Lung Function in Children with and Without Sickle Cell Anaemia at the Lagos State University Teaching Hospital

LUNG FUNCTION IN CHILDREN WITH AND WITHOUT SICKLE CELL ANAEMIA AT THE LAGOS STATE UNIVERSITY TEACHING HOSPITAL

A DISSERTATION SUBMITTED TO THE FACULTY OF PAEDIATRICS, NATIONAL POST GRADUATE MEDICAL COLLEGE OF NIGERIA, IN PART FUFILMENT OF THE REQUIREMENTS FOR THE AWARD OF THE FELLOWSHIP OF THE COLLEGE IN PAEDIATRICS.

FALETI, ABIODUN OLUSEYI

M.B. , Ch. B. (IFE) 1993

NOVEMBER, 2012

DECLARATION

It is hereby declared that this work is original unless otherwise acknowledged. The dissertation has not been presented to any other College for a Fellowship.

……………………………………………

Dr Abiodun Oluseyi Faleti.

CERTIFICATION PAGE

We certify that Dr Faleti Abiodun Oluseyi carried out the study under our supervision. We also supervised the writing of the dissertation.

…………………………………………… Dr O Ogundipe, FMC Paed, 1971

…………………………………………………

Dr OF Njokanma, FMC Paed, 1990

TABLE OF CONTENTS PAGES

DECLARATION i

CERTIFICATION ii

TABLE OF CONTENTS iii

ACKNOWLEDGEMENTS iv

DEDICATION v

LIST OF ABBREVIATIONS vi

LIST OF TABLES vii

LIST OF FIGURES viii

SUMMARY x - xii

INTRODUCTION 1

LITERATURE REVIEW 3

JUSTIFICATION 40

AIMS AND OBJECTIVES 41

SUBJECTS AND METHODS 42

RESULTS 53

DISCUSSION 91

CONCLUSIONS 97

RECOMMENDATIONS 98

LIMITATIONS 99

AREAS OF FUTURE STUDY 100

REFERENCES 101 APPENDICES 113-121

ACKNOWLEDGEMENTS

I am grateful to the Almighty God for seeing me through this journey and the Holy Spirit for his comfort and strength to carry on.

Special thanks go to Prof OF Njokanma and Prof Oluyinka Ogundipe my supervisors who provided some of the materials used, supervised the work and made me feel welcome every time

I went to them. God bless you, Sirs. I also thank Dr SO Akodu for providing valuable assistance during the analysis of the results. I am also grateful to all the consultants and senior colleagues that I worked with during my residency training programme at Lagos State University Teaching

Hospital (LASUTH), Ikeja for their training and advice.

I wish to thank my assistants Gbemi Adeniyi and Peju Ogunkoya for helping out with the anthropometric measurements and laboratory investigations respectively.

I wish to thank my wife, Mrs .Abidemi Adetoun Faleti, my children, Temiloluwa Atoke and

Oluwatoni Aremu for their understanding during the work.

I thank my parents Mr and Mrs Faleti, my siblings Bosede Adeyemi, Bolanle Faleti and Segun

Faleti and my in-laws Mr and Mrs Olaifa, Funke Afolabi, Folake Olaifa, Ayodeji Olaifa and

Debo Olaifa-Olaibi for their prayers and support.

DEDICATION

This work is dedicated to my wife, Mrs Abidemi Adetoun and my children Temiloluwa and

Oluwatoni for their understanding during my residency training.

LIST OF ABBREVIATIONS

Acute chest syndrome……………………………………ACS

Body mass index………………………………………...BMI

Circumference…………………………………………...Cir

Force Expiratory Flow………………………………… FEF

Force expiratory volume in one second………………...FEV1

Force vital capacity……………………………………..FVC

Force Expiratory Volume percent………………………..FEV1%

Haemoglobin genotype AA HbAA

Foetal haemoglobin………………………………………HBf

Haemoglobin genotype SS………………………………HbSS

Litre ……………………………………………………..L

Minute……………………………………...... Min

Peak Expiratory Flow Rate……………………………… PEFR

Pulmonary function test…………………………………PFT

Coefficient of determination …………………………… R2

Red blood cell……………………………………………RBC

Sickle cell anaemia……………………………..………..SCA

Sickle cell chronic lung disease…………………………SCCLD

Standard deviation………………………………………SD

Standard error of the estimate……………………………SEE

Total lung capacity………………………………………TLC Vital capacity……………………………………………VC

LIST OF TABLES PAGE

Table I: Uses of pulmonary function test. 19 Table II: Subjects distribution into age groups. 46 Table III: Demographic characteristics of study population 54

Table IV: Anthropometric distribution of study subjects 56

Table V: Pulmonary Function Test values in HbSS and genotype AA subjects. 57 Table VI: Social strata and age specific prevalence of obstructive lung abnormality among HbSS study subjects 66

Table VII: Social strata and age specific prevalence of restrictive lung abnormality among HbSS subjects. 67

Table VIII: Socio-demographic characteristics of children with obstructive lung abnormality among HbSS 69

Table IX: Socio-demographic characteristic of children with restrictive lung abnormality among HbSS 70

Table X: Summary of correlation coefficients between pulmonary function test indices and age/anthropometry among male study subjects 75

Table XI: Comparison of correlation coefficients between pulmonary function test

indices and age/anthropometry among female HbSS subjects and HbAA controls. 80

Table XII: Regression of predictor(s) on FVC of female control subjects (n = 50) 82

Table XIII: Regression of predictor(s) on FVC of male control subjects (n = 50) 83

Table XIV: Regression of predictor(s) on FEV1 of female control subjects (n = 50) 85

Table XV: Regression of predictor(s) on FEV1 of male control subjects (n = 50) 86

Table XVI: Regression of predictor(s) on PEFR of female control subjects (n = 50) 87

Table XVII: Regression of predictor(s) on PEFR of male control subjects (n = 50) 88

Table XVIII: Regression equations for predictors of FVC, FEV1 and PEFR in male and female control subjects 89

Table XIX: Comparison between predicted values generated using regression equations from current study and Iranian study. 90 LIST OF FIGURES PAGE

Figure 1: Subdivisions of lung volume 16

Figure 2: Spirometry Volume Time Curve 21

Figure 3: Spirometry flow volume loop 22

Figure 4: Spirometry volume loop showing PEFR, Forced expiratory and Forced inpiratory flow 23

Figure 5: spirometry obstructive volume loop 25

Figure 7: Spirometry mixed obstructive restrictive volume loop showing reduced FVC (A), normal FVC (A2), TLC in abnormal and normal condition (B), reduced PEF (C) and normal PEF (C2). 27

Figure 8: Pulmonary function indices in male HbSS and AA subjects according to age with FVC and FEV1 in centiliters and PEFR in liters per minute. 59

Figure 9: Pulmonary function indices between female HbSS and AA subjects according to age with FVC and FEV1 in centiliters and PEFR in liters per minute. 59

Figure 10: Pulmonary function indices in male HbSS and AA subjects according to weight with FVC and FEV1 in centiliters and PEFR in liters per minute. 61

Figure 11: Comparison of pulmonary function indices between female HbSS and AA subjects according to weight with FVC and FEV1 in centiliters and PEFR in liters per minute. 61

Figure 12: Pulmonary function indices between male HbSS and AA subjects according to height with FVC and FEV1 in centiliters and PEFR in liters per minute 62

Figure 13: Pulmonary function indices between female HbSS and AA subjects according to height with FVC and FEV1 in centiliters and PEFR in liters per minute 62

Figure 14: Pulmonary function indices between male HbSS and AA subjects according to arm span with FVC and FEV1 in centiliters and PEFR in liters per minute. 64

Figure 15: Pulmonary function indices between female HbSS and AA subjects according to arm span with FVC and FEV1 in centiliters and PEFR in liters per minute. 64

Figure 16: Relationship between FVC and standing height among male study subjects 72

Figure 17: Relationship between FEV1 and standing height among male study subjects 73

Figure 18: Relationship between PEFR and standing height among male study subjects. 74

Figure 19: Relationship between FVC and standing height among female study subjects. 77

Figure 20: Relationship between FEV1 and standing height among female study subjects. 78

Figure 21: Relationship between PEFR and standing height among female study subjects. 79

SUMMARY

Sickle cell anaemia (SCA) is a chronic disorder with multi-systemic manifestations. The burden of the disease is highest in sub-Saharan West Africa, especially Nigeria, where approximately

4.2 million people are believed to be living with the disorder. Although much is known about the clinical presentation and complications of the disease, studies on lung function in children with sickle cell anaemia have not received enough attention. The study was therefore conducted to determine the pattern of lung function abnormality, if any, in children with sickle cell anaemia.

A prospective, cross-sectional study was conducted between 15TH March 2011 and 17th June

2011 involving 200 children aged five to twelve years, 100 each with genotype SS and AA.

Measurements taken included height, sitting height, weight, arm span, chest circumference and body mass index. Pulmonary function indices like peak expiratory flow rate (PEFR), forced vital capacity (FVC) and forced expiratory volume in one second (FEV1) were measured using One

Flow Spirometer (Clement Clerk International, England) while FEV1% was derived from the values of FVC and FEV1.

Mean weight (26.71kg), sitting height (65.48cm), arm span (131.58cm) and body mass index

(15.68kg/m2) of controls were significantly higher than corresponding figures for HbSS subjects

(23.64kg, 63.72cm, of 126.45cm and 14.64gk/m2 respectively): p < 0.05 in each case. Also, mean lung function test indices were lower in HbSS subjects (PEFR: 214.95 L/min Vs 230.30

L/min, FVC: 1.52 L Vs 1.71 L, and FEV1: 1.30 L Vs 1.48 L, p < 0.05 in each case). However, with regard to FEV1%, the mean values 86.94% for AA was higher than 85.75% for SS subjects but the difference was not significant (p = 0.08).

A total of six HbSS subjects were identified with obstructive lung disease giving a prevalence of

6% while none were found among controls. The prevalence was highest among subjects in the lower socio-economic strata at 7.8% of obstructive lung disease in comparison to 4.5% and 3.9%, of middle and upper socio-economic strata respectively. The prevalence of obstructive lung disease also increased with age with the highest prevalence of 13.6% in age group 11 to 12 years.

Also, the 11.1% prevalence of obstructive lung abnormality among those with family size of five or more was higher than 5.5% observed in those with family size less than five suggesting that overcrowding may influence the prevalence of obstructive lung disease. HbSS subjects who had been hospitalized up to three times in the past had a 19.0% prevalence of obstructive lung disease in comparison to 2.5% among those with lower number of hospitalizations. With regard to restrictive lung abnormality, an overall 5% prevalence (five subjects) rate was recorded among subjects. The highest prevalence of 8.0% was found in lower socio-economic strata while the upper and middle strata had prevalence of 4.2% and 3.9% respectively. The prevalence of restrictive lung abnormality was also higher in older subjects: 10% in children aged ≥ nine years compared to 3.3% in the seven to eight years age group. Family size greater than five was associated with higher prevalence of 11.1% compared to 4.4% with smaller family size. Also, higher prevalence of 23.8% was observed among those with three or more admissions related to respiratory problems. No case of restrictive lung abnormality was identified in those with fewer admissions.

There was a strong positive correlation between pulmonary function variables and anthropometric parameters such as standing height, sitting height, arm span, chest circumference and weight (range of “r” between 0.694 to 0.939) while a weak positive correlation was observed in the case of BMI (range of “r” between 0.415 to 0.482).

Multiple regression analyses with pulmonary function indices as the outcome variable of interest and anthropometry (height, weight and age) as independent variables showed that combination of height and age had the highest coefficient of determination (R2 = 0.844 and 0.824), as well as the lowest standard error of the estimate (SEE) of 0.173 and 0.211 for the prediction of FVC among female and male controls respectively. The use of other possible anthropometric combinations resulted in lower R2 range and higher SEE range. In the same manner, height and age had the highest R2 of 0.848 and 0.837, as well as the lowest SEE of 0.173 and 0.175 for the prediction of FEV1 among male and female controls respectively. The PEFR prediction was also highest with the use of height and age with R2 of 783 and 761, as well as SEE of 28.222 and

26.118 for male and female controls respectively. The predicted values were used in determining the pattern of lung function abnormality among HbSS subjects.

In conclusion, children with sickle cell anaemia have reduced pulmonary function compared to their AA counterparts. Therefore, there is a need for routine pulmonary function study among children with sickle cell anaemia during follow up clinic visit for early detection of pulmonary function abnormality. This is particularly important because the use of bronchodilators has been found to reduce the frequency of acute chest syndrome thereby reducing the rate of deterioration of lung function. INTRODUCTION

Sickle cell disease is one of the commonest genetic disorders worldwide and is the most common inherited haematological disease affecting man.1 This condition is inherited as an autosomal recessive disorder. The homozygous state otherwise known, as sickle cell anaemia is a lifelong disorder affecting about 2-3% of Nigerians 2 especially children, and this makes it a major health problem in Nigeria. With the population of Nigeria at about 140 million and of which about 50% are children, 3 it is estimated that there are about 4.2 million Nigerians suffering from sickle cell anaemia. With a carrier state prevalence of about 25%, 2 about 25 million of Nigerian children carry the sickle cell gene which though, is associated with little or no morbidity, is a setting for transmitting the homozygous state which reduces life expectancy to 42-48years.4.

One major mechanism in the pathophysiology of sickle cell anaemia is the sickling phenomenon in which there is obstruction of the microvasculature by abnormally shaped (sickle) red blood cells. This phenomenon affects all organs and tissues of the body including the lungs.5 In the lungs, sickle cell anaemia is associated with complications such as acute chest syndrome, pulmonary thromboembolism, pulmonary fat embolism and lung fibrosis. Recurrence of these conditions may lead to deterioration of lung function as a result of potential complications such as lung fibrosis, chronic hypoxia and pulmonary hypertension.6 Lung function abnormality in sickle cell anaemia can be obstructive, restrictive or both. These abnormalities also referred to as chronic lung diseases are often heralded by recurrent acute chest syndrome in late infancy and early childhood. It is progressive in nature and continues into adulthood causing pulmonary hypertension, heart diseases and death. 7,8

In Nigeria, there have been studies of lung function in healthy children and in children with asthma. On the contrary, limited studies are available on lung function of children with sickle cell anaemia. In one of the few available studies, Vanderjagt et al 9 studied lung function in children and young adults attending the sickle cell clinic at the

Federal Medical Center, Gombe and the Jos University Teaching Hospital, Jos and concluded that abnormal lung function can occur in Nigerian children with sickle cell disease compared to controls

With improved management, the life expectancy of SCA patients has increased significantly over the years.

Consequently, complications of the disease associated with long-standing illness would expectedly increase in prevalence also. Pulmonary complications account for significant morbidity and mortality in patients with sickle cell disease. Sickle cell chronic lung disease can manifest as restrictive and or obstructive lung diseases, pulmonary hypertension and radiographic interstitial abnormalities6,7. These complications can cause deterioration in lung function that can impact negatively on the quality of life of patients and may lead to mortality if not detected early and managed appropriately. A study of lung function in children with and without sickle cell anaemia is desirable for elucidating the pathophysiology of the disease. This will enable better understanding of progression of morbidity and clinical problems associated with this disease.

LITERATURE REVIEW

Sickle cell disorder is the umbrella term used for a group of conditions in which red blood cells undergo sickling when deoxygenated. In some cases, there is homogenous inheritance of two sickle cell genes. This leads to the haemoglobin genotype SS called sickle cell anaemia. In other cases, there is heterozygous inheritance of the sickle cell gene as well as another abnormal haemoglobin leading to diverse haemoglobin genotypes like haemoglobin SC, haemoglobin SD and haemoglobin-S-beta thalasaemia. Sickle cell anaemia (Haemoglobin SS) is the most severe sickle cell disorder while haemoglobin-SD is the mildest. Haemoglobin SC and haemoglobin S beta thalasaemia are in-between with variable overlap in severity.14 The prevalence of sickle cell anaemia varies worldwide being highest in the West African subregion. Homozygous prevalence is about 2-3% while the heterozygous is about 25% - 30%

2,10.

Herrick in 1910 first observed sickle shaped red blood cells in an acutely ill black Grenadian dental student11. This brought about the initial thought that the sickling phenomenon was confined to the blacks and people living around the Mediterranean region11. With subsequent studies, it was confirmed that the distribution of the sickle cell gene is highest in, but not limited to blacks12. In 1949, the genetic basis of sickle cell anaemia was demonstrated13. The origin of the sickle cell gene is not exactly known, but is thought to be as a result of gene mutation arising spontaneously in different geographic areas as suggested by restriction endonuclease analysis14. Restriction endonuclease, an enzyme found in bacteria and archaea is used in genetic engineering to study DNA structure with the aim of determining its characteristics and origin. In sickle cell disease, restriction endonuclease has been used to identify four major different subtypes of Hb S genes; these are Benin, Senegalese, Bantu, and Meditaranian14. The result suggested that Hb S genes may have spontaneously mutated at these four areas independently as opposed to the initial belief that Hb S gene arose from West Africa and later spread to other areas through human migration.

PATHOGENESIS OF SICKLE CELL DISEASE

Haemoglobin S arises from a mutation substituting thymine for adenine in the 6th codon of the beta chain gene i.e.

GAG to GTG. This leads to coding of valine instead of glutamine at position 6 of the beta chain. The resulting haemoglobin has the physical property of forming polymers under deoxygenated conditions. The deoxygenation of

SS erythrocytes leads to intracellular haemoglobin polymerization to form spindle shaped crystalline gel-like structures called tactoids. 15 Tactoid formation leads to loss of deformability and increased mechanical fragility. The gel-like form of Hb is in equilibrium with its liquid-soluble form, and a number of factors influence this equilibrium.

For instance, low oxygen tension favours polymer formation while in the presence of oxygen the liquid state prevails. Also, the haemoglobin S concentration in the red blood cell favours sickling when it is greater than

20mg/dl. Thirdly, the presence of fetal haemoglobin has an inhibitory effect on gelation.

Generally, HbSS individuals have reduced oxygen delivery to the tissues at the capillary bed.16 This presumably results from intracellular spindle formation and associated vascular obstruction that is unique to sickle cell anaemia.

The microvascular occlusion affects various organs of the body including the lungs where it may manifest as acute chest syndrome, thromboembolism, pulmonary infarction and cor-pulmonale.17

CLINICAL FEATURES OF SICKLE CELL ANAEMIA

Clinical symptoms usually start at about the age of six months. This is due to the high level of haemoglobin F (HBF) which prevents sickling of rbc in newborn and young infants with sickle cell anaemia. The concentration of HBF gradually reduces to its lowest level at about the age of six months when it has least effect on circulatory dynamics thereby rendering its protective effect insignificant.

