has got a statistically
significant correlation with Ischemic stroke with a P value of 0.005 with an
average MPV in cases being 7.35±0.81 compared to controls who average
6.94±0.59.Though MPV(EDTA) also shows a difference in cases and controls
7.86±0.82 and 7.58±0.70, the difference is not statistically significant. Thus
the study has shown an elevation of MPV in acute phase of Ischemic stroke.
Within this relationship and confounding for other significant variables in
multivariate regression analysis, it can be stated that an increase in MPV is
independently associated with stroke. The observations here suggest a role for
larger platelets in the genesis of cerebral thrombosis and are likely to represent
changes occurring at thrombopoiesis. Further research is required into the role
of platelet volume in stroke pathology, outcome, and, most importantly, in
individuals at risk for stroke.
2) The platelet count is lower in the cases with an average of 2.56±0.58 (1.434.40) when compared to the controls in which the average was 2.69±0.83
(1.60-5.40). The platelet mass being a product of platelet count and mean
platelet volume is almost a constant. This is evident from the values in cases
and controls in both EDTA (20.09±4.60, 20.19±5.79) and citrate (18.85±4.67,
18.52±5.31) samples.
3) The Oxfordshire community stroke project classification of stroke syndromes
was used to classify strokes into Lacunar and Non Lacunar Syndromes
(PACS, POCS and TACS). In this study no statistically significant correlation
has been established. The Infarct territory on MRI and MPV (EDTA and
Citrate) were compared to look for any correlation. The p values obtained
were 0.525 for MPV- EDTA and 0.720 for MPV – MPV citrate. However
these were not statistically significant.
4) The clinical severity of stroke at presentation was determined by the modified
Rankin‘s scale and severe disability was seen with 20% of the cases. 28% of
the cases had no significant disability. Others included 18% with slight
disability, 12% with moderate disability and 22% with moderately severe
disability. There were no deaths recorded. The association of MPV with
severity of stroke was determined by comparing the Modified Rankin‘s score
with corresponding mean values of MPV‘s in each group. MPV – EDTA
showed a p value of 0.283 and MPV –citrate a p value of 0.318, both of which
were statistically insignificant.
In conclusion, this study has shown an elevation of MPV and reduction of
platelet count in acute stroke. With this relationship and confounding for other
significant variables in univariate analysis, an increase in MPV is
independently associated with stroke. The observations here suggest a role for
larger platelets in the genesis of cerebral thrombosis and are likely to represent
changes occurring at thrombopoesis. Further research is required into the role
of platelet volume in stroke pathology, outcome, and most importantly in
individuals at risk of stroke.
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10.ANNEXURE
PROFORMA FOR CASES
Informed Consent Form
Study title – To Determine an association between mean platelet volume and ischemic stroke.
Stroke is a condition that occurs when there is a blockage in the blood supply to the brain.
This causes death or disability [inability to move or loss of sensation] that is often long-term.
Globally, strokes are an important medical and social problem.
Human blood consists of three components the red cells, white cells and the platelets. Studies
have shown that platelets play an important role in the occurrence of stroke. We are studying
if there is an association between large platelets (indicated by mean platelet volume) and
stroke.
We invite you to participate in this study, which is a part of the post graduate dissertation and
will be done in St John‘s medical college hospital. You qualify for this study because you
either suffered a stroke for the first time or you are in the age category of an individual who
has had a stroke. Participation in this study is entirely voluntary. If you chose not to
participate in this study or if you withdraw from the study at any time, your care and
treatment in the hospital for the stroke or your relationship with the doctors or researchers will
not change. There will be no monetary compensation for participation in this study.
If you agree to participate, you will be asked to answer some questions on your past illness
and medications. You will have some clinical measurements taken such as blood pressure,
heart rate, weight, height, waist circumference and hip circumference. The waist
circumference will be done using a measurement tape over the unclothed abdomen. The hip
circumference will be measured around the buttocks with only light clothing.
One sample of blood (5ml/1 teaspoon) will be drawn and analysed in an automated machine
to determine the platelet size.
The only risk is bruising around the veins from where the blood sample is drawn and minimal
chance of infection. You will not be exposed to any other risk in this study. If you are a
patient with a stroke there will be no change in the treatments given to you for the stroke. If
you are an individual without a stroke and may have any other medical condition, there will
be no change in you treatments. The information collected will be held in strict confidence
and you will not be identified in any report or publication.
This study has been approved by the local ethics committee.
After reading or having read to me and understanding the contents adequately I agree to
participate in this study.
----------------------Name of subject
----------------------Signature
----------------------Date
----------------------Name of witness
----------------------Signature
----------------------Date
-----------------------
-----------------------
-----------------------
Name of Investigator
Signature
Date
PROFORMA FOR CASES
Demographic Details
Date
Name of the patient
Hospital No
Age
Sex
Address
Phone No
History
Previous Stroke /TIA
Hypertension
Diabetes
Alcohol
Smoking
Angina
Previous Myocardial Infarction
Atrial Fibrillation
Drug History
Aspirin
Other Anti platelet Drugs Yes/No
If yes Specify
Anti Hypertensive‘s
OHA‘s/ Insulin
Chemotherapy drugs
Other drugs
Physical Examination
Vital Signs
Pulse
BP
RR
Temperature
WHR
Systemic Examination
CNS
Other systems
RS
CVS
P/A
Investigations
Hemoglobin
Total Leukocyte count
Differential count
Mean Platelet volume
Platelet count
Peripheral Smear
Blood Sugar
Lipid Profile
CT scan Brain
Type of infarct
Area Involved
Modified Rankin‘s score
PROPOSED PROFORMA FOR CONTROLS
Demographic Details
Date
Name of the Control
Hospital No
Age
Sex
Address
Phone No
History
Previous Stroke /TIA
Hypertension
Diabetes
Alcohol
Smoking
Angina
Previous Myocardial Infarction
Atrial Fibrillation
Platelet disorders
Investigations
Hemoglobin
Total Leukocyte count
Differential count
Mean Platelet volume
Platelet count
Peripheral Smear
Blood Sugar
Consent
We invite you to participate in this study,
which is a part of the post graduate
dissertation and will be done in St John‘s
medical college hospital. You qualify for
this study because you are in the age
category of an individual who has had a
stroke. Participation in this study is entirely
voluntary. If you chose not to participate in
this study or if you withdraw from the study
at any time, your care and treatment in the
hospital for the stroke or your relationship
with the doctors or researchers will not
change. There will be no monetary
compensation for participation in this study.
One sample of blood (5ml/1 teaspoon)
will be drawn and analysed in an
automated machine to determine the
platelet size.
--------------------------Name of subject
Date
-----------------Signature