The Islamic University of Gaza
Deanship of Research and Graduate Studies
Faculty of Health Sciences
Master of Medical Laboratory Sciences
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The Association of Iron Profile Parameters and
Selected Minerals (Zinc and Magnesium) with
Febrile Seizures in Children (6-60 months) at Al-
Nasir Hospital in Gaza City
المعادن المختارة (الزنك والمغنيسيوم) مع بعضو العلاقة بين الحديد
مستشفى النصر في شهر) ٦٠-٦( التشنجات الحرارية لدى الأطفال
غزة مدينةفي
By
Ohood Mohammed Shamallakh
Supervised by
A thesis submitted in partial fulfillment of the requirements for the degree of
Master of Medical Laboratory Science
May/2019
Dr. Mazen Medhat Alzaharna
Assistant Prof. of Biomedical Sciences
I
إ(ــــــــــــــ"ار
أ�2 ا���(4 أد�2ه ��0م ا�"���� ا�#� /��. ا��-�ان:
The Association of Iron Profile Parameters and Selected
Minerals (Zinc and Magnesium) with Febrile Seizures in
Children (6-60 months) at Al- Nasir Hospital in Gaza City
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�Fة �E?7#$ ا�-!" -(�� �D� BC �D") ٦٠-٦( ?�لا��"ار)� ��ى ا>ط
ا�-�ص، �� �%+�ء �� ( ا)��رة إ��� &�%� ورد، وأن ا�� ��� إ�� ھ� ���ج ���ي أ�� ��ن �� ا��� ���� ھ�ه
�ھ�ه ا�� ��� ?<5 أو أي �=ء �+�� �> �47م �6 �:5 ا67�89 �+�5 در�� أو �34 ��1 أو �2%1 ��ى أي �/ .
� أو ��%2� أ�8ى.���A)
Declaration I understand the nature of plagiarism, and I am aware of the University’s policy on
this.
The work provided in this thesis, unless otherwise referenced, is the researcher's own
work, and has not been submitted by others elsewhere for any other degree or
qualification.
:3��C�ا > ا �� ���& ��د �2��D Student's name:
:E����D ا��� ���& ��د �2�� Signature:
:D7ر���14/05/2019 ا Date:
III
Abstract Background: Febrile seizures (FSs) are the commonest form of seizures in children aged between 6-60 months with 38oC or higher body temperature. 2-5% of neurologically healthy children encounter at least one, usually simple FS. Iron is a nutritional element that plays a significant role in brain energy metabolism, myelin formation, and neurotransmitter metabolism. So, it is likely that iron deficiency anemia (IDA) may predispose to other neurological disturbances like FS. Zinc (Zn) and Magnesium (Mg) play a crucial role in the function of the brain and neurological disorders development and prevention, these elements could also be involved in the etiology of FS. Objective: To investigate the association between iron profile parameters, Zn, and Mg levels among children in Gaza City. Materials and methods: The study is a case-control one, performed on eighty patients, 40 patients with FS and 40 without seizures. Informed consent was obtained, a detailed history and clinical examination has been carried out for both groups, serum ferritin, iron, total iron binding capacity, and soluble transferrin receptor were measured by ELISA, Zn and Mg were determined chemically, transferrin saturation was calculated, complete blood count indices measurements and anthropometric measurements were performed for all participants. An approval was obtained from Helsinki committee to perform this study. SPSS program version 22 was used for all data analysis.
Results: The mean age of the cases (24.7 ± 13.8 months) and controls (23.2 ± 15.7 months), (p = 0.634). Moreover, the percentage of male and female participants was 52.5% & 47.5% for cases while 60.0% & 40.0% for controls respectively with (p = 0.499). The mean levels of serum iron, and transferrin saturation among cases were higher significantly compared to controls (50.9 ± 23 Fg/dL & 19.8 ± 13.3% versus 24.3 ± 16.3 Fg/dL & 7.5 ± 8.0% respectively with p < 0.001). The mean level of TIBC among cases was lower significantly compared to controls (296.6 ± 64.6 Fg/dL versus 372.1 ± 56.5 Fg/dL respectively with p < 0.001). In addition, the percentage of cases with anemia was 85% compared to 80% for controls (p = 0.556). In contrast, 12.5% of cases had ID and IDA compared to 30% and 27.5% in controls respectively, (p > 0.05). The mean level of serum Zn in cases was lower compared to control group (77.3 ± 11.4 µg/dL versus 78.8 ± 9.5 µg/dL respectively), (p > 0.05). The mean levels of Mg [Fg/dL] and hs-CRP [mg/L] were lower among cases (2.0 ± 0.2 & 3.0 ± 2.7) compared to controls (2.1 ± 0.2 & 8.5 ± 5.8) with (p < 0.05). Conclusions: There was no association between IDA or decreased serum level of Zn and the presence of FS. While, our results showed that Mg may play a role in FS pathogenesis.
Keywords: Febrile Seizures, Serum Iron, Zinc, Magnesium, Gaza City.
IV
ملخص الدراسة
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V
Dedication
I dedicate this thesis to
My great parents who have given me endless love, support, durable
patience, and faith through the years,
My sisters and brothers for their encouragement and love,
My best friend Heba,
All my teachers, friends and colleagues who have been directly or
indirectly involved in the research,
The souls of all martyrs who sacrificed themselves for the sake of
Palestine to give us the freedom we deserve,
My university "The Islamic University of Gaza" that continuously
improves research,
To everyone who made this work possible
To all of them, I dedicate this work
Ohood Mohammed Shamallakh
VI
Acknowledgments
First and foremost, I would like to start by thanking Allah for giving me the
strength, knowledge, ability and opportunity to undertake this study.
The success of this thesis is attributed to the extensive support and assistance
from my supervisor, Dr. Mazen Alzaharna, Assistant Professor of Biomedical
sciences. I would like to express my grateful gratitude and sincere appreciation to him
for his helpful guidance, advice and encouragement throughout this work. Also, I am
deeply thankful to all those who stood beside me during this long journey.
Special thanks from the deepest of my heart to my Mother and Father, thank
you for support, inspiration and always asking Allah to grant me success. Many thanks
to my family, specially my sister Kholoud who furnished me love guidance and
extreme support. I am extremely grateful to my best friend Heba Arafat, for her
support, encouragement and standing beside me during all the difficulties.
I am indebted to all staff at Al- Nassir Pediatric hospital for their assistance,
active participation, and their precious time. My special thanks to Dr. Mohammed
Arafat, consultant Pediatrician in Public Aid Hospitals for his help and support. My
sincere thanks to Dr. Shireen Abed, consultant Pediatrician and head of NICU in Al-
Nassir Pediatric hospital for her kind support in reviewing the questionnaire. And
special thanks to Dr. Ihab Naser, Head of Clinical Nutrition Department, Al Azhar
University -Gaza for his help and support. Also, my special thanks to Dr. Ashraf
Shaqaliah, Head of laboratory medicine Department, Al Azhar University -Gaza for
his support and encouragement.
I want to thank the Director of the Palestinian Medical Relief Society
laboratory in Gaza City, Mr. Mohamed Abu Afash, and laboratory personnel for the
great help, high quality work, and promptness, who worked for the determination of
Biochemical tests in this study. Special thanks to Dr. Aymen Abu Mustafa and
Sastek Center for their assistance in statistical analysis.
Finally, not to forget any one, I greatly thankful to everyone who supported me
through finishing this work.
With respect
Ohood Mohammed Shamallakh
VII
Table of Contents
Declaration .................................................................................................................... I
Abstract ...................................................................................................................... III
Dedication ................................................................................................................... V
Acknowledgments ...................................................................................................... VI
Table of Contents ...................................................................................................... VII
List of Tables ............................................................................................................. XI
List of Figures ........................................................................................................... XII
List of Abbreviations .............................................................................................. XIII
Chapter 1: Introduction ................................................................................................ 1
1.1 Overview ................................................................................................................ 2
1.2 Objectives of the Study .......................................................................................... 4
1.2.1 General objective ............................................................................................ 4
1.2.2 Specific objectives .......................................................................................... 4
1.3 Significance of the Study ....................................................................................... 4
Chapter 2: Literature Review ....................................................................................... 5
2.1 Seizures in Childhood ............................................................................................ 6
2.2 Febrile Seizures ...................................................................................................... 7
2.2.1 Definition ....................................................................................................... 7
2.2.2 Types of Febrile Seizures ............................................................................... 8
2.2.3 Epidemiology ................................................................................................. 8
2.2.4 Mortality rate .................................................................................................. 9
2.2.5 Risk factors ................................................................................................... 10
2.2.5.1 Fever .................................................................................................. 10
2.2.5.2 Metabolic abnormalities and deficiencies .......................................... 11
2.2.5.3 Genetics .............................................................................................. 11
2.2.5.4 Vaccinations ....................................................................................... 12
2.3 Minerals and Trace Elements ............................................................................... 12
2.3.1 Iron ............................................................................................................... 13
2.3.1.1 Introduction ........................................................................................ 13
2.3.1.2 Iron Overload ................................................................................... 14
VIII
2.3.1.3 Iron Deficiency .................................................................................. 15
2.3.1.3.1 Definition .................................................................................... 15
2.3.1.3.2 Stages of Iron Deficiency Development ..................................... 15
2.3.1.3.3 Iron deficiency Anemia ............................................................... 16
2.3.1.3.4 Prevalence of Anemia ................................................................. 17
2.3.1.3.5 Clinical Features and Manifestations .......................................... 18
2.3.1.3.6 Role of Iron deficiency in FSs .................................................... 19
2.3.1.4 Diagnosis of Iron Deficiency ............................................................. 20
2.3.1.5 Laboratory Evaluation of Iron Status ................................................. 23
2.3.1.5.1 Assessment of Iron Stores ........................................................... 23
2.3.1.5.1.1 Direct Assessment Methods ................................................. 23
2.3.1.5.1.2 Indirect Assessment Methods .............................................. 24
2.3.2 Zinc .............................................................................................................. 28
2.3.2.1 Introduction ........................................................................................ 28
2.3.2.2 Zinc deficiency ................................................................................... 29
2.3.2.3 Role of Zinc in febrile seizures .......................................................... 29
2.3.3 Magnesium ................................................................................................... 31
2.3.3.1 Introduction ........................................................................................ 31
2.3.3.2 Role of Magnesium in febrile seizures .............................................. 32
2.4 Previous Studies ................................................................................................... 33
Chapter 3: Materials & Methods ................................................................................ 38
3.1 Study Design ........................................................................................................ 39
3.2 Study Population .................................................................................................. 39
3.3 Sampling and Sample Size ................................................................................... 39
3.4 Selection Criteria ................................................................................................. 39
3.4.1 Inclusion Criteria .......................................................................................... 39
3.4.2 Exclusion Criteria ......................................................................................... 39
3.5 Ethical Considerations ......................................................................................... 40
3.6 Data Collection .................................................................................................... 40
3.6.1 Questionnaire Interview ............................................................................... 40
3.6.2 Anthropometrics Measurements .................................................................. 40
3.7 Specimen Collection ............................................................................................ 41
IX
3.8 Blood Sampling and Processing .......................................................................... 41
3.9 Materials .............................................................................................................. 42
3.9.1 Equipment .................................................................................................... 42
3.9.2 Chemicals, Kits and Disposables ................................................................. 42
3.10 Biochemical parameters and CBC analysis ....................................................... 43
3.10.1 Determination of serum iron ...................................................................... 43
3.10.2 Determination of UIBC .............................................................................. 43
3.10.3 Determination of Serum Ferritin ................................................................ 44
3.10.4 Calculation of Transferrin Saturation: ........................................................ 45
3.10.5 Determination of Soluble Transferrin Receptor ......................................... 45
3.10.6 Determination of Complete Blood Count .................................................. 47
3.10.7 Determination of Zinc ..................................................................................... 47
3.10.8 Determination of Magnesium ......................................................................... 48
3.10.9 Determination of High-sensitivity C-reactive Protein .................................... 49
3.11 Statistics and Data Analysis ............................................................................... 49
Chapter 4: Results ...................................................................................................... 51
4.1 General characteristics of the study Population ................................................... 52
4.2 Anthropometric assessment measurements of the study population.................... 54
4.3 Clinical characteristics and medical history of the study population ................... 56
4.4 Biochemical parameters among the study population ......................................... 58
4.5 Complete blood count indices among the study population ................................ 61
4.6 Anemia, iron deficiency and iron deficiency anemia among the study
population…... ........................................................................................................... 64
4.7 Correlation between SI, sTfR, Zn, Mg and different characteristics and parameters
among the study population ....................................................................................... 65
4.8 Correlation between SI, sTfR, Zn, Mg and different CBC indices among the study
population .................................................................................................................. 66
Chapter 5: Discussion ................................................................................................ 69
5.1 General characteristics of the study population ................................................... 70
5.2 Clinical characteristics and medical history of the study population ................... 71
5.3 Biochemical parameters among the study population ......................................... 73
5.3.1 Iron profile parameters, CBC, and CRP ....................................................... 73
X
5.3.2 Zinc and Magnesium .................................................................................... 79
Chapter 6: Conclusions and Recommendations ......................................................... 82
6.1 Conclusions .......................................................................................................... 83
6.2 Recommendations ................................................................................................ 83
6.3 Limitations ........................................................................................................... 84
References .................................................................................................................. 85
Annexes ...................................................................................................................... 98
Annex (1): Helsinki approval ..................................................................................... 99
Annex (2): Ministry of Health facilitation letter ...................................................... 100
Annex (3): Questionnaire ......................................................................................... 101
XI
List of Tables
Table 2.1: Simple and complex febrile seizures. ........................................................ 9
Table 2.2: WHO hemoglobin thresholds to define anemia in different age groups. . 16
Table 2.3: Indicators of Iron- Deficiency Anemia. Modified from. .......................... 21
Table 2.4: Laboratory Studies Differentiating the Most Common Microcytic Anemias.
Modified from. ........................................................................................................... 22
Table 3.1: The major equipment used in the study.................................................... 42
Table 3.2: Chemicals, kits, and disposables. .............................................................. 42
Table 3.3: Reference ranges of the TIBC. ................................................................. 44
Table 3.4: Reference ranges of ferritin. ..................................................................... 45
Table 3.5: Reference ranges of the Tfsat. .................................................................. 45
Table 3.6: Reference range of CBC parameters. ....................................................... 47
Table 3.7: Reference ranges of Zn. ............................................................................ 48
Table 3.8: Reference ranges of Mg. ........................................................................... 49
Table 3.9: Reference ranges of hs-CRP. .................................................................... 49
Table 4.1: General characteristics of the study population. ....................................... 53
Table 4.2: Length of pregnancy, type of delivery and birth weight among the study
population. ................................................................................................................. 54
Table 4.3: Anthropometric assessment measurements of the study population. ....... 55
Table 4.4: Vital signs at admission of hospital among the study population. ............ 56
Table 4.5: Clinical characteristics and medical history of the study population. ...... 57
Table 4.6: The mean of different biochemical parameters among the study population.
................................................................................................................................... 59
Table 4.7: Comparison of different biochemical parameters among the study
population. ................................................................................................................. 60
Table 4.8: The mean of CBC indices among the study population. .......................... 62
Table 4.9: Comparison of CBC indices among the study population. ....................... 63
Table 4.10: Anemia, iron deficiency and iron deficiency anemia among the study
population. ................................................................................................................. 64
Table 4.11: Correlation between SI, sTfR, Zn, Mg and different characteristics and
parameters among the study population. .................................................................... 66
Table 4.12: Correlation between SI, sTfR, Zn, Mg and different CBC indices among
the study population. .................................................................................................. 68
XII
List of Figures
Figure 2.1: The role of Zn & Mg in activation of glutamate decarboxylase enzyme and
production of GABA. ................................................................................................. 30
Figure 2.2: Mechanism of seizure due to hypomagnesaemia. ................................... 33
XIII
List of Abbreviations
AAP American Academy of Pediatrics
CBC Complete Blood Count
CLIA Chemiluminescence Immunoassay
CLSI Clinical and Laboratory Standards Institute
CNS Central Nervous System
CRP C- Reactive Protein
CSF Cerebrospinal Fluid
Cu Copper
DNA Deoxyribonucleic Acid
DPT Diphtheria-Pertussis-Tetanus
EDTA Ethylene Diamine Tetra Acetic Acid
ELISA Enzyme-Linked Immunosorbent Assay
Fe2+ Ferrous iron
Fe3+ Ferric iron
FEP Free Erythrocyte Protoporphyrin
FS Febrile Seizure
GABA Gamma Amino Benzoic Acid
GAD Glutamic Acid Decarboxylase
GIT Gastrointestinal tract
Hb Hemoglobin
HBW High Birth Weight
Hct Hematocrit
hs-CRP High-sensitivity C-Reactive Protein
IBE International Bureau for Epilepsy
ID Iron Deficiency
IDA Iron Deficiency Anemia
ILAE The International League Against Epilepsy
ICU Intensive Care Unit
LBW Low Birth Weight
MCH Mean Corpuscular Hemoglobin
XIV
MCHC Mean Corpuscular Hemoglobin Concentration
MCV Mean Corpuscular Volume
Mg Magnesium
MPV Mean Platelet Volume
NBW Normal Birth Weight
NIH National Institutes of Health
NMDA N-Methyl-D-Aspartate oC Degree Celsius
PDW Platelet Distribution Width
PMRS Palestinian Medical Relief Society
RBCs Red Blood Cells
RDW Red Blood Cell Distribution Width
RNA Ribonucleic Acid
SF Serum Ferritin
SI Serum Iron
SOD Superoxide Dismutase
SPSS Statistical Package for the Social Science
sTfR Soluble Transferrin Receptors
TE Trace Elements
Tf Transferrin
Tfsat Transferrin Saturation
TIBC Total Iron Binding Iron Capacity
TRF Serum Transferrin
UIBC Unsaturated Iron Binding Capacity
URTI Upper Respiratory Tract Infection
US United States
WBCs White Blood Cells
WHO World Health Organization
Zfp Zinc-finger proteins
Zn Zinc
1
2
Chapter 1
Introduction
1.1 Overview
Febrile seizures (FS) are the most common form of seizures in children aged
between six months to five years with a body temperature of 38oC (100.4°F) or higher,
which are not the result of central nervous system (CNS) infection or any metabolic
imbalance, and which occur in the absence of a history of prior afebrile seizures
(Kliegman et al., 2016).
Febrile seizures (FS) are classified into two groups, as follows: simple FSs and
complex FSs. FS is a simple type if it occurs in short-term (lasting for a maximum of
15 minutes) generalized tonic clonic activity (without a focal component), which
occurs without a recurrence in 24 hours or within the same febrile illness and resolving
spontaneously. Conversely, it is a complex type if it occurs in prolonged (lasting for
more than 15 minutes), partial onset or focal features, multiple (more than one seizure
happen during a 24-hour period for the same febrile illness) (Kliegman et al., 2016).