Dactylitis is usually the first clinical symptom occurring between six months and 24 months. This occurs as a result of recurrent ischaemic necrosis of the small bones of hands and feet. It is believed to be caused by a choking-off of the blood supply as a result of the rapidly growing bone marrow. 18 This is usually associated with tender warm non- pitting swelling of dorsa of hands and feet – Hand-Foot syndrome. Anaemia due to rapid haemolysis in the reticulo- endothelial system is at a rate higher than that of haemopoiesis in the bone marrow. 19 The rapid haemolysis eventually results in jaundice. SCA anaemia patients are prone to recurrent infection because of their inability to kill encapsulated organisms, thus increasing their susceptibility to organisms like Pneumococcus, Klebsiella pneumoniae, Haemophilus influenzae type b and Salmonella typhi. Sickle cell anaemia is characterized by recurrent crisis. The four different types of crisis are hyperhaemolytic crisis, aplastic crisis, acute sequestration crisis and vaso-occlusive crisis. Sickle cell anaemia patients haemolyse during their steady state but in hyper-haemolytic crisis, the rate of red cell destruction is more than expected during the steady state of the disease. Aplastic crisis is bone marrow erythrogenesis depression that may result from parvovirus type b infection while acute sequestration crisis is massive pooling of blood into the spleen and in rare cases the liver. Vaso-occlusive crisis results in severe bone pain as a result of vascular stasis leading to ischaemia at the capillary end. It can also present as acute chest syndrome, rib infarction and atelectasis. Each of these conditions can reduce lung function indices either individually or in combination. Rib infarction causes reduced chest expansion; atelectasis causes alveolar damage and emphysema while acute chest syndrome can reduce lung compliance by causing lung fibrosis. Thus, of the crisis states, vaso- occlusive has the most direct consequence on lung function. Other later features of sickle cell anaemia include bossing of the skull, gnathopathy, long thin extremities, protuberant abdomen, and stunting of growth.

RESPIRATORY COMPLICATIONS OF SICKLE CELL ANAEMIA:

This is classified into infectious and non-infectious complications. Crisis states are very common problems in SCA, but bacterial infection is the commonest cause of morbidity and mortality in children with SCA. 4 Reports from autopsies done on over three hundred and six sickle cell disease patients by Manci et al20 at the University of

Alabama show infection constituting 33-48% of causes of death in all age groups. Infection was heralded by upper respiratory tract syndromes in 72.6% of the cases, most of whom were children. 21 Pneumonia especially that caused by pneumococcus is particularly common in sickle cell anemia patients 22 This is because of associated abnormal compliment activity, poor splenic function and lack of type – specific pneumococcal antibody.23 After early childhood, the spleen in SCA patients undergoes progressive infarction and fibrosis. Even while enlarged, the spleen in SCA is functionally hypoactive in clearance of bacterial particles from the blood.

Non-infectious conditions like, acute chest syndrome, asthma, fat embolism, thromboembolism, lung fibrosis and pulmonary hypertension are common causes of respiratory morbidity in SCA. 17 Acute chest syndrome (ACS) is an acute pulmonary illness that affects patients with SCA and it is defined as new infiltrates on chest radiograph in conjunction with one other new symptom or sign such as chest pain, cough, wheezing, tachypnoea, and or fever greater than 38.50C .24 The incidence of ACS in SCA is 12.8 episodes per one hundred patient years 25 Its incidence is inversely related to age with children between two to four years having the highest incidence of 25.3 episodes per one hundred patient years. The haematologic risk factors for the development of ACS include high steady state leukocyte count, low steady state haemoglobin and low steady state HbF concentration.23 Children often have febrile and pain episodes preceding ACS. There is no known cause of ACS but rather several risk factors such as pulmonary infection, fat embolism, rib infarction, thromboembolism, free radicals and excessive hydration are capable of triggering the disease. 6

Free radicals are potent initiators of acute chest syndrome (ACS). Free radicals are molecules or molecular

- fragments with single unpaired electrons such as super oxide (02 ) and hydroxyl (0H) . They are produced in the normal course of metabolism but the rate of production increases in the presence of tissue damage. Free radicals are aggressive as they attempt to achieve stability by attracting electrons from other molecules. They are very destructive to living tissue and are responsible for organ and tissue damage. Thus, there is a vicious cycle between increased production of free radicals and tissue damage. There is spontaneous generation of free radicals in SCA because of continued tissue damage 26 Free radicals initiate ACS by causing damage to the pulmonary vascular endothelium thereby increasing leukocyte adhesion to the damaged endothelium. The endothelial leukocyte adhesion leads to thrombus formation. The resulting hypoxia distal to the thrombus leads to hypoxic vasospasm and subsequently ischaemia. Ischaemic injury causes release of nitrous oxide, a potent vasodilator that initiates reperfusion of the ischaemic tissues distal to the thrombus thereby reducing free radical generation. In sickle cell disease, the nitrous oxide that is produced is deactivated by the excess free radicals generated. Consequently, increased tendency for generation of free radicals in sickle cell disease leads to recurrent attacks of ACS.27

The various risk factors for ACS have in common the ability to create regional hypoxia, which prevents reoxygenation of RBC returning to the lungs and leaves them in their sickled form. The sickle RBCs are trapped in the pulmonary vascular bed causing hypoxic injury to the lung tissue distal to the blockage. The injured lung and hypoxia promote up regulation of adhesion molecules on the vascular endothelium causing sickled RBC to adhere to the endothelium. 28 Failure to reoxygenate, vascular stasis and inflammation are suspected to create further RBC sickling, microvascular occlusion and pulmonary infarction.29 The most common presentation of ACS at diagnosis are fever, cough, and chest pain.6 Other less common presenting symptoms are shortness of breath, productive cough, wheezing and haemoptysis. On physical examination, tachypnoea, tachycardia, rales and variable degree of hypoxia may be found. Chest radiograph remains the cornerstone of diagnostic test for ACS.6 The radiograph will reveal new infiltrates often involving the lower lobe, but any lobe may be affected. It also can present with normal chest radiographic features and subsequently develop infiltrates and ACS. The limitation of chest radiograph is the fact that the clinical severity of the disease and the degree of hypoxia may not be appreciated on the initial study.30

Therefore supporting investigations such as arterial blood gas analysis which will reveal hypoxia, haemoglobin level which will be reduced, blood culture which may reveal infection as a trigger factor and bronchoscopically collected sputum for microscopy, culture and sensitivity test are essential.

Various studies have revealed that repeated attacks of ACS can reduce pulmonary function in children with SCA. In one of such studies, Sylvester et al 8 at the Guy’s King’s College and Saint Thomas’ Hospital, London studied lung function of twenty children with sickle cell disease aged six to sixteen years with previous history of hospitalization due to ACS and compared the results with twenty children with sickle cell disease of the same age range without previous history of ACS episodes. They measured the FEVI, FVC, FEV/FVC ratio, PEF, FEF(25) of FVC, FEF(50) of FVC, FEF(75) of FVC, lung volumes and airway resistance in both groups. Additionally, fifteen age-matched pairs in the two groups were assessed before and after bronchodilator use. Their result revealed significantly higher mean airway resistance (p = 0.03), TLC (p = 0.01) and RV ( p = 0.003) in the group with ACS than the group without ACS. There were no significant differences in the changes in lung function test results in response to bronchodilator administration between the two groups, but the children with ACS had a lower FEF(25) (p =0.04) and FEF(75) (p = 0.03) pre bronchodilator use and a lower mean FEVI / FVC ratio (p = 0.03) and FEF(75) (P=0.03) post bronchodilator. They concluded that children with sickle cell disease who experienced ACS hospitalization episode had significant differences in lung function compared with those who did not experience ACS episodes.

Acute chest syndrome is the most common cause of death and the second most common cause of hospitalization after pain crisis. Vichinsky et al 6 at Children’s Hospital Oakland with colleagues in three other hospitals did a collaborative study of sickle cell disease. Prospectively, they conducted a one month follow up of 3,751patients aged

66 years and below. The study revealed 1,722 acute chest syndrome episodes in 939 patients making it the commonest presentation after pain. Acute chest syndrome usually starts after vaso- occlusive crisis and it is characterized by respiratory distress. Repeated attacks of acute pulmonary complications such as ACS can progress to chronic pulmonary disease in patients with SCA.32

The chronic lung complications of SCA are usually collectively referred to as Sickle Cell Chronic Lung Disease

(SCCLD). It is defined by radiological and clinical features of ventilatory dysfunction (restrictive and obstructive) and pulmonary hypertension which may later progress to cor-pulmonale. 31 The exact prevalence of and method of diagnosis of SCCLD have not been established owing to lack of detailed epidemiological studies. A recent study done in Nigeria by Fawibe 32 showed a prevalence of 18.9%. This implies that SCCLD may not be as uncommon as previously thought. SCCLD results from pulmonary scarring due to repeated episodes of ACS. 33 It is characterized by progressive disabling dyspnoea, exercise limitation, chest pain of increasing severity, hypoxaemia and pulmonary function derangement. 34 The pulmonary function derangement usually affects the ventilatory and gas exchange function of the lungs negatively. The ventilatory derangement when assessed by lung function testing often reveals obstructive leision in the early stage of the disease while restrictive pattern becomes prominent as the disease progresses 35. Koumbourlis et al35 conducted a retrospective analysis of 63 children with sickle cell disease receiving voluntary pulmonary function testing at Division of Paediatrics, Columbia University and Children Hospital New

York. Thirty five percent of those studied had obstructive lung disease, eight percent had restrictive lung disease while normal pattern was found in fifty-seven percent.

Airway reactivity was suggested to be part of pathogenic mechanism for the obstructive disease while reduction in lung compliance due to repeated episodes of ACS or sickle cell related vasculopathy was thought to be responsible for the restrictive leision. Boyd et al 36 in a related study conducted pulmonary function test on one hundred and two children with sickle cell disease aged six to eighteen years at the Washington University of Medicine, Washington.

The result of pulmonary function test obtained for different clinical conditions were classified as lower airway obstruction in which FEV1/FVC was less than 95% confidence interval adjusted for age, gender, race and height, restriction in which TLC was less than 80% predicted adjusted for gender, age, race, and height, and normal lung function. Seventy-five children had normal lung function, thirteen had obstruction, another thirteen percent had restrictive pattern while one was considered as having combined obstructive and restrictive disease. Incidence rate of pain or ACS were also compared between children with lower airway obstruction or restrictive and children with normal lung function. Children with lower airway obstruction had twice the rate of morbidity compared with children with normal lung function (p = 0.003) while children with restriction did not have different rates of future morbidity compared to children with normal lung function (p = 0.68).

Restrictive and obstructive lung diseases are significant co-morbidity in patients with SCA.37 Obstructive lung diseases such as asthma, bronchiolitis, bronchitis, bronchiectasis and chronic obstructive air way diseases are lung diseases associated with narrowing of the airways such that complete exhalation of inhaled air is very difficult and sometimes incomplete.37 it is usually due to acute inflammation that progresses to chronic inflammation because of oxidative stress resulting from increase in free radical generation.38 The inflammation is often triggered by recurrent viral infections, a well documented risk factor for the development of bronchial hyperresponsiveness and obstructive lung diseases.39 Recurrent inflammation initially causes narrowing of the airways, then scarring and remodeling of the airways and ultimately thickening of the walls of the bronchi and the bronchioles.40 The resulting narrowing of the airways and limitation of airflow will ultimately affect lung volumes significantly.40 A common compensatory mechanism in obstruction is prolongation of expiration and increase in functional residual capacity to allow for increased gas exchange.40 The chronic obstruction will eventually lead to increase in the total lung capacity.41

Obstructive lung disease is characterized by chronic cough with sputum production, wheezing, and dyspnoea.

Physical examination may reveal prolonged expiration, use of accessory muscle of respiration, barrel shaped chest and crackles on auscultation.41 The diagnosis of airway obstruction is based on changes in airflow as evaluated by maximal forced expiratory maneuver. Reduced forced expiratory volume in one second to the forced vital capacity

42 42 (FEV1/FVC) ratio less than seventy percent is diagnostic. Chest radiograph may also show hyper-inflated lungs.

Asthma, a form of obstructive lung abnormality is a topic of controversy in sickle cell anaemia. Difficulty in the diagnosis of asthma in children with SCA is due to the significant overlap in clinical manifestation between an asthma exacerbation and ACS episodes. This has led to the conflicting conclusions concerning prevalence of asthma in children with sickle cell anaemia as against the general population. While some agree that asthma and sickle cell anaemia are distinct co-morbid disease 43,44,45 others are of the opinion that asthma symptoms are a manifestation of sickle cell anaemia,46,47,48,49. Evidence supporting the former opinion includes a similar prevalence of asthma between children with SCA and those in general population and the observation that asthma is inherited in a familial pattern in families of children with SCA.50 In contrast, the latter opinion was argued with various studies46,47,48,49 showing significant evidence that airway hyper-responsiveness and pulmonary function abnormalities are commoner among children with SCA than in general population, suggesting that these clinical features of asthma may be related to the pathogenesis of SCA. Furthermore, Inflammation is known to be critical to the pathogenesis of pulmonary complication in SCA, more so, when anti-inflammatory therapies have demonstrated efficacy in the treatment of ACS.50,51 Since pulmonary complications are commoner in individual with SCA, 7,33 the interaction between asthma, ACS, pulmonary function abnormality and SCA related morbidity and mortality is likely complex and overlapping. Therefore, individuals with SCA who have symptoms of wheezing and diagnosed as asthma but have few other characteristics of asthma, the diagnosis of asthma in such individual may be related to sickle cell anaemia.

Restrictive lung diseases are characterized by reduced lung volume either because of an alteration in lung parenchyma (intrinsic restrictive lung disease) or because of a disease of the pleura, chest wall or neuro-muscular apparatus (extrinsic restrictive lung disease).52 In physiological terms, they are characterized by reduced total lung capacity, vital capacity or functional residual capacity.53 Restrictive lung disorders are accompanied by reduced gas transfer and may be marked clinically by desaturation after exercise.44 The prevalence of restrictive lung disease is difficult to determine because of its multiple aetiology, but it has been found to be high in people with sickle cell anaemia and the prevalence increases with age.35 Other disease conditions associated with restrictive lung disease are interstitial pneumonia, pulmonary fibrosis, pulmonary vasculitis, eosinophilic pneumonia, collagen vascular disease and rib cage deformity among others. Affected patients present with progressive exertional dyspnoea, dry cough, haemoptysis, wheezing, cyanosis, digital clubbing and terminally with features of cor-pulmonale such as loud P2, right sided gallop, and right sided precordial hyper-activity.37 Spirometric testing can be used in the evaluation of restrictive lung diseases. A reduction in forced expiratory volume in one second (FEV1) and forced

53 vital capacity (FVC) in the presence of normal or increased FEV1 to FVC ratio is suggestive of restrictive disease.

Confirmation is however based on total lung capacity (TLC) which can be evaluated through plethismography.54

Pulmonary hypertension is now getting more recognized as a complication of sickle cell anaemia. Repeated episodes of hypoxic events in the pulmonary vascular bed causes ischaemia and altered pulmonary vascular tone. An associated hypercoagulable state causes pulmonary thrombosis of the constricted vessels resulting in progressive loss of the vascular bed and eventually causing pulmonary vasculopathy and pulmonary hypertension.55 Studies conducted have shown that up to 40% of patients have moderate to severe pulmonary hypertension. 56 In a study conducted by Onyekwere et al 56 at the center for sickle cell disease, Howard University, Washington DC; in collaboration with other five hospitals. Fifty-two sickle cell disease children and adolescents were screened for pulmonary hypertension; 24(46.15%) were found to have increased pulmonary arterial pressure. Sickle cell patients with pulmonary hypertension have a significant increased mortality rate compared with sickle cell patient without pulmonary hypertension. 7, 57 Pulmonary hypertension is however not common in younger children. 58

PULMONARY FUNCTION

The respiratory system is vital to human life. The respiratory system takes in oxygen for metabolism while carbon dioxide, which is by-product of metabolism, is expired. The respiratory tract is divided into the upper and lower respiratory tract. The upper respiratory tract begins from the nostrils and ends at the larynx while the lower respiratory tract begins at the trachea down to the lungs.59 The respiratory system is controlled by the respiratory center located largely in the medulla oblongata. Some areas of the cortex also exert control on respiration and this explains the ability of an individual to interfere with respiration such as breath holding and respiratory maneuvers in lung function testing. The functions of the respiratory system include breathing or ventilation, respiration or gas exchange, regulation of body pH, defense against microbes through the activity of the alveolar macrophages, control of body temperature and phonation. Ventilation is the exchange of air between the external environment and the alveoli. It consists of inspiratory and expiratory phases during which air moves from an area of high pressure to an area of low pressure. The body changes the pressure in the alveoli by changing the volume of the lungs through the alternating increase and decrease in volume of the chest cavity. As volume increases, pressure reduces and vice versa. Ventilation is initiated by the contraction of the diaphragm in quiet inspiration while in condition of exercise such as running, abdominal and intercostal muscles are involved. The contraction of the diaphragm increases intrathoracic volume thereby creating a negative pressure in the chest cavity and the lungs within. If the airway is open, air follows its pressure gradient by flowing from the atmosphere with higher pressure into the lungs with lower air pressure to expand and fill the alveoli. As long as pressure within the alveoli is lower than the atmospheric pressure, air will continue to move inwardly. As soon as the pressure equalizes on both sides at the peak of inspiration, the lungs would have stretched to a degree at which the stretch receptors within the alveoli send inhibitory nerve impulses to the medulla oblongata, causing it to stop sending signals to the rib cage and the diaphragm. Thereafter, expiration commences when the muscles of respiration and the lungs undergo elastic recoil. The recoil creates positive pressure gradient in the pleural cavity against the atmospheric pressure. Air then moves from the lungs along the pressure gradient into the atmosphere.

The amount of pressure needed to drive air into the lungs is dependent on lung compliance.60 By definition, compliance is the magnitude of the change in lung volume produced by a change in pulmonary pressure. Low compliance would mean that the lung would need greater than average change in intrapleural pressure to change the volume of the lungs, while high compliance would indicate that little pressure difference in intrapleural pressure is needed to change the volume of the lungs. More energy is therefore required to breathe normally in individual with low lung compliance. Two major factors determine lung compliance. The first is the elastic recoil of the lung tissue.

Any thickening of the lung tissue due to disease will reduce lung elasticity thus decrease lung compliance. The second factor determining lung compliance is the surface tension at air-water interface in the alveoli. This is called the surface tension. The surface tension is modulated by surfactant secreted by type ii pneumatocytes. Whenever the surface tension is increased by disease such as pulmonary oedema, lung compliance is reduced and consequently more energy will be required to inflate the lungs. At the alveolar level, oxygen diffuses by osmosis into the blood in the capillaries surrounding the alveoli while carbon dioxide diffuses in the opposite direction. The oxygen diffuses into the blood because the partial pressure of oxygen in the atmosphere is higher than that at the alveolar capillary bed while carbon dioxide diffuses in the opposite direction because its partial pressure is higher in the blood than in the atmosphere.

LUNG VOLUMES

The air within the lungs is divided into volumes and capacities (Fig 1).61 Dividing the air in such a manner enables the measurement of specific functions using the various pulmonary function tests more accurately. Volumes are measured directly while capacities are inferred from volumes. A wide range of pulmonary function tests is necessary to assess and diagnose pulmonary function abnormalities.

