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Dentofacial morphology in children with obstructive sleep apnea. Lee, Kevin Chien-Hsun 2015

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DENTOFACIAL MORPHOLOGY IN CHILDREN WITH OBSTRUCTIVE SLEEP APNEA  by Kevin Chien-Hsun Lee   B.Sc., The University of British Columbia, 2007  D.M.D., The University of British Columbia, 2011  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Craniofacial Science)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)   August 2015   ©  Kevin Chien-Hsun Lee, 2015 ii  Abstract  Objectives:  Altered dentofacial morphology has been suggested as an etiology for childhood OSA. Nevertheless, existing reports on the dentofacial characteristics of children with OSA vary significantly and are limited by the infrequent use of polysomnography (PSG) for diagnosis. Therefore, the objective of this study is to establish the prevalence of dentofacial morphology in children with OSA diagnosed using PSG.  Methods: The sample comprised 64 children between the ages of 4-16 who were referred to BC Children’s Hospital for PSG. Diagnosis of OSA was provided by an overnight, in-laboratory PSG. Malocclusion was assessed clinically by one orthodontist (K.L.), blinded to PSG results.   Results:  Children with previous orthodontic treatment were excluded and children with craniofacial syndromes were analyzed separately. The 17 patients with craniofacial syndromes presented a significantly different dentofacial features and higher prevalence of OSA when compared to the non-syndromic children. The remaining 39 patients were divided into an OSA group (AHI ≥ 2; n=17) and a non-OSA group (AHI < 2; n=22). There were no statistically significant differences in frequency of any dentofacial features between the two groups, although the OSA group had a lower prevalence of convex profile, Class II molar relationship, and overjet (OJ) ≥ 5mm.   Subjects in the OSA group were further divided into a lower AHI (AHI between 2-5; n=9) group and a higher AHI group (AHI ≥ 5; n=8). There was no statistically significant difference in iii  frequency of any dentofacial features between the three groups. Nevertheless, subjects in the higher AHI group had a lower prevalence of convex profile and poster crossbite, with less crowding and smaller OJ on average.   Conclusions:  In this patient population of 39 children between the ages of 4-16 who were referred to BCCH for an overnight sleep study, no statistically significant differences in dentofacial morphology and occlusal characteristics were found between children diagnosed with and without OSA. It is likely that children with OSA have a highly variable presentation of anatomical features, and future studies with a larger sample size and a true control group is needed to establish the dentofacial morphology of this population. iv  Preface Dr. Fernanda Almeida suggested the research topic of this project and together Drs. Fernanda Almeida and Nelly Huynh identified the research question and designed the project. Kevin Lee collected and analyzed the data. Lastly, Kevin Lee prepared the manuscript with content editing by Drs. Fernanda Almeida, Nelly Huynh, Alan Lowe and Benjamin Pliska.  The study was approved by the University of British Columbia Office of Research Services, Humans Research Ethics Board (Certificate Number: H12-03285).  v  Table of Contents  Abstract .......................................................................................................................................... ii Preface ........................................................................................................................................... iv Table of Contents ...........................................................................................................................v List of Tables ............................................................................................................................... vii List of Figures ............................................................................................................................... ix List of Abbreviations .....................................................................................................................x Acknowledgements ...................................................................................................................... xi Dedication ................................................................................................................................... xiii Chapter 1: Introduction ........................................................................................................... 1 1.1 Epidemiology .............................................................................................................. 3 1.2 Pathophysiology .......................................................................................................... 5 1.3 Diagnosis................................................................................................................... 12 1.4 Treatment of OSA ..................................................................................................... 21 1.5 Sequelae of Untreated Pediatric OSA ....................................................................... 27 1.6 Obstructive Sleep Apnea and Craniofacial and Dentofacial Development .............. 29 1.7 Hypothesis................................................................................................................. 35 1.8 Objectives ................................................................................................................. 36 Chapter 2: Material and Methods ......................................................................................... 37 2.1 Subjects ..................................................................................................................... 37 2.2 Methods..................................................................................................................... 38 vi  2.3 Clinical Orthodontic Examination: ........................................................................... 39 2.4 Overnight Polysomnography .................................................................................... 47 2.5 Statistical Analysis .................................................................................................... 48 2.6 Analysis of Error ....................................................................................................... 49 Chapter 3: Results................................................................................................................... 50 3.1 Error Analysis ......................................................................................................... 