Between 2 to 5 percent of infants and children who are neurologically healthy
encounter at minimum one, usually simple FS. Currently identified risk factors for FS
include, close blood relative with history of FS, cigarette smoking during gestation,
low birth weight, a neonatal nursery stay greater than month, attending to daycare
center, increase the number of febrile diseases, fever higher than 39.4 degree Celsius,
specific infectious diseases, disturbance in the levels of serum minerals, and iron
deficiency anemia (IDA) (Amiri, Farzin, Moassesi, & Sajadi, 2010; Shinnar &
Glauser, 2002).
Iron deficiency (ID) consider the commonest micronutrient deficiency globally
which can be prevented and treated. Iron is a nutritional element that required for the
hemoglobin (Hb) synthesis, plays a significant role in brain energy metabolism, myelin
formation, and neurotransmitter metabolism. Furthermore, it's important for enzymes
that contribute to neurochemical reactions (Kliegman et al., 2016; Kumari, Nair, Nair,
Kailas, & Geetha, 2012). ID can cause several neurological manifestations including,
delayed motor development, learning deficits, poor attention span, weak memory, and
behavioral disturbances. In addition, high body temperature can exacerbate negative
3
effects of ID on the brain. Therefore, it is likely that ID may predispose to other
neurological disturbances like FSs (Fallah, Tirandazi, Karbasi, & Golestan, 2013;
Kumari et al., 2012).
Minerals and trace elements (TEs) have been demonstrated to affect several
biochemical and physiological processes. They are integrated in the protein, enzyme
and complex carbohydrates structure. In addition to various insignificant pathological
findings, other life-threatening diseases result from insufficient intake of food rich of
these elements (Kumari et al., 2012). Zinc (Zn) and Magnesium (Mg) are key elements
which have been continuously studied in a number of diseases. They play a crucial
role in the function of the brain and neurological disorders development and
prevention. It was assumed that certain elements might be involved in the etiology of
FS (Amiri et al., 2010).
Zinc is one of the main TEs in the normal development of the CNS in the
human body. It modulates glutamic acid decarboxylase (GAD) activity which is rate-
limiting enzyme in the synthesis of gamma-aminobutyric acid (GABA), furthermore
facilitates the inhibitory effect of calcium on N-methyl-d-aspartate (NMDA) receptors
and increases the affinity of neurotransmitters like glutamate to their receptors. When
a patient develops low Zn level, the NMDA receptors will be stimulated and induce
an epileptic discharge in children suffering from elevated temperatures (Amiri et al.,
2010; Joshi, 2014).
Magnesium is a factor that is involved in neuronal function that exerts a voltage
dependent blockage of the NMDA receptor channel and also inhibits calcium's
facilitative effects on synaptic transmission (Khosroshahi, Ghadirian, & Kamrani,
2015). Occasionally, low concentrations of serum Mg has related to significant effects
on the CNS, particularly in epilepsy. A positive correlation between low levels of
serum Mg and the predisposition of FS has been found in children (Bharathi &
Chiranjeevi, 2016; Namakin, Zardast, Sharifzadeh, Bidar, & Zargarian, 2016;
Nemichandra, Prajwala, Harsha, & Narayanappa, 2017; Salah et al., 2014).
4
1.2 Objectives of the Study
1.2.1 General objective
To investigate the association between iron profile parameters and selected
minerals (Zn and Mg) with FS among children from Gaza City.
1.2.2 Specific objectives
1. To compare the iron profile parameters (serum iron, serum ferritin, Total Iron
Binding Capacity, soluble transferrin receptor and transferrin saturation) and
Complete Blood Count indices in both children with FS (cases) and controls.
2. To compare the concentrations of selected minerals (Zn and Mg) in cases and
controls.
3. To investigate the possible relationship between FS and the different
parameters.
1.3 Significance of the Study
Febrile seizures are one of the most common causes of pediatric emergencies
in the world. It leads to hospital admission that actually costs families and health
sector. It tends to cause emotional, physical and mental damage that is stressful to
parents and has an impact on the quality of life of families. After a simple FS, a child's
risk of developing epilepsy is 1.5 %. However, if the child was under 12 months of
age when he had his first seizure, the risk rises to 2.5 %. Understanding the risk factors
associated with FS could help parents take the necessary precautions during the seizure
episode and help doctors to take appropriate treatment by formulating guidelines for
the supplementation of TEs as part of the FS management for the prevention of
recurrence and/or its associated complications. According to our knowledge, this study
will be the first one that focuses on iron profile parameters and selected minerals (Zn
& Mg) among children with FS in Gaza City.
5
6
Chapter 2
Literature Review
2.1 Seizures in Childhood
Seizures or convulsions are simply defined as a paroxysmal, transient alteration
in the behavior and/or motor activity that caused by irregular brain electrical activity.
Convulsions are the commonest neurological disorder in pediatric. Occurs in about ten
percent of children. Most childhood seizures are caused via somatic diseases that
originate outside the brain, such as elevated body temperature, syncope, hypoxia,
infection, head injury, toxins or cardiac arrhythmias. Other as gastroesophageal reflux,
and, breath-holding spells may lead to events that trigger seizures (Sangani, Shah,
Murlikrishna, Parikh, & Patel, 2014).
Depending on how they start, seizure events are generally classified into two
types. Generalized seizures are those which start mainly from the whole brain at once.
In contrast, partial seizures (also called " focal" or " local") start from one part of the
brain. For several reasons, this distinction between generalized and partial seizures is
important. It first affects the observations to be made during a seizure; secondly,
medical work; and thirdly, the treatment of a child with seizures (Kutscher, 2006).
In the context of epileptic seizure and epilepsy, the International League
Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE) have come
to a consensus definition. An epileptic seizure is “a transient occurrence of signs and/or
symptoms due to abnormal excessive or synchronous neuronal activity in the brain”
(Fisher et al., 2005).
Epilepsy is “a disorder of the brain characterized by an enduring predisposition
to generate seizures and by the neurobiological, cognitive, psychologic, and social
consequences of this condition”. The clinical diagnosis of epilepsy needs at minimum
one unprovoked epileptic seizure, either with a second or with sufficient
electroencephalogram and clinical data to show a persistent susceptibility to recurrence
(Kliegman et al., 2016).
7
Epilepsy is considered epidemiologically and commonly clinically when two
or more unprovoked seizures occur in a time period longer than 24 hours. About 4-10
percent of children encounter at least one (febrile or afebrile) seizure during their first
16 years of life. The cumulative incidence of epilepsy throughout the lifetime is 3 %,
and more than half of cases begin in infancy. Annually, the prevalence is between 0.5
and 1.0 %. Consequently, the occurrence of a single or febrile seizure doesn’t
necessarily involve in the diagnosis of epilepsy (Kliegman et al., 2016).
Seizures are more likely to arise in infants and children than adults. This seems
to reflect greater neuronal excitability at certain ages as there is not always a balance
between both the excitatory glutamate system and the inhibitory GABA system. This
also leads to the tendency to show symptomatic seizures related to elevated
temperature, virus infection, minor asphyxia, medication, bacterial toxins and
biochemical disorders such as hypo- or hypernatremia and hypocalcemia (S. M.
Kumar & Sasikumar, 2015).
2.2 Febrile Seizures
2.2.1 Definition
Febrile seizures are the commonest form of seizures during childhood, have an
impact to at least one in ten children. FS is associated with an elevated body
temperature higher than 38oC, and not linked with any definite causative diseases,
such as metabolic abnormality or infection in the CNS. Most FS cases are benign and
self-limiting, and generally, treatment is not recommended (Chung, 2014; Khair &
Elmagrabi, 2015).
At the present time, there are three definitions used to describe FS which will
be listed below chronologically. In 1980 the National Institutes of Health (NIH)
defined FS as “an abnormal, sudden, excessive electrical discharge of neurons (gray
matter) that propagates down the neuronal processes (white matter) to affect an end
organ in a clinically measurable fashion, occurring in infancy or childhood, usually
between 3 months and 5 years of age, and is associated with fever but lacks evidence
of intracranial infection or defined cause” (American Academy of Pediatrics, 1980).
8
The ILAE in 1993, issued a modified definition that had a similar concept
however, it expanded the inclusion age group. It defined the FS as “an epileptic seizure
occurring in childhood after the age of 1 month, associated with a febrile illness not
caused by an infection of the CNS, without previous neonatal seizures or a previous
unprovoked seizure, and not meeting criteria for other acute symptomatic seizures”
(Epilepsy, 1993).
The American Academy of Pediatrics (AAP) recently launched in 2008 a
standard FS definition as “a seizure occurring in febrile children aged between six to
sixty months who do not have an intracranial infection, metabolic disturbance, or
history of afebrile seizures” (Dougherty et al., 2008). This definition was applied in
our study.
2.2.2 Types of Febrile Seizures
Febrile seizures are classified into two classes: simple or complex. FS is a
simple type if it occurs in short-term (lasting for a maximum of Fifteen minutes)
generalized tonic clonic activity (without a focal component) occurring in 24 hours or
in the same febrile disease without recurrence and resolving spontaneously. Most
patients suffering from this condition have a postictal state which is very short and
returns to normal behavior and consciousness within minutes of a seizure. Conversely,
it is a complex type if it occurs in prolonged (lasting for more than 15 minutes), partial
onset or focal features, multiple (occurrence of more than one seizure during the same
febrile illness over a 24-hour period). Prolonged FS is associated with developmental
delay and younger age. Febrile status epilepticus is an FS that lasts for more than 30
min which is a subgroup of complex FS (Kliegman et al., 2016). Simple and complex
FS characteristics are reviewed in Table 2.1 (Fetveit, 2008).
2.2.3 Epidemiology
Febrile seizures most commonly occur in children aged between 6 to 60 months
with peak incidence at 18 months of age and is low before 6 months or after 3 years of
age. Most FSs are simple with approximately 20–30 percent being complex (Chung,
2014; Seinfeld & Pellock, 2013).
9
Table 2.1: Simple and complex febrile seizures (Fetveit, 2008).
In the United States (US) and Western Europe, FSs affecting 2-5% of
children by their fifth birthday. The incidence elsewhere in the world varies between
8.8% for Japan, 14% in Guam, 5% and 10% for India, 0.5-1.5% for China, and 0.35%
for Hong Kong. The highest prevalence is 34.0% in Australia (Byeon, Kim, & Eun,
2018; Millichap & Gordon Millichap, 2015).
2.2.4 Mortality rate
The risk of mortality is extremely low in children with simple FS. However,
the mortality rate is increased to two-fold during the first two years if the seizures
occurred in the first year of life or were elicited by a temperature of < 39°C and if the
seizures were complex (Millichap & Gordon Millichap, 2015).
In children with FS, the incidence of epilepsy is slightly greater than in the
general population (2% versus 1%). Risk factors for the development of epilepsy later
10
in life include complex FS, developmental delay and the epileptic or neurological
abnormality family history. Patients with two risk factors are able to develop afebrile
seizures up to 10% (Millichap & Gordon Millichap, 2015).
2.2.5 Risk factors
Generally, half of the cases with FS are without identified risk factors.
2.2.5.1 Fever
Usually, FS occur during the raising phase of the temperature curve early in an
infectious illness. At this point, rectal temperatures may override thirty-nine degrees
Celsius, and about one-fourth of seizures occur at a temperature over forty-degree
Celsius. Temperature itself doesn't decrease the seizure threshold despite the implicit
relationship between fever and seizure activation. The incidence of FS doesn't increase
in proportion to temperature elevation and these episodes are infrequent in the later
stages of persistent illness. Moreover, children aged between sixteen and eighteen
months who suffer from fever greater than 40oC have a seven-fold reduction in seizure
recurrence compared with children with a fever below 40oC (El-Radhi, Withana, &
Banajeh, 1986). An increased risk of seizure recurrence was associated with a short
period of fever before the FS was initially present (Wyllie, Cascino, Gidal, &
Goodkin, 2006).
Febrile seizures are typically linked with common infections of the childhood,
most often the upper respiratory tract (URT), the gastrointestinal tract (GIT), and the
middle ear, which are viral. Rare concomitants of FSs include bacteremia, pneumonia,
sepsis and meningitis. However, none of the common infectious diseases in childhood,
viral or bacterial, seem to be able to activate FSs (Wyllie et al., 2006).
Additionally, seizures associated with immunization also occur with fever,
commonly within two days of injection. Approximately one quarter of cases are
linked to immunization by diphtheria-pertussis-tetanus (DPT) vaccine, and one-
fourth follows measles vaccine (Wyllie et al., 2006).
11
2.2.5.2 Metabolic abnormalities and deficiencies
Several studies showed a statistical association between IDA and FS (Daoud
et al., 2002; Hartfield et al., 2009; Kumari et al., 2012), while other studies haven't
found a significant association (Amirsalari et al., 2010; Bidabadi & Mashouf, 2009;
Derakhshanfar, Abaskhanian, Alimohammadi, & ModanlooKordi, 2012; Kobrinsky,
Yager, Cheang, Yatscoff, & Tenenbein, 1995). Numerous case-control studies found
lower levels of serum Zn in FSs children than those who had only fever (Amiri et al.,
2010; Ganesh & Janakiraman, 2008; Mahyar, Pahlavan, & Varasteh-Nejad, 2008).
Furthermore, several studies show a significant relationship between low Mg levels
with FS (Bharathi & Chiranjeevi, 2016; Talebian, Vakili, Talar, Kazemi, & Mousavi,
2009). Other studies showed that FS, regardless of the severity of original infection,
has been associated with respiratory alkalosis (Schuchmann et al., 2011). Large
population studies are required to decide whether such relationships can be predictive
or preventive factors.
2.2.5.3 Genetics
Genetic and environmental causes are evident in multiple family members
encounter an FS. There is inconstant pattern of inheritance with no single mechanism.
The most identified risk factor for the development of FS is probably the positive
family history (first-degree family members), as the number of family members with
this history increase, the risk increases (Fetveit, 2008).
However, the genetic part of FS is complicated, and the risk changes
significantly among families with the history for similar conditions. Estimated risk of
developing FS is the positive family history in about 25-40% of children with FS and
9-22% of FS child siblings. In this regard, identical twins are reported to show more
concordance rate than non-identical twins (Fetveit, 2008).
Specific genetic loci have been identified on several chromosomes to FS, such
as 2q, 5q, 5, 8q, 19p, and 19q, with the strongest link to chromosome 2q and in
particular to the sodium channel receptor genes, in specific, a mutation in the alpha (α)
subunit of the first sodium neuronal channel gene (Fetveit, 2008).
To date, no clear evidence has been found of specific genetic loci and
studies in this area are sophisticated because FS is most likely multifactorial.
12
2.2.5.4 Vaccinations
Vaccinations was recommended by the AAP for children at risk of disease that
are important for their health and have demonstrated efficacy and safety (Kroger,
Atkinson, Marcuse, & Pickering, 2006). In 2002, the World Health Organization
(WHO) published and recommends immunization safety for children. In general, post-
vaccination FS was not found to differ from FS from other causes (Cendes & Sankar,
2011).
Historically, vaccine-induced FS were thought to cause severe FS,
encephalopathy and recurrent seizures in a group of children. They are known to have
a genetic mutation in the sodium channel known as Dravet syndrome that causes these
symptoms. Usually, FS is the first manifestation of Dravet syndrome, but the first
seizure may result from any febrile disease in a genetically susceptible individual.
Vaccinations can lead to the onset of seizures in 1/3 of patients with Dravet syndrome
(Cendes & Sankar, 2011).
Febrile syndrome will not cause a child's epileptic encephalopathy without a
genetic susceptibility mutation. The AAP and the WHO even in children with genetic
mutations, does not recommend that the immunization schedule is stopped or changed
after an FS (Cendes & Sankar, 2011).
The public's fear of vaccine-induced FS has resulted in several studies.
Children under age of two have an increased risk of FS following the immunization
with first dose of measles containing vaccines when administered with varicella
vaccine. The risk of FS was not increased for vaccine-containing measles in children
over four years, irrespective of whether they received varicella at the same time (Klein
et al., 2012). Whole-cell diphtheria/tetanus/pertussis and measles-containing vaccines
that have been used previously seem to be associated with FS. Currently, less
reactogenic diphtheria, tetanus, and acellular pertussis vaccines are used and do not
increase the risk of FS. There is no proof that children shouldn’t be immunized
(Cendes & Sankar, 2011).
2.3 Minerals and Trace Elements
Minerals are inorganic substances that the human body requires in small
amounts for various functions. These include bone and teeth formation; as components
13
of enzyme systems and for the normal function of the nerves; as essential components
of body fluids and tissues. By concentration they can be sub-classified (trace or major)
in body fluids and tissues. Elements are categorized as major (when it’s concentrations
in fluids above 10 mg/L; and above 100 Fg/g in tissues) for example, Mg, calcium,
phosphorus, sodium, potassium, and chloride. And as a TE (body content 0.01 to 100
Fg/g; 10 to 104 Fg/L), for example, Fe, Zn, iodine, selenium, copper (Cu), and fluoride
according to the Clinical and Laboratory Standards Institute (CLSI) (British Nutrition
Foundation, 2009; Ramos, 2012).
Many minerals as (Cu, calcium, Mg, manganese, Fe, Zn, molybdenum and
cobalt) are necessary for the optimal functioning of the CNS. In brain function, they
play an essential role as second messengers, catalysts and, gene expression regulators.
TE are essential cofactors for functional expressions of many proteins to activate and
stabilize enzymes such as superoxide dismutase (SOD), metalloproteases, protein
kinases and transcriptional factors with zinc finger proteins. Metals clearly need to be
supplied to the CNS at an optimum quantities, since both deficiency and excess can
lead to aberrant CNS function (Zheng, Aschner, & Ghersi-Egea, 2003).
In FS, a number of elements are thought to play a role by their co-enzyme
activity or their ability to influence ion channels and receptors. Studies have
demonstrated that in FS, Fe, Zn, selenium, Cu, and Mg plays an important role
(Selvaraju, 2018).
2.3.1 Iron
2.3.1.1 Introduction
Iron is vital to all living organisms, as it has significant functions in the human
body. In the form of Hb, it serves as an oxygen carrier from the lungs to the tissues,
in the form of myoglobin, it facilitates the use of oxygen in muscle tissue, in
cytochromes, it acts as a transport medium for electrons, and as an integral part of
important enzyme systems in different tissues (Conrad & Umbreit, 2000).
Total body iron averages about 3.8 g which is equal to 50 mg/kg body weight
for a 75 kg adult male, and 2.3 g equal to 42 mg/kg body weight for a 55 kg adult
female (Centers for Disease Control and Prevention, 1998).
14
Iron is classified according to the biological role of iron-containing compound
into functional iron and transport or storage iron. The majority of iron in proteins is
functional that has an important role in utilization and transport of oxygen to produce
cellular energy including Hb, myoglobin, heme enzymes (cytochromes, catalases,
peroxidases), and iron-sulfur proteins, whereas 30% are storage or for transporter of
iron (Centers for Disease Control and Prevention, 1998).
The iron storage compounds are ferritin and hemosiderin, they are involved in
the maintenance of iron homeostasis and contain almost 20% of body iron found
primarily in hepatocyte, reticuloendothelial cells, and erythroid precursors of the bone
marrow. Transferrin and Transferrin receptor are two other proteins involved in the
delivery, transport, and regulation of iron absorption in the different tissues (Centers
for Disease Control and Prevention, 1998).
Disorders of iron metabolism is divided into two main categories: iron
overload and iron deficiency (ID) disorders (Conrad & Umbreit, 2000).
2.3.1.2 Iron Overload
In contrast to other minerals in human body, iron levels are controlled only by
absorption process. The iron excretion mechanism is an unregulated process. If the
physiological pathway for excreting the excess iron is absent, this means that the
patient who has an increased iron is at risk. When the maximum iron storage capacity
of the body reached, iron begins to build up in different parts of the body and leads to
iron overload (Ems & Huecker, 2019).
Iron overload typically occurs in one of two particular forms. In cases of
hereditary hemochromatosis where erythropoiesis is normal but the iron content of
plasma exceeds the iron- binding capacity of transferrin, iron is deposited in heart,
hepatocyte, and a subgroup of endocrine tissues. In contrast, when iron overload
results from increased catabolism of erythrocyte (e.g. transfusional iron overload), iron
first accumulates in reticuloendothelial macrophages and then moves into
parenchymal cells. Whether the iron overload is primary or secondary, it needs to be
treated in both cases. If not, parenchymal deposition damages the tissue, causing
fibrosis and ultimately organ damage will occur (Andrews, 1999).
15
2.3.1.3 Iron Deficiency
Iron deficiency is the most prevalent micronutrient deficiency worldwide.
According to the WHO, ID affecting a quarter of the world's population, nearly two
billion people. Because of the high demands for iron during infancy and pregnancy,
ID is most commonly considered as a global public health issue in developing and
industrialized countries in young children and women. ID results from a long-term
negative iron balance; it causes anemia in its more severe stages (Benoist, McLean,
Egll, & Cogswell, 2008; Petry, 2014).
2.3.1.3.1 Definition
Iron deficiency is a situation in which enough amount of iron is not existing in
the human body to keep its physiological functions normal. ID is usually defined as a
reduction in total iron of the body or, in some circumstances, serum ferritin (SF) levels
for children aged under five years, less than 12 mg/L and less than 15 mg/L for children
five years of age or older. Although SF levels are valuable in the definition of ID,
however, it can only be taken into account if no other conditions affect SF levels (i.e.
inflammation or liver disease). SF concentrations <30 mg/L for children aged under
five years with concurrent infection are reflective of depleted iron stores (Roganović
& Starinac, 2018).
2.3.1.3.2 Stages of Iron Deficiency Development
Since most iron in the body is directed toward the synthesis of Hb, erythrocyte
production is one of the first ID casualties to be shown clinically in normal laboratory
evaluations. It is, however, a late stage of iron depletion (Orkin & Nathan, 2009).
As stated by Nathan And Oski’s Hematology of Infancy and Childhood, "Iron
deficiency progresses through three discernible phases:
1. Prelatent iron deficiency occurs when tissue stores are depleted, without a
change in hematocrit or serum iron levels. This stage of iron deficiency may
be detected by low SF measurements.
2. Latent iron deficiency occurs when reticuloendothelial macrophage iron stores
are depleted. The serum iron level drops and TIBC increases without a change
in hematocrit. This stage may be detected by a routine check of fasting, early
16
morning transferrin saturation. Erythropoiesis begins to be limited by a lack of
available iron, and sTfR levels increase. The reticulocyte hemoglobin content
decreases because newly produced erythrocytes are iron deficient. The bulk of
the erythrocyte population appears normal. For this reason, sole reliance on
indicators derived from the entire erythrocyte population frequently fails to
detect this stage of iron deficiency.
3. Frank iron deficiency anemia is associated with erythrocyte microcytosis and
hypochromia. It is detected when iron deficiency has persisted long enough
that a large proportion of the circulating erythrocytes were produced after iron
became limiting” (Orkin & Nathan, 2009).
2.3.1.3.3 Iron deficiency Anemia
Anemia is defined according to WHO as “Hb concentration that is more than
two standard deviations below the average reference value for age- and sex-matched
healthy population”. WHO Hb thresholds used to define anemia in various age groups
are listed in Table 2.2 (Benoist et al., 2008):
Table 2.2: WHO hemoglobin thresholds to define anemia in different age groups.
The development of IDA begins when iron in the body is too low for normal
production of red blood cells (RBC). In most cases; It is defined as the presence of SF
levels <12 mg/L and Hb levels <11 g/dL in young children (up to five years) in the
absence of any additional conditions that might affect such results (McDonagh,
Blazina, Dana, Cantor, & Bougatsos, 2015; Roganović & Starinac, 2018).
17
Often in the same context, the terms "ID" and "IDA" are used. ID without
anemia, however, is threefold more prevalent than IDA. The overall body iron
decreases gradually as iron requirements fall below the iron intake. Initially, Hb levels
are normal, which reflect the phase in which ID is present without anemia. The level
of SF and transferrin saturation is reduced at this point (Benoist et al., 2008; Roganović
& Starinac, 2018).
As total body iron declines and iron stores depleted, the concentrations of Hb
are lower than normal. ID is therefore defined as reduced body iron, but the level of
Hb remains above the cut-off value for anemia. The deterioration of this situation leads
to iron-deficient erythropoiesis and ultimately progress to IDA (Benoist et al., 2008;
Roganović & Starinac, 2018).
The IDA is generally referred to reduction in the oxygen carrying capacity of
the blood and is considered as the main reason for microcytic hypochromic anemia.
This remarkably reduces the Hb per deciliter of blood and hematocrit, or the number
of erythrocytes (Burke, Leon, & Suchdev, 2014).
Red blood cell indices abnormalities in Complete Blood Count (CBC) usually
occur before the progression of lowered Hb levels. Iron shortage usually grows slowly
over time, and may not be symptomatic, or clinically clear. Once iron stores are
completely exhausted, the convenience of iron in the tissues decreases and
symptomatic anemia results (Burke et al., 2014).
2.3.1.3.4 Prevalence of Anemia
Anemia Worldwide
The most recent estimates for anemia in 2016 according to WHO indicate that
“anemia affects 33% of women of reproductive age globally (about 613 million
women between 15 and 49 years of age). In Africa and Asia, the prevalence is the
highest at over 35%. Severe anemia, which is associated with substantially worse
mortality and cognitive and functional outcomes, affects 0.8-1.5% of these same
population groups” (Stevens et al., 2013; World Health Organization, 2017).
In a recent WHO report presenting 2011 data on the prevalence of anemia, “the
WHO African Region, South-East Asia Region and Eastern Mediterranean Region had
the lowest mean Hb concentrations, as well as the highest prevalence of anemia among
18
women and children. The WHO African Region had the countries with the lowest Hb
levels and highest prevalence of anemia. Children under 5 years of age in the WHO
African Region represented the highest proportion of individuals affected with anemia
(62.3%), while the greatest number of children and women with anemia resided in the
WHO South-East Asia Region, including 190 million non-pregnant women, 11.5
million pregnant women, and 96.7 million children aged under 5 years” (World Health
Organization, 2017).
Anemia in Palestine
The prevalence of anemia among preschoolers in the Gaza Strip had reached
(59.7%) (El Kishawi, Soo, Abed, & Muda, 2015), and being ≥40.0%, is considered
severe according to anemia classification and should be recognized as a major problem
of public health (World Health Organization, 2008b). It had been deteriorating since
2002 and thus anemia is considered a severe public health problem in the Palestinian's
community. Not surprisingly, the Gaza Strip, being subjected to on-going, blockade
has one of the highest rates of anemia in the Middle East region, similar to the figure
in Iraq, 56%. The lowest prevalence was in Israel (11.8%) (Radi, El Sayed, Nofal, &
Abdeen, 2013).
2.3.1.3.5 Clinical Features and Manifestations
Most iron-deficient children are asymptomatic and are identified at 12 months
of age by recommended laboratory screening or earlier if they are at high risk. The
most important clinical manifestation of ID is color paleness. Nevertheless, until the
Hb levels drop to 7-8 g/dL, it will not be visible. It is most easily noted as pallor of the
palms, palmar creases, nail beds, or conjunctiva. The pallor is frequently not noticed
by parents due to the typical slow decline of Hb over time. A friend or relative who
came for visiting is often the first person to notice. Compensatory mechanisms,
including increased levels of 2,3-diphosphoglycerate and oxygen dissociation curve
shift, can be so effective in mild to moderate ID (i.e., 6-10 g/dL of Hb levels) that few
anemia symptoms are noticeable regardless the mild irritability. When the level of Hb
drops to below 5 g/dL, it often causes irritability, anorexia, lethargy, and systolic flow
19
murmurs are frequently heard. Tachycardia and heart failure can occur as Hb continues
to fall (Kliegman et al., 2016).
Iron deficiency has non-hematological systemic consequences. Both ID and
IDA are associated with neurocognitive impairment in childhood. Furthermore, with
cognitive defects which are probably irreversible. Although ID with or without anemia
causing these defects is supported, it has not confirmed unambiguously. Several
studies indicate an increased risk of strokes, seizures, breath holding spells in children,
and aggravation of restless leg syndrome in adults. Due to ID and IDA frequency and
potential negative neurodevelopment outcomes, it is an important aim to reduce the
incidence of ID (Kliegman et al., 2016).
Moreover, there are other non-hematological consequences of ID include pica,
and pagophagia. The pica (the desire to ingest nonnutritive substances) can result in
the ingestion of lead-containing substances and result in concomitant plumbism
(Kliegman et al., 2016).
The symptoms associated with IDA depend on the rapid progression of the
anemia. In cases of chronic, slow blood loss, the body adjusts to increasing anemia
and patients can sometimes tolerate extremely low Hb concentrations, such as <7.0
g/dL, with notable symptoms. The majority of patients complain of increasing lethargy
and dyspnea. More unusual symptoms include headaches, tinnitus and taste
disturbance (Provan, 2018).
Chronic ID may be seen in examining skin, nail and other epithelial changes.
About one third of patients suffer atrophy of the skin and nail changes such as
koilonychias, "spoon-shaped nails- may result in brittle, flattened nails". Patients may
also complain of angular stomatitis, "painful cracks appear at the angle of the mouth",
sometimes accompanied by glossitis. Esophageal and pharyngeal webs can be a feature
of IDA, however, it's uncommon. These changes are believed to be due to a reduction
in the iron-containing enzymes in the epithelium and GIT (Provan, 2018).
2.3.1.3.6 Role of Iron deficiency in FSs
Some clinical events may relate to iron's role in certain enzyme responses.
Monoamine oxidase, an iron-dependent enzyme, has a vital role in CNS
neurochemical reactions. Catalase and peroxidase comprise of iron. Thus, ID causes a
20
reduction in their activities, but their biologic essentiality is not well established. ID
alters the electron transport and the synthesis neurotransmitter in the brain thereby
affecting the normal function of the neural tissue (Pediatrics, 2002).
It is obvious that ID during gestation and lactation results in abnormalities in
brain development in animal models that are irreversible. All this suggests that it is
imperative to prevent ID in woman of childbearing age, including during gestation and
also throughout infancy and childhood. Developmental problems, risk of pediatric
stroke, the occurrence of FS and breath-holding spells are perhaps the tip of iceberg of
the neurological consequences of ID. The neurological sequelae of the ID are
completely preventable and possibly reversible with appropriate recognition, treatment
or even better prevention of ID are occur (S. M. Kumar & Sasikumar, 2015).
Iron is an important element for metabolism in the brain. It also helps in
neurotransmitter metabolism. Deficiency of iron acts as an important factor in
development of FS. ID is one of the most common nutritional problem worldwide.
Kumari et al. conducted a case-control study involving large sample size. They
reported that "deficiency of iron was seen in majority of the patients". They concluded
that, "deficiency of iron is one of the important factors in development of FS" (Kumari
et al., 2012). According to a study conducted in Kenya, deficiency of iron is not a risk
factor for other acute convulsions. But it acts as important factor in FS (Johnston, 2012;
Kirtichandra, 2015).
2.3.1.4 Diagnosis of Iron Deficiency
As ID progression, a series of hematological and biochemical events occur
(Tables 2.3 and 2.4). First, tissue iron stores are diminishing which is demonstrated by
a decreased SF. Next, levels of serum iron decreases, serum iron-binding capacity
(serum transferrin) increases, and the transferrin saturation falls below normal. As iron
stores decline, iron becomes unavailable to complex with protoporphyrin to form
heme, causing free erythrocyte protoporphyrins to accumulate, and impaired the
synthesis of Hb. ID progresses to IDA at this point. With less Hb available in every
cell, the RBC begin to be smaller and vary in size. This variation measured by
21
Table 2.3: Indicators of Iron- Deficiency Anemia. Modified from (Kliegman et al., 2016).
22
Table 2.4: Laboratory Studies Differentiating the Most Common Microcytic Anemias. Modified from (Kliegman et al., 2016).
23
increasing the red cell distribution width. This is followed by a reduction in the mean
corpuscular volume and mean corpuscular hemoglobin (Kliegman et al., 2016).
2.3.1.5 Laboratory Evaluation of Iron Status
2.3.1.5.1 Assessment of Iron Stores
Body-iron supply and stores can be directly and indirectly evaluated, but no
single indicator or combination of indicators is suitable for evaluating the iron status
in all clinical conditions. Direct methods are painfully invasive or costly; conversely,
the indirect methods are noninvasive (Hoffman, 2008).
2.3.1.5.1.1 Direct Assessment Methods
The direct measurement of iron status in the body results in the quantitative,
specific and sensitive determination of iron stores in the body or tissue. Quantitative
phlebotomy provides a direct measure of total mobilizable storage iron "calculated as
the amount of Hb iron removed, with corrections for the Hb deficit and estimated
gastrointestinal iron absorption during the course of phlebotomy". Most anemic
disorders cannot be evaluated by quantitative phlebotomy, but sometimes is of useful
in diagnostics of some types of iron overload (for example, patients not subject to liver
biopsy with hereditary hemochromatosis) (Brittenham, Sheth, Allen, & Farrell, 2001;
Hoffman, 2008).
Aspiration and biopsy of the bone marrow could provide information
concerning; (Hoffman, 2008).
i) Macrophages storage of iron by using Perls' Prussian-blue stain; for semi
quantitative grading of marrow hemosiderin or, if necessary, by chemical
non-heme iron measurement;
ii) Iron supply to erythroid precursors through the determination of marrow
sideroblasts proportions and morphology (i.e., normoblasts with visible
iron aggregates in the cytoplasm); and
iii) General morphological characteristics of hematopoiesis.
There are several disadvantages of this method that limit its use including, its
invasiveness, with their accompanying discomfort, lack of acceptability to patients,
and, in the case of liver biopsy, risk. It is therefore not used to detect ID in large
24
populations. It is primarily used to evaluate the iron status in hospitalized patients
(Hoffman, 2008).
2.3.1.5.1.2 Indirect Assessment Methods
Indirect body-iron measurements have the advantages of ease and
convenience, but all are subject to extraneous influences and lack of specificity,
sensitivity, or both (Hoffman, 2008).
There are several laboratory tests for evaluating body iron status indirectly:
hematological and biochemical, the first based on characteristics of RBCs [i.e
Hemoglobin concentration (Hb), hematocrit (Hct), mean corpuscular volume (MCV),
mean corpuscular hemoglobin (MCH), and red blood cell distribution width (RDW)],
the biochemical tests include: concentration of SF, transferrin saturation (Tsat), and
free erythrocyte protoporphyrin (FEP) concentration, these tests detect the earlier
changes in iron biochemical tests (Centers for Disease Control and Prevention, 1998).
2.3.1.5.1.2.1 Hematological Findings
Hematological testing is generally much more easily available and have a low-
priced than biochemical testing. It relies on red blood cells features (that is, Hb, Hct,
MCV and RDW) (Centers for Disease Control and Prevention, 1998).
Hemoglobin Concentration and Hematocrit
Hemoglobin measurement, the concentration of oxygen-carrying protein, is a
more sensitive and direct anemia test than Hct measurement, the % of the whole blood
occupied by RBCs (Wu, Lesperance, & Bernstein, 2016).
In general, Anemia in a healthy reference population is defined as Hb levels
below the fifth percentile: 11.0 g/dL (110 g/L) for children aged between 6 months to
2 years. Both measurements are cost-effective, readily available tests for anemia and
are most often used in ID screening. Hb and Hct, However, are late markers for ID,
are not specific to IDA and are less predictive as the IDA prevalence decrease (Wu et
al., 2016).
25
Mean cell volume and Mean cell hemoglobin
Mean cell volume, is a measure of the average volume of red blood cells in
femtoliters (fL). MCV is useful for categorizing anemia as microcytic, normocytic,
and macrocytic. It can be directly measured by automated hematology analyzer, or it
can be calculated from Hct and the RBC as follows (Greer & Wintrobe, 2014; Wu et
al., 2016):
MCV (fl) = (Hct [in L/L]/RBC [in x1012/L]) x 1000
Mean cell hemoglobin (MCH), the average Hb content per red cell, expressed
in picograms (pg). Thus, the MCH is a reflection of Hb mass. It can be calculated using
the following formula either manually or by automated methods (Greer & Wintrobe,
2014; Wu et al., 2016):
MCH = Hb (g/L)/RBC (1012/L)
Iron deficiency Anemia is a microcytic (small average RBC size), and
hypochromic (there is a reduced amount of hemoglobin per erythrocytes: reduced
MCH), however, hypochromic, microcytic RBCs are also encountered in other
anemias like thalassemia and chronic diseases (Greer & Wintrobe, 2014).
Red Distribution Width
The RDW is a red cell measurement that quantitatively reflects the
heterogeneity of the cell volume in a sample. In early classification of anemia, the
RDW was proposed to useful because it becomes abnormal in nutritional deficiency
anemias earlier than other red cell parameters, especially in IDA cases. RDW is
particularly useful in characterizing microcytic anemia, allowing for discrimination
between uncomplicated IDA (high RDW, normal to low MCV) and uncomplicated
heterozygous thalassemia (normal RDW, low MCV) (Greer & Wintrobe, 2014).
2.3.1.5.1.2.2 Biochemical Markers
Biochemical assessment of iron status to identify ID includes measurement of
serum iron (SI), serum ferritin (SF), transferrin saturation (Tfsat), total iron binding
capacity (TIBC), and more recently soluble transferrin receptor (sTfR) (Centers for
26
Disease Control and Prevention, 1998; Karlsson, Sjöö, Kedinge Cyrus, & Bäckström,
2010).
Serum Iron
The concentration of SI is a measurement of the total iron in the serum and can
be assessed by automated laboratory chemistry panels. SI may not accurately reflect
the iron store, as the results may be influenced by several factors. For example, SI level
increase following every meal and decreases during inflammations and infections.
Furthermore, SI influenced by diurnal variation means that it can elevate in the
morning and reduce at night. Among individuals, the diurnal variation in the
concentration of SI is greater than that of Hb and Hct values (Centers for Disease
Control and Prevention, 1998).
Serum Transferrin and Total Iron Binding Iron Capacity
Serum transferrin (TRF) can be measured directly and indirectly. TRF can be
estimated directly using immunological methods. On the other hand, it can be
indirectly measured by the TIBC, which is the amount of added iron that can be bonded
to plasma transferrin molecules (Gambino et al., 1997). TIBC reflects the availability
of iron-binding sites on transferrin and a measure of the iron-binding capacity within
the serum. TIBC and SI have an inverse relationship. Therefore, when the SI levels
(and stored iron) are low, TIBC values increases, and when it's high, TIBC values
decreases (Centers for Disease Control and Prevention, 1998).
Results of this test can be affected by factors other than iron. For instance,
Chronic infection, inflammation, nephrotic syndrome, liver disease, malignancies, and
malnutrition, can lead to lowering the readings of TIBC, and using contraceptive pills
and pregnancy can increase the results. However, the diurnal variation is less than that
for concentration of SI. The sensitivity to ID for TIBC is lower than the concentration
of SF due to changes in TIBC occur following depletion of iron stores. The TIBC
should not be muddled with the UIBC, or "unsaturated iron binding capacity ". The
UIBC is calculated by subtracting the SI from the TIBC (Centers for Disease Control
and Prevention, 1998).
27
Transferrin Saturation
Transferrin saturation (Tfsat) represents the percentage of occupied iron-
binding sites and reflects iron transport instead of storage (For example, low Tfsat
implies a high percentage of unoccupied iron-binding sites). Neonates have the highest
saturation, declines by age of four months and rises in childhood and adolescence until
adulthood (Centers for Disease Control and Prevention, 1998; Wu et al., 2016).
Serum iron concentration and TIBC are two laboratory measurements using
the following formula to calculate the percentage of Tfsat (Centers for Disease Control
and Prevention, 1998):
Transferrin saturation (%) = [SI concentration (µg/dL)/TIBC (µg/dL)] × 100
Low Tfsat means low levels of SI compared to the number of iron binding sites
available, indicating low iron stores. Tfsat declines prior to the development of anemia,
but not early enough to detect iron depletion. Tfsat is affected by similar factors that
affect levels of SI and TIBC and is less sensitive to changes in iron stores than is SF.
(Wu et al., 2016).
Serum Ferritin
Almost all the ferritin in the body is present intracellularly; a minor quantity
circulates in the plasma. In typical circumstances, SF concentration directly related to
the amount of iron stored in the body, so that 1Fg/L of SF is equivalent to about 10mg
of stored iron. SF is an essential reliable and sensitive parameter for evaluating iron
stores at all stages of ID, especially when combined with other iron status tests.
(Centers for Disease Control and Prevention, 1998).
In patients with anemia, a low value of SF is diagnostic for IDA. The test is
however costly and limited in clinical laboratories; it is therefore not commonly used
for screening. Furthermore, SF is an acute-phase protein that can become elevated
regardless of iron status in a number of acute or chronic inflammatory conditions, or
other diseases. Thus, by combining SF with a C- reactive protein (CRP) measurement
helps to detect these false-negative results for SF (Kliegman et al., 2016; World Health
Organization, 2007; Wu et al., 2016).
28
Soluble Transferrin Receptors
The transferrin receptor mediates cellular iron uptake through binding iron
carrier-protein transferrin (Tf). After the iron-Tf-TfR complex has been internalized,
iron liberate from its binding sites, and the Tf-TfR complex returns to the cell surface
to release apo-transferrin once more. For erythropoiesis, humans use 80% of their body
iron, and almost the same percentage of TfR in the body is found in erythroid
progenitor cells. The reticulocytes that enter the peripheral bloodstream carry a high
concentration of surface receptors; which released to the circulation as cells mature
(Koulaouzidis, Said, Cottier, & Saeed, 2009).
Serum TfR is derived largely from developing RBC. By modulating the
expression of TfR on the cell surface and by storing excess iron as ferritin, cells can
regulate their iron uptake. Levels of serum TfR, therefore, reflect the intensity of the
RBC formation or erythropoiesis and iron demand. As iron supplies decrease gradually
in tissues, TfR expression increases. ID causes high regulation of cell surface
expression of TfR that are reflected by an increased concentration of sTfR in
circulation (World Health Organization, 2014b).
Using of serum TfR levels in conjunction with the SF concentrations was also
recommended to increase both diagnostic sensitivity and specificity for diagnosing ID,
as a serum transferrin receptor-to-log ferritin ratio, which also called serum transferrin
receptor index (World Health Organization, 2014b).
2.3.2 Zinc
2.3.2.1 Introduction
Zinc is a critical TE and has many metabolic and signaling pathways in the
human body. It plays an important role in different physiological functions including
mitotic cell division, immune system activity, protein, and nucleic acid synthesis and
as a cofactor of enzymes or metalloproteins. Zn is essential for at least 80 different
enzymes of the CNS. Many of these enzymes, includes DNA and RNA polymerases,
DNA ligases, and histone deacetylases, which are clearly needed for normal DNA
replication and cell proliferation. Other Zn dependent enzymes that play important
roles in normal function of CNS include metalloproteinases and many dehydrogenases
in intermediary metabolism (V. Kumar et al., 2016).
29
Additionally, Zn plays an essential structural role in "a family of DNA-binding
transcription factors known as zinc-finger proteins (Zfp). Nuclear receptors, such as
those that mediate the transcriptional roles of vitamin D, retinoic acid, glucocorticoids,
estrogen, and thyroid hormone in the brain, are all Zfp". All of these receptors are
known to regulate key genes involved in cellular proliferation, brain development, and
neurogenesis (V. Kumar et al., 2016).
2.3.2.2 Zinc deficiency
There are two classes of reasons for Zn deficiency: (a) Nutritional deficiency
like food intake either with low Zn content or unavailable Zn forms and (b) Conditional
(secondary) reason which is connected to diseases and genetic disorders that diminish
the absorption ability of the intestines and/or an increase of Zn losing (Nriagu, 2007).
One of the most common risk factors for nutrition-related diseases is Zn
deficiency and is considered a leading contributor to the worldwide burden of anemia
(as a direct cause or by potentiating the function of iron in anemia). In developing
countries, individuals taking limited animal products and plants or cereal meals high
in inhibitors are at potential risk of Zn deficiency. According to the WHO, the Zn
deficiency is estimated to affect one-third worldwide population (around two billion
people). Approximately twenty percent of perinatal mortality around the world is
estimated to be attributable to Zn deficiency, a predisposing risk factor for pneumonia
and diarrhea, the two most common causes of death in children under five. Zn
deficiency is considered as a risk factor for numerous chronic diseases, accounting for
approximately 10 percent of diarrheal diseases, 16 percent of lower respiratory tract
infections and 18 percent of malaria attacks globally (Nriagu, 2007).
2.3.2.3 Role of Zinc in febrile seizures
In brain, Zn is present in large amounts in the hippocampus (~ 30Fg/g weight.
Zn regulates the activity of GAD, a major enzyme in GABA production in the CNS
(Figure 2.1). It also regulates the neurotransmitter affinity. It mediates calcium
inhibition on NMDA receptors thereby reducing excitatory neuronal discharge. In
hypozincemia, these receptors get stimulated which may produce epileptiform
discharges in children with fever. According to Ganesh et al, Zn levels in FSs children
30
were lesser than febrile children. This indicates that Zn deficiency can be an significant
factor in the pathogenesis of FS (Ganesh & Janakiraman, 2008).
Figure 2.1: The role of Zn & Mg in activation of glutamate decarboxylase enzyme
and production of GABA. (Jockers, 2019)
In CNS, Zn acts as a neurosecretory product or cofactor. It is highly
concentrated in the synaptic vesicles of a specific contingent of neurons called "Zinc
Containing neurons" which are a subset of glutamatergic neurons (Ehsanipour, Talebi-
Taher, Harandi, & Kani, 2009).
Zinc increases the storage capacity of glutamate or slows the release rate of
glutamate. Apart from this it also activates pyridoxal kinase, which in turn helps in the
pyrioxal phosphate synthesis from pyridoxal. Pyridoxal phosphate in turn activates
GAD which is involved in synthesis of GABA. Post synaptic receptors in interaction
with Zn facilitate GABA action. Hence hypozincemia leads to decrease in GABA level
which leads to development of seizures. According to Ehsanipour et al, Zn values will
be low in FS and during infection. Zn levels in patients with FS were low significantly
(Ehsanipour et al., 2009).
31
2.3.3 Magnesium
2.3.3.1 Introduction
Magnesium is the second most abundant intracellular cation and the fourth
most abundant cation in the body. 90% Mg in cells is bound to different ligands (e.g.,
nucleic acids, adenosine triphosphate, ATP, ADP, citrates, negatively charged
phospholipids, proteins, etc.), while 10% of Mg is in a free form. The normal
concentration of plasma Mg is 1.5-2.3 mg/dL with some variations between clinical
laboratories. Only 1% of the Mg in the body is extracellular (60% ionized, 15%
complex, 25% protein bound). In cells, Mg has structural and dynamic roles as, for
instance, stabilization of protein structure, phosphate groups in lipids of cellular
membranes, negatively charged phosphates of nucleic acids, and activation or
inhibition of many enzymes (Čepelak, Dodig, & Čulić, 2013; Kliegman et al., 2016).
In many body functions, Mg plays an important physiological role. Two
important Mg properties achieve this role: the ability to form chelates with important
intracellular anionic-ligands, particularly, ATP, and their ability to compete with
calcium for binding sites on proteins and membranes (Swaminathan, 2003). Mg is
actually important for the catalytic activity of more than 300 enzymes (e.g., creatine
kinase, ATP-ase, adenylate cyclase, phosphofructokinase, enolase, DNA polymerase,
5-phosphoribosyl pyrophosphate synthetase, etc.), particularly of those that catalyze
energy metabolism reactions. These reactions involve glycolysis, gluconeogenesis, ,
Krebs cycle, pentose phosphate pathway, urea cycle, respiratory chains, etc. also it
maintains nerve tissue and cell membranes electrical potential (Čepelak et al., 2013).
Magnesium's biological role is somewhat heterogeneous. In addition to the
above-mentioned structural and dynamic function, and because of its relatively small
atomic radius, Mg easily competes for specific protein binding sites with other divalent
cations (particularly calcium). It aids to maintain a low resting intracellular free
calcium ion concentration, which is substantial in many cellular functions, through its
ability to, compete with calcium for membrane binding sites and by stimulating
calcium sequestration through sarcoplasmic reticulum. As an endogenous calcium
antagonist, Mg is involved, for example, in blocking the NMDA receptor, inhibiting
the release of exciting neurotransmitters, blocking calcium channels and relaxing
vascular smooth muscle cells (Čepelak et al., 2013; Swaminathan, 2003).
32
Among other uses, Mg is essentially necessary for maintenance of normal
neurological function and neurotransmitter release, muscular contractions/relaxations,
regulation of vascular tonus and blood pressure, of cardiac rhythm, insulin signal
transmission, parathormone secretion and activity, modulation of immunological
functions, etc. (Čepelak et al., 2013).
2.3.3.2 Role of Magnesium in febrile seizures
Magnesium is a chemical gatekeeper, so that the entrance of calcium into the
nervous cell increases because of hypomagnesemia that ultimately leads to stimulation,
spasm and seizure. Glutamate is an essential excitatory brain neurotransmitter which
acts as an agonist to the NMDA receptor that bound to extracellular Mg producing a
voltage-dependent block, thus reducing synaptic transmission (Selvaraju, 2018).
Hypomagnesemia-related seizure mechanism is explained in (Figure 2.2).
Deficiency of Mg leads to release of the voltage-dependent gradient inhibition in the
NMDA receptor, resulting in massive neuronal network depolarization and bursting of
action. This leads to glutamate-mediated depolarization of the postsynaptic membrane
and improvement of the electrical activity of the epileptiform. Mg also works as an
antagonist of voltage - based calcium channels, thus hypomagnesemia causes calcium
ions to be released that causes nerve excitations (Selvaraju, 2018).
In the nervous system, Mg reduces the acetylcholine release at the
neuromuscular junction by antagonizing calcium ions at the presynaptic junction,
decreases nerves excitability, and works as an anticonvulsant, reverses vasospasm of
cerebrum. Low level of serum Mg was sometimes suggested to have important effects
on the CNS particularly in causing seizures. Changes in the plasma and intracellular
matrix concentrations of Mg are suggested to cause cell membranes functional
impairment which may lead to seizures. Recently, studies show that Mg deficiency may
play a major role in FS (Bharathi & Chiranjeevi, 2016).
33
Figure 2.2: Mechanism of seizure due to hypomagnesaemia. (Selvaraju, 2018)
2.4 Previous Studies
Mahyar et al., (2008) performed a case-control study about the association of
serum Zn level with FS at Qods Children Hospital, Qazvin (Iran) in 2006. By
comparing 52 children aged between nine months to five years with first episode of
FS with 52 healthy children in the same age group. They reported that "the mean serum
Zn levels in the case group were 62.84 ± 18.40 Fg/dl and in the control group was
85.70 ± 16.76 (P < 0.05). The difference was statistically significant indicating that Zn
deficiency predisposes to FS".
Ganesh & Janakiraman (2008) investigated the association of serum Zn in
children with FS in a case-control study comparing thirty-eight cases of FS and thirty-
eight aged matched controls (fever alone). The results showed that "the mean level of
serum Zn in cases was lower than controls (32.17 vs. 87.6 Fg/dL), respectively. This
difference was significant statistically (P < 0.001)". This study shows an inverse
relationship between serum Zn level and FS, consequently indicating that Zn
deprivation plays a significant role in FS pathogenesis.
Hartfield et al., (2009) studied the association between ID and FSs in a sample
of 361 children between 6 to 36 months of age admitted to the emergency department
34
in Stollery Children’s Hospital, Edmonton, Alberta, Canada from January 2001 to May
2006. The results showed that "a total of 9% of cases had ID and 6% had IDA,
compared to 5% and 4% of controls respectively. The conditional logistic regression
odds ratio for ID in patients with FS was 1.84 (95% CI, 1.02-3.31). They concluded
that, children with FS were almost twice as likely to be iron-deficient as those with
febrile illness alone".
Bidabadi & Mashouf (2009) in a Case–Control study about the association of
IDA and first febrile convulsion in a sample of 200 children. The value of TIBC was
lower significantly, and levels of SI, plasma ferritin, and RBC count were higher
significantly, among the cases than in the controls. The level of Hb in case group was
higher insignificantly than controls. Additionally, the levels of Hct, MCV, MCH, and
MCHC in children with FS were higher than control group but the difference failed to
reach a statistically significant value. Findings of this study indicated that "IDA was
less frequent in cases than in controls, and their difference was statistically
insignificant; however, there was no protective effect of ID against FS development
(Odd Ratio=1.175)".
Talebian et al., (2009) conducted a case-control study with sixty children in
each group hospitalized in Kashan Shahid Beheshti Hospital in 2006 in order to
determine the relationship between the levels of serum Zn & Mg in FS-children. The
mean levels of serum Zn & Mg in children with FS (116.28 mg/dl and 2.21 mg/dl,
respectively), were significantly low compared to control group (146.00 mg/dl and
2.39 mg/dl, for Zn and Mg respectively) (P = 0.003). They decided that the mean levels
of serum Zn and Mg were related to the occurrence of FS in children.
Amiri et al., (2010) studied the levels of serum selenium, Zn and Cu in thirty
children with FS and thirty healthy children. Zn value was found to be lower
significantly in cases compared to controls (66.13±18.97 Fg/dL vs. 107.87± 28.79
Fg/dl) (with p < 0.0001). This study showed that decreased level of serum Zn plays an
significant role in FSs.
Amirsalari et al., (2010) in a case-control study at Baqyiatallah Hospital,
studied the relationship between IDA and FSs in a sample of 132 children. The results
of the study showed that "low Hb level in 4 cases (3%) compared to 6 controls (6.8%),
35
low plasma ferritin in 35 cases (26.5%) compared to 26 controls (29.5%), and low
MCV in 5 cases (3.8%) compared to 6 controls (6.8%). In the case and control groups,
there was no significant difference in ferritin, Hb and MCV levels. Regarding to the
aforementioned results, there is no relationship between IDA and FSs".
Vaswani et al., (2010) in a case-control study, studied the role of ID as a risk
factor for first FS in a sample of fifty children. The mean SF level (ng/ml) was low
significantly in cases compared to controls (31.9 ± 31.0 & 53.9 ± 56.5 respectively,
with P = 0.003). ID could be a potential risk factor for children with FS.
Momen et al., (2010) in a case-control study at Abuzar Hospital evaluated iron
status in nine-month to five-years-old children with FSs in a sample of fifty children.
Between two groups, the difference in the levels of CBC parameters, SI and TIBC
were statistically not significant. But the difference in the level of MCV was
statistically significant with (P < 0.017). The ferritin level in the cases was lower
significantly compared to the controls (30.3 ±16.5 ng/ml, 84.2 ± 28.5 ng/ml,
respectively) (P < 0.000). The results of the study suggests a positive association
between ID and the first FS in children.
Derakhshanfar et al., (2012) in a case-control study done on 500 children for
each group to investigate the role of IDA in children with FS referred to Mofid hospital
in Tehran during 2009-2010. The Hb, Hct, MCV, MCH, MCHC, count of RBC,
plasma ferritin, and SI values were higher significantly, whereas TIBC value was
lower significantly in cases compared to the controls. IDA incidence in the controls
was higher significantly in comparison to the cases (with p < 0.016). The results of
this study indicate that the risk of FS in anemic children is lower than in non - anemic
children.
Iyswarya et al., (2013) in their case-control study estimated the levels of serum
Mg, Zn, Cu and plasma malondialdehyde in FS-children. This study included 60
children divided equally into three groups - includes children with FS as cases, children
with only febrile illness and healthy children as controls. They stated that "mean serum
Zn was decreased significantly (p < 0.001) in FS (50.49 ± 5.17 Fg/dL) and in children
with only fever (67.25 ± 4.97 Fg/dL) as compared to controls (94.42 ± 7.28 Fg/dL).
The mean level of Mg was decreased significantly (with p < 0.001) in children with
36
FS compared to children with only fever and healthy one (1.99 ± 0.18 mg/dL, 2.34 ±
0.08 mg/dL, and 2.33 ± 0.09 mg/dL, respectively)". The results of the study suggest
that the decreased levels of serum Mg and Zn could be responsible for enhanced
neuronal excitability in children with FS.
Aly et al., (2014) investigate in a case-control study the levels of serum Cu,
Zn, and iron profile parameters with sample of 40 children for each group in Banha
city in Egypt. The median of SF and serum Zn levels in cases were lower significantly
(10 Fg/dl and 53 Fg/dl, respectively) compared to the controls (46.5 Fg/dl and 95 Fg/dl,
respectively; P = 0.00). They found significant positive correlations between
occurrence of FSs and positive family history of FSs and malnutrition. And significant
negative correlations for Hb level, SI, SF and serum Zn. Thus, they consider as risk
factors for FSs.
Bharathi & Chiranjeevi (2016) studied serum Mg level and its correlation
with FSs as a prospective study in a sample of one hundred twenty children from 6-60
months. Among the 120 cases: 104 (86.67%) were typical FS, 16 (13.33%) were
atypical FS. 19(16%) had hypomagnesemia. This study revealed that the association
of hypomagnesemia and typical FSs were significant statistically.
Sreekrishna et al., (2016) performed a prospective case-control study with a
sample of one-hundred children admitted in the department of pediatrics in
Rajarajeswari Medical College and Hospital, Bangalore. The study was conducted to
determine the association between level of serum Mg in FS-children. They reported
that "the mean level of serum Mg among cases was lower than among controls (2.1 ±
0.15 mg/dl and 2.13 ±0.22 mg/dl, respectively), but the difference was statistically
insignificant (P = 0.233). This study indicated that no significant role existed between
serum Mg levels and FS occurrence".
Sultan et al., (2017) investigated in a case-control study the association of IDA
with FS in a sample of 200 children for each group. Mean Hb and HCT levels in cases
were (9.86 ± 2.28 mg/dl and 29.75 ± 5.22%, respectively) compared to controls (9.48
± 1.86 mg/dl and 32.85 ± 11.86%, respectively). Mean MCV in cases was lower than
controls (69.03 ± 10.84 fL vs. 72.91 ± 11.63fL, respectively). 47% of cases and 28%
of controls had IDA. The Odds Ratio of 2,235 indicates that children with IDA
37
compared to those without anemia had 2.235 more chances for seizures occurrence.
Results of this study were statistically significant with odds ratio of 2.235 (1.475-
3.386). They concluded that IDA is considered as a risk factor for FS.
Kumar & Annamalai (2017) of Sree Balaji medical college and hospital,
Chennai in a case-control study studied the relationship between ID and FSs in a
sample of fifty children for each group, found that the mean level of Hb, MCV, MCH,
SF to be statically significant higher in control compared to cases with (p <0.001).
They conclude that children with FS are almost twice as likely to have IDA as
compared to children with febrile illness without seizures.
Nemichandra et al., (2017) in a case-control study carried out in JSS hospital,
Mysuru, India on eighty-two children for each group. The aim was to determine the
association of serum Mg and Zn levels in FS pathogenesis. Mean serum Zn levels in
cases and control were (8.93 ± 2.01 µmol/L and 12.74 ± 3.47 µmol/L, respectively).
Mean levels of serum Mg in children with FS (2.13 ± 0.46 mg/dl) and control group
(2.61 ± 0.54 mg/dl). Both the differences were significant statistically. This study
infers that deficiency of TE may be significantly related to the risk of FS in children.
Baek et al., (2018) from pediatric emergency department, performed a case-
control study, investigated the status of serum ionized Mg (iMg2+) in one-hundred
thirty-three children with FS and compared with 141 controls. Consequently, Mg
deficiency (< 0.50 mmol/L) in children with FS was significantly more common than
in controls (42.9% vs 6.9% respectively; p < 0.001). It was an independent risk factor
for FS (OR =22.12, 95% CI = 9. 23–53.02, P <0.001). They concluded that Mg
deficiency was more common and level of serum iMg2+ was significantly lower in
cases compared to controls.
38
39
Chapter 3
Materials and Methods
3.1 Study Design
The present study is a case-control one.
3.2 Study Population
The target population of this study comprised of children with FS (Case Group)
and children with febrile illness without any seizures (Control Group).
3.3 Sampling and Sample Size
The sample was 40 infant/children with FS taken from the emergency room
and 40 infant/children with febrile illness but without any seizures selected from the
outpatient clinic at Al Nassir Pediatric Hospital in Gaza, in a period from June 2018
up to September 2018. The infant/children aged six to sixty months. The cases and
controls were matched for age and gender.
3.4 Selection Criteria
3.4.1 Inclusion Criteria
Children between six months to five years of age, both gender, with
temperature of 38°C (100.4°F) or higher, and normally developed neurologically
with an FS diagnosis.
3.4.2 Exclusion Criteria
The following individuals were excluded from the study to eliminate potential
confounding factors:
• Seizures caused by infection of CNS or by metabolic imbalance.
• Developmentally delayed children.
• Children on iron therapy or had received Zn or/and Mg supplements or both.
40
3.5 Ethical Considerations
The necessary approval was obtained from the Helsinki committee to carry out
the study in the Gaza City (Annex 1). Parents of each of the participants were provided
with enough knowledge about the purpose of the study. The acceptance was taken
from parents of all participants. A formal letter of request was sent from the Palestinian
ministry of health to Al Nassir Pediatric Hospital in Gaza City to facilitate the task of
the researcher (Annex 2).
3.6 Data Collection
3.6.1 Questionnaire Interview
A meeting interview was used to complete the questionnaire that was designed
to meet the needs of the case and control groups (Annex 3). All participants were
interviewed face to face by the researcher. During the interview, the researcher
explained to the participants the unclear questions. Most questions were yes/no
questions. The questionnaire included questions about child personal data (address,
age, and gender); occupation of children parents; socioeconomic status (family
income, source of income, number of household and type of home); child
anthropometric measurements (body weight, length/height); child neonatal history
(birth weight and admission to ICU) and child medical history.
3.6.2 Anthropometrics Measurements
To determine the nutritional status of children, anthropometric measurements
(weight and height-length) were measured by a well-trained nurse. The body weight
measured in kilograms (weighed to the closest 100 grams) via a digital electronic scale
(Seca model 770; Seca Hamburg, Germany) and its accuracy was periodically verified
utilizing reference measurements. The child was weighed in light clothes, by
determining the mean weights of dressed clothes and during weighing, a correction of
the clothes was carried out by subtracting 100 grams from every child's weight. By
using a pediatric measuring board, child's length measured in cm (to the nearest mm)
in a recumbent posture (lying down) (World Health Organization, 2008a).
The software program to evaluate the growth and development of the world's
children was used to compare with reference standards. The software program
41
combines the raw data on the variables (age, sex, length, weight) to calculate an index
of nutritional status, namely "height-for-age Z-score (HAZ), weight-for-age Z-score
(WAZ) and weight-for-height Z-score (WHZ)". Stunting, underweight and wasting
were defined as being less than 2 SD below the median value for HAZ, WAZ, and
WHZ, respectively (World Health Organization, 2006, 2011).
3.7 Specimen Collection
Blood samples were collected from all participants, children with FS (case
group) as well as from children with febrile illness without any seizures (control
group), after getting informed consent from the parents.
3.8 Blood Sampling and Processing
The blood sample collection process began with blood collection at Al Nassir
Pediatric Hospital and then samples were transferred under suitable conditions to avoid
high or low-temperature exposure, to Palestinian Medical Relief Society (PMRS)
laboratory, where blood tests were performed.
Five-ml venous blood samples were obtained from each child by a qualified
nurse and divided into two tubes. About one-ml was placed into Ethylene diamine tetra
acetic acid (EDTA) vacutainer tube to perform CBC test. The remaining quantity of
the blood was placed into the vacutainer plain tube that was left to clot for a short time,
and then clear serum samples were centrifuged for 10 minutes at 3000 revolutions per
minute. The separated serum was placed in plain tubes and sealed for biochemical
analysis (SI, SF, TIBC, sTfR, Zn and Mg). To prevent loss of bioactivity and
contamination, samples were stored at -20°C.
42
3.9 Materials
3.9.1 Equipment
The present work was carried out in the PMRS Gaza. The major equipment’s
used in the study are listed in Table 3.1.
Table 3.1: The major equipment used in the study.
# Items Manufacture
1. ELISA reader Snibe, China
2. Chemistry auto analyzer Respons 920 DiaSys, Germany
3. CBC auto analyzer Orphee mythic 18 equipment, Sweden
4. Centrifuge Germmy, Taiwan
5. Vortex mixer BioRad, Germany
6. Different Micropipettes Dragon-lab, USA
7. Refrigerator Pharml, Spain
3.9.2 Chemicals, Kits and Disposables
Chemicals, kits and disposables used in the study are shown in Table 3.2.
Table 3.2: Chemicals, kits, and disposables.
# Items Manufacture
1. Ferritin reagent kit MAGLUMI series fully auto-chemiluminescence immunoassay kit, United Kingdom
2. Serum iron reagent kit DiaSys Diagnostic Systems, Germany
3. UIBC reagent kit DiaSys Diagnostic Systems kit, Germany
4. sTFR reagent kit AccuBind ELISA Kits, USA
5. Zn reagent kit Coral Clinical Systems, INDIA
6. Mg reagent kit DiaSys Diagnostic Systems kit, Germany
7. hs-CRP DiaSys Diagnostic Systems kit, Germany
8. EDTA tubes HyLabs, Park Tamar, Rehovot
9. Five ml vacutainer tubes HyLabs. Park Tamar, Rehovot
10. Disposable tips Labcon, USA
11. Five ml disposable syringes HOMED, Palestine-Gaza
43
3.10 Biochemical parameters and CBC analysis
The biochemical analysis involved the determination of different analytes
including SI, UIBC, SF, sTfR, Zn, Mg, and hs-CRP. Calculation of Tfsat and analysis
of CBC were made.
3.10.1 Determination of serum iron
Serum iron was carried out using Photometric test, Ferene method (Artiss,
Vinogradov, & Zak, 1981; Higgins, 1981).
Principle
In the presence of ascorbic acid and an acidic medium, iron bound to transferrin
released as ferric iron (Fe3+) and reduced to ferrous iron (Fe2+) that forms a blue
complex with Ferene. The absorption is directly proportional to the concentration of
iron at 595 nm.
The reference range of the SI in all age groups is 22-184 Fg/dL (Kliegman et
al., 2016).
3.10.2 Determination of UIBC
The determination of UIBC was applied by using Photometric test, Ferene
method on analytical kits (Burtis, Ashwood, & Bruns, 2012; Wick, Pinggera,
Pinggera, & Lehmann, 2003).
Principle
A known concentration of Fe2+ incubated with the sample will specifically bind
to transferrin at the unsaturated iron binding sites. The ferene reaction is used to
measure the residual unbound Fe2+. The difference between the excess amount of iron
and the total amount added to the serum is equivalent to the quantity bound to
transferrin. This is the UIBC of the sample. TIBC [µg/dL] is then calculated from the
sum of UIBC [µg/dL] + Iron [µg/dL].
44
The reference ranges of the TIBC are listed in Table 3.3 (Kliegman et al.,
2016):
Table 3.3: Reference ranges of the TIBC.
Category Concentration (Og/dL)
Infant 100-400
Thereafter 250-400
3.10.3 Determination of Serum Ferritin
Quantitative determination of Ferritin in human serum was performed using
the MAGLUMI series fully – Automated chemiluminescence immunoassay (CLIA)
using analytical kits (Campbell & Campbell, 1988; White, Kramer, Johnson, Dick, &
Hamilton, 1986).
Principle
The Ferritin assay is a two-step sandwich chemiluminescence immunoassay.
The sample and magnetic microbeads coated with anti-Ferritin monoclonal antibody
are incubated at 37°C, and then a wash cycle is performed. Then N-(4-aminobutyl)-N-
ethyl-isoluminol (ABEI) labeled with monoclonal anti-Ferritin antibody is added, are
thoroughly mixed and incubated to form sandwich complexes. After precipitation in a
magnetic field, the supernatant is decanted, and another washing cycle is performed.
Subsequently, a substrate is added to initiate a chemiluminescence reaction. The light
signal is measured by a photomultiplier as relative light unit (RLUs) within 3 seconds,
which is proportional to the concentration of ferritin present in the sample. The
reference ranges of ferritin are listed in Table 3.4 (Kliegman et al., 2016):
45
Table 3.4: Reference ranges of ferritin.
Age group Concentration (ng/mL)
0-6 weeks 0-400
7 weeks-365 days 10-95
1-9 years 10-60
3.10.4 Calculation of Transferrin Saturation:
The two laboratory measurements serum iron concentration and TIBC are used
to calculate the percentage of Tfsat (Centers for Disease Control and Prevention,
1998):
Transferrin saturation (%) = [SI concentration (µg/dL)/TIBC (µg/dL)] × 100
The Tfsat reference ranges varies according to age, values are listed in Table 3.5
(Kliegman et al., 2016; Shalini Paruthi, 2015):
Table 3.5: Reference ranges of the Tfsat.
Category (%)
Children > 16
Adults 20-50
3.10.5 Determination of Soluble Transferrin Receptor
The quantitative determination of sTfR concentration in human serum was
performed using colorimetric analytical kits (Åkesson, Bjellerup, & Vahter, 1999;
Allen et al., 1998; Suominen, Punnonen, Rajamäki, & Irjala, 1997).
Principle
Immunoenzymometric sequential assay (TYPE 4):
High affinity and specificity antibodies (enzyme and immobilized) with
different and distinct epitope recognition, in excess, and native antigen are essential
reagents required for an immunoenzymometric assay. During this process, the
immobilization occurs on the surface of a microplate well through the interaction of
streptavidin coated on the well and biotinylated monoclonal anti-sTfR antibody are
added exogenously.
46
A reaction between the native antigen and the antibody, forming an antibody
antigen complex, is produced following a mixture of monoclonal biotinylated
antibodies with a serum containing the native antigen. The following equation
illustrates the interaction:
BtnAb (m) = Biotinylated Monoclonal Antibody (Excess Quantity)
AgI (sTfR) = Native Antigen (Variable Quantity)
Ag (sTfR)-BtnAb (m) = Antigen-antibody complex (Variable Quantity)
ka = Rate Constant of Association
k-a = Rate Constant of Disassociation
Simultaneously, the complex is deposited to the well through the high affinity
reaction of streptavidin and biotinylated antibody. This interaction is illustrated below:
StreptavidinCW = Streptavidin immobilized on well
Immobilized complex (IC) = Ag-Ab bound to the well
After an appropriate incubation period, the antibody-antigen bound fraction is
isolated by decantation or aspiration from the unbound antigen. Another antibody
(directed to another epitope) is added, labeled with an enzyme. Another interaction
occurs at the surface of the wells to form an enzyme-labeled antibody-antigen-
biotinylated- antibody complex. The excess enzyme is washed away through a
washing step. To produce color measurable by using a microplate spectrophotometer,
a suitable substrate is added.
The activity of the enzyme on the well is directly proportional to the native
concentration of free antigen. A dose response curve can be produced using several
serum references of the known antigen concentration, to determine the concentration
of an unknown antigen. The normal range for sTfR is 8.7-28.1 nmol/L (MayoClinic,
2019).
47
3.10.6 Determination of Complete Blood Count
The test was carried out on PMRS laboratory in Gaza using a hematology auto-
analyzer CBC that assess the composition and concentration of the cellular
components of blood. It includes a series of tests: RBC count, WBC count, and platelet
count; Hb and MCV measurement; WBC differential; WBC differential; and Hct and
RBC indices calculation. The reference range of CBC parameters are listed in Table
3.6 (Kliegman et al., 2016).
Table 3.6: Reference range of CBC parameters.
Parameter Age group
1-23 months 2-9 years
HCT (%) 32-42 33-43
Hb (g/dL) 10.5-14.0 11.5-14.5
MCH (pg) 24-30 25-31
MCHC (g/dl) 32-36 32-36
MCV (fL) 72-88 76-90
WBC (103/Ol) 6.0-14.0 4.0-12.0
3.10.7 Determination of Zinc
Zinc determination was applied using a colorimetric analytical kits (Abe &
Yiamashita, 1989; Makino, 1991).
48
Principle
In an alkaline medium, Zn with Nitro-PAPS to form a purple colored complex. The
intensity of the formed complex is directly proportional to the quantity of Zn in the
sample. The reference ranges of the Zn are listed in Table 3.7 (Lin et al., 2012):
Zinc + Nitro-PAPS
Purple Colored
According to the WHO, all Zn values bellow <65 Fg/dL in morning samples
of blood serum were defined as Zn deficiency (Simon-Hettich, Wibbertmann, Wagner,
Tomaska, & Malcolm, 2001).
Table 3.7: Reference ranges of Zn.
Age group Concentration (Og/dL)
0.5-2 years 56-125
3-4 years 60-120
5-6 years 64-117
3.10.8 Determination of Magnesium
The determination of Mg was applied by Photometric method using xylidyl
blue on analytical kits (Bohuon, 1962; Mann & Yoe, 1957)
Principle
In alkaline solution, Mg ions complex with xylidyl blue forming a purple
colored. The reaction is specific when GEDTA is present that complexes the calcium
ions. The color intensity is proportional to the concentration of Mg. A serum Mg 1.8
mg/dL is considered Mg deficiency (Costello et al., 2016).The reference ranges of
the Mg are listed in Table 3.8 (Kliegman et al., 2016):
Alkaline Medium
complex
49
Table 3.8: Reference ranges of Mg.
Age groups Concentration (Og/dL)
7 days-2 years 1.6-2.6
2-14 years 1.5-2.3
3.10.9 Determination of High-sensitivity C-reactive Protein
Quantitative determination of CRP in serum or plasma was applied by particle
enhanced immune-turbidimetric method on analytical kits (Dupuy, Badiou,
Descomps, & Cristol, 2003; Rothkrantz-Kos, Schmitz, Bekers, Menheere, & van
Dieijen-Visser, 2002).
Principle
Concentration of CRP determined by photometric measurements of antigen-
antibody reaction on polystyrene particles loaded with antibodies specific to human
CRP present in the sample. The reference range of the hs-CRP are listed in Table 3.9
(Dati et al., 1996; Schlebusch, Liappis, Kalina, & Klein, 2002).
Table 3.9: Reference ranges of hs-CRP.
Category Concentration (mg/L)
Adults <5
Newborns up to 3 weeks <4.1
Infants and children <2.8
3.11 Statistics and Data Analysis
Statistical Package for the Social Science (SPSS, version 22) is a computer
program that is used for data processing and analysis (IBM/SPSS, 2018).
For all variables of the study, cross tabulation and simple distribution system
were used. To identify the significance of the associations, relationships, and
interactions between the different variables, Chi-square (χ2) was used and means of
quantitative variables were compared by independent sample t-test. Pearson
50
correlation test and range as minimum and maximum values were also used.
Percentage difference was calculated according using the formulae:
The results of the aforementioned techniques were statistically significant
when the p-value was < 5% (p < 0.05).
51
52
Chapter 4
Results
4.1 General characteristics of the study population
Eighty children from Gaza participated in the present study (40 cases and 40
controls). Table (4.1) shows that the age of the participants ranged from (6 – 60
months). The mean age of the cases (24.7 ± 13.8 months) and controls (23.2 ± 15.7
months) were not significantly different (p = 0.634). There was no statistically
significant difference between the cases and controls regarding the birth weight,
height, and current weight.
On the other hand, the percentage of male and female participants was 52.5%
& 47.5% for cases while 60.0% & 40.0% for controls respectively with no significant
difference (p = 0.499). Regarding the monthly income of the child's families, there was
no significant difference between cases and controls (p = 0.288). There was also no
significant difference between cases and controls in the type of home, number of
households and parental consanguinity (Table 4.1).
The length of pregnancy between the cases' mothers and controls' mothers was
not significantly different (p = 0.132) (Table 4.2). 7.5% of the controls were delivered
prematurely, while 97.5% of cases and 92.5% of controls were delivered in full term.
Regarding the type of delivery, 82.5% of cases were delivered normally compared to
85.0% for controls with no significant difference (p = 1.000) (Table 4.2). Low birth
weight (LBW) has been defined by the WHO as weight at birth of less than (2,500)
grams (World Health Organization, 2014a). Table (4.2) shows that most of the
participants had a normal weight at delivery, 75.0% of cases and 75.0% of controls,
with no significant difference (p = 0.499).
53
Table 4.1: General characteristics of the study population.
Characteristics Cases
(n = 40)
Controls
(n = 40) t/ χ2test P-value
Age (Months)
Mean ± SD (min-max)
24.7 ± 13.8 (6.0-60.0)
23.2 ± 15.7 (8.0-58.0)
0.478 0.634
Birth weight (kg) 3.2 ± 0.6 (1.8-4.5)
3.3 ± 0.6 (1.6-4.3)
-0.872 0.386
Height (cm) 85.4 ± 13.9 (64.0-122.0)
83.5 ± 13.5 (60.0-115.0)
0.618 0.538
Current Weight
(kg)
11.3 ± 3.0 (7.0-20.5)
10.7 ± 3.4 (5.5-20.0)
0.921 0.360
Gender
n (%)
0.457
Male 21 (52.5) 24 (60.0) 0.499 Female 19 (47.5) 16 (40.0)
Monthly Income
(NIS)
≤2000 37 (92.5) 34 (85.0) 1.127 0.288 > 2000 3 (7.5) 6 (15.0)
Type of home Owned 34 (85.0) 38 (95.0) 2.222 0.136 Rented 6 (15.0) 2 (5.0)
No. of households
0.798 0.671 < 2 persons 20 (50.0) 18 (47.5) 3-5 persons 15 (37.5) 18 (45.0) > 6 persons 5 (12.5) 3 (7.5)
Parental
consanguinity
0.952 0.329 Positive 10 (25.0) 14 (35.0) Negative 30 (75.0) 26 (65.0)
n: Number of the subjects; χχχχ2: Chi-square test; t: Student t-test; NIS: New Israeli shekel; SD: Standard deviation.
54
Table 4.2: Length of pregnancy, type of delivery and birth weight among the study
population.
Variables Cases (40)
n (%)
Controls (40)
n (%) χ2test
p-
value
Length of Pregnancy (weeks)
4.05 0.132 Premature (<37) 0 (0.0) 3 (7.5)
Full term (37-42) 39 (97.5) 37 (92.5)
Post mature (>42) 1 (2.5) 0 (0.0)
Type of delivery
0.09 1.000 Normal vaginal 33 (82.5) 34 (85.0)
CS 7 (17.5) 6 (15.0)
Birth Weight
0.80 0.670 LBW <2.5 kg 6 (15.0) 4 (10.0)
NBW 2.5-4 kg 30 (75.0) 30 (75.0)
HBW >4 kg 4 (10.0) 6 (15.0)
n: Number of the subjects; χχχχ2: Chi-square test; CS: Caesarean section; LBW: Low birth weight; NBW: Normal birth weight; HBW: High birth weight.
4.2 Anthropometric assessment measurements of the study
population
Anthropometric measurements of children participating in the study are shown
in Table (4.3). About (15.0%) of FS children and (22.5%) of febrile children without
seizure were found to have weight between (5-8 kg) while (85.0%) of FS children and
(77.5%) of febrile children without seizure were more than (8 kg). In addition, results
showed that (0.0%) of cases and (5.0%) of controls had height less than (60 cm).
(47.5%) of cases and (50.0%) of controls had height in the range of (60-80 cm).
Whereas (52.5%) of cases and (45.0%) of controls their height were more than (80
cm).
In addition, Table (4.3) shows that the percentage of normal weight for age
based on the z-score for cases was (92.5%) and for controls was (85.0%). On the other
hand, it was found that (7.5%) and (10.0%) of cases and controls, respectively were
55
moderately underweight and (0.0%) of cases and 5.0% of controls were severely
underweight, but the differences were statistically insignificant between case and
control groups (with p = 0.321).
Table 4.3: Anthropometric assessment measurements of the study population.
Anthropometric
Measurements
Research Category
χ2 test P-value Cases (40)
n (%)
Controls
(40)
n (%)
Body Weight (kg)
0.738 0.390 5-8 6 (15.0) 9 (22.5) >8 34 (85.0) 31 (77.5) Total 40 (100.0) 40 (100.0)
Length/Height (m)
2.256 0.324
<0.60 0 (0.0) 2 (5.0) 0.60-0.80 19 (47.5) 20 (50.0) >0.80 21 (52.5) 18 (45.0) Total 40 (100.0) 40 (100.0)
Weight for age
2.270 0.321 Normal 37 (92.5) 34 (85.0) Moderate Underweight 3 (7.5) 4 (10.0) Sever Underweight 0 (0.0) 2 (5.0) Total 40 (100.0) 40 (100.0)
Length-Height for Age
1.261 0.532
Normal 32 (80.0) 34 (85.0) Moderate Stunting 6 (15.0) 3 (7.5) Sever Stunting 2 (5.0) 3 (7.5) Total 40 (100.0) 40 (100.0)
Weight for Length-Height
2.883 0.090 Normal 39 (97.5) 35 (87.5) Moderate Wasted 1 (2.5) 5 (12.5) Total 40 (100.0) 40 (100.0)
n: number of the subjects; χχχχ2: chi-square test.
Table (4.3) also shows that the majority of study samples had normal values of
length-height for age, which were observed in about (80.0%) of cases and (85.0%) of
controls. In turn, (15.0%) for cases and (7.5%) for controls were moderately stunted
and (5.0%) and (7.5%) for cases and controls respectively were severely stunted, but
56
the differences between case and control groups were statistically insignificant (p =
0.532).
The percentage of children with a normal weight for length-height was (97.5%)
for cases and (87.5%) for controls. In addition, (2.5%) of the cases and (12.5%) of
controls were moderately wasted, and the differences between case group and control
group failed to reach statistically significant value (p = 0.090) (Table 4.3).
4.3 Clinical characteristics and medical history of the study
population
Although the mean admission temperature of the cases (39.1 ± 0.7) was higher
compared to that of the controls (38.9 ± 0.7), the difference was not statistically
significant (p = 0.215) (Table 4.4). In contrast, the heart rate of the cases (129.6 ± 25.3)
was significantly higher than that of the controls (100.9 ± 35.6) (p < 0.001) (Table
4.4).
Table 4.4: Vital signs at admission of hospital among the study population.
Variables
Cases (40) Controls (40)
t test P-value Mean ± SD
(min-max)
Temperature at
admission (°C)
39.1 ± 0.7
(38.0-40.3)
38.9 ± 0.7
(38.0-40.3) 1.250 0.215
Heart Rate
(bpm)
129.6 ±
25.3
(87-184)
100.9 ± 35.6
(60-189) 4.158 < 0.001
The participants of the cases and controls had fever upon admission to hospital.
The cause of the fever was due to URTI in (85.0%) of the cases and (57.5%) of the
controls compared to (15.0%) of cases and (42.5%) of controls due to Gastroenteritis
(p = 0.007) (Table 4.5).
57
Table 4.5: Clinical characteristics and medical history of the study population.
Research Category
Variables Cases (40)
n (%)
Controls (40)
n (%) χ2 test P-value
Admission to ICU
0.092
0.762
Yes 6 (15.0) 7 (17.5)
No 34 (85.0) 33 (82.5)
Fever
0.000 1.000 Yes 40 (100.0) 40 (100.0)
No 0 (0.0) 0 (0.0)
Cause of fever
7.384
0.007
URTI 34 (85.0) 23 (57.5)
Gastroenteritis 6 (15.0) 17 (42.5)
Type of febrile seizure
--- --- Generalized 40 (100.0) -
Focal 0 (0.0) -
Number of episodes / 24hrs
--- --- Once 37 (92.5) -
More than once 3 (10.0) -
Past history of febrile seizure
Yes 3 (7.5) 0 (0.0) 3.117 0.077
No 37 (92.5) 40 (100.0)
Family history of febrile
seizure
Yes 12 (30.0) 0 (0.0) 14.118 < 0.001
No 28 (70.0) 40 (100.0)
Family history of epilepsy
Yes 2 (5.0) 0 (0.0) 2.051 0.152
No 38 (95.0) 40 (100.0)
n: Number of the subjects; χχχχ2: Chi-square test; ICU: Intensive care unit; URTI:
Upper respiratory tract infections.
58
In addition, the results showed that all cases had generalized FS for 15 minutes,
where most of them (92.5%) had FS Once/24hr. Moreover, most of the cases and
controls did not have past history of FS (92.5 & 100.0%) nor family history of epilepsy
(95.0 & 100.0%) (p = 0.077 & 0.152) respectively (Table 4.5). In contrast, there was
a statistically significant difference between the cases (30.0%) and controls (0.0%)
regarding the family history of FS (p < 0.001).
4.4 Biochemical parameters among the study population
Table 4.6 shows that the mean level of SI was higher in cases (50.9 ± 23.0
Fg/dL) compared to controls (24.3 ± 16.3 Fg/dL) (p < 0.001). SI was low in 35.0% of
the cases compared to 82.5% in the controls. Whereas, 65% of the cases have normal
level of SI compared to 17.5% only for the controls (p < 0.001) (Table 4.7). There was
also a statistically significant difference in the mean levels of TIBC (296.6 vs
372.1Fg/dL) and Tfsat (19.8 vs 7.5 %) between cases and controls respectively (p <
0.001) (Table 4.6).
The percentage of cases with high TIBC was 2.5% compared to 27.5% for
controls (p = 0.002). In contrast, 60% of cases had low Tfsat compared to 97.5% in
controls (p < 0.001) (Table 4.7). On the other hand, the mean SF levels (37.5 & 47.9
ng/ml) and sTfR levels (23.1 & 26.9 nmol/L) were lower in cases compared to controls
respectively, the difference were not statistically significant (p = 0.362 & 0.173)
respectively (Table 4.6).
On the other hand, the levels of Zn were not significantly different between
cases (77.3 ± 11.4 µg/dL) and controls (78.8 ± 9.5 µg/dL) (p = 0.518). In contrast, the
levels of Mg were lower in cases (2.0 ± 0.2 mg/L) compared to controls (2.1 ± 0.2
mg/L) and the difference was statistically significant (p = 0.028) (Table 4.6). The
percentage of cases with low Zn was 15% compared to 7.5% for controls (p = 0.288).
In contrast, 25% of cases had low Mg compared to 10% in controls (p < 0.077) (Table
4.7).
Moreover, the levels of hs-CRP were significantly lower in cases (3.0 ± 2.7
mg/L) compared to controls (8.5 ± 5.8 mg/L) (p < 0.001) (Table 4.6). 37.5% of the
cases had higher hs-CRP levels compared to 77.5% in controls (p <0.001) (Table 4.7).
59
Table 4.6: The mean of different biochemical parameters among the study population.
Biochemical parameters
Cases (40) Controls (40)
t test P-value Mean ± SD
(min-max)
SI (Og/dL) 50.9 ± 23.0
(10-98)
24.3 ± 16.3
(7.2-98) 5.966 < 0.001
TIBC (Og/dL) 296.6 ± 64.6
(192-462)
372.1 ± 56.5
(197-470) 5.566 < 0.001
Tfsat (%) 19.8 ± 13.3
(2.2-51)
7.5 ± 8.0
(1.6-49.8) 4.996 < 0.001
SF (ng/ml) 37.5 ± 31.1
(7.3-158.5)
47.9 ± 64.3
(4.5-390) 0.917 0.362
sTfR (nmol/L) 23.1 ± 9.3
(11.6-51.6)
26.9 ± 14.7
(12.4-72.3) 1.375 0.173
Zn (µg/dL) 77.3 ± 11.4
(52.8-98.2)
78.8 ± 9.5
(58-96.3) 0.649 0.518
Mg (mg/dL) 2.0 ± 0.2
(1.6-2.4)
2.1 ± 0.2
(1.7-2.4) 2.240 0.028
hs-CRP (mg/L) 3.0 ± 2.7
(0.4-12.7)
8.5 ± 5.8
(0.7-20.8) 5.406 < 0.001
60
Table 4.7: Comparison of different biochemical parameters among the study
population.
Variables
Research Category Odds
ratio
Chi-
square p-value Cases (40)
n (%)
Controls (40)
n (%)
SI
Low 14 (35.0) 33 (82.5)
8.8 18.62 < 0.001 Normal 26 (65.0) 7 (17.5)
High 0 (0.0) 0 (0.0)
TIBC
Low 0 (0.0) 0 (0.0)
14.8 9.80 0.002 Normal 39 (97.5) 29 (72.5)
High 1 (2.5) 11 (27.5)
Tfsat
Low 24 (60.0) 39 (97.5)
21.0 16.84 < 0.001 Normal 14 (35.0) 1 (2.5)
High 2 (5.0) 0 (0.0)
SF
Low 5 (12.5) 6 (15.0)
- 1.15 0.563 Normal 35 (87.5) 33 (82.5)
High 0 (0.0) 1 (2.5)
sTfR
Low 0 (0.0) 0 (0.0)
- - 1.000 Normal 28 (70.0) 28 (70.0)
High 12 (30.0) 12 (30.0)
Zn Low 6 (15.0) 3 (7.5)
- 1.127 0.288 Normal 34 (85.0) 37 (92.5)
Mg Low 10 (25.0) 4 (10.0)
- 3.117 0.077 Normal 30 (75.0) 36 (90.0)
hs-CRP Normal 25 (62.5) 9 (22.5)
5.7 13.09 < 0.001 High 15 (37.5) 31 (77.5)
61
4.5 Complete blood count indices among the study population
Table 4.8 shows that the mean value of total WBCs counts was lower in cases
(9.1 ± 3.2 ×103/Fl) compared to controls (10.1 ± 3.6 ×103/Fl) but the differences were
not statistically significant (p > 0.05). WBCs was low in 10.0% of the cases compared
to 2.5% in the controls. Whereas, 87.5% of the cases have normal count of WBCs
compared to 95.0% for the controls (p > 0.05). (Table 4.9).
Regarding the differential count for WBC, there were no statistically
significant differences (p > 0.05) between cases and controls according to the absolute
value of lymphocytes (4.5 ± 1.7 & 4.2 ± 2.4 ×103/Fl) and monocytes (0.9 ± 0.4 & 0.8
± 0.3 ×103/Fl) respectively. In contrast, the mean levels of granulocytes were lower in
cases (3.8 ± 2.1 ×103/Fl) compared to controls (5.2 ± 2.7 ×103/Fl) and the difference
was significantly different (p = 0.010). (Table 4.8). Granulocytes count was high in
20% of the cases compared to 32.5% in the controls. Whereas, 25.0% of the cases have
normal count of granulocytes compared to 47.5% for the controls (p < 0.05) (Table
4.9).
About the relative value of differential count for WBC, the mean levels of
Lymphocyte (50.2 ± 11.7 & 41.7 ± 15.9 %), Monocyte (9.8 ± 2.7 & 7.7 ± 2.6 %) and
Granulocyte (40.0± 13.1 & 50.6 ± 16.8 %). The differences were statistically
significant (p = 0.008 & 0.001 & 0.002) between cases and controls respectively (Table
4.8).
On the other hand, the mean value of RBCs count was lower in cases (4.4 ± 0.3
×106/Fl) compared to controls (4.7 ± 0.5 ×106/Fl) and the difference was statistically
significant (p = 0.002). (Table 4.8). RBCs count was low in 7.5% of the cases
compared to 2.5% in the controls. Whereas, 92.5% of the cases have normal count of
RBCs compared to 97.5% for the controls (Table 4.9).
Moreover, the mean value of Hb and Hct were lower in cases compared to
controls (10.2 ± 1.0 & 10.4 ± 1.3 g/dl) and (32.3 ± 2.4 & 33.0 ± 3.5 %) respectively,
and the differences were not statistically significant (p > 0.05) (Table 4.8).
About the RBCs indices, the mean value of MCV were significantly higher in
cases (72.8 ± 6.5 fL) compared to controls (69.8 ± 6.8 fL) (p = 0.045), While the
difference in MCH (pg), MCHC (g/dl), and RDW (%) values between cases and
controls were not statistically significant. Additionally, the mean value of platelet was
lower in case group (346 ± 109 ×103/Fl) compared to control group (357 ± 124 ×103/Fl)
but the difference was statistically insignificant (p = 0.674) (Table 4.8).
62
Table 4.8: The mean of CBC indices among the study population.
Variables
Cases (40) Controls (40)
% t-test P-value Mean ± SD
(Min-Max)
WBCs (103/Ol) 9.1 ± 3.2 (4.6-19.6)
10.1 ± 3.6 (5.4-21.3)
-10.4 -1.310 0.194
Lymphocyte (103/Ol) 4.5 ± 1.7 (2-9.4)
4.2 ± 2.4 (0.8-12.4)
6.9 0.656 0.514
Monocyte (103/Ol) 0.9 ± 0.4 (0.4-2.5)
0.8 ± 0.3 (0.4-1.4)
11.8 1.517 0.133
Granulocyte (103/Ol) 3.8 ± 2.1 (1-9.5)
5.2 ± 2.7 (1.7-12.2)
-31.1 -2.642 0.010
Lymphocyte (%) 50.2 ± 11.7 (24.6-71.2)
41.7 ± 15.9 (8.6-67.3)
18.5 2.712 0.008
Monocyte (%) 9.8 ± 2.7 (4.7-16.8)
7.7 ± 2.6 (2.6-13.4)
24.0 3.536 0.001
Granulocyte (%) 40.0 ± 13.1 (12-69.5)
50.6 ± 16.8 (24.9-88.8)
-23.4 -3.136 0.002
RBCs (106/Ol) 4.4 ± 0.3 (3.8-5.5)
4.7 ± 0.5 (4-6.1)
-6.6 -3.139 0.002
Hb (g/dl) 10.2 ± 1.0 (7.9-12.6)
10.4 ± 1.3 (8.4-13.5)
-1.9 -0.879 0.382
Hct (%) 32.3 ± 2.4 (26.5-37.7)
33.0 ± 3.5 (27-43.3)
-2.1 -1.034 0.304
MCV (fL) 72.8 ± 6.5 (53.8-82.9)
69.8 ± 6.8 (57-82.1)
4.2 2.039 0.045
MCH (pg) 23.1 ± 2.6 (16.1-27.9)
22.1 ± 2.6 (17.7-27)
4.4 1.626 0.108
MCHC (g/dl) 31.6 ± 1.1 (29.8-33.9)
31.6 ± 1.0 (29.6-34.1)
0.0 -0.084 0.934
RDW (%) 15.9 ± 3.2 (1.9-23.2)
16.7 ± 2.0 (13.5-20.1)
-4.9 -1.406 0.164
Platelet (103/Ol) 346 ± 109 (130-635)
357 ± 124 (193-628)
-3.1 -0.422 0.674
MPV (fL) 8.5 ± 0.9 (6.8-10.5)
8.9 ± 1.0 (7.3-11.5)
-4.6 -1.956 0.054
PDW (%) 14.8 ± 1.6 (11.7-21.4)
15.1 ± 3.0 (9.7-27.3)
-2.0 -0.568 0.572
63
Table 4.9: Comparison of CBC indices among the study population.
Variables Category
Research Category
χ2 test p-value Cases (40) n (%)
Controls (40) n (%)
WBCs (103/Ol) Low 4 (10.0) 1 (2.5)
1.92 0.382 Normal 35 (87.5) 38 (95.0) High 1 (2.5) 1 (2.5)
Lymphocyte (103/Ol)
Low 0 (0.0) 2 (5.0) 4.15 0.126 Normal 7 (17.5) 12 (30.0)
High 33 (82.5) 26 (65.0)
Monocyte (103/Ol)
Low 0 (0.0) 0 (0.0) 1.87 0.172 Normal 6 (15.0) 11 (27.5)
High 34 (85.0) 29 (72.5)
Granulocyte (103/Ol)
Low 22 (55.0) 8 (20.0) 10.52 0.005 Normal 10 (25.0) 19 (47.5)
High 8 (20.0) 13 (32.5)
Lymphocyte (%) Low 1 (2.5) 6 (15.0)
4.97 0.083 Normal 2 (5.0) 4 (10.0) High 37 (92.5) 30 (75.0)
Monocyte (%) Low 0 (0.0) 1 (2.5)
5.14 0.077 Normal 8 (20.0) 16 (40.0) High 32 (80.0) 23 (57.5)
Granulocyte (%) Low 33 (82.5) 26 (65.0)
3.94 0.139 Normal 5 (12.5) 7 (17.5) High 2 (5.0) 7 (17.5)
RBCs (106/Ol) Low 3 (7.5) 1 (2.5)
1.05 0.305 Normal 37 (92.5) 39 (97.5) High 0 (0.0) 0 (0.0)
Hb (g/dl) Low 34 (85.0) 32 (80.0)
0.35 0.556 Normal 6 (15.0) 8 (20.0) High 0 (0.0) 0 (0.0)
Hct (%) Low 15 (37.5) 19 (47.5)
2.03 0.363 Normal 25 (62.5) 20 (50.0) High 0 (0.0) 1 (2.5)
MCV (fL) Low 16 (40.0) 24 (60.0)
3.20 0.074 Normal 24 (60.0) 16 (40.0) High 0 (0.0) 0 (0.0)
MCH (pg) Low 26 (65.0) 30 (75.0)
0.95 0.329 Normal 14 (35.0) 10 (25.0) High 0 (0.0) 0 (0.0)
RDW (%) Low 0 (0.0) 0 (0.0)
3.13 0.077 Normal 7 (17.5) 2 (5.0) High 33 (82.5) 38 (95.0)
64
4.6 Anemia, iron deficiency and iron deficiency anemia among the
study population
According to WHO guidelines, Anemia was defined as Hb <11.0 g/dl, ID was
defined as SF < 12 and < 30 Fg/l in the presence of infection and inflammation and
Tfsat < 16%, and IDA was defined as having both anemia and ID (World Health
Organization, 2001).
Table 4.10 shows that the percentage of cases with anemia was 85.0%
compared to 80.0% for controls (p = 0.556). In contrast, 32.5% of cases had an ID and
32.5% had IDA compared to 40.0% and 30.0% in controls respectively, and the
difference was not statistically significant (p > 0.05).
Table 4.10: Anemia, iron deficiency and iron deficiency anemia among the study
population.
n: number of the subjects; OR: Odds Ratio; CI: Confidence Interval; χχχχ2: chi-square test; ID: Iron Deficiency; IDA: Iron Deficiency Anemia.
Category
Research Category
OR 95% CI χ2 test p-
value Cases (40)
n (%)
Controls (40)
n (%)
Anemia Yes 34 (85.0) 32 (80.0)
1.42 0.4-4.5 0.350 0.556 No 6 (15.0) 8 (20.0)
ID Yes 13 (32.5) 16 (40.0)
0.72 0.3-1.8 0.487 0.485 No 27 (67.5) 24 (60.0)
IDA Yes 13 (32.5) 12 (30.0)
1.12 0.4-2.9 0.058 0.809 No 27 (67.5) 28 (70.0)
65
4.7 Correlation between SI, sTfR, Zn, Mg and different
characteristics and parameters among the study population
Table 4.11 presents the correlation between SI, sTfR, Zn, and Mg with the
studied parameters. SI has a moderate negative correlation which is statistically
significant with hs-CRP (r = -0.462, P < 0.001). There is a negligible correlation
between SI and birth weight (r = -0.049, P = 0.663), temperature at admission (r = -
0.099, P = 0.384), and has a positive correlation which is statistically not significant
with age (r = 0.035, P = 0.755), number of households (r = 0.015, P = 0.895), heart
rate (r = 0.146, P = 0.198), height (r = 0.117, P = 0.300), and weight (r = 0.067, P =
0.555).
On the other hand, sTfR has a moderate negative correlation which is
statistically significant with age (r = -0.403, P < 0.001), height (r = -0.494, P < 0.001),
and weight (r = -0.413, P < 0.001), while a weak negative correlation with birth weight
(r = -0.226, P = 0.044). In contrast, there is a negligible correlation between sTfR and
hs-CRP, number of households, heart rate, and temperature at admission.
Furthermore, there is a negligible correlation between Zn with age, number of
households, height, weight, birth weight, heart rate, temperature at admission, and hs-
CRP.
Table 4.11 also shows that there is a significant weak correlation between the
Mg and Age (r = -0.274, P = 0.014), height (r = -0.267, P = 0.017), and weight (r = -
0.239, P = 0.033). In contrast Mg showed a negligible correlation with number of
households (r = -0.096, P = 0.396), birth weight (r = -0.081, P = 0.475), heart rate (r =
-0.017, P = 0.884), temperature at admission (r = -0.165, P = 0.143), and hs-CRP (r =
0.114, P = 0.313).
66
Table 4.11: Correlation between SI, sTfR, Zn, Mg and different characteristics and
parameters among the study population.
Variables
SI
(Og/dL)
sTfR
(nmol/L)
Zn
(µg/dL)
Mg
(mg/dL)
r P-value r P-value r P-value r P-value
Age (Months) 0.035 0.755 -0.403 < 0.001 -0.153 0.176 -0.274 0.014
Number of
households 0.015 0.895 0.025 0.829 -0.053 0.643 -0.096 0.396
Birth weight
(kg) -0.049 0.663 -0.226 0.044 0.105 0.353 -0.081 0.475
Heart Rate
(bpm) 0.146 0.198 0.041 0.721 0.002 0.984 -0.017 0.884
Height (cm) 0.117 0.300 -0.494 < 0.001 -0.15 0.186 -0.267 0.017
Weight (kg) 0.067 0.555 -0.413 < 0.001 -0.096 0.398 -0.239 0.033
Temperature
at admission
(°C)
-0.099 0.384 0.03 0.794 0.069 0.543 -0.165 0.143
hs-CRP -0.462 < 0.001 -0.002 0.986 0.048 0.671 0.114 0.313
SI: Serum Iron; sTfR: Soluble Transferrin Receptors; Zn: Zinc; Mg: Magnesium; hs-CRP:
High-sensitivity C-reactive Protein.
4.8 Correlation between SI, sTfR, Zn, Mg and different CBC indices
among the study population
Table 4.12 presents the correlation between SI, sTfR, Zn, and Mg with different
CBC indices. SI has a significant weak negative correlation with WBCS (r = -0.221, P
= 0.049), absolute and relative count of Granulocytes (r = -0.387, P < 0.001), and RDW
(r = -0.351, P < 0.001). While the correlation is negligible with RBCs (r = -0.186, P=
0.098), platelets (r = -0.028, P = 0.807), MPV (r = -0.137, P = 0.225), and PDW (r = -
0.156, P = 0.167). In contrast SI showed a significant weak positive correlation with
relative count of lymphocytes (r = 0.368, P = 0.001), monocytes (r = 0.284, P = 0.011),
MCV (r = 0.342, P = 0.002), and MCH (r = 0.315, P = 0.004). While the correlation
67
with absolute value of lymphocytes (r = 0.092, P = 0.417), monocytes (r = 0.069, P =
0.542), Hb (r = 0.173, P = 0.125), HCT (r = 0.168, P = 0.136), and MCHC (r = 0.12,
P = 0.287) is negligible.
Additionally, sTfR has a negative moderate correlation which is statistically
significant with MCV and MCH, and a negative weak correlation which is statistically
significant with Hb, HCT and MCHC. While a positive moderate correlation with,
RDW, and a positive weak correlation with RBCs, platelets, MPV and PDW. In
contrast, it has a negligible correlation with the other variables.
Moreover, there is a negligible correlation between Zn and the different
variables (Table 4.12).
Table 4.12 also shows that there is a significant positive weak correlation (p <
0.05) between Mg and RBCs (r = 0.291, P = 0.009). In contrast Mg showed a negligible
correlation with the other variables.
68
Table 4.12: Correlation between SI, sTfR, Zn, Mg and different CBC indices among
the study population.
SI: Serum Iron; sTfR: Soluble Transferrin Receptors; Zn: Zinc; Mg: Magnesium; CBC:
Complete Blood Count; WBCs: White Blood Cells; RBCs: Red Blood Cells; Hb: Hemoglobin; Hct: Hematocrit; MCV: Mean Corpuscular Volume; MCH: Mean Corpuscular Hemoglobin; MCHC: Mean corpuscular hemoglobin concentration; RDW: Red Blood Cell Distribution Width; MPV: Mean Platelet Volume; PDW: Platelet distribution width; r: Pearson correlation.
69
70
Chapter 5
Discussion
Convulsions or seizures are one of the important problems in the health of
pediatrics in developing and developed countries. FSs are the most common childhood
seizure disorder that affects 2 to 5 percent of children aged 6 to 60 months. In general,
FS is thought to be an age-dependent response of the immature brain to fever. This is
based on the fact that most FSs (80 - 85 percent), occur between the ages of 6 months
and 3 years, with a peak incidence at 18 months (Joshi, 2014).
In febrile children, some may develop FSs and some may not develop FSs. The
underlying mechanism is still not clear. Various mechanisms like genetic factors,
family history of FS, disturbance in the levels of serum minerals, and IDA were
proposed (Kliegman et al., 2016). Various studies showed that IDA, deficiency of Zn
and Mg as risk factors for development of seizures. In the present study, we
investigated the relationship between Fe, Mg and Zn levels with FS on children from
Gaza City.
5.1 General characteristics of the study population
The age of the children who participated in the present study was between (6 -
60 months). The mean age of occurrence of FS was 24.7 ± 13.8 months which was
comparable to the other studies such as Namakin et al., (2016) study who reported
similar observation with mean age of 24 months. Mahyar et al., (2008) also reported a
mean age of 27.1 ± 15.1 months in cases. Furthermore, Ganesh & Janakiraman (2008)
and Jehangir et al., (2018) reported the mean age of FS occurrence at 23.8 & 22.1
months respectively.
In the present study, there was a male predominance with a male to female ratio
of 1.3:1. 21 (52.5%) in the FS group and 24 (60%) in the control group were males.
This finding is in agreement with other studies which showed that males have
consistently emerged with a higher frequency of FS (Daoud et al., 2004; Hartfield et
al., 2009; Jehangir et al., 2018; Nemichandra et al., 2017; Singh & Yadav, 2018; Sultan
et al., 2017; Talebian et al., 2009).
71
On the other hand, the results of the present study showed that there were no
significant differences in the means of weight and height in cases compared to controls.
This is similar to the results of different studies who also didn’t find any significant
difference of weight and height between cases and controls (E. D. Kumar &
Annamalai, 2017; Kunwar Bharat et al., 2015; Vaswani et al., 2010). Moreover, basic
demographic characteristics (monthly income, type of home, and no. of households)
were comparable in the two studied groups with no significant difference. Moreover,
none of the neonatal history data (Length of pregnancy, type of delivery and birth
weight) had a significant incidence in the FS group compared to the control group (P
> 0.05).
Regarding the length of pregnancy, it was found that the majority of cases and
controls were delivered after full-term pregnancy (97.5% & 92.5% respectively) (P >
0.05), which is similar to Aly et al., (2014) who indicated that preterm labor is not a
risk factor for FS.
Consanguineous marriages are common practice among the Palestinians in the
Gaza Strip, with a significant difference between different governorates and age
groups. Consanguineous marriages were associated with a higher risk for autosomal
recessive diseases as well as increased susceptibility to polygenic and multifactorial
disorders, infertility, infant mortality, congenital malformations and miscarriage
(Sirdah, 2014). In the present study, there was no significant difference between cases
and controls in parental consanguinity status, which is similar to Aly et al., (2014) who
reported parental consanguinity in 5 children with FS. However, the genetic part of FS
is complicated, and the risk changes significantly between families with the history for
similar conditions (Fetveit, 2008).
5.2 Clinical characteristics and medical history of the study
population
In the present study, the difference in the heart rate between cases and controls
was statistically significant, but the difference in the temperature rate was not
observed, which was similar to Aly et al., (2014) results who reported that "there was
72
a significant difference in the heart rate but no significant difference in temperature
and respiratory rate between case and control groups".
In patients with FSs, a threshold for FSs has been established based on body
temperature increase. The threshold varies depending on the age and maturity of the
individuals. Increased temperature degree after admission has been reported to
progressively increase the risk of first FS (Bidabadi & Mashouf, 2009). The most
significant risk factor for the development of a first FS as was reported by Berg et al.,
(1995) and Weng et al., (2010) is the degree temperature rising. The higher the
temperature, the higher the probability of simple FS occurrence. On the other hand,
other studies could not show a relationship between the mean high temperature and FS
(Aly et al., 2014; Daoud et al., 2002). In our study, the mean peak temperature upon
admission was higher in FS group (39.1°C) when compared to the control group
(38.9°C) but the difference was statistically non-significant (P > 0.05).
Fever is "a clinical signal that is characterized by rising body temperature more
than normal level". Hypothalamus controls the central body temperature in normal
conditions and sets it within the normal range (36.5-37.5 °C). An exogenous pyrogen
or endogenous ones cause fever by acting directly on the hypothalamic
thermoregulatory center and then rise the body temperature by releasing epinephrine,
vessels contraction (particularly peripheral vessels), finally reach a new regulation
point and fever occurs (Dinarello, 2004; Shokrzadeh, Abbaskhaniyan, Rafati,
Mashhadiakabr, & Arab, 2016).
In our study, the main cause of fever was URTI (85.0%) in children with FSs.
Rutter et al. reported that URTI was the most common trigger followed by tonsillitis
(Rutter & Smales, 1976). Different studies have reported that acute respiratory
infection is the main cause of FS (Gündüz, Kumandaş, Yavuz, Koparal, & Saraymen,
1994; Margaretha & Masloman, 2010; Nemichandra et al., 2017). In Shah & Parmar,
study, (2017) the common causes of fever were undifferentiated viral fever that was
present in 52.9% of children, and acute URTI was present in 32.4% of children.
Also, it was found that (85%) of the case group and (82.5%) of the control
group had no history of a nursery stay in ICU but the difference was not statistically
significant (p > 0.05). This finding was in agreement with (Aly et al., 2014) study.
While Millar, (2006) and Sadleir & Scheffer, (2007), indicated that the neonatal
73
nursery increases the possibility of simple FSs occurrence by staying for more than 30
days.
The etiology of FSs is still not understood clearly. It is believed that simple FS
occurs as a combination between genetic and environmental factors. Today, there is a
consensus that the most important factor for FS risk is genetic predisposition (Waruiru
& Appleton, 2004). In the present study, 30% of children have family history of FS
and 5% has a history of epilepsy in their family. We found that family history of FS is
associated with FS condition which is similar to the results of different researchers
who reported a positive family history of seizures (Daoud et al., 2002; Kafadar, Akinci,
Pekun, & Adal, 2012; Kumari et al., 2012; Margaretha & Masloman, 2010; Van Esch
et al., 1994).
5.3 Biochemical parameters among the study population
It may be challenging to diagnose IDA in the presence of fever/ infection.
Hematological parameters (like Hb, Hct, MCV, RDW), microscopic examination of
peripheral blood film, SF, SI, TIBC, Tsat, sTfR, and FEP may aid in the diagnosis.
The gold standard test for the diagnosis of IDA is bone marrow examination, but
unfortunately it is painful and traumatic method and, therefore, it is not used in the
current study.
Most of the authors have compared mean levels of SI, TIBC, Tfsat, SF, and
hematological parameters with FS case and control groups, while others have also
studied the number of cases having ID & IDA in a given subject population. In the
present study, data were analyzed by using both methods. According to WHO
guidelines, anemia is defined as Hb <11.0 g/dl, ID is defined as SF < 12 and < 30 Fg/l
in the presence of infection and inflammation respectively and Tfsat < 16%, and IDA
is defined as having both anemia and ID (World Health Organization, 2001). These
guidelines were used in our study.
5.3.1 Iron profile parameters, CBC, and CRP
In the present study, SI was significantly higher (p < 0.001) and TIBC was
significantly lower (p < 0.001) in cases with FS compared to controls which disagree
74
with the studies that related FSs with IDA. The incidence of ID & IDA was higher in
controls compared to cases.
The results of SI and TIBC in the present study agreed with the study of Bidabadi
& Mashouf, (2009) who reported: "higher levels of SI and lower levels of TIBC in
children with FS compared to the control febrile group". Also, Derakhshanfar et al.,
(2012) found a statistically significant difference between the case and control groups
in the mean of SI level and TIBC. Moreover, the mean TIBC level was lower in FS
group compared to the control group but failed to reach a statistically significant level
(p = 0.85) in Salma et al., (2015) study.
Contrary to our observations, Nawar et al., (2017) and Modaresi et al., (2012)
indicated that the mean SI levels were lower significantly among the FS group than
those in the control febrile group without a seizure. However, the mean level of TIBC
in Nawar et al., (2017) study was higher significantly in cases compared to controls.
Moreover, other studies did not show a significant difference in the mean level
of TIBC between cases and controls (Modaresi et al., 2012). While others showed that
there was no significant difference in SI & TIBC levels between case and control
groups (P > 0.05) (Shaikh, Inamdar, & K., 2018; Yousefichaijan et al., 2014).
On the other hand, the mean Tfsat percent in our study was higher in the seizure
group compared to controls with statistically significant difference (p < 0.001). The
findings coincide with Shaikh et al. study which showed that the mean value of Tfsat
in children with FS was higher compared to the control group, but the difference was
not statistically significant (p > 0.05) (Shaikh et al., 2018).
Our findings are inconsistent with the results of different studies who showed
that the mean value of Tfsat in children with FS was lower compared to the control
group, but the difference was statistically non-significant (Miri-Aliabad, Khajeh, &
Arefi, 2013; Potdar et al., 2017; Salma et al., 2015; Sharif, Kheirkhah, Madani, &
Kashani, 2016). Also, Nawar et al., (2017) study showed that "the mean Tfsat level
was lower significantly in cases compared to control (p < 0.001)".
Serum ferritin concentration is a reliable way of examining the body's iron status.
SF is ≤ 12 ng/ml in ID cases. Diagnostic levels raised up to ≤ 30 ng/ml in the presence
of infection/inflammation (World Health Organization, 2001). The disadvantage of SF
75
is that it rises non-specifically with inflammation because it belongs to acute phase
proteins.
The current study showed a fever/infection in both case and control groups;
therefore, any difference in the levels of ferritin between cases and controls could not
be attributed solely to fever. Our study's main limitation is the use of hospital control
that may have introduced a selection bias, as this group of patients shows higher ID
levels than the cases group. It would be better to use community control (Neupane,
Walter, Krueger, & Loeb, 2010), but there are ethical difficulties in taking blood in
well children unless there is an ID screening program with adequate treatment in
children.
In the present study and concerning SF and Hb, the mean levels in the case
group were lower compared to the control group but the differences were statistically
non-significant (p > 0.05). This agrees with a study carried out by Shaikh et al., (2018)
who showed that the mean values of SF and Hb in patients with FS were lower than
the control group, but the difference was statistically not significant (p > 0.05). Also,
similar observations were seen in the studies carried out by Kamalammal & Balaji,
(2016); Kunwar Bharat et al., (2015); Miri-Aliabad et al., (2013).
Differently, different studies showed that the mean levels of SF and Hb in the
case group were lower significantly when compared to the control group (p < 0.001)
(E. D. Kumar & Annamalai, 2017; Naseer & Patra, 2015; Nawar et al., 2017).
On the other hand, different researchers' results disagree with our findings. They
reported that SF levels are significantly higher among cases compared to controls
(Bidabadi & Mashouf, 2009; Potdar et al., 2017). Derakhshanfar, et al. (2012) results
showed that the mean Hb level in cases was significantly higher compared to controls.
The mean levels of sTfR in the present study were lower in cases in comparison
to controls but the difference failed to reach a statistically significant value (p > 0.05).
Similar observation was seen in Papageorgiou et al., (2015) study. Another study did
not agree with our results, where the sTfR level in cases was higher than controls (p =
0.007) and suggesting that sTfR was a risk factor in children with FS (Salma et al.,
2015).
76
Our data clearly reveals that there were no significant differences between the
two groups (p > 0.05) in the mean levels of Hct, MCH, MCHC, and RDW. The mean
levels of MCV were significantly higher (p = 0.045) and RBCs count was significantly
lower (p = 0.002) in cases compared with controls. In a study carried out by Azizet
al., (2017) they reported that "the mean level of Hct, RBCs, MCV, MCH, MCHC, and
RDW were significantly lower in cases compared to controls", which was in agreement
with our finding in the mean level of RBCs count only. Moreover, Yousefichaijan et
al., (2014) and Derakhshanfar, et al., (2012) showed that "the mean level of Hct, MCV,
MCH, and MCHC were higher significantly in the FS group in comparison to the
control group", which agrees with our finding in the mean level of MCV.
According to our results, 34 (85.0%) of children in the case group and 32
(80.0%) in the control group were anemic, revealing no significant relationship (p =
0.556). The results also show that 32.5% of cases had an ID and 32.5% had IDA while
the controls 40.0% had ID & 30.0% had IDA with no statistically significant difference
between the results. The findings of the previous studies are controversial; some of
them concluded that ID &/or IDA caused intensification of FS, others mentioned
protective effects of ID &/or IDA against FS and the remaining confirmed our results.
Moreover, the study by Kamalammal & Balaji, (2016) showed no strong
association between IDA and FS. Similarly, Amirsalari et al., (2010) indicated that
there was no relationship between IDA and FS. In addition, in the research by Miri-
Aliabad et al., (2013), 44% of the cases and 36% of the controls were diagnosed with
anemia.
On the other hand, Derakhshanfar et al., (2012) reported the lower risk of FS in
anemic children. Similarly, Bidabadi & Mashouf, (2009) indicated that "IDA was
less frequent among FS than controls". The incidence of IDA was higher significantly
in controls compared to the cases as the results of another study by Yousefichaijan et
al., (2014) which revealed that "22.5% of children in the group of FS were anemic
compared to 34.0% in the control group (p < 0.001)".
While Momen et al., (2010) claimed that ID was more common among the
children with the first episode of FS. Kumar & Sasikumar, (2015) reported also the
higher susceptibility to FS in the cases with ID, which is consistent with the results
77
obtained by Kankane & Kankane, (2015) and Sreenivasa et al., (2015). In other
researches, Fallah et al., (2013) and Ghasemi & Valizadeh (2014) considered IDA to
be a risk factor that might be involved in FS. The findings showed a higher rate of ID
in FS cases compared to healthy controls in the study by Hartfield et al., (2009)
suggested that screening for ID should be considered in FS - presented children.
Febrile seizure is a multi-factorial disease. Independent risk factors for FSs
include the rise of temperature, family history of FS, fever episodes each year, history
of smoking or alcoholism during pregnancy. It was also found that children with IDA
mostly have low socioeconomic status and may have a deficiency of other
micronutrients like Zn, Mg, selenium, and Cu which may act as important confounding
factors (Huang et al., 1999).
Possible factors that may cause contradictory of the results of various studies
include different diagnostic criteria for the diagnosis ID &/or IDA, sample size, age of
patients in each study, nutritional status, geographical area, retrospective nature of
many studies and the background prevalence of ID &/or IDA. However, even with
greater frequency of anemia in patients, a causal relationship cannot be assumed
between ID and FS. More prospective studies with a larger sample size should be
conducted. Furthermore, another possible explanation is that the rate of anemia is high
(59.7%) in our population (El Kishawi et al., 2015), the difference between the ratio
of anemia in FS patients and controls is not high enough to show a significant
difference.
The current study showed that the mean count of neutrophils (103/Fl) in
children with FS was lower significantly compared to the control group (40.0 versus
50.6; p < 0.002). Our results agree with Goksugur et al., (2014) and Yigit et al., (2017).
Higher counts of neutrophils may correlate with the more advanced inflammatory
process in the control group. Children with fever without seizure were entered to the
hospital at the peak of the febrile illness (with the highest value of the body
temperature). The count of neutrophils may also be predicted to be higher than those
in the children with FS.
Contrary to our observations, Gontko–Romanowska et al., (2017) reported that
the mean count of neutrophils among FS children was higher than among febrile
78
children without seizures (62.55 vs. 48.48; p < 0.001). During the intense activity of
skeletal muscle (e.g., seizures and chills), may result from an inflammatory reaction
(after 4-5 hours) or may be associated with the presence
of circulating toxins in the blood, the number of neutrophils can increase temporarily
and rapidly.
In comparison with febrile children without a seizure, FS children had high
mean counts of lymphocytes and the difference was statistically significant. This result
is inconsistent with Gontko–Romanowska et al., (2017) who showed that lymphocytes
count in FS-children were lower significantly compared to febrile children without
seizures. In our study, the main cause of fever was URTI (85%) in children with FSs
which may results of viral infection this lead to a higher count of lymphocyte, as
expected, higher lymphocytes seen in viral than in bacterial infections (Inoue &
Willert, 2018; Korppi, Kröger, & Laitinen, 1993).
In children with FS, the levels of CRP were lower significantly compared to
children in the control group (3.0 vs 8.5 mg/L; p < 0.001). This may depend on the
infection which leads to a significant increase in children's body temperature, usually
viruses. The half-life of CRP is about 19 hours long, begins to rise after 12-24 hours
of an inflammatory response, and peaks within 2-3 days. The presence of infection
causes an increase in CRP values. Children with FS may be suspected of developing
inflammatory processes and increasing body temperature to very high values fast
enough that CRP levels do not reach their highest values. In febrile children without
seizures, the inflammatory process grew slowly enough to achieve higher levels of
CRP (Gontko–Romanowska et al., 2017; Markanday, 2015).
Several studies evaluated CBC in febrile and FS children but they did not
analyze the inflammatory mediators. However, Gontko–Romanowska et al., (2017)
showed that the mean CRP levels in FS children were lower significantly in
comparison to children without seizures (15.73 versus 58.50 mg/L; p < 0.001) which
is similar to our observation.
79
5.3.2 Zinc and Magnesium
The functions of TEs in CNS were emphasized in recent years and are
considered to play a role in the production of certain brain neurotransmitters. Zn is
one of these most important TEs. It enters in many metalloenzyme structures and acts
in the CNS as a neurotransmitter or neuroregulator (Burhanoğlu, Tütüncüoğlu, Tekgül,
& Özgür, 1996). It is a fundamental component of body enzymes that modulates CNS
activities. CSF hypozincemia activates NMDA receptors or disinhibits GABAergic
action, thus resulting in FS (Joshi, 2014). Several studies in this field were performed,
some of which showed that hypozincemia was associated with FS, while few
concluded that no association exists.
Most of the authors have compared the mean levels of serum Zn in children
with FS cases and controls, while others have also studied the number of cases having
hypozincemia in a given subject population. In the present study, data were analyzed
by both these methods. As recommended by WHO, the cut-off value for hypozincemia
that was used is 65 Fg/dl (Simon-Hettich et al., 2001; World Health Organization,
2004).
In our study, the mean level of serum Zn in the case group was lower (77.3
Fg/dl) compared to the control group (78.8 Fg/dl). The percentage of hypozincemia in
cases was 15.0% compared to 7.5% in controls but the differences were not statistically
significant. Similar to our observations, different studies found that the difference in
the concentration of serum Zn in children with FS and control groups were not
statistically significant (ÇELİK et al., 2012; Kafadar et al., 2012; Salah et al., 2014;
Singh & Yadav, 2018; Uluhan, Yucemen, Unaldi, & Güvener, 1990).
On the other hand, different studies disagree with our results. They found that
Zn levels are significantly lower in the case group compared to those in the control
group (Bonu S, 2016; Burhanoğlu et al., 1996; Choudhury & Sidharth, 2016;
Ehsanipour et al., 2009; Ganesh & Janakiraman, 2008; L. Kumar, Chaurasiya, &
Gupta, 2011; Palliana, Singh, & Ashwin, 2010). While in another study, Gatoo et al.,
(2015) reported that "hypozincemia in the presence of other risk factors of FS may
enhance the occurrence of FS".
80
The relationship between low levels of Zn and convulsion is not understood
whether it is a cause or a result. The lower levels of serum Zn in the FS group were
elucidated by the fact that Zn levels decrease in cases of acute infection and stress, and
that Zn is found in concentrated levels in recovering tissue (Kafadar et al., 2012).
Magnesium is involved in neuronal function and inhibits the calcium
facilitating effects on synaptic transmission and also exerts a voltage-dependent
blockage of NMDA receptor channel. Mg's effect on the nervous system is that it
reduces acetylcholine releasing at the neuromuscular junction by antagonizing calcium
ions at the presynaptic junction, reduces nerve excitability and acts as an
anticonvulsant, reverses cerebral vasospasm (Sreekrishna et al., 2016).
Hypomagnesemia has been suggested to have significant effects on the CNS,
particularly in causing seizures. An alteration of Mg levels in the plasma and
intracellular matrix has suggested that the cell membranes will be impaired
functionally, which could cause a seizure. Recent evidence indicates that in FS, Mg
deficiency can play an important role (Sreekrishna et al., 2016). The deficiency of this
element is therefore assumed to have a contributing effect on the incidence of FS.
In our study, we observed that mean serum levels of Mg were lower
significantly in the FS group when compared with controls. Percentage of cases with
hypomagnesemia (25.0%) was higher compared to controls (10.0%) but the difference
was not statistically significant (p = 0.288).
Chhaparwal et al., (1971) found out that levels of serum Mg were low
significantly among children with FS than that of normal children in the same region,
boosting the hypothesis that "Hypomagnesemia may be related to the occurrence of
FS". Later on, different studies indicated that the levels of serum Mg in children with
FS were lower significantly when compared to normal children which strengthened
this association (Bharathi & Chiranjeevi, 2016; Mishra, Singhal, Upadhyay, Prasad, &
Atri, 2007; Namakin et al., 2016; Nemichandra et al., 2017; Salah et al., 2014; Sherlin
& Balu, 2012; Talebian et al., 2009).
In contrast to our results and in separate studies, it was reported that the level
of serum Mg in children with FS is in the normal range. The results indicate that there
81
was no role for serum Mg in the case of FSs (Donaldson, Trotman, Barton, &
Melbourne-Chambers, 2008; Rutter & Smales, 1976; Sreekrishna et al., 2016).
Overall, two major reasons for diversity in results were the difference in the
target population of studies and sample sizes. Given present discrepancies among
findings, it seems that there is a need for further researches with larger sample sizes or
different methodologies to show the role of Mg in inducing convulsion in febrile
children.
The mean levels of SI had a negative correlation which is statistically
significant with hs-CRP. A Similar finding was observed in Richardson et al. study
(Richardson, Ang, Visintainer, & Wittcopp, 2009). In addition, our results also showed
a significant negative correlation of SI with RDW. In contrast, SI showed a significant
positive correlation with MCV and MCH. In this aspect, a similar finding was
observed (Hadler, Juliano, & Sigulem, 2002).
Our results also showed that the mean levels of sTfR have a moderate negative
correlation which is statistically significant with age, our results are in line with a
physiological perspective of Kratovil et al., (2007) study who found that sTfR levels
appear to be high during the toddler period, a period in which ID is common, is
potentially novel finding because it suggests that there may be increased physiological
need for iron during this time. Increased sTfR levels reflect increased RBC surface
expression of transferrin receptor on RBCs which in turn reflects increased iron need.
In addition, our results also showed a significant negative correlation of sTfR with Hb,
and MCV, and it showed a significant positive correlation of sTfR with RDW, this is
in agreement with Çulha & Uysal, (2002) and Yoon et al., (2015) studies which
indicated that the serum sTfR levels are significantly correlated with other diagnostic
iron parameters of IDA.
On the other hand, the mean levels of serum Mg showed a significant negative
correlation in our study with the age of onset.
82
83
Chapter 6
Conclusions and Recommendations
6.1 Conclusions
The conclusions of the present study are:
1. The main cause of fever was URTI which accounts for (85%) of children with
FSs.
2. The mean MCV was significantly higher and RBCs count was significantly lower
in cases compared with controls.
3. The mean levels of SI and Tfsat were significantly higher and TIBC was
significantly lower among the cases with FS compared to controls.
4. The incidence of ID & IDA was higher among the control group compared with
the case group.
5. In children with FS, the mean level of hs-CRP was lower significantly than in
children without seizures.
6. The mean count of neutrophils in FS children was significantly lower than in the
control group. While, the mean count of lymphocytes was higher significantly
among children with FS in comparison to febrile children without seizures.
7. The mean level of serum Zn and the percentage of Zn deficiency in the case group
was lower than in the control group, but the differences were not statistically
significant.
8. The mean levels of serum Mg were low significantly in FS group when compared
with control group. Despite, hypomagnesemia between cases and controls was
statistically insignificant.
6.2 Recommendations
1. Using Mg loading test to evaluate the Mg stores of the body properly or measure
the physiologically active free, and ionized form of Mg.
2. In FSs, the levels of other micronutrients such as selenium, Cu, and iodine
can be evaluated to uncover the probable etiology.
84
3. Conduction of another study with a larger sample size and different control groups
(e.g. healthy children) to investigate the existing hypothesis that IDA, low serum
and CSF Zn and Mg have significant roles in FSs.
6.3 Limitations
1. The use of only hospital controls in this study may have introduced a selection
bias since these patients are more likely to have higher levels of ID than does the
reference population. A better design would have included two sets of controls:
hospital and community controls.
2. Different definitions and different parameters used for ID diagnosis.
3. Lumbar puncture (LP) is strongly advised in children under one year old with first
FS to rule out meningitis because of the probability of absence of other signs of
infection. For similar reasons, LP is suggested until 18 months (Kliegman et al.,
2016), but after that, performing LP has considerable limitations.
4. The study performed at Al Nassir Pediatric Hospital and the sample size wasn't
large enough. Sample collection was relatively difficult due to the objection of
many parents to participate and the rare of the cases in our country.
85
86
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Annex (1): Helsinki approval
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Annex (2): Ministry of Health facilitation letter
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Annex (3): Questionnaire
I am a researcher: Ohood Mohammed Shamallakh - I am studying at the Faculty of
Health Sciences, Islamic University of Gaza " The Role of Iron Profile Parameters and
Selected Minerals (Zinc and Magnesium) with Febrile Seizures in Children from Gaza
City", As a requirement to graduate and obtain a master's degree in Medical Laboratory
Sciences. I will be very thankful for your help.
Basic Information:
1. Date of interview: / /
2. Research Category
□ Case □ Control
General and Social Information:
1. Name: ....................................................... 1. File Number ....................................
2. Birth Date: ............................................ 3. Age in years ....................................
4.
Gender: □ Male □ Female
5. Address: ........................................................ 6. Telephone/Mobile ........................... 7. Number of household: ( ................. )
8.
Monthly income: □ <1000 NIS □ ≥1000 <2000 NIS □ ≥2000NIS
9.
Home: □ Owned □ Rented
10.
Consanguinity: □ Positive □ Negative Neonatal History:
1. Length of Pregnancy: ( ......................... ) weeks
□ Premature (<37 wks) □ Full term (37-42 wks)
□ Post mature (>42 wks)
2. Type of delivery: □ Normal vaginal, □ CS, □Assisted vaginal 3. Birth weight (………....…) Kg
4. Admission to ICU □ Yes □ No
Medical History:
1. Fever □ Yes □ No
Cause of fever ..........................................................................................
102
2. Febrile seizures □ Yes □ No 3. Type of febrile seizures □ Generalized □ Focal 4. Duration of seizure □ < 15 minutes □ > 15 minutes 5. Number of episodes □ Once/24hr □ More than once/24hr
6. Past history of febrile
seizures □ Yes □ No
If yes;
- Mention age of onset of seizure ..........................................................................................
-How many times it occurred/ year?...........................................................................................
7.
Family history of
febrile seizures
□ Yes □ No 8. Family history of epilepsy □ Yes □ No The clinical examination
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Value Vital Signs
............... °C Temperature at admission 1.
................ g/dl Hemoglobin level at
admission
2.
............... (bpm) Heart rate 3.
............... cm Length or Height 4.
............... kg Weight 5.
............... Body Mass Index (BMI) 6.
............... Weight-for-age 7.
103
Date: / /
- Name: .................................................. - File Number:
..........................................
The laboratory tests
Any further tests/comments:
Thank you
Normal Range Results Test Name
28-135 µg/dL Serum iron level 1.
µg /dL TIBC 2.
% Transferrin Saturation 3.
Male: 25-350 ng/ml
Female: 13-232 ng/ml
Serum Ferritin Level 4.
8.7- 28.1 nmol/L Soluble Transferrin Receptor
(sTFR)
5.
60-120 µg/dL Serum Zinc Level 6.
1.5-2.3 mg/dL Serum Magnesium Level 7.
< 2.8 mg/L High-Sensitivity C-Reactive
Protein (hs-CRP)
8.