The normal volume of air moved in and out of the lungs during quiet respiration is called the tidal volume (TV).

This volume can be increased voluntarily by breathing deeply. The maximal volume of gas that can be inhaled from the end inspiratory level is referred to as inspiratory reserve volume (IRV). The maximal volume of air that can be expired from the end expiratory level is expiratory reserved volume (ERV). The volume of gas remaining in the lungs at the maximal expiratory level following maximal inspiration is the residual volume (RV). This volume is available for gas exchange. The amount of gas contained in the lungs at the end of maximal inspiration is the total lung capacity (TLC). It is the summation of TV, IRV, ERV, and RV. The maximal volume of gas that can be expelled from the lungs by forceful effort following a maximal inspiration is the vital capacity (VC). It is the sum of the TV, IRV and the ERV and it is normally eighty percent of the TLC. The volume of air that can be maximally inspired from the resting expiratory level is the inspiratory capacity (IC). It is the summation of the TV and the IRV.

The volume of gas remaining in the lung at the resting expiratory level is the functional residual capacity (FRC). It is the summation of the RV and the ERV. Some of the air in the lungs does not participate in gas exchange. Such air is located in the anatomical dead space within bronchi and bronchioles.

Figure 1: Subdivisions of lung volume.

PULMONARY FUNCTION IN SCA

Pulmonary function in sickle cell disease is characterized by gradual reduction in lung function indices with increasing age.62 In a longitudinal analysis of lung function in African American children with sickle cell disease,

Maclean et al 62 at the University of Ontario Children Hospital, Canada, measured lung function in 413 children with sickle cell disease aged eight to eighteen years. The results showed a significant decline in spirometric lung volumes across childhood. The average decline in FEV1, and TLC were 2.93% and 2.15% predicted per year for males and

2.95% and 2.43% predicted per year for females. Various studies in sickle cell anaemia reveal different lung function anomalies such as obstructive lung disease, restrictive lung disease , mixed obstructive restrictive lung disease and abnormal carbon dioxide difuseability.21,35,63 These abnormal lung function tests are thought to result from chronic effects of sickle cell anaemia which worsen with increasing age. Sylvester et al 64 at Kings College

Hospital, London conducted lung function tests on sixty-four children with sickle cell anemia aged five to sixteen years and compared it with lung function study of sixty four children of same ethnic origin and similar age without sickle cell disease. No child was tested within two weeks of an upper respiratory tract infection while children with sickle cell anaemia were not tested within one month of a vaso-occlusive crises. Short acting bronchodilators were also withheld for four hours before lung function testing. After history and physical examination, the weights, height, sitting height, sitting height to standing height ratio were measured. Thereafter, the FEV1, FVC, and PEF were measured using standard spirometer. The children were allowed to rest for twenty minutes and then two hundred micrograms of salbutamol was given via volumatic spacer device. The result showed a significant reduction in FEV1, FVC, and PEF in children with sickle cell disease before and after the use of salbutamol. However, the mean values for children with SCA were not outside the normal range, while only few had sufficiently impaired lung function to classify them as having obstructive or restrictive lung abnormalities. These group of children were ten years and older. However, there may have been underdiagnosis or overdiagnosis because their result was compared with reference range of white children, since race is known to affect lung volumes. 65 Another important finding in the results of the study is that children with SCA did not have significantly higher bronchodilator responsiveness than non SCA children. The restrictive pattern that was reported agrees with study by Pianosi et al66 which also shows increasing restrictive disease in few older children.

In a related study by Onigbinde 67 at Obafemi Awolowo University Teaching Hospital Ife and Ladoke Akintola

University Teaching Hospital, Ogbomooso, a cross sectional spirometric lung function study was performed on 74

SCA patients and 73 sex and age group matched non-SCA controls. It was concluded that generally, the mean values of FVC, FEV1 and FEV % were higher in the controls than in the HBSS subjects. The difference was most significant in FEV1 and FVC and least marked in the FEV%. Reduction of FEV1 and FVC in an individual is suggestive of restrictive disorder while reduction of FEV1 and FEV% signify obstructive disorder. Thus, the finding of significant reduction in FEV1 and FVC imply the possibility of increased restrictive lung disorder in SCA. These findings were thought to be due to high predisposition of the subjects to frequent pulmonary insults like pneumonia, acute chest syndrome and pulmonary infarction that could cause lung impairment and abnormal lung function. The studies by Sylvester and Onigbinde provide good evidence that spirometric lung function test in children with sickle cell disease may be abnormal. There is therefore justification in similar studies among SCA patients so that children with abnormal lung function can be identified early and subsequently provided appropriate management.

LUNG FUNCTION TESTS

The diagnosis and management of patients with pulmonary disease have been improved by the introduction of

Pulmonary Function Test. Tests using tasks that can be performed easily by children are of considerable value to the paediatrician. Two simple tests of pulmonary function, the volume – time (V-T) curve and flow-volume (F-V) curve can provide enough information to diagnose or manage most patients with pulmonary disease. Most children older than five years of age can be taught to perform these tasks with a large degree of reliability.

Uses of pulmonary function studies Pulmonary function tests can help a doctor diagnose a range of respiratory diseases that might not otherwise be obvious to the doctor or the patient. The tests are important since many kinds of lung problems can be successfully treated if detected early.

The tests are also used to measure how a lung disease is progressing, and how serious the lung disease has become. Pulmonary function tests are also used to assess how a patient is responding to different treatments. The uses of pulmonary function test are summarized in the table 1 bellow68.

Table 1: Uses of pulmonary function test.

Diagnosis Clinical Research

(Patient management)

 To characterize pulmonary diseases * To follow the course of *To study changes in lung

physiologically pulmonary disease function with age.

 To evaluate the risks of diagnostic or *To evaluate the response to *To investigate the long- term

therapeutic procedures therapy effects of acute and

 To quantify disease severity *To regulate the duration chronic factors, on lung

 To suggest disease aetiology and form of therapy growth.

 To indicate specific therapy

Assessment of lung function can be done through various techniques such as spirometric lung volume, lung diffusing capacity, respiratory mechanics and plethysmographic lung function assessment.

SPIROMETRY

Spirometry is a medical screening test that measures various aspects of breathing and lung function. It is performed using a spirometer, a special device that registers the amount of air a subject inhales or exhales and the rate at which the air is moved into or out of the lungs. Spirograms are tracings or recordings of the information obtained from the test. The most common spirometric test requires that the subject exhale as forcefully as possible after taking in a full, deep breath. The subject’s effort is called the forced expiratory manoeuvre.

There are two types of spirometers- volume spirometers and flow spirometers. 69 The volume spirometer records the amount of air exhaled or inhaled within a certain time. It records the forced expiratory maneuver as it is produced.

The forced expiratory volume generated is recorded in relation to time. The vertical (y) axis plots volume in liters and the horizontal (x) axis plots time in seconds (Figure 2). The FVC and the FEV1 can be determined with the volume spirometer. Tracings recorded with volume spirometer can also be used for initial diagnosis of obstructive, restrictive or mixed obstructive/restrictive lung disease.

Figure 2: Spirometry Volume Time Curve 61

Many volume spirometers can produce flow/ volume curves and loops with the addition of special electronics or digital circuitry. The flow spirometer measures the rate of airflow in and out, as the volume of air inhaled or exhaled increases. Flow spirometers measure how quickly air flows past a detector and then derive the volume by electronic means. They record the flow rate at very brief intervals, such as 30-300 times a second, and use the data obtained to reconstruct the flow rate at each point in time and volume. This process is called digitalization. Tracings measure flow in relation to volume. The vertical (y) axis plots the rate of airflow in liters per second and the horizontal (x) axis plots volume in liter. (Figure 3) The tracings are not produced during the actual maneuver but instead are reconstructed afterwards from the computerized information that has been recorded.

Figure 3: Spirometry flow volume loop. 61

A normal Flow-Volume loop begins on the X-axis (Volume axis). At the start of the test, both flow and volume are equal to zero. Directly after this starting point the curve rapidly mounts to a peak (Peak Expiratory) Flow. If the test is performed correctly, this PEF is attained within the first 150 milliseconds of the test. The Peak Flow is a measure for the air expired from the large upper airways (trachea and bronchi). After the PEF, the curve descends due to diminished flow as more air is expired. When 25% of the total volume is expired, the parameter FEF25 is reached

(Figure 4). Halfway the curve, when the patient has expired half of the volume, the FEF50 is attained. This is Forced Expiratory Flow at 50% of the FVC. After 75% the volume is expired,

FEF75 is achieved. When the patient has blown out as much air as he can, the flow reaches zero and FVC is reached. After this, it is recommended that the patient make a complete and forced inspiration to obtain a closed flow-volume loop. However, the test can still be interpreted without this as well.

Figure 4: Spirometry volume loop showing PEFR, Forced expiratory and Forced inpiratory flow61

The mean flow between the points FEF25 and FEF 75 is also a very important parameter and is termed the FEF25-

75. This is actually the first parameter that will decline in many respiratory diseases.

A normal, non-pathological flow volume loop will descend in a straight or a convex line from top (PEF) to bottom (FVC) (Figure 4).

It is important to realize that there is no time axis on the flow-volume loop so one cannot interpret time intervals. A healthy patient will expire between 70 and 90% of the FVC in the first second of the test and roughly 5 seconds to expire the last 10 to 30 % of the FVC.

The morphology of the flow-volume loop is very important. To the trained eye, the flow-volume loop tells immediately if the test was well done. If well done, pulmonary function abnormality can also be easily diagnosed.

Pulmonary function abnormality that may be diagnosed or suspected in a flow volume loop include:

(a) Obstructive lung disease: this is characterized by FVC and FEV1 less than 80% of predicted value for age,

75 sex, height and race . In addition, the FEV1 -to-FVC ratio that is more than 8-9 absolute percentage points 75 below the predicted ratio . Global Initiative for Chronic Obstructive Lung Disease also classify it as FEV1 –

to-FVC less than 70%.120

(b) Restrictive lung disease: this is suspected when FVC is less than 80% of predicted value with a normal or

elevated FEV1 -to-FVC ratio for age, sex, height and race. Further diagnostic workup with more

appropriate instrument such as plethysmography is needed to confirm or rule out the suspicion.

If the flow-volume loop is concave, a bronchial obstruction as in case of asthma can be suspected (Figure 5). A patient with obstructive lung disease typically has a concave Flow

Volume Loop in which FEF25-75 and FEV1 will be too low in the presence of normal FVC. The

PEF will also be normal because the air in the large airways can be expired without problems.

The FEF and FEV1 will be low because with obstructive lung disease, the smaller airways are partially blocked, so the air will come out slower. This will result in a lower flow and a sharp fall in the flow-volume.

Figure 5: spirometry obstructive volume loop69

Restrictive lung disease means that the total lung volume is too low. Although an accurate diagnosis of total lung volume is not possible with spirometry because residual lung volume cannot be measured with a spirometer, spirometry results can be very suggestive for a restrictive lung disease. Since the airways are normal, the flow volume loop will have a normal shape, but with a low FVC. In restrictive condition, the total lung volume is low and these consequently results in a low FVC. PEF can be normal or low (Figure 6).

FLOW

A A2

VOLUME

Figure 6: Spirometry restrictive volume loop showing FVC in restrictive condition (A), normal FVC (A2), TLC in restrictive and normal condition (B), PEF in restrictive condition (C) and normal PEF (C2). 69 When there is mixed restrictive-obstructive lung abnormality, the flow-volume loop will have characteristics of both syndromes as explained earlier (Figure 7).

FLOW

A A2

VOLUME

Figure 7: Spirometry mixed obstructive restrictive volume loop showing reduced FVC (A), normal FVC (A2), TLC in abnormal and normal condition (B), reduced PEF (C) and normal PEF (C2). 69

Obstructive diseases or conditions affect the rate at which air can move through the lungs while restrictive diseases interfere with the ability of the lungs to expand. Since spirograms reveal both the rate of airflow and the volume of air moved, they are useful in identifying individuals who have these diseases or conditions. Although spirometry can provide useful diagnostic and screening information, it has a few limitations. Test results can show restrictive or obstructive disease patterns, but they are not disease-specific. For example, a person’s spirogram may show a low

FEV1, but a physician may not be able to determine whether the cause is from asthma, emphysema, or some other obstructive disease. Thus additional information, such as a physical examination, chest radiograph, and exposure histories, are needed to make diagnosis. Spirometry often can detect obstructive diseases in their early stages, but for some of the restrictive diseases, it may not be sensitive enough to show abnormalities before extensive and in some cases, irreversible damage has been done. For example, signs of silicosis and coal workers pneumoconiosis may be found on chest radiograph while spirometry results are still normal. Thus spirometry should not be the sole screening tool of a respiratory surveillance programme

Measurement of lung capacities

- Forced vital capacity (FVC) is the volume of maximally expired air following maximal inspiration. It is the same volume as the VC but exhaled as quickly and forcefully as possible. It is performed with the use of a spirometer to assess flow rate. (Fig 2) The blow is terminated when expiration is proceeding at not more than 25mls/ minute.

Forced vital capacity is reduced in both obstructive and restrictive disorder. If FVC is not less than 80-85% of reference value, it is normal. If FVC is however less than 80%, the patient is subjected to bronchodilator or slow vital capacity (SVC) test. Improvement of 10-15% in FVC is suggestive of obstructive disorder while no improvement is suggestive of restrictive lung disorder. Reduction in FVC is present in both obstruction and restriction; it is however less pronounced and reversible in obstruction.

- Forced expiratory volume in one second (FEV1.0) is a timed subdivision of FVC in the first second (Fig 2). This timed subdivision may also be 0.5second (FVE0.5); 2.0 seconds (FEV2.0) or 3.0 seconds (FEV3.0). FEV1.0 is usually

75-80% of FVC in healthy individuals. FEV1.0 is very useful in the diagnosis of obstructive lung disorder. The degree of reduction in FEV1.0 and FEV1.0 percent (FEV1 / FVC) should lead to the suspicion of obstructive lung disease. Patients with restrictive disorder on the other hand will have reduced FEV1.0 and FVC and both may be equally affected. Therefore, FEV1.0 % may be as high as 80-100% of normal in restrictive lung disorder. If FEV1.0 % is 85% or greater in the presence of low percentage predicted FEV1.0 and FVC, restrictive disorder should be suspected. In the presence of low % predicted FEV1.0 and FVC, a patient with percent predicted FEV1.0 /FVC of 88-

90% or higher has restrictive disorder while someone with percent predicted FEV1.0 /FVC of 69% or lower has an obstructive lung disorder.47,53

- Forced expiratory volume percent (FEV %) is another variable of respiratory volume. It is calculated from FEV1.0 and FVC as follows;

FEV1.0/FVC %=( FEV1.0/FVCx100)

In normal lung function, this should generally be over 75% i.e. the subject should get at least three quarters of inspired total air out in the first second. During a vital capacity maneouvre, expired volume-time (V-T) curves are recorded as illustrated in figure 3.

-Peak expiratory flow rate (PEFR or PF) is the fastest flow rate that can be sustained for 10 milliseconds. This is assessed by asking patient to breathe in as deeply as possible, followed by blowing all the air out as quickly and forcefully as possible. PEFR is the simplest test of forced expiration that can be measured repeatedly with a peak flow meter without discomfort. The procedure is similar to FVC and measures the same volume as maximum expiratory flow rate (MEFR), but the PEFR only calculates one value instead of the many values calculated in a

FVC. The FVC and FEV1 are read directly from the tracing at ambient temperature and pressure saturated with water vapor (ATPS). The volume of gas expired from the lungs at body temperature saturated with water vapour (BTPS), may be eight to ten per cent greater than the volume measured with a spirometer at room temperature.

Thus, expired volume and airflow must be corrected to BTPS conditions75.

The results of lung function tests can be interpreted in relation to reference values and in terms of whether or not they are considered to be within the “normal” range. 75 To maximize the clinical value of lung function tests, the

American Thoracic Society (ATS) 68 and the European Society for Clinical Respiratory Physiology 76 have published guidelines, focusing primarily on spirometry as the most widely used lung function test. Therefore, spirometry test can be reliably used to assess lung function either to generate data bank for normal children as done by Aderele and Oduwole, 77 or to compare lung function in children with lung disorder with the predicted values.

Relationship between PEFR and FEV1

Several measures exist to aid the diagnosis of upper airway obstruction (UAO). These include subjective clinical signs such as the presence of stridor and objective measures such as the pattern of the flow-volume curve.

However, by far the simplest and easily measured, but yet relatively unknown and underutilized, is the forced

70 expiratory volume in 1 second (FEV1) / peak expiratory flow (PEF) ratio.

70,71 Several pioneering studies have previously determined the usefulness of the FEV1/PEF ratio in diagnosing UAO.

FEV1 is defined as the volume measured during the initial one second of a forced expiration from full inspiration and PEF is the maximum flow rate maintained for at least 10 milliseconds during a forced expiration from full inspiration. That is PEF is one tenth of FEV1. Therefore, PEF would be affected more than FEV1 in UAO, since the former reflects more proximal airway flow. Evidently, the FEV1/PEF ratio has been shown to be significantly higher in patients with UAO compared to patients with asthma, chronic obstructive pulmonary disease, and normal subjects.70 A value of above 10ml/L/min was initially thought to represent UAO. This was subsequently found to vary between 7ml/L/min and 12ml/L/min depending on the different subgroups of UAO such as extrathoracic, fixed, and variable intrathoracic.70

Management of air flow obstruction is focused heavily on categorizing patients based on severity of airflow limitation measured on formal pulmonary function testing. It is suggested that either

FEV1 which is the gold standard or PEF can be expressed as a percentage of predicted values and

71,72 used for this purpose. . There is, however, no consensus on whether or not FEV1% and percentage of predicted PEF (PEF%) can be used interchangeably in patients with obstructive lung diseases. Most clinicians assume a general parity between these measurements, and some guidelines72 on management of obstructive lung disease such as asthma also recommend the same. However, other guidelines72 also suggest that PEF% may underestimate the degree of

72,73,74 airways obstruction assessed by FEV1%. This is further corroborated by some studies addressing comparisons between FEV1% and PEF% with conclusion that some degree of variability existed between FEV1 and PEFR correlation.

73 There could be several reasons for lack of equivalence between FEV1% and PEF%. For one, measured PEF values depend heavily on lung volumes. Any disease process leading to reduced lung volumes will effect a corresponding reduction in measured PEF. This implies that in addition to patients with airway obstruction, those with restrictive lung defects are also likely to have a reduced PEF. Secondly, normal population variability of PEF is quite large. Hence calculation of lower limits of predicted normal based on regression equations leads to values that are much lower than corresponding values for other spirometric indexes like FEV1. Thirdly, while PEF is measured on the first effort-dependent portion of the forced expiratory maneuver,

FEV1 is determined both by the effort-dependent and effort-independent portions of this

73,74 maneuver. Thus differential changes in FEV1 and PEF may be observed, depending on the amount and predominant site of airways narrowing. These factors are likely to lead to a greater discrepancy in patients with obstructive pulmonary disease and airway collapsibility secondary to the loss of elastic tissue. In these patients, the initial rapid rise in expiratory flow is similar but, as intra-thoracic pressure increases, that pressure is transmitted to the segmental and other large airways, which “collapse” and obstruct passage of air through those airways. This result in the rapid reduction in flow after a relatively normal peak has been attained, leading to significantly lower values of FEV1 compared to PEF.

Though PEFR correlates well with FEV1, it is not a substitute for spirometry. A difference of

20% or more between morning and night values is considered a good predictor of obstruction.

Since early obstruction can be missed by PEFR measurement, spirometry should be preferred to diagnose obstructive lung disease such as asthma. However, PEFR plays a major role in asthma follow up. A sudden fall of PEFR may be an early warning of impending attack of asthma 75.

PEFR plays a major role to monitor asthma therapy and serial recording will reflect the prognosis of the disease as well as outcome of therapy. Furthermore, it provides an objective assessment of lung function in those children with obstructive lung disease who are unable to do a FVC procedure.

The diffusing capacity ( ) is another form of pulmonary function test that is used to determine the overall ability of the lung to transport gas into and out of the blood. In many ways, DLCO is a general measure of the complete efficiency of the lungs. This is because it is influenced by three key components:

The surface area of the lung with contact to diffusing alveoli, the thickness of the alveolar-capillary membrane and the volume of blood available in the capillary bed of the lung77.

The single-breath diffusing capacity test is the most common way to determine .77,78 The test is performed by having the subject blow out all of the air that he/she can, leaving only the residual lung volume of gas. The person then inhales a test gas mixture rapidly and completely, reaching the total lung capacity as nearly as possible. This test gas mixture contains a small amount of carbon monoxide (usually 0.3%) and a tracer gas that is freely distributed throughout the alveolar space but which doesn't cross the alveolar-capillary membrane. Helium and methane are two such gasses. The test gas is held in the lung for about 10 seconds during which time the CO (but not the tracer gas) continuously moves from the alveoli into the blood. Then the subject exhales. The inspired air must pass through the mouth, trachea, bronchi and bronchioles before it gets to the alveoli where gas exchange will occur. On exhalation, alveolar gas must return along the same path, and so the exhaled sample will be purely alveolar only after a 500 to 1,000 ml of gas in the anatomical death space has expired. Then the next portion which contains gas that has been in the alveoli is analyzed.78 By analyzing the concentrations of carbon monoxide and inert gas in the inspired gas and in the exhaled gas, it is possible to calculate which is the rate at which

CO is taken up by the lungs. The volume of the alveoli ( ) can also be calculated by the degree to which the tracer gas has been diluted by inhaling it into the lung.

In general, a healthy individual has a value of between 75% and 125% of the averag79 However, individuals vary according to age, sex, height and a variety of other parameters such as altitude and population group. It has an advantage of revealing abnormal lung function when spirometry is normal. A breath-holding component of the procedure is a major drawback in its suitability for children. Additionally, population reference value is very essential in the interpretation of the values recorded

Body Plethysmography

The body plethysmograph provides the clinician with complete pulmonary function testing capacity to improve diagnostic capability and make testing quick, and accurate. However, the acquisition costs of a body plethysmograph and the high technicality required in its operation made it inappropriate for hospitals in poor resource countries79. In a traditional plethysmograph, the test subject is placed inside a sealed chamber the size of a small telephone booth with a single mouthpiece. At the end of normal expiration, the mouthpiece is closed. The patient is then asked to make an inspiratory effort. As the patient tries to inhale, the lungs expand, decreasing pressure within the lungs and increasing lung volume. This, in turn, increases the pressure within the box since it is a closed system and the volume of the box compartment has decreased to accommodate the new volume of the subject.

Body plethysmography is based on Boyle’s gas law, which states that if the temperature of a given mass of gas remains constant, the volume and pressure of that gas are inversely related. As the volume of the gas decreases, the pressure increases. This can be illustrated by taking a 5mL syringe and occluding its end. When the plunger is pushed in, the volume of gas inside of the syringe decreases while the pressure inside the syringe increases. This same concept is applied to the plethysmograph. Because the mouth shutter is closed, the pressure at the mouth during inspiration decreases. This pressure is recorded by the mouth pressure transducer. As the chest wall expands during this maneuver and occupies more space, the volume of gas surrounding the patient decreases, thus the pressure inside the plethysmograph cabinet increases. As the patient attempts to exhale against a closed shutter, the pressure at the mouth increases. As the chest wall compresses and occupies less space, the volume of gas surrounding the patient increases, and the pressure inside the plethysmograph cabinet decreases. Because it is a closed system, the pressure plethysmograph has an extremely good frequency response and is excellent for measuring the small volume and pressure changes that occur during testing 80.

There are three basic types of body plethysmographs commonly termed ‘pressure’, ‘volume’, and ‘flow’. The three types are different in the type of device that is used to measure changes in cabinet volume It carries out spirometry, thoracic lung volumes and airways resistance measurement. The system can also include tests for diffusing capacity and dilutional lung volume by nitrogen washout, maximum inspiratory/expiratory pressures, static and dynamic compliance, and bronchial provocation values. As a result, the plethysmograph has many advantages over standard pulmonary function systems. In addition, the amount of time needed to perform a complete and accurate pulmonary function test is much less with a plethysmograph. One major disadvantage in a poor resource country is the cost of procuring the equipment despite the reduction in the cost overtime.81

Arterial blood gas (ABG) is a blood test, which requires taking a sample of blood from the artery, usually in the wrist. Blood from the artery comes straight from the heart after it has been oxygenated. The blood sample from the artery is then analyzed for oxygen, carbon dioxide and carbon monoxide level in it. The pH of the blood, hemoglobin, and several other tests are also run on the blood sample. The information gained by this test will help determine if a person might require oxygen or help explain other possible processes occurring.82

Pulse oximetry measures the oxygen levels in the blood. Oxygen saturation tells us how much of the hemoglobin is loaded with oxygen in the blood stream. Most people will be between 92% and 99% saturated. This test is not nearly as accurate as doing an arterial blood gas, but will often be more than enough for evaluation of a patient's oxygen level82.

Advantages of spirometry

Spirometric pulmonary function testing has many advantages in poor resource countries because of its availability, the simplicity of the equipment and the ability to give reliable results for a long time without recalibration. Maintenance and running cost is equally affordable. It can easily be handled by children of five years and above with a good degree of accuracy and does not subject the subjects to any pain or discomfort83. Spirometry may be subject to technique errors such as patient input and instructor techniques, the values derived are generally reliable when properly done. Although spirometry is not disease specific and may not detect very minimal leision, it is a valuable and reliable tool in initial diagnosis and monitoring of respiratory disease conditions.

This is corroborated by studies which have demonstrated the reliability of spirometric test in detecting presence or absence of disease conditions such as obstructive and restrictive diseases.

This is especially true when subjects were compared with controls84. Comprehensive pulmonary function test often require laboratory which may scare children, spirometric PFT can be done in the out-patient clinic without subjecting the subject to any scare and unnecessary delay.

Considering these advantages and the high cost that will be involved in other methods of pulmonary function test, spirometric method of testing was chosen as the preferred method in the present study.

FACTORS AFFECTING INDICIES OF LUNG FUNCTION TEST

Increase in body size is a strong determinant of spirometry measurement in children and adolescents.85 This implies that anthropometry is a determinant of lung function and ventilatory flow.

Relationship to height: height has been established as the best predictor of lung function both in longitudinal and cross-sectional studies. 86 Although, relationship between height and lung function from childhood to adulthood is not linear, there are prediction equations for children, which are based on power, or exponential functions of height and both seem to present the data equally well.

Relationship to age: adolescent growth spurt is associated with a non-proportional growth rate of different parts of the body. For example, increase in standing height recorded in longitudinal or cross-sectional studies is not in phase with chest growth. 87 This rapid growth in chest dimensions begins before that of the legs. The vital capacity in boys attains its maximal capacity at the age of 25 years though growth in height stops at about 17 years of age.

In girls however, maximal vital capacity is attained at 16 years of age, which is about the age at which maximal

85 height is attained. In younger children, FVC and FEV1 seem to be of constant percentile over time. This is because the force expiratory volume and forced vital capacity grow almost at the same rate in younger children. Ideally, developmental rather than chronological ages should be included in prediction equations for children and adolescents. This is because height or body mass, which is components of development, affects lung volumes and both are not absolutely related to chronological age.

Relationship to respiratory muscle: the opposing effect of increasing muscularity and obesity have been used to explain the observed increase in ventilatory function that paralleled increase in weight and decline in lung function beyond an optimal weight.87 Furthermore increase in lung volumes when growth in height has stopped can be attributed to increase in muscle mass and the subsequent increase in respiratory muscle tone.87 However, data generated at different ages on maximal inspiratory and expiratory pressure in relation to muscle mass are inconclusive as no differences were observed between respiratory pressure in adolescents and adults 88. In adolescents, growth of the lungs and thorax is associated only with small increase in maximal respiratory pressure. 89,90 This average maximal respiratory pressure is however greater in boys than in girls. Although large variability in maximal inspiratory and expiratory pressure exist between individuals of the same sex, only a small portion of the differences in ventilatory function is accounted for by respiratory forces.90

Relationship to lung elastic properties: At most lung volumes, the recoil of the lungs is inwardly directed, whereas the recoil of the chest wall is outwardly directed. When the two recoil forces are of equal magnitude, but in opposite directions, the lung and chest wall system is in dynamic equilibrium. The lung volume where this occurs is functional residual capacity.91 In health the functional residual capacity to the total lung capacity ratio is relatively constant during growth from childhood to adulthood. 91 This is as a result of progressive increase in size of thoracic cage and increase in lung recoil. Lung recoil however decreases from adulthood to old age.

Lung volumes and ventilatory flows: from childhood to adulthood, the FEV1/FVC ratio and ratio of maximal expiratory flow to the FVC is almost constant. Expiratory flow is more in girls than in boys of the same age and stature. 92 This is because girls have a smaller VC than boys for the same TLC. It is also because girls have smaller muscle mass and smaller number of alveoli. Furthermore, airway tone decreases after deep inspiration in girls as against boys.92 Finally, airway resistance is just marginally less in girls than in boys amongst children between the age of two and twelve years93. The group that conducted this study however felt that the best method of determining the airway resistance now may not be totally foolproof. Having these observations in mind, different prediction equations for pulmonary function test should be used for boys and girls of all ages.

Special considerations for testing children

According to the American Thoracic society, 75 no indication of position (i.e. sitting or standing) is necessary in reporting results of pulmonary function tests in adults. However, in children below the age of 12 years, it is

94 recommended that the position be indicated. Torres et al has recently reported that FEV1 and FVC values were significantly higher in the standing than in the sitting posture. This was attributed to slightly larger inspirations taken in the standing position because the abdominal contents do not interfere with diaphragmatic motion in this position. In a study conducted by Renner et. al. 95at the Lagos University Teaching Hospital, standing position was found to give the highest PFT values. They also found out that there is close correlation between standing, sitting and lying stance such that PFT value obtain in any stance can be used to calculate the attainable values in other stance

Equipment for testing children should have accuracy for volume of + or – 50ml and be able to measure volume below 10.5 litres. There should be a real-time display to encourage child and to ensure that effort is sustained over

76 a sufficient time. Predicted FEV1, FVC and PEFR values could be calculated from the formulae derived of normal in

Nigerian children.

In conclusion, this study aimed at using One Flow Spirometer to determine lung function indices in standing position with the view to identify lung function abnormality among children. From the value obtained, obstructive lung abnormality can be diagnosed while restrictive abnormality can be suspected. The value of pulmonary function indices obtained from the subjects in this study will be compared with the predicted value for their corresponding age, sex and height.

JUSTIFICATION

Sickle cell anaemia is a chronic haematological problem that can have negative effects on all organs of the body including the respiratory system 21. Improvement in clinical management has increased the life expectancy of people living with sickle cell anaemia. Therefore it is expected that to some extent, the complications associated with SCA will increase in prevalence.

Various studies in Nigeria 9,32 and different areas of the world have demonstrated reduced pulmonary function in adults with SCA 6,7,21. These abnormal findings were believed to have started in childhood. To lend credence to this notion are various studies in America 8,36,37,45 and other areas of the world 45,56,66 demonstrating abnormal pulmonary function in children with SCA. In Nigeria, studies on lung function in children with SCA have conflicting conclusions. While some found abnormal lung function 9,96, others 68 observed similar lung function values between SCA and their healthy haemoglobin AA counterparts. This may have resulted in limited action towards reducing the rate of progression of chronic lung disease in children with SCA. The study therefore was designed to examine the pattern of pulmonary function abnormality in children with SCA. If any, this will add to the pool of data that can be used in applying appropriate intervention, with the view to reducing the rate of progression of chronic lung abnormality among children with sickle cell anaemia.

AIMS AND OBJECTIVES

General aim To determine Forced Vital Capacity (FVC), Forced Expiratory Volume in one second (FEV1), and Peak Expiratory

Flow (PEF) in children aged five to twelve years with and without sickle cell anaemia at the Lagos State University

Teaching Hospital

Specific objectives

a) To determine FEV1, FVC and PEF in children aged five to twelve years with sickle cell anaemia and

compare with values in age and sex matched healthy children without sickle cell anaemia

b) To determine the pattern of lung function abnormalities if any in the study subjects

c) To determine the demographic factors that may contribute to differences in lung function indices in both

study and control subjects.

d) To determine the correlation if any between lung function and anthropometric indices

SUBJECTS AND METHODS

STUDY DESIGN

The study was hospital-based, prospective and cross sectional.

STUDY POPULATION

The primary subjects were sickle cell anaemia patients (aged 5 years to 12 years) diagnosed by cellulose acetate electrophoresis, attending the Paediatric sickle cell clinic at LASUTH. Apparently healthy, age and sex-matched controls that met the inclusion criteria and have normal haemoglobin genotype AA, attending routine follow-up

Paediatrics clinics were recruited as controls.

STUDY LOCATION

The study was carried out at the Paediatrics Out-Patient Clinic of Lagos State University Teaching Hospital

[LASUTH], Ikeja. Lagos State Government upgraded the center, formerly a general hospital to a tertiary institution in 1999. It serves as a referral center to all peripheral hospitals and health centers in the State. The State has a population of about 15 million people and runs free health services for children less than 12 years of age. The hospital has a total bed capacity of 550 out of which 98 (17.8%) are allocated to medical paediatric patients. An average of 110 children attend the sickle cell anaemia clinic monthly.

STUDY DURATION

Study commenced on March 15 2011 and continued until June 17, 2011when the total sample size of 100 each for

HbAA and HbSS was attained.

INCLUSION CRITERIA

A. For sickle cell anaemia subjects

1. Children with haemoglobin genotype SS attending the sickle cell clinic at LASUTH who are in steady state

for at least four weeks..

2. Age 5years to 12years

3. No medical history suggestive of bronchial asthma

B. For controls

Controls were recruited from apparently healthy children attending non sickle cell clinic at LASUTH. Recruitments were done from the Dermatology clinic with the exclusion of those with atopic skin leisions using Hanifin and Rajka diagnostic criteria for atopic dermatitis. Children earlier treated for minor non-chronic ailments in other paediatrics clinics were also included.

1. Normal haemoglobin genotype AA confirmed by cellulose acetate electrophoresis

2. Age 5 years to 12 years matched age for age with subjects

3. No acute illness such as coryza and pneumonia for at least four weeks prior to recruitment

EXCLUSION CRITERIA FOR SCA SUBJECTS

 Structural abnormality of the rib cage

 Denial of consent

 Presence of sickle cell crisis state in the preceding three weeks

EXCLUSION CRITERIA FOR CONTROLS

History was obtained from controls after which complete physical examination were conducted along with haemoglobin genotype to exclude:

 Past medical history suggestive of bronchial asthma

 Structural abnormality of the rib cage

 Denial of consent.

 Haemoglobin genotype AS

 Patients on drugs that can affect lung function indices such as steroids.

 Patients with overt mental subnormality.

 HIV

 Oedema

 Heart failure

SAMPLE SIZE DETERMINATION

The minimum sample size to measure the proportion of sickle cell anaemia children with lung function abnormality as against children without sickle cell anaemia was calculated using the formula: 97

2 2 2 2 N = ( Zα/2 +Z1-β ) (σ1 +σ2 ) /µ

Where:

N = estimated sample size

Z1-β = One sided percentage point of the normal distribution corresponding to 100% minus power, (1.96 for 95% power)

1 – β =power = 95%

Zα/2 = percentage point of the normal distribution corresponding to the (two sided) significance level = 1.96 (95% level of significance)

σ1 = standard deviation for cases which is 0.194

σ2 = standard deviation for controls which is 0.241

µ =the difference to be detected between the means of the two samples = 0.15 The mean and standard deviation values of vital capacity for HbSS subjects and control groups of 0.194 and 0.241 respectively (for age group below 15 years) of the population studied by Olanrewaju96 were used in this study.

Substituting these figures into the formula,

N = (1.96+1.96)2(0.1942 + 0.2412) / 0.152 = 66

In order to accommodate possible attrition or unforeseen errors in completing the study questionnaire, and also to increase the power of the study an additional 50% (33 subjects) of the calculated figure were recruited to bring the figure to 99, approximated to 100 subjects.

The average monthly clinic attendance of sickle cell anaemia patient was 110 out of which there were about 60 children aged 5-12 years. Further stratification of the 60 patients shows that about 18 were 5-6 years; about 18 were

7-8 years; 12 were 9-10 years while 12 were11-12 years. This gives a distribution ratio of 3:3:2:2. The average male to female ratio in these distributions was about 1.1:1

In order to avoid lopsided clustering of subjects around a particular age or sex, the calculated sample size was stratified according to the distribution pattern of patient in the follow up clinic as shown in the table below.

Age range (years) Male Female All

5 - 6 15 15 30

7 - 8 15 15 30

9 -10 10 10 20

11- 12 10 10 20 Total 50 50 100

Table ii: Subjects distribution into age groups.

The age of the children was determined using their last birthday as given by their parents or guardians

SUBJECT SELECTION

Consecutive patients with sickle cell anaemia attending routine Sickle Cell Anaemia follow up clinic who satisfied the study criteria were recruited. Healthy controls who satisfied the study criteria were recruited from the

Dermatology and other follow up clinics. They were matched (one-for-one) in respect of, age and sex with the sickle cell anaemia study group.

Information on each subject was entered into a purpose-designed proforma. (Appendix 2) Abnormal findings in both subject and control were promptly treated or referred to the appropriate specialist clinic. As incentives, subjects and controls were given a token amount of money for snacks.

Ethical Considerations

Ethical approval (appendix V) was sought from the Ethics Committee of LASUTH prior to the commencement of research. Subjects were recruited following detailed explanation about the research. All recruitments were strictly voluntary and backed by written informed consent. (Appendix 1II)

Data collection

The proforma (appendix IV) was used to collect socioeconomic and demographic data, knowledge of sickle cell disease and risk factor for crisis. Data were taken from both the caregiver and patient. It was administered principally in English language and translated to the local languages including Pidgin English as each case demanded. Thereafter, patients were physically examined and the findings entered into the study proforma. The physical examination was to:

1) Exclude respiratory or cardiovascular disorders like pneumonia or congenital heart disease

2) Exclude structural rib and spinal deformities

3) Take relevant anthropometric measurement

Socio-economic status

Socio-economic status of each subject was determined using the Oyedeji99 method of classification. Thereafter they were classified into upper (social-economic class 1 and II), middle (social-economic class III) and lower (socio economic class IV and V) socioeconomic strata.

Variables Measured

(a) Body Weight:

Body weight was measured in kilogrammes (kg) with light clothing on and without shoes. These precaution

were taken to avoid error that may result from differences in weight of these wears.87 A mechanical floor

scale (SECA, United Kingdom, Model ® 761.) with a sensitivity of 0.05kg was used

(b) Standing height:

Standing height was measured using a stadiometer (Hopkins Medical, Maryland, USA, model ® PE- WM-

60-84) graduated in centimeters with a sensitivity of 0.1cm. Subjects stood barefooted with heels together,

and heels, calves, buttocks and back all touching the stadiometer and with the head in Frankfurt plane, in

which the line connecting the outer canthus of the eyes and the external auditory meatus is perpendicular to

the long axis of the trunk. 84

Sitting height was measured with subject sitting erect on a sitting height table. Sitting height table is a sit

with horizontal flat firm sitting surface and a vertical calibrated backrest that is at right angle to the sitting

surface. The vertical calibrated back rest has an up/down sliding caliper for seating height measurement84 in

centimetres (cm) with a sensitivity of 0.1cm.

(d) Chest circumference:

It was measured at the level of the nipple during inspiration after resting for five minutes. The same non-

elastic tape calibrated in centimetres was used for all the patients. 87 It has a sensitivity of 0.1cm.

(e) Arm span:

Arm span was measured using non-elastic tape calibrated in centimeter and a sensitivity of 0.1cm.

Measurements were taken from the tip of the middle finger of one hand to the tip of the middle finger of the

other hand. The individual stood with the back to the wall, both arms abducted to 900, the elbows and the

wrists extended and the palm facing directly anteriorly 88

(f) Standing height, sitting height, chest circumference and arm span were measured in centimetres to the

nearest 0.1 centimetre. Measurements were done twice. When the two measurements agreed with not more

than 0.4 centimetre between the two measurements their average were taken as the best estimate for the

true value. 88

(g) Forced vital capacity:

This was done with One Flow Spirometer (Clement Clerk International, England). The author did the

spirometry after receiving training at the chest clinic where spirometry is regularly done under the supervision of consultant chest physician. Hygiene was strictly observed by using one mouthpiece per

patient per day. A Universal Sterilizable Mouthpiece with mouth end diameter of 22 millimeter was used.

At the end of each day the mouth pieces were rinsed with centrimide and thereafter autoclaved for the next

day use.

(h) Forced expiratory volume in 1second: with One Flow Spirometer.

(i) Peak expiratory flow rate: with One Flow Spirometer.

Spirometry

Spirometry test were performed in the Consultant Outpatient Clinics for subjects and controls using the One-flow spirometer (Clement Clerk International, England). One flow spirometer is a digital light weight hand held spirometer that can be held comfortably by a child of 5 years and older. It has an inlet through which air can blown through into the spirometer. It also has a small digital screen from where the values obtained can be read. The control of the spirometer is through the buttons on the side of the screen. The spirometer is battery-operated which is an advantage because patients will not be delayed during public power outage. A spare battery is kept handy in case of low battery.

Detachable Universal Sterilizable Mouthpieces are included in the spirometer pack. The spirometer can also be connected to a personal computer to store values and to print values obtained. The spirometer is quick to operate, does not require elaborate laboratory conditions, and does not scare children. Displaying of the value on a digital screen also encourages the children to do better in subsequent manoeuvre.

To operate the spirometer, the device was switched on after inserting specified batteries. The standby signal showed on the screen, and few seconds later the GO sign showed on the screen. The spiromerter was held in a horizontal position for the GO sign to appear on the screen after which measurements were commenced.

The purpose of the study was clearly explained to the subjects and the controls as they come in one after the other in the outpatient clinic. They put on light loose clothing to avoid restriction of chest movement while performing the procedure. Each subject in a standing position 84 put the mouthpiece into the mouth in a horizontal plane with lips firmly applied around the mouthpiece, care being taken not to allow leakage of air around the mouthpiece. The subject were then requested to take in a full inspiratory breath, and then expire as forcefully, rapidly, and completely as possible through the mouthpiece into the spirometer until they can blow no more. By pressing select on the spirometer, FEV1, PEF, FVC, and FEV1/FVC were selected and recorded on the personal computer. The subjects were allowed to practice the procedure until it was properly done. Thereafter, three completed attempts were recorded. The highest of the best three readings was taken as the result for the parameter. Subjects were allowed five minutes rest between each blow attempt. All faults in procedures such as occurrence of coughing spells or sub- optimal effort were regarded as potentially affecting airflow and the entire procedure was repeated. All attempts where FVC values were less than the highest value by 50% were disregarded. Faulty attempts such as when a subject fails to apply the mouthpiece tightly or when a subject coughs into the flow meter were disregarded and the procedure repeated. After three successful attempts, BEST button is pressed on the spirometer to select the best value for either of the parameters, which are FEV1, PEF, or FVC.

The spirometer has an inbuilt predicted value for the Caucasian, but this may not be suitable for our environment since spirometric indices vary with race. Therefore, observed values among HbSS subjects were compared with predicted values that were generated using the values of controls with the same gender. The mean values in current study were also compared with mean values of an earlier existing study conducted by Aderele and Oduwole 76.

-to-FVC ratio that is more than 8-9 absolute percentage points below the predicted ratio

Data Analysis

All data collected were entered into a standard proforma. The statistical analysis was done using the SPSS software version 17.0 Continuous variables were expressed as mean +/- standard deviation (SD) and categorical variables as percentages. Differences in categorical variables were assessed by chi-square analysis while the Student t-test was used for the comparison of continuous variable. Simple linear correlation was used to determine the strength of relationship between variables. Level of significance was set at p = < 0.05.

RESULTS

Characteristics of the study populations

A total of 200 children, 100 each with genotype SS and AA respectively, who met the study criteria were recruited over a study period of four months (March 2011 to June 2011). The demographic characteristics of the study patients are given in Table iii. Equal numbers (100 each) of males and females were recruited. The age of the study subjects ranged from five years to twelve years. Age groups five years to six years and seven years to eight years accounted for

30% each of the total study subjects, while age groups nine years to ten years and eleven years to twelve years each accounted for 20% of the study group. Approximately a third (34.0%) of the study subjects belonged to the upper socioeconomic strata (Socioeconomic classes I and II), while 45% and 21% belonged to the middle (Socioeconomic class III) and lower

(Socioeconomic classes IV and V) socioeconomic strata respectively.

Table iii Demographic characteristics of study population

Characteristic AA SS ALL n (%) n(%) n(%)

Gender Male 50 (50.0) 50 (50.0) 100 (100) Female 50 (50.0) 50 (50.0) 100 (100) Total 100 (100) 100 (100) 200 (100)

Age in years Male 5-6 15 (15.0) 15 (15.0) 30 (30.0) 7-8 15 (15.0) 15 (15.0) 30 (30.0) 9-10 10 (10.0) 10 (10.0) 20 (20.0) 11-12 10 (10.0) 10 (10.0) 20 (20.0) Total 50 (50.0) 50 (50.0) 100 (100)

Female 5-6 15 (15.0) 15 (15.0) 30 (30.0) 7-8 15 (15.0) 15 (15.0) 30 (30.0) 9-10 10 (10.0) 10 (10.0) 20 (20.0) 11-12 10 (10.0) 10 (10.0) 20 (20.0) Total 50 (50.0) 50 (50.0) 100 (100)

Socioeconomic strata Upper 44 (44.0) 24 (24.0) 68 (34.0) Middle 39 (39.0) 51 (51.0) 90 (45.0) Lower 17 (17.0) 25 (25.0) 42 (21.0) Total 100 (100) 100 (100) 200 (100)

Anthropometry and body proportions of study subjects

The weight (mean ±SD range) for SS was 23.64 (±6.60) kg as compared with 26.71 (±8.244) kg for AA. (Table IV). The mean weight of the AA controls was significantly higher than that of SS subjects (p = 0.004). Similarly, The mean BMI, sitting height, and arm span of controls were significantly higher than those of subjects (p = < 0.000, 0.022 and 0.015 respectively). On the contrary, the mean standing height and chest circumference of the AA controls were comparable to those of SS subjects (p =0.61 and 0.132 respectively).

Table V shows pulmonary function test values of HbSS and genotype AA controls. The mean values of 1.52L for

FVC, 1.30L for FEV1 and 214.95L/min for PEFR are significantly lower in HbSS subjects than corresponding FVC of

1.71L, FEV1 of 1.48 and PEFR of 230.30l/min in AA controls (p = 0.045, 0.01 and 0.02 respectively) while the FEV1% showed comparable mean values (p= 0.08).

Table iv

Anthropometric distribution of study subjects

AA SS ALL t value P value

Weight (Kg) Mean 26.71 (8.24) 23.64(6.60) 25.17(7.63) 2.907 0.004*

Range 15.50-62.00 14.00-53.00 14.00-62.0-

Height (cm) Mean 129.00(13.20) 125.88(11.87) 127.44(12.65) 1.755 0.061

Range 105.00-162.50 104.00-162.00 104.00-162.50

Sitting height (cm) Mean (SD) 65.48(5.52) 63.72(5.26) 64.60(5.34) 2.309 0.022*

Range 56.00-81.00 54.00-81.00 54.00-81.00

Arm span (cm) Mean (SD) 131.58(15.03) 126.45(14.48) 129.02(14.77) 2.459 0.015*

Range 107.00-167.50 104.00-172.50 104.00-172.50

Chest circumference(cm) Mean(SD) 61.21(6.57) 59.96(5.10) 60.01(7.58) 1.512 0.132

Range 51.00-85.00 50.00.5-76.00 50.50-85.00

BMI(Kg/m2 ) Mean(SD) 15.68(2.32) 14.64(1.60) 15.16(2.06) 3.717 0.000*

Range 11.89-25.95 10.22-17.78 10.22-25.95

BMI = Body Mass Index; SD= standard deviation; *= statistically significant

Table V

Pulmonary Function Test values in HbSS and genotype AA subjects.

PFT SS AA t- value p value n (%) n (%)

PEFR ( L/m) 214.95(50.62) 230.30(58.03) 1.994 0.045*

FEV1 (L) 1.30(0.31) 1.48(0.39) 3.532 0.01*

FVC (L) 1.52(0.35) 1.71(0.41) 3.198 0.02*

FEV1 85.75(4.95) 86.94(4.71) 1.742 0.08 FVC

SD standard deviation, * statistically significant; n= number in group.

The comparison of pulmonary function test values among HbSS and AA male study subjects in different age groups is shown in Figure 8. The mean PEFR values for HbSS and HbAA subjects were mostly comparable except in the eleven to twelve years age group where the latter had a significantly higher mean PEFR of 307.50 L/min compared to 252.50 L/min in the former.(p = 0.016). With regard to FEV1 and FVC, controls had significantly higher mean value in children aged seven years and above (p < 0.05 in each case) while in the case of FEV1%, the controls younger than seven years had a significantly higher mean value (p = 0.015) while the other age groups had comparable values with HbSS subjects (p > 0.05 in each case).

The pulmonary function test values among HbSS and AA female study subjects in different age group is shown in figure 9. With respect to PEFR, mean values for HbSS and HbAA subjects were mostly comparable except in the seven to eight years age group where the subjects had a significantly lower mean of 186.33 L/min compare to

214.00L/min in controls (p = 0.003). In a similar manner, both groups had comparable mean values with regard to

FEV1 and FVC (p > 0.05 in each case) except age group seven to eight years with significantly higher FVC of 1.60L in controls compared to 1.33L in subject, and age seven to ten years for FEV1 in whom there was a significantly higher mean values among the controls (p < 0.05 in each case). In the case of FEV1%, both groups had similar mean in all age groups with p value greater than 0.05 in each age group.

350

300

250

males 5-6yrs 200 males 7-8yrs 150 males 9-10yrs males 11-12yrs 100

0 FVC-SS FVC-AA FEV1-SS FEV1-AA PEFR-SS PEFR-AA

Figure 8: Pulmonary function indices in male HbSS and AA subjects according to age with FVC and FEV1 in centiliters and PEFR in liters per minute.

350

300

250

females 5-6yrs 200 females 7-8yrs 150 females 9-10yrs females 11-12yrs 100

0 FVC-SS FVC-AA FEV1-SS FEV1-AA PEFR-SS PEFR-AA

Figure 9: Pulmonary function indices between female HbSS and AA subjects according to age with FVC and FEV1 in centiliters and PEFR in liters per minute.

Figure 10 showed the pulmonary function indices between HbSS and HbAA male study subjects in weight groups.

Significantly higher mean FVC 1.90L was found among control compare to 1.66L in subjects in weight group

24.0kg-33.9kg (p = 0.04). The mean FEV1 of 1.63L in controls was also significantly higher than 1.45L observed in subjects in weight group 24.0kg-33.9kg (p < 0.05) All other mean PFT values are comparable in both groups ( p>0.05 in each case) except weight group 14.0kg to 23.9kg where the FEV1% of 90.29% in controls was significantly higher than 86.23% in subjects (p = <0.001)

The pulmonary function indices between HbSS and HbAA female study subjects in weight groups showed that mean PFT values are generally comparable in both study group with p value less than 0.05 in each case (Figure 11).

Figure 12 outlined the pulmonary function test values in HbSS and AA male study subjects in height groups. Only height groups 128cm to 139.9cm shows a significantly higher mean FEV1 of 1.61L in controls compared to 1.45L in subjects(p = 0.002) while height group 104cm to 115.9cm showed significantly higher FEV1% of 90.92% in controls compared to 84.55% in subjects (p = 0.043). Consequently, all other mean PFT values are comparable between both study groups (p > 0.05 in each case).

The mean PFT values are generally comparable between HbAA controls and HbSS subjects in all female height groups (p < 0.05 in each case) except height group 104cm to 115.9cm where the FEV1% of 87.67% in controls was significantly higher than 82.14% in subjects with p value of 0.012 (Figure 13).

350

300

250

200 males 14-23.9kg males 24-33.9kg 150 males >33.9kg 100

0 FVC-SS FVC-AA FEV1-SS FEV1-AA PEFR-SS PEFR-AA

Figure 10: Pulmonary function indices in male HbSS and AA subjects according to weight with FVC and FEV1 in centiliters and PEFR in liters per minute.

350

300

250

200 females 14-23.9kg females 24-33.9kg 150 females >33.9kg 100

0 FVC-SS FVC-AA FEV1-SS FEV1-AA PEFR-SS PEFR-AA

Figure 11: Comparison of pulmonary function indices between female HbSS and AA subjects according to weight with FVC and FEV1 in centiliters and PEFR in liters per minute.

350

300

250 males 104-115.9cm 200 males 116-127.9cm 150 males 128-139.9cm

100 males >139.9cm

0 FVC-SS FVC-AA FEV1-SS FEV1-AA PEFR-SS PEFR-AA

Figure 12: Pulmonary function indices between male HbSS and AA subjects according to height with FVC and FEV1 in centiliters and PEFR in liters per minute

350

300

250 females 104-115.9cm 200 females 116-127.9cm 150 females 128-139.9cm

100 females >139.9cm

0 FVC-SS FVC-AA FEV1-SS FEV1-AA PEFR-SS PEFR-AA

Figure 13: Pulmonary function indices between female HbSS and AA subjects according to height with FVC and

FEV1 in centiliters and PEFR in liters per minute.

The pulmonary function test values between HbSS and AA male study subjects according to arm span groups is shown in figure 14.

There was significantly higher mean FEV1% of 91.83% and 89.92% in controls compared to 84.00% and 85.71% among subjects in arm span groups104cm to 113.9cm and 114cm to 123.9cm respectively. (p = 0.004 and 0.037 respectively). The FVC of 1.69L in controls was also significantly higher than 1.49L among subjects in arm span group 144cm to153.9cm (p = 0.042). In other arm span groups, the mean PFT values are mostly comparable in both AA and SS study groups with p value greater than 0.05 in each case.

In the female arm span group, the mean FVC (2.40L), FEV1 (2.07L) and PEFR (301.00L/min) in AA controls was higher than the mean FVC (2.10L), FEV1(1.86L) and PEFR (298.00L/min) in female arm span group > 143.9cm but the difference was not significant (p = 0.067, 0.164 and 0.823 respectively). PFT values between HbAA controls and HbSS study groups in all other female arm span groups also showed comparable mean values with p value greater than 0.05 in each case. (Figure 15)

350

300

250 males 104-113.9cm 200 males 114-123.9cm males 124-133.9cm 150 males 134-143.9cm 100 males >143.9cm

0 FVC-SS FVC-AA FEV1-SS FEV1-AA PEFR-SS PEFR-AA

Figure 14: Pulmonary function indices between male HbSS and AA subjects according to arm span with FVC and

FEV1 in centiliters and PEFR in liters per minute.

350

300

250 females 104-113.9cm 200 females 114-123.9cm females 124-133.9cm 150 females 134-143.9cm 100 females >143.9cm

0 FVC-SS FVC-AA FEV1-SS FEV1-AA PEFR-SS PEFR-AA

Figure 15: Pulmonary function indices between female HbSS and AA subjects according to arm span with FVC and

FEV1 in centiliters and PEFR in liters per minute.

Six cases of obstructive lung abnormality was found among HbSS subjects giving a prevalence of six percent among subjects while none was found among controls.

The socio-demographic characteristics of obstructive lung abnormality are shown in table VI. Six cases of obstructive lung abnormality, three each among male and female SS subjects respectively were detected while none was found among controls. The highest prevalence was found in lower socioeconomic strata of the SS groups with a prevalence of 7.8% while the upper and middle socioeconomic strata had prevalence of 4.5% and 3.9% respectively. With regard to age groups among the SS subjects, the highest prevalence was found in the oldest age group 11 to 12 years with a prevalence of 13.6% while age group seven to eight years and nine to ten years had a prevalence of 3.6% and 10% respectively. None was found in age group five to six years.

Demographic characteristic of restrictive lung abnormality among SS subjects is shown in table VII. There were five cases of restrictive lung abnormality with three and two cases among males and females respectively. In the social strata, the highest prevalence was found in lower socioeconomic strata of the SS groups with a prevalence of 8.0% while upper and middle socioeconomic strata had prevalence of 4.2% and 3.9% respectively. In the age groups, among the SS subjects, prevalence of 3.3% was found in age group seven to eight years while 10% each was found in age groups 9-10years and 11-12 years respectively

Table VI

Social strata and age specific prevalence of obstructive lung abnormality among HbSS study subjects

obstructive Normal n(%) n(%)

Gender

M 3(6.0) 47(94.0)

F 3(6.0) 47(94.0)

Socioeconomic strata

Upper 1(4.5) 21(87.5)

Middle 3(3.9) 49(96.1)

Lower 2(7.8) 24(96.0)

Age in years

5-6 0 30

7-8 1(3.6) 27(90.0)

9-10 2(10.0) 18(90.0)

11-12 3(13.6) 19(95.0)

Table VII

Social strata and age specific prevalence of restrictive lung abnormality among HbSS subjects.

Restrictive Normal n(%) n(%)

Gender

M 3(6.0) 47(94.0)

F 2(4.0) 48(96.0)

Socioeconomic strata

Upper 1(4.2) 23(95.8)

Middle 2(3.9) 49(96.1)

Lower 2(8.0) 23(92.0)

Age in years

5-6 0 30

7-8 1(3.3) 29(96.7)

9-10 2(10.0) 18(90.0)

11-12 2(10.0) 18(90.0)

Five of the six primary caregivers of the SS subjects with obstructive lung abnormality are married while one was single. Table VIII. Five of the SS subjects with obstructive lung abnormality had family size less than five, while one was recorded in those with family size greater than equal to or greater than five. Of the six HbSS subjects with obstructive lung abnormality, two children had less than three chest-related hospital admissions per year while four had three or more such admissions per year. Thus the prevalence of obstructive disease was significantly higher among those who had three or more admissions (2.5% Vs 19.0%, 푥2 = 5.36 with Yates correction, p = 0.021).

There were five SS subjects with restrictive lung abnormality and four of them are from married caregivers while one is from single caregiver. Table IX. Four of those with restrictive lung abnormality had family of five or more while one was found in those with family size of less than five. All the five subjects with restrictive lung abnormality had three or more chest related hospital admissions per year while no restriction was found in those with two or less chest related admission in a year (0% Vs 23.8%, 푥2 = 15.1 with Yates correction, p = <0.001).

Table VIII

Socio-demographic characteristics of children with obstructive lung abnormality among HbSS

No in group No with obstructive abnormality n(%) n(%)

Marital status of parents

Married 89 5(5.6)

Single 11 1(9.1)

Family size

<5 91 5(5.5)

≥5 9 1(11.1)

Number of admissions due to respiratory problems

≤2 79(97.5) 2(2.5)

>2 21(84.0) 4(19.0)

Table IX

Socio-demographic characteristic of children with restrictive lung abnormality among HbSS

No group No with obstructive abnormality n(%) n(%)

Marital status of parents

Married 89 4(4.5)

Single 11 1(9.1)

Family size

<5 91 4(4.4)

≥5 9 1(11.1)

Number of admission due to respiratory problem

≤2 79 0

>2 21(76.2) 5(23.8)

Bivariate linear regression analyses between PFT and age, anthropometry and body proportions in male HbSS subjects.

Series of linear regression analyses were done to test the relationship between pulmonary function test values as dependent variables and age, anthropometry and body proportions as independent variables. Strong positive correlations were detected between standing height and

FVC with correlation coefficient (r) value of 0.906 in AA controls and 0.804. Strong positive correlation was also detected between height and FEV1 (r = 0.914 and 0.834 for AA and SS subjects respectively) as well as PEFR (r = 0.870 and 0.686 for AA and SS subjects respectively). (Figure 16-18)

Other anthropometric parameters such as weight, sitting height, arm span and chest circumference also had a strong positive correlation with pulmonary function test indices with r ranging between 0.614-0.831 (Table X). For BMI the positive correlation coefficients were lower, ranging from 0.226 to 0.374.

AA : r = 0.906

SS : r = 0.804 p-value = 0.000

Figure 16: Relationship between FVC and standing height among male study subjects.

r = correlation coefficient

AA : r = 0.914

SS : r = 0.834 p-value = 0.000

Figure 17: Relationship between FEV1 and standing height among male study subjects.

r = correlation coefficient

AA: r = 0.870

SS : r = 0.686 p-value = 0.000

Figure 18: Relationship between PEFR and standing height among male study subjects.

r = correlation coefficient

Table X

Summary of correlation coefficients between pulmonary function test indices and age/anthropometry among male study subjects

PFT CORRELATION PEFR (L/min) FEV1 (L) FVC(L)

COEFFICIENT SS SS SS

Age (years) r 0.669 0.694 0.695

Weight (kg) r 0.665 0.813 0.760

Sitting height (cm) r 0.614 0.778 0.745

Chest r 0.630 0.777 0.706 circumference (cm)

Arm span (cm) r 0.713 0.831 0.795

BMI (kg/M2) r 0.329 0.374 0.266

Bivariate linear regression analyses between PFT and age, anthropometry and body proportions in female subjects.

The relationship between pulmonary function test values as dependent variables and height as independent variables are shown in figures 19 to 21. Strong positive correlations were detected between height and FVC with correlation coefficient (r) value of 0.828 and 0.897 for AA and SS subjects respectively. There also strong positive correlation between height and FVE1 (r = 0.842 and 0.925 for AA and SS respectively) as well as height and PEFR with r value of 0.808 and

0.870 for AA and SS subjects respectively. Similarly, all other anthropometric parameters except BMI had a strong positive correlation with pulmonary function test indices with coefficient (r) ranging between 0.832 and 0.921. Table XI

For BMI the positive correlation coefficients were lower, ranging from 0.616 to 0.646.

AA: r = 0.828

SS : r = 0.897 p-value = 0.000

Figure 19: Relationship between FVC and standing height among female study subjects. r = correlation coefficient

AA: r = 0.842

SS : r = 0.925 p-value = 0.000

Figure 20: Relationship between FEV1 and standing height among female study subjects.

r = correlation coefficient

AA: r = 0.808

SS : r = 0.870 p-value = 0.000

Figure 21: Relationship between PEFR and standing height among female study subjects.

r = correlation coefficient

Table XI

Comparison of correlation coefficients between pulmonary function test indices and age/anthropometry among

female HbSS subjects and HbAA controls.

PFT CORRELATION PEFR(L/min) FEV1 (L) FVC (L)

COEFFICIENT

SS SS SS

Age (years) r 0.871 0.857 0.847

Weight (kg) r 0.853 0.907 0.884

Sitting height (cm) r 0.850 0.921 0.890

Chest r 0.832 0.865 0.832

Circumference (cm)

Arm span (cm) r 0.877 0.908 0.883

BMI(kg/M2 ) r 0.616 0.640 0.646

Multiple regression analyses with pulmonary function indices as the outcome variable of interest, and

anthropometry (height, weight and age) as independent variables shows that combination of height and age had

the highest coefficient of determination with R2 of 0.824, as well as the lowest standard error of the estimate (SEE) of 0.211 for the prediction of FVC among female controls. Table XII. Combination of height and weight as well as age and weight led to reduction in R2 (0.816 and 0.768 respectively) with increase in SEE (0.216 and 0.242 respectively). With the use of individual anthropometric parameter, height has R2 of 0.818 and SEE of 0.215 while the other two anthropometric parameters had reduced R2 and increase SEE when compared with values obtained when combined anthropometry are used. The R2 of 0.824 obtained when the three parameters were combined was the same as that obtained with height and age used but the SEE of 0.214was slightly higher.

The highest coefficient of determination with R2 of 0.844 was obtained with combination of height and age as well height, weight and age, but the SEE of 0.173 for height and age combination was lower than 0.175 of height, weight and age combination for the prediction of FVC among males. Table XIII The combination of height and weight as well as age and weight gave a lower R2 (0.815 and 0.787 respectively) and higher SEE (0.185 and 0.198 respectively). When the individual parameters are used independently, height gave a R2 of 0.818 with SEE of 0.183 while the other two parameters gave a much lower R2 and higher SEE. This implies that height alone accounted for

81.8% while height and weight accounted for 84.4% of variability in FVC among males.

Table XII

Regression of predictor(s) on FVC of female control subjects (n = 50)

Predictor(s) R2 Standard Error p value

of the Estimate

Age (years) 0.695 0.278 0.001

Weight (kg) 0.556 0.335 0.001

Height (cm) 0.818 0.215 0.001

Age and Weight 0.768 0.242 0.001

Age and Height 0.824 0.211 0.001

Height and Weight 0.816 0.216 0.001

Age, Weight and Height 0.824 0.214 0.001

Table XIII

Regression of predictor(s) on FVC of male control subjects (n = 50)

Predictor(s) R2 Standard Error p value

of the Estimate

Age (years) 0.747 0.216 0.001

Weight (kg) 0.637 0.259 0.001

Height (cm) 0.818 0.183 0.001

Age and Weight 0.787 0.198 0.001 Age and Height 0.844 0.173 0.001

Height and Weight 0.815 0.185 0.001

Age, Weight and Height 0.844 0.175 0.001

For FEV1 prediction among female controls, height and age as well as height, weight and age combination gave the highest R2 (0.837 and 0.836 respectively) and the lowest SEE (0.175 and 0.176 respectively). Table XIV. The other parameters either individually or in combination did not improve the value of the R2 nor the SEE.

2 For the prediction of FEV1 among male controls, Height and weight combination gave the highest R of 0.848 and the lowest SEE of 0.131. Table XV Closest to this value is the combination of height, weight and age with R2 of

0.846 and SEE of 0.132. Other anthropometric parameters either individually or in combination gave lower R2 or higher SEE.

The prediction of PEFR among female control is best with combination of height and age with R2 of 0.766 and SEE of 26.118. Figure XVI With the combination of height weight and age, the R2 of 0.761 was slightly lower while the

SEE of 26.915 was slightly higher. Other anthropometric parameters whether individually or in combination produced lower R2 and higher SEE.

Table XVII shows that combination of height and age had the highest R2 of 0.786 and the lowest SEE of 28.082 for the prediction of PEFR among male controls. The combination of height, weight and height had R2 value that is almost as high as the former combination (R2 =0.783) with SEE almost as low (SEE=28.222). Other combinations of anthropometric parameters did not yield higher R2 or lower SEE

Table XIV

Regression of predictor(s) on FEV1 of female control subjects (n = 50)

Predictor(s) R2 Standard Error p value

of the Estimate

Age (years) 0.696 0.242 0.001

Weight (kg) 0.553 0.291 0.001

Height (cm) 0.810 0.198 0.001

Age and Weight 0.773 0.211 0.001

Age and Height 0.837 0.175 0.001

Height and Weight 0.832 0.178 0.001

Age, Weight and Height 0.836 0.176 0.001

Table XV

Regression of predictor(s) on FEV1 of male control subjects (n = 50)

Predictor(s) R2 Standard Error p value

of the Estimate

Age (years) 0.747 0.170 0.001

Weight (kg) 0.688 0.188 0.001

Height (cm) 0.833 0.138 0.001

Age and Weight 0.810 0.147 0.001

Age and Height 0.848 0.131 0.001

Height and Weight 0.830 0.139 0.001

Age, Weight and Height 0.846 0.132 0.001

Table XVI

Regression of predictor(s) on PEFR of female control subjects (n = 50)

Predictor(s) R2 Standard Error p value

of the Estimate

Age (years) 0.658 32.512 0.001

Weight (kg) 0.483 39.973 0.001

Height (cm) 0.763 27.050 0.001

Age and Weight 0.707 30.101 0.001

Age and Height 0.761 26.118 0.001

Height and Weight 0.758 27.336 0.001

Age, Weight and Height 0.766 26.915 0.001

Table XVII

Regression of predictor(s) on PEFR of male control subjects (n = 50)

Predictor(s) R2 Standard Error p value

of the Estimate

Age (years) 0.722 31.424 0.001

Weight (kg) 0.696 33.461 0.001

Height (cm) 0.752 30.228 0.001

Age and Weight 0.781 28.394 0.001

Age and Height 0.783 28.222 0.001

Height and Weight 0.763 29.533 0.001

Age, Weight and Height 0.786 28.082 0.001

In both males and females, regression analyses showed that height in combination with age yielded the highest R2 values and the lowest SEE values for all the pulmonary function test (PFT) indices. Therefore, regression equations using height and age were derived for predicting PFT values in females and males (Table XVIII).

Table XVIII

Regression equations for predictors of FVC, FEV1 and PEFR in male and female control subjects (n = 50) Regression Equation R square Standard Error p value

of the Estimate

MALES

FVC (L) = 0.060Age + 0.021Height – 1.431 0.844 0.173 0.001

FEV1 (L) = 0.042Age + 0.017Height −1.059 0.848 0.173 0.001

PEFR (L/min) = 8.447Age + 2.743Height – 186.166 0.783 28.222 0.001

FEMALES

FVC (L) = 0.045Age + 0.026Height – 2.088 0.844 0.211 0.001

FEV1 (L) = 0.030Age + 0.024Height −1.933 0.837 0.175 0.001

PEFR (L/min) = 5.481Age + 2.733Height – 173.773 0.761 26.118 0.001

Table XIX

Comparison between predicted values generated using regression equations from current study and Iranian study.

Mean value using current Mean value using Iranian t value p value study regression equation regression equation

MALES

FVC (L) 1.751 1.806 1.153 0.252

FEV1 (L) 1.464 1.564 1.047 0.298

FEMALES

FVC (L) 1.645 1.730 1.11 0.269

FEV1 (L) 1.419 1.568 1.020 0.309

DISCUSSION

The study showed notable differences in most anthropometric parameters between SS subjects and HbAA controls.

This is in agreement with earlier studies conducted in Nigeria 96,98,,99 and elsewhere 100,101,,64. HbSS subjects tend to weigh less, and are thinner than HbAA children. This observation probably reflects the adverse effect of sickle cell anaemia on growth. Specifically, with regard to weight and BMI, the differences are explainable based on attendant chronic hypoxia in the presence of elevated resting energy expenditure and elevated protein turnover both of which affect body weight, particularly fat free mass.89 The mean sitting height was also significantly higher in controls than

SS subjects. This is comparable to the findings in a study of Indian children with sickle cell anaemia. 102,103 The lower sitting height in sickle cell anaemia study subjects may reflect their shorter trunks resulting from narrowed inter-vertebral disc spaces and deformities of vertebral bodies. 104,105 Similarly, the mean arm span was significantly longer among AA controls than SS subjects. This observed finding may be a consequence of shorter limbs resulting from repeated infarctions of the long bones of the upper limbs in patients with sickle cell anaemia. 106 Although the overall mean height was lower among HbSS subjects, the difference was not significant. Similar results had been reported in earlier studies 67,96. The lack of significant difference may be explained by the less severe HbSS haplotype in our subregion13, and thus may have had a milder effect on height. It was also observed that the mean chest circumference was higher but not significantly so among controls than children with sickle cell anaemia. This finding is in line with what was reported by Onigbinde 67 in a study of Nigerian children with sickle cell anaemia aged five to 18 years. The lower chest circumference in children with sickle cell anaemia may be due to reduction in thoracic capacity and lung sizes due to rib and lung infarctions. 96

The mean FVC was lower in SS subjects than AA controls across all age groups, although the difference was not significant. This finding is consistent with previous studies62,63,64,67,96. Endothelial hypoxic injury due to hypoventilation during painful crisis affecting the lungs and the chest wall can eventually result in fibrotic lung injury, and this can reduce FVC in HbSS patients 21. There was progressive rise in the value of FVC with increasing age among SS subjects and AA controls. This is due to progressive increase with age of physical characteristic such

85,86,87 as weight, height and chest circumference, all of which have direct relationship with FVC . The mean FEV1 among HbSS subjects in the present study of 1.30L is lower than 1.70L reported by Onigbinde 67 in children with

SCA at Oshogbo and Ile Ife in 2006. The disparity in the age range of the study subjects may account for the observed difference in mean values; the upper age limit for the present study is 12 years while it was 15 years in the study by Onigbinde. It is plausible that the lower mean FEV1 observed in present study was because younger children were studied than was the case in the study by Onigbinde. Since FEV1 is directly related to height, weight, age and lung size, it is therefore expected that older children should have higher values. Additionally, the observed difference could possibly be an effect of the smaller sample size of 74 subjects used in the earlier study as against

100 used in current study. Small sample size is known to give exaggerated sample mean value115. It was also observed that the FEV1 increased in both groups as their ages increased. Since FEV1 is derived from FVC, factors

85,86,87 that FVC such as anthropometry variables, will affect the value of FEV1. . The mean PEFR was consistently lower among HbSS subjects than HbAA controls. This corroborates reports from earlier studies8,9,35,63,67,96. This is because PEFR is dependent on lung size, lung compliance, rib cage size and mobility. Reduced values therefore, could be due to repeated pulmonary hypoxic injury from pneumonia, acute chest syndrome and pulmonary infarction associated with sickle cell anaemia.96 The mean PEFR also increased in both HbAA and HbSS subjects with age. This corroborates earlier studies in Nigeria and many other studies in developed countries.,64 66,77 This is because PEFR is directly related to lung size, height, muscle mass and understanding of the technique,85,86,87 all of which increase as the child grows older. FEV1%, a timed subdivision of FVC in the first second is a measure of air flow rate in the air ways. The mean FEV1% at different ages was often higher in controls than HbSS subjects but the finding was not consistent. This observation corroborates the finding of earlier workers in Nigeria 67 and elsewhere 64,66. The lower values in SS subjects may be explained by ongoing subclinical inflammatory process within the respiratory system of children with SCA 44,45 . The ongoing inflammation may result in airway hyper- reactivity thereby causing spasm of bronchial smooth muscle and consequently reducing the diameter of the bronchioles. The reduced bronchial diameter result in reduced airflow rate which translate to reduced FEV1%.

One of the specific objectives of the study was to determine the pattern of lung function abnormalities among children with SCA. The two types of abnormalities identified were obstructive and restrictive. The basis for obstructive disease in HbSS patients is in chronic hypoxia and ongoing subclinical inflammation in the respiratory tract of children with SCA. The low prevalence of obstructive disease herein reported (6.0%) agrees with 4.5% reported by Sylvester et al 64 in black Americans. Indeed, in an earlier study conducted in southwestern Nigeria, no obstructive lung disease was reported. On the other hand, another study done among African–Americans, a much higher prevalence rate of 35% was reported. It is noteworthy that the upper age limit in the study by Kamboulis 35 was 15 years (three years older than the subjects of the current study). It is however doubtful if that factor would be enough to explain the large difference in prevalence rates. Also, a much smaller sample size of 63 was used in the

Kamboulis study, which has the risk of generating high prevalence rates.115 With respect to restrictive abnormalities, five subjects with sickle cell anaemia were identified with the disorder in the study. Restrictive lung dysfunction probably reflects the effect of recurrent vaso-occlusive crisis affecting the lung and the rib cage. The resulting lung fibrosis and rib infarction restrict lung expansibility thereby reducing its volumes and capacities. The five percent prevalence of restrictive lung abnormality in current study is in line with the findings of the study of 64 children by

Sylvester et al64 in which 6.3% of children studied had restrictive lung abnormality. This pattern of lung dysfunction in children with SCA is still a matter of continuing investigation. While some workers have reported high prevalence in children and adolescents 35,64,96, others have emphasized its rarity. 67

It would appear that there is a relationship between socioeconomic status and abnormal lung function. There was a higher prevalence of obstructive lung abnormality among subjects in the lower socioeconomic strata. The number of affected subjects was small and do not suffice for stronger conclusions but the pattern of observation is in line with earlier studies which indicate that the prevalence of obstructive lung abnormality was higher among children of parents in the lower socioeconomic strata.109,110 The pulmonary function was lower in those in lower socioeconomic strata because of substandard living conditions, inadequate personal health care and clinical follow–up. The findings of this work however differs from observation from earlier works 77,96 done in Nigeria over twenty years ago that showed similar values among the three social strata. The reason for the similar prevalence in those studies was not stated. In the same vein, the prevalence of restrictive lung abnormality was highest among children of parents in the lower socioeconomic strata. This is due to increased frequency of sickle cell crisis that may be associated with inadequate health seeking behavior and clinical follow-up; a trend that is common among people in the lower socioeconomic strata. The frequent crises result in pulmonary parenchyma and rib cage infarction and consequently reducing lung expansibility 121. Another social factor that showed some relationship with abnormal lung function was family size. The prevalence of obstructive lung abnormality among SS subjects in the current study was much higher in association with family size of five or more. This is contrary to observations by earlier workers in

Europe116,117 and America118,119 where lower prevalence was found in larger families. The theoretical explanation is that larger families predispose children to early infection and development of protection against atopy-like conditions. Hygiene hypothesis125 states that early exposure to infection reduces the tendency to be atopic. It may have been expected that children in our setting would even have earlier and more frequent exposure to infection and would have developed some protection. Therefore, it appears paradoxical that those from larger families in present study were more frequently affected by obstructive airway disease. The reason for this observation is not clear.

Unfortunately, there is a paucity of local studies to compare with in order to state categorically that there are regional differences. Restrictive lung abnormality also had a higher prevalence among children with family of five or more. This is due to increased respiratory infection that may be associated with overcrowding; increased respiratory infection has been associated with increased rate of vaso-occlusive crisis involving chest, which can overtime affect pulmonary function. The observation that HbSS children with frequent ACS had lower pulmonary function test indices than their counterpart without ACS is in line with the findings of earlier study by Sylvester et. al8 In the current study, the prevalence of obstructive lung abnormality increased with number of admissions due to chest symptoms which may have included pneumonia, vaso-occlusive crisis in the lungs and acute chest syndrome.

The limitation here is that the information on admissions was obtained through history taking and as such, there was no sub-classification into specific diseases. However, it is known that these conditions are causes of pulmonary inflammation and can lead to recurrent hyper-reactivity of the bronchial tree and ultimately abnormal PFT values.

The finding corroborates earlier study 8 to the extent that the more the cases of acute chest condition, the more the deterioration of PFT values.

Pulmonary function correlates to varying extent with different anthropometry indices. While the strength of correlation is strong with some, it is relatively weaker with others. In the current study, there are strong positive correlations between PFT values and variables such as height, weight, arm span, chest circumference and age. This confirms the fact that body size is a strong determinant of spirometry measurement in children and adolescents.85 It therefore implies that anthropometry will be a strong determinant of lung function and ventilatory flow. The observation in the present study is in line with findings of other works done in Nigeria 9,67,77,96 and other parts of the world 85,86,87,88. For example, Oduwole et al77 in Ibadan also found that lung function had strong positive correlation with anthropometry in healthy school children. In view of the strong relationship between anthropometry and PFT indices, it was possible to generate reliable regression equations between PFT and the best correlates which were height and age. In a related Iranian 122 and Indian study 123, height and age combinations gave the best prediction equations that yielded prediction closest to the measured.

In conclusion, the reason for obstructive lung abnormality in children with SCA has been a subject of controversy.

While some believe that obstructive lung abnormality is a manifestation of SC 49,50,51 others suggest that it is a significant co-morbidity46,47,48. To support the latter claim, Ozbek and co workers 49 in Washington DC reported prevalence as high as 78% among children with SCA as against 18% prevalence in the general population. The 6% prevalence in current study is similar to 4.7% reported by Sylvester et al 64 and this highlights the occurrence of this condition in children with SCA. In the same vein, the issue of restrictive lung abnormality in children with SCA is still a matter of continuing investigation. While some workers have reported high prevalence in children and adolescents 35,64,97, others have emphasized its rarity 67. The prevalence of five percent highlights the existence of this condition in children with sickle cell 4anaemia. Therefore, there is the need for early screening and interventional strategies in childhood to slow its progression to chronic obstructive lung disease in adulthood.

Incentive spirometry is a form of physiotherapy that can be used to slow down this progression.124 The identification of obstructive lung disease in sickle cell anaemia subjects raises the question of intervention. The six affected subjects in the current study have been referred to specialist respiratory and haematology clinic for further evaluation with view to starting appropriate therapeutic intervention.

CONCLUSIONS

The following deductions about pulmonary function in children with and without sickle cell anaemia in the study can be made:

(1) Anthropometric measurements such as body mass index, height, weight, sitting height, arm span, and chest

circumference are generally lower among HbSS subjects than controls.

(2) Pulmonary function test values in children with sickle cell anaemia are significantly lower than the values

for HbAA controls.

(3) Pulmonary function correlates strongly with anthropometric measurements such as height, weight, sitting

height, arm span, and chest circumference among subjects and controls.

(4) Abnormal pulmonary functions are present in HbSS subjects. With regard to obstructive abnormality, the

prevalence was six percent. While in the case of restrictive abnormality, it was five percent.

(5) The prevalence of restrictive lung abnormality increased with age.

(6) Abnormal pulmonary function was highest in subjects with parents in the lower socioeconomic strata.

RECOMMENDATIONS

(1) Children with sickle cell anaemia should have regular evaluation of pulmonary functions to identify and

manage those with abnormalities promptly.

(2) Paediatrics departments in tertiary health facilities should be provided with spirometers for the monitoring

of long term effect of sickle cell anaemia on lung function in children.

LIMITATIONS

1) Plethysmography, a vital tool in the diagnosis of restrictive lung abnormality was not used because it is

not available at the study centre. Spirometry, while excellent for the diagnosis of obstructive disease is at

best, a screening tool for restrictive disease.

2) Predicted standards of lung function indices for children in the sub-region are yet to be generated.

Consequently, the observed values among subjects in current study were compared with predicted values

derived using the values of the controls.

AREAS OF FUTURE STUDIES

1) The generation of a local predicted reference values for children is necessary to facilitate spirometry. Since

pulmonary function varies with race, international reference values would most likely be unreliable and

may miss or over diagnose pulmonary function abnormality.

2) There is need for a larger study, preferably collaborative on a national scale to determine the pattern of lung

function abnormality in children and adolescents with sickle cell.

3) A longitudinal study among children with sickle cell anaemia is necessary to determine the pattern of lung

function deterioration if any, to institute appropriate management to those affected and to assess their

response.

References

1. Makani J, Kirkham FJ, Komba A et al. Transcranial doppler in sickle cell disease in Africa. Brit J

Haematol. 2007; 137(1):74.

2. 59th world health assembly. Sickle cell anemia April 2006A 59/9

3. Nigerian national population commission 2006

4. Orah SP, Donald JB, Windell FR et al. Mortality in sickle cell disease – life expectancy and risk factor for

early death. New Eng J Med 1994; 330: 1639-44 5. Lisbona R, Derbekya NV, Novanes –Diaz J.A. Scintigraphic evidence of pulmonary vascular occlusion in

sickle cell disease. J Nucl Med 1997; 38:1151 – 1153

6. Vichinsky EP, Neumayr LD, Earles AN, et al. Causes and outcome of the acute chest syndrome in sickle

cell disease. National acute chest syndrome study group. New Eng J Med. 2000; 342:1855 –65

7. Siddiqui AK, Ahmed S. Pulmonary manifestation of sickle cell disease. Post Grad Med J 2003; 79 :384 –

8. Sylvester Karl P, Patey RA, Milligan P, et al. Impact of acute chest syndrome on lung function of child

with sickle cell disease. J Pediatr 2006 149(1): 17-22

9. Vanderjagt DJ, Trujillo MR, Jalo I et al. Pulmonary function correlates with body composition in

Nigerian children and young adults with sickle cell disease. J Trop Pediatr, 2008; 54:87-93.

10. Akinyanju OO. A profile of sickle cell disease in Nigeria. Ann N Y Acad Sci 1989; 565:126 – 36.

11. Serjeant, G.R., The emerging understanding of sickle cell disease. Br J Haematol, 2001. 112;1:3-18

12. Ragusa A, Frontini V, Lombardo M. Presence of an African Beta-globin Gene Cluster Haplotype in Normal

Chromosomes in Sicily. Am J Hematol 1992; 40:313-315

13. Ajayi AA. "Should the sickle cell trait be reclassified as a disease state?" Eur. J. Intern. Med. 2005;16:

463. doi:10.1016/j.ejim.2005.02.010

14. Desai DV, Dhanani H: Sickle cell disease: History and Origin: J Haematol. 2004; Vol 1 No 2.

15. Bunn HF. Pathogenesis and treatment of sickle cell disease New Eng J Med 1997; 337:762 – 69.

16. Bowers AS, Pepple DS, Reid HC. Oxygen delivery index in homozygous sickle cell disease: steady and

crisis state. Br J Biomed Sci. 2009; 66:148-9.

17. Hassell KL, Deutsch JC, Kolhouse JF, et al. Elevated serum levels of free fatty acid in sickle cell patient

with acute chest syndrome and multiorgan failure syndrome. Blood 1994; 84:1633-524

18. Stevens MC, Padovic M, Sergeant GR. Observation on the natural history of dactylitis in homozygous

sickle cell disease. Clin Pediatr (Philadelphia) 1981; 20: 311 – 7.

19. Juwah A. Nlemadim E, Kain W. Types of anemic crisis in paediatric patient with sickle cell anemia seen

in Enugu, Nigeria. Arch Dis Child 2004; 89 572 – 576.

20. Manci EA, Culberson DE, Yan YM, et al. Cause of death in sickle cell disease, an autopsy study. Brit J

Hematol. 2003; 123:359 – 365. 21. Santoli F, Zerah F, Visile N, et al. Pulmonary function in sickle cell disease with or without acute chest

syndrome. Eur Resp J. 1998; 12:1224 – 9

22. Thomas AN, Pattison C, Sergeant GR. Cause of death in sickle cell disease in Jamaica. Br Med J.1982;

285:633-635.

23. Ali H.A, Ibrahim A.A, Sundara KC et al. Splenic function in sickle cell anaemia patient. Am J Hematol

2000; 63:68 – 73

24. Platt OS. The acute chest syndrome of sickle cell disease. N Eng J Med. 2000; 342: 1904-7

25. Castro O, Brambilla DJ Thorinton B, et al. The acute chest syndrome in sickle cell disease : Incidence and

risk factors : The cooperative study of sickle cell disease. Blood 1994; 84:643-9

26. Aslan M, Thunky–Brwon D, Freeman B. A. Reactive specie in sickle cell disease. Ann N Y. Acad. Sci

2000; 899:375 – 391

27. Elizabeth S, Harrinson WF. Role of free radicals in the pathogenesis of acute chest syndrome in sickle cell

disease. Respir Res 2001; 2: 280 – 28

28. Hammerman SI, Klings ES, Hendra KP, et al. Endothelial cell nitric oxide production in acute chest

syndrome Am J Physiol. 1999; 277:1579-92.

29. Aldrich TK, Dhuper SK, Pana NS, et al. pulmonary entrapment of sickled cells: the role of regional

hypoxia. J Appl Physiol 1996; 80:531-9.

30. Bhalla M, AbboudMR, Mcloud TC, et al. Acute chest syndrome in sickle cell disease. CT evidence of

microvascular occlusion. Radiology 1993; 187:45-9.

31. Weil JV, Castro O, Malik AB, et al. NHLBI workshop summary: pathogenesis of lung disease in sickle

cell haemoglobinopathy. Am Rev Respir Dis 1993; 148: 249-57. 44

32. Fawibe AE, Salami AK, Oluboyo PO, et al. Sickle cell chronic lung disease among young adult Nigerians.

West Afr J Med. 2010;29:30-3.

33. Powars D, Weidman JA, Odom-maryonT, Niland JC, Johnson C, et al. Sickle cell chronic lung disease:

prior morbidity and risk of pulmonary failure. Medicine 1988; 67:66-76

34. Childs JW. Sickle cell disease: the clinical manifestation. J Am Osteopath Assoc 1995; 95:593-8

35. Koumbourlis AC, Zar HJ, Hunlet – Jensen A, et al. Prevalence and reversibility of lower airway

obstruction in children with sickle cell disease. J Pediatr. 2001; 138: 188-192. 36. Boyd JH, Debaun MR, Morgan WJ, Mao J, Strunk RC. Lower airway obstruction is associated with

increased morbidity in children with sickle cell disease. Pediatr Pulmonol. 2009; 44(3) :290. doi: 10.

1002/ ppul.

37. Des Jardens TR, Burton GG. Clinical manifestation and assessment of respiratory diseases. Fifth edition

page 108

38. Kluchova Z, Petrasova D, Joppa P, Dorkova Z, Tkacova R. The association between oxidative stress and

obstructive lung impairment in patients with COPD. Physiol Res 2007;56:51-56.

39. Kosciuch J, Chazan R. The role of virus in the pathogenesis of obstructive lung diseases. Pol Merkur

Lekarski. 2003; 15:292-5.

40. James Hoggs. Pathophysiology of airflow limitation in chronic obstructive pulmonary disease. Lancet

2004;364:709-21

41. Porth CM. Essentials of Pathophysiology: Concepts of Altered Health States. Second Edition Pages 499-

501.

42. Omur A, Adile BD, Kurt B, et al. Correlation of functional and radiological findings of lung in

asymptomatic smokers. Trop Respir J, 2008; 9:15-19

43. Webber MP, Carpiniello KE, Oruwariye T, Appel DK. Prevalence of asthma and asthma-like symptoms

in inner-city elementary school children. Pediatr Pulmonol. 2002;34:105–111

44. Boyd JH, Moinuddin A, Strunk RC, DeBaun MR. Asthma and acute chest in sickle-cell disease. Pediatr

Pulmonol. 2004;38:229–232.

45. Bernaudin F, Strunk RC, Kamdem A, et al. Asthma is associated with acute chest syndrome, but not with

an increased rate of hospitalization for pain among children in France with sickle cell anemia: a

retrospective cohort study. Haematologica. 2008;93:1917–1918.

46. Phillips KL, An P, Boyd JH, et al. Major gene effect and additive familial pattern of inheritance of asthma

exist among families of probands with sickle cell anemia and asthma. Am J Hum Biol. 2008;20:149–153

47. Leong MA, Dampier C, Varlotta L, Allen JL. Airway hyper-reactivity in children with sickle cell disease.

J Pediatr. 1997;131:278–283. 48. Strunk RC, Brown MS, Boyd JH, Bates P, Field JJ, DeBaun MR. Methacholine challenge in children

with sickle cell disease: a case series. Pediatr Pulmonol. 2008;43:924–929

49. Ozbek OY, Malbora B, Sen N, Yazici AC, Ozyurek E, Ozbek N. Airway hyperreactivity detected by

methacholine challenge in children with sickle cell disease. Pediatr Pulmonol. 2007;42:1187–1192.

50. Bernini JC, Rogers ZR, Sandler ES, Reisch JS, Quinn CT, Buchanan GR. Beneficial effect of intravenous

dexamethasone in children with mild to moderately severe acute chest syndrome complicating sickle cell

disease. Blood. 1998;92:3082–3089.

51. Griffin TC, McIntire D, Buchanan GR. High-dose intravenous methyl prednisolone therapy for pain in

children and adolescents with sickle cell disease. N Eng J Med. 1994;330:733–737.

52. Zanen P, Folgering H, Lammers JJ. Flow- volume indices as means to discriminate between intra and

extrapulmonary restrictive disease. Respir Med 2005; 99:825-29

53. Guerra S, Sherill DL, Venker C, et al. Morbidity and mortality associated with restrictive spirometric

pattern: a longitudinal study. Thorax 2010; 65:499-504.

54. Pesola GR, Magari RT, Dartey-Hayford S, Coelho- D’Costa V, Chinchilli VM. Total lungcapacity: single

breath methane dilution versus plethysmography in normals. Respirology 2007; 12:291-94.

55. Vichinski EP. Pulmonary Hypertension in Sickle Cell Disease. N Eng J Med. 2004; 350:857-60

56. Caboot JB, Allerri JH. Preliminary complication of sickle cell disease in children. Curr Opin, Pediatr

2008; 20:279 – 87.

57. Onyekwere OC, Campbell A, Teshome EM, et al. Pulmonary hypertension in children and adolescents

with sickle cell disease. Paediatr Cardiol, 2008; 29::309-312

58. Sedrak A, Rao SO, Miller ST, et al. A prospective appraisal of pulmonary hypertension in children with

sickle cell disease. J Paediatr Heamatol Oncol 2009; 3:97 – 100.

59. Kaelin M. Professionalization of exercise physiology online. 2001; Vol 4, No 8.

http://faculty.css.edu/tboone2/asep/PEPonlineJan2002ExerciseAsMedication.html. Accessed on 01: 02

:2011.

60. Ganong WF. Review of Medical Physiology. Twenty-first Edition, Lange, USA: McGraw Hill Company.

Pages 656-7.

61. AARC Guidelines: Static Lung Volumes: 2001 Revision and Update. Respir Care, 200: 46:531-39 62. Maclean JA, Atenafu E, Kirby-Allen M et al. Lungitudinal decline in lung volume in apopulation of

children with sickle cell disease. Am J Respr Cri Care Med 2008; 178:1055-59.

63. Hijazi Z. Onadeko BO, Khadadah M, et al. Pulmonary function studies in Kuwait children with sickle cell

disease and elevated HbS. Int J Clin Pract 2005; 59:163-167 62

64. Sylvester KP, Patey RA, Milligan P, et al. pulmonary function abnormality in children with sickle cell

disease. Thorax 2004; 59:67-70.

65. Stocks J, Gappa M, Rabbette DS, et al. a comparison of respiratory function in Afro-Caribbean and

Caucasian infants. Eur Respir J, 1994; 7:11-6.

66. Pianosis PA, D’Souza SJ, Dic Chaege TA, Esselture EA, Allan LA. Pulmonary function abnormality in

childhood sickle cell disease. J Paediatr1993; 122:366-71.

67. Onigbinde MO. Lung Function Test in Nigerian Children With Sickle Cell Amaemia. FMCP Dessertation.

National Post Graduate Medical Collegeof Nigeria. May 2006.

68. Crapo RO. Pulmonary function testing. N Eng J Med. 1994; 331:25-30

69. Booker R. Spirometry in Primary Care. Primary Health Care 2008; 1837-47. American Thoracic

Society. Standardization of spirometry. 1994 update. Am J Respir Crit Care Med. 1995; 152: 1107-36.

70. Mellisant CF, Van Noord JA, Van de Woestijne KP, Demedts M. Comparison of dynamic lung function

indices during forced and quiet breathing in upper airway obstruction, asthma, and emphysema. Chest

1990; 98: 77-83.

71. Meltzer AA, Smolensky MH, D’Alonzo GE, Harrist RB, Scott PH. An assessment of peak expiratory flow as

a surrogate measurement of FEV1 in stable asthmatic children. Chest 1989; 96(2): 329-33.

72. Dekker FW, Schrier AC, Sterk PJ, Dijkman JH. Validity of peak expiratory flow measurement in assessing

reversibility of airflow obstruction. Thorax 1992; 47(3): 162-66.

73. Gautrin D, D’Aquino LC, Gagnon G, Malo JL, Cartier A. Comparison between peak expiratory flow rates

(PEFR) and FEV1 in the monitoring of asthmatic subjects at an outpatient clinic. Chest 1994; 106(5):

1419–26.

74. American Thoracic Society. Standardization of spirometry: 1987 update. Am rev Respir Dis 1987; 12:85-

98. 75. Quanjer PH, Helms P, Bjure J, et al. Standardization of lung function tests in paediatrics. Eur Respir J

1989; 2:(Suppl 4:121S-264S).

76. Oduwole O, Aderele WI, Tweedle MCK. Ventilatory capacity in Nigerian school children. Ann Trop

Paediatr 1983; 3:103-9.

77. Macintyre N, Crapo RO, Viegi G, et al. Standardisation of the single-breath determination of carbon

monoxide uptake in the lung. Eur Respir J 2005; 26:720.

78. Buchvald F, Baraldi E, Carraro S et al. Measurements of exhaled nitric oxide in healthy subjects age 4–17

years. J Allergy Clin Immunol. 2005; 115:1130-6.

79. Fields DA, Higgins PB, Radley D. Air-displacement plethysmography: here to stay. Curr Opin Clin Nutr

Metab Care. 2005;8(6):624-629.

80. Coates AL, Peslin R, Rodenstein D, et al. Measurement of lung volumes by plethysmography. Eur Respir

J 1997; 10:1415-1427

81. Layton AM, Garber CE, Basher RC, Bartel MN. An assessment of pulmonary function testing and

ventilator kinetics by optoeletronic plethysmography. Clin Physiol Funct Imaging. 2011;31:333-36.

82. Behr J and Furst DE. Pulmonary Function Test. Rheumatol. 2008;47:65-67.

83. Townsend C. Spirometry in Occupational Health Setting-2011 update. JOM. 2011;53:569-84

84. Quanjer PH, Burshoom GJJ, Kivastik J, et al. Cross-sectional and longitudinal spirometry in children and

adolescents. Am J Respr Cri Care Med 2008; 178:1262-70

85. Chin DJ, Cotes JE, Martin AJ. Modeling the lung function of Caucasians during adolescence as a basis for

reference values. Ann of Hum Biol 2006; 33:64-7.

86. Neve V, Girard F, Flahault A, Boule M. Lung and thorax development during adolescence: relationship

with pubertal status. Eur Respir J. 2002; 20:1292-1298.

87. Carpenter MA, Tockman MS, Hutchinson RG, Dans CE. Demographic anthropometric correlates of

maximum inspiratory pressure. Am J Respir Cri Care Med 2000; 195:415- 22

88. Daniela ST, Jean-Williams FT. Sniff nasal inspiratory pressure. Reference values in Caucasian children.

Am J Respr Cri Care Med 1999; 159:107-11.

89. Waldemar T, Andrzej P, Jaroslow P. normal values of maximal static inspiratory and expiratory pressure

in healthy children. Pediatr Pulmonol. 2002; 349:42-46. 90. Paul McCulloch. A simple model illustrating the balancing forces of lung and chest wall recoil. Advan.

Physiol. Educ. 2004; 28:125-27.

91. Sala H, Galindez F, Badolati A, Rodenstein D. Relationship between supramaximal flows and flow-

limiting mechanisms. Eur Respir J, 1996, 9, 512–516

92. Landau LI, Morgan W, McCoy KS, Tausig LM. Gender related differences in airway tone in children.

Pediatr Pulmonol 1993; 16:31-35.

93. McKenzie SA, Chau E, Dundas I, et al. Airway resistance measured by the interrupter technique :

normative data for 2-10 years old of three ethnicities. Arch. of Dis. in child 2002; 87:249-51.

94. Torres LA, Martinez FE, Manco JC. Correlation between standing height, sitting height, and arm span as

an index of pulmonary function in 6-10 years old children. Pediatr. Pulmonol.2003; 36:202-8

95. Renner JK, Oduwole AO, Jaja SI. Effect of Stance on Peak Expiratory Flow. Nigerian Journal of Clinical

Practice 1999;2:56-58.

96 Olanrewaju DM, Adekile AD, Ariwoola JO. Pulmonary function in Nigerian children and young adults

with sickle cell anaemia. Nig J Paediatr 1986;15:7-14.

97 Kirkwood BR, Sterne JA. Calculation of required sample size. In: medical statistics, 2nd Edition, Oxford,

UK: Blackwell science page 413-428.

98 Solarin AU. Microalbuminuria among aged 5-15 years with SCA attending The Lagos Staate University

Teaching hospital, Ikeja. A Dissertation submitted to the West African College of physician. Oct 2010.

99 Lesi FEA. Anthropometric status of sickle cell anaemia in Lagos Nigeria .Nig Med J 1979;9:337-44.

100 Barden EM, kawchak A, ohene-freepongK et al. Body composition in children with

sickle cell disease. Am J Clin Nutr. 2002;76:218-25.

101 Stephens MCG, Maude GH, Cupidore L et al. Prepubertal growth and skeletal maturation in children

with sickle cell disease. Am J Pediatr. 1986;78:124-132.

102 Dhananjay BN, Kulkarmi AP, Aswan ND. Birth Weight and Anthropometry of Newborn. Indian J

Pediatr. 2003;70:145-46.

103 Mohanty SP, Suresh BS, Sreekumaran NN. The use of arm span as a predictor of height. A study of south Indian women. J Orthop Surg 2001; 9:19-23.

104 Sadat-Ali M, Ammar A, Corea JR, Ibrahim AW. The spine in sickle cell disease. Int Orthop.993; 18:154

– 6.

105 Ozoh JO, Onuigbo MAC, Nwankwo N, Ukabam SO, Umerah BC, Emeruwa CC. Vanishing of vertebra

in a patient with sickle cell haemoglobinopathy. Br Med J 1990; 301:1368 – 9).

106 Collett-Solberg PF, Ware RE, O’Hara S. asymmetrical closure of epiphysis in a patient with sickle cell

anaemia. J Pediatr Endocrinol Metab.2002;151207-12

107 Demissie K, Ernst P, Hanley JA, et al. Socioeconomic status and lung function among primary school

children in Canada. Am J Respir Crit Care Med 1996;153:719–23

108 Harik-Khan RI, Fleg JL, Muller DC, et al. The effect of anthropometric and socioeconomic factors on

the racial difference in lung function. Am J Respir Crit Care Med 2001;164:1647–54..

109 Wheeler, BW, Ben-Shlomo, Y Environmental equity, air quality, socioeconomic status, and respiratory

health: a linkage analysis of routine data from the Health Survey for England. J Epidemiol Community

Health 2005;59:948-954

110 Barreiro TJ, Perillo I. An Approach to Interpreting Spirometry. Am Fam Physician. 2004;69:1107-15.

111 Oyedeji GA. Socio-economic and cultural background of hospitalized patients children in Ilesha. Nig J

Paediatr. 1985;12:111-7

112 Charache S. Terrin ML, Moore RD, et al. Effect of hydroxyurea on the frequency of painful crises in

sickle cell anemia. N. Eng. J. Med. 1999;332:1317–1322.

113 Singh, S.A., Koumbourlis, A.C., Aygun, B. Resolution of chronic hypoxemia in pediatric sickle cell

patients after treatment with hydroxyurea. Pediatr. Blood Cancer 2008;50:1258–1286.

114 Ballet PS, Kalinyak KA, Shikla R et al. Incentive spirometry to prevent acute pulmonary complication in

sickle cell disease. N Eng J Med. 1995;333:699-703.

115 Hackshaw A. Small studies: Strength and limitations. Eur Respir J 2008;32:1141-43

116 Bonder C, Godden D, Seaton A. Family size, childhood infection and atopic disease. The aberden

WHEASE Group. Thorax. 1998;53:28-32 117 Rona RJ, Duran-Tauleria E, Chinn S. Family size, atopic disorder in parents, asthma in children and

ethnicity. J Allergy Clin Immunol. 1997;99:454-60.

118 Ponsonby AL, Couper D, Dwyer T et al. Cross sectional study of the relationship between sibling

number and asthma, hay fever and eczema. Arch Dis, Child. 1998;79:328-33

119 Jarvis D, Chinn S, Luczynska C et al. The association of family size with atopy and atopic disease. Clin

Exp Allergy. 1997;27:240-245

120 Mannino DM, Doherty DE, Buist AS. Global Initiative on Obstructive Lung Disease (GOLD)

Classification of Lung Disease and Mortality: findings from atherosclerotic risk in communities (ARIC)

study. Respir Med. 2006;100:115-22.

121 Palermo TM, Schwartz L, Drotar D, McGowan K. Parental report of health-related quality of life in

children with sickle cell disease. Journal of Behavioral Medicine. 2002;25:269–283.

122 Boskabady MH, Tababaei S, Shahmohammadi S, et al. Prediction equations for pulmonary function

values in healthy Iranian children (aged 4–10 years). Thorax 2010;65:A134

doi:10.1136/thx.2010.150987.34

123 Sumathi Swaminathan, Bronwyn Diffey and Mario Vaz. Evaluating the Suitability of Prediction

Equations for Lung Function in Indian Children: A Practical Approach. Indian Pediatrics 2006; 43:680-

698.

124 Ballet PS, Kalinyak KA, Shikla R et al. Incentive spirometry to prevent acute pulmonary complication in

sickle cell disease. N Eng J Med. 1995;333:699-703.

125 Yazdanbakhsh M, Kremsner PG, Ronald R. Allergy, Parasites, and the Hygiene Hypothesis. Science

2002; 296: 490-94

Appendix I

Socioeconomic stratification

This was based on the socioeconomic class described by Oyedeji.111 The occupation and educational attainment of the parents/guardians were used to determine the socioeconomic class scores of the children. Each child was given two class scores for the father: one for occupation and the other for educational attainment according to the score described by Oyedeji (below). The same criteria were also used to assign class scores to the mother. The four scores were summed and the mean (approximated to the nearest whole number) obtained. The score was used to assign the child to one of five socioeconomic groups (I to V).

Education:

1) University graduate or equivalent 2) School Certificate + Teaching or other professional training. 3) School Certificate or Grade II Teacher’s Certificate or equivalent 4) Modern 3 and Primary 6 5) Barely literate or illiterate

Occupation:

1) Senior public servants, professionals, managers, large scale traders and contractors 2) Intermediate grade public servants and senior secondary school teachers 3) Junior secondary school teachers, drivers and artisans 4) Petty traders, labourers, messengers and similar grades 5) Unemployed, full-time housewives, students and subsistence farmers

The five socioeconomic classes can be sub-classify into Upper (socioeconomic classes I and II), Middle (socioeconomic classes III) and Lower (socioeconomic classes IV and V) socioeconomic strata.

Appendix II

Comparison of mean male PFT values in current study with an existing male PFT values by Oduwole and

Aderele 76.

Height group subjects reference subjects reference subjects reference mean FEV1 mean FEV1 mean FVC mean FVC mean PEFR mean PEFR

105-109.99 1.07(0.15) 0.90(0.07) 1.15(0.20) 0.95(0.07) 178.33(28.43) 149.63(21.58)

110-114.99 1.13(0.10) 1.10(0.22) 1.24(0.13) 1.18(0.24) 170.83(11.58) 174.84(29.22)

115-119.99 1.14(0.13) 1.15(0.17) 1.29(0.16) 1.28(0.18) 178.57(23.14) 189.46(34.88)

120-124.99 1.30(0.09) 1.20(0.15) 1.45(0.14) 1.35(0.15) 200.00(10.80) 225.78(40.91)

125-129.99 1.43(0.13) 1.39(0.19) 1.65(0.17) 1.54(0.21) 236.88(29.87) 261.80(38.67)

130-134.99 1.59(0.13) 1.56(0.25) 1.91(0.21) 1.72(0.27) 246.67(27.69) 282.32(37.85)

135-139.99 1.75(0.20) 1.78(0.23) 2.04(0.34) 1.96(0.28) 257.00(48.04) 304.75(34.45)

140-144.99 1.90(0.09) 1.86(0.26) 2.19(0.11) 2.05(0.27) 296.00(38.49) 316.58(41.47)

145-149.99 1.91(0.21) 1.98(0.33) 2.24(0.22) 2.18(0.33) 313.75(45.16) 342.16(41.76)

150-154.99 1.75 - 2.25(0.24) 2.15 - 2.47(0.30) 300.00 - 361.86(35.32)

155-159.99 -- 2.47(0.32) -- 2.67(0.27) -- 396.80(39.01)

160-164.99 2.15 - 2.74(0.36) 2.45 - 2.98(0.37) 410.00 - 402.71(48.05)

SD= Standard deviation, - Implies no standard deviation due to single subject, -- implies no subject in the height

group

Appendix III

Comparison of mean female PFT values in current study with an existing female PFT values by Oduwole and

Aderele 76.

Height group subjects reference subjects reference subjects reference mean FEV1 mean FEV1 mean FVC mean FVC mean PEFR mean PEFR

105-109.99 1.10 - 1.03(0.15) 1.3 - 1.15(0.13) 170 - 154.07(28.56)

110-114.99 1.09(0.13) 1.03(0.19) 1.25(0.22) 1.15(0.17) 177.14(13.50) 168.48(36.88)

115-119.99 1.08(0.15) 1.08(0.12) 1.28(0.16) 1.22(0.13) 180.83(26.35) 182.83(33.98)

120-124.99 1.16(0.13) 1.20(0.22) 1.34(0.16) 1.33(0.24) 190.00(21.21) 227.93(42.86)

125-129.99 1.61(0.53) 1.28(0.24) 1.83(0.66) 1.40(0.25) 239.00(66.28) 253.52(44.13)

130-134.99 1.57(0.15) 1.41(0.24) 1.79(0.19) 1.56(0.25) 231.25(27.22) 270.18(41.18)

135-139.99 1.58(0.15) 1.54(0.22) 1.84(0.21) 1.67(0.24) 233.75(21.18) 289.00(40.71)

140-144.99 1.83(0.24) 1.67(0.24) 2.15(0.39) 1.85(0.24) 264.00(54.36) 301.82(46.56)

145-149.99 1.90 - 1.99(0.32) 2.20 - 2.15(0.32) 315 - 344.33(40.52)

150-154.99 2.13(0.13) 2.23(0.32) 2.50(0.50) 2.42(0.33) 330.00(25.98) 374.74(40.04)

155-159.99 2.00 - 2.44(0.34) 2.40 - 2.63(0.38) 305.00 - 377.87(42.83)

160-164.99 2.85 - 2.51(0.39) 2.95 - 2.74(0.40) 330.00 - 407.22(37.20)

SD= Standard deviation, - Implies no standard deviation due to single subject, -- implies no subject in the height

group

APPENDIX IV

Statement of informed consent and consent form

I am Dr. Faleti Abiodun of the Paediatrics Department of the Lagos State University Teaching

Hospital (LASUTH). I am carrying out a study to compare lung function among children with sickle cell anaemia with those without sickle cell anaemia

The information you and other people give to me will be helpful to doctors to make better decisions on treatment of children who have sickle cell anaemia.

I will need to ask you some questions about your child/ward. Also, medical examination and tests will be carried out on your child/ward to detect some signs that are related to lung function.

All precautions will be taken to ensure that the process of testing and examination will not cause your child/ward any harm or injury. All information obtained in this study is strictly confidential.

You are free to refuse to take part in this programme. You also have the right to withdraw at any given time if you choose. Your refusal to participate will not in any way affect my professional relationship with your child/ward or affect your child’s treatment in the hospital. If you have any questions concerning this study, you may contact me in the ward in the

Department of Paediatrics, LASUTH or call me on this telephone number- 08033312060. If you agree for your child to participate, please sign below.

Thank you.

Dr Faleti Abiodun.

Date……………………. Signature of parent/guardian…………………………….

Name of parent/guardian……………………………………………………………………

APPENDIX V

DATA COLLECTION PROFORMA ON PULMONARY FUNCTION TEST IN CHILDREN WITH

SICKLE CELL ANAEMIA AND CONTROL SUBJECTS

A. SUBJECT BIODATA

1. Subject study code number…………………………………

2. Age………………………………………………………….

3. Gender: M F

4. Address…………………………………………………..……………………

………………………………………

5. Single or marrie parents

6. Number of children in family including subject 7. Parent’s educational level:

Father……………………………………………………

Mother…………………………………………………...

8. Occupation of parents

Father……………………………………………………

Mother…………………………………………………..

B HISTORY

9. Genotype ( if known )………………………………………

10. Genotype confirmed when…………………………………..

11. Number of crisis per year……………………………………

12. When experienced last crisis…………………………………

13. Type of last crisis experienced………………………………

14. Any cough with fever in the last six months? ………….. If yes, give details

……………………………………………………………………………….

15. Have you been admitted for cough and chest pain before?...... If

yes, how many times. 16. Any recurrent episodes of cough associated with breathlessness? ………….. if

yes give details.

………………………………………………………………………….

…………………………………………………………………………………

…….

17. Is any member of your family receiving treatment for chronic cough?

…………. If yes give details

…………………………………………………………………….

…………………………………………………………………………………

…

C EXAMINATION

1 Anthropometry

a. Height (cm)…………………………….

b. Sitting height (cm)………………………………..

c. Chest circumference (cm)………………………...

d. Arm span (cm)……………………………………..

e. weight (kg)………………………………………...

2 General physical findings a. Pallor Yes No

b. Jaundice Yes No

c. Cyanosis Yes No

3 Respiratory system

a. Any breathlessness or fast breathing

b Any chest deformity Yes No

4 Cardiovascular system

a. Gallop rhythm: Yes No

b. Murmur: Yes No

if yes, type………………………………….

D LABORATORY TEST RESULTS

(i) Genotype ( if unknown) ……………………..

(ii) Packed cell volume …………………………..

(iii) PULMONARY FUNCTION TESTS

1st 2nd 3rd best value

attempt attempt attempt

(1) FEV 1.0 ( litres ) …………… ………….. ………… …………..

(2) FVC ( lit …………… ………….. ………… …………

(3) PEFR(liters/ m) ………… …………. ……….. ………….

(4) FEV1/FVC ……………. ……………. …………… …………...

‘

Appendix VI