50 3.2 Subjects .................................................................................................................... 51 3.3 Questionnaire and PSG results .............................................................................. 55 3.4 Dentofacial Morphology ......................................................................................... 58 3.5 Need for Orthodontic Treatments ......................................................................... 63 3.6 Correlations between dentofacial morphology and OSA diagnosis ................... 64 Chapter 4: Discussion ............................................................................................................. 66 4.1 Error Analysis ........................................................................................................... 67 4.2 Subjects ..................................................................................................................... 68 4.3 Questionnaire & PSG results .................................................................................... 70 4.4 Dentofacial morphology ........................................................................................... 71 4.5 Need for orthodontic treatment ................................................................................. 76 4.6 Limitations of the study: ........................................................................................... 78 Chapter 5: Potential Future Studies ..................................................................................... 80 Chapter 6: Conclusions .......................................................................................................... 83 Bibliography .................................................................................................................................84 Appendix A ...................................................................................................................................94  vii  List of Tables  Table 1-1 Symptoms and Signs of OSA 12 ................................................................................... 13 Table 1-2 Phase I Screening Questionnaires  3 ............................................................................. 18 Table 1-3 Summary of Literature Review .................................................................................... 32 Table 2-1 Inclusion and Exclusion Criteria .................................................................................. 38 Table 2-2 Frontal View ................................................................................................................. 40 Table 2-3 Profile View.................................................................................................................. 40 Table 2-4 Functional assessment .................................................................................................. 41 Table 2-5 Dental Health Component of Index of Orthodontic Treatment Need .......................... 43 Table 2-6 Intra-Oral Examination ................................................................................................. 44 Table 2-7 CDC Weight Categories ............................................................................................... 48 Table 3-1 Percentage agreement of repeated clinical orthodontic examination measurements recorded 2-6 months apart. ........................................................................................................... 50 Table 3-2 Percentage agreement between measurements recorded with clinical examination and orthodontic photographic records. ................................................................................................ 51 Table 3-3 Comparison of dentofacial morphology between children with and without craniofacial syndromes ................................................................................................................. 53 Table 3-4 Demographic distribution of children in Non-OSA and OSA group ........................... 54 Table 3-5 Demographic Data ........................................................................................................ 55 Table 3-6 Sleep Questionnaire and PSG results of OSA patients compared with non-OSA patients .......................................................................................................................................... 56 viii  Table 3-7 Prevalence of dentofacial morphology characteristics of patients of the study sample, non-OSA group, OSA group, lower AHI OSA group, and higher AHI OSA group.................... 59 Table 3-8 Association between evaluated dentofacial morphology, weight status, and diagnosis of OSA (AHI ≥2) .......................................................................................................................... 65  ix  List of Figures  Figure 3-1 Sensitivity and Specificity of the 6-Questions Questionnaire in predicting patients with AHI≥2 ................................................................................................................................... 58 Figure 3-2  A comparison of  the percentage of patients in the non-OSA and OSA groups that presented with altered dentofacial morphology including convex profile, anterior crossbite, increased OJ of ≥5mm, Class II molar relationship, increased lower face height, deep bite of ≥50% OB, anterior openbite, posterior crossbite, and maxillary and mandibular crowding of ≥4mm. ........................................................................................................................................... 60 Figure 3-3 A comparison of the percentage of patients in the non-OSA, lower AHI OSA, and higher AHI OSA group that presented with convex profile, anterior crossbite, increased OJ of ≥5mm, increased lower face height, deep bite of ≥50% OB, posterior crossbite, and maxillary and mandibular crowding of ≥4mm. ............................................................................................. 61 Figure 3-4 Box plot presentation of measurements of (a) overjet, (b) overbite, (c) maxillary intercanine width, and (d) maxillary intermolar width in non-OSA, lower AHI OSA, and higher AHI OSA children. Each box plot represents the median and 25th and 75th percentile. ............. 63 Figure 3-5 Comparison of the need for orthodontic treatment as indicated using IOTN criteria and need for maxillary expansion and growth modification treatment between non-OSA group and OSA groups. ........................................................................................................................... 64  x  List of Abbreviations AASM: American Academy of Sleep Medicine AAP: American Academy of Pediatrics AHI: apnea hypopnea index  BMI: body mass index CHAT: