The Association of Iron Profile Parameters and Selected ...

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


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


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

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.

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


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


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


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


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.

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).

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


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


% 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.

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.

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.

86

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Annex (1): Helsinki approval

100

Annex (2): Ministry of Health facilitation letter

101

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.

The Association of Iron Profile Parameters and Selected ...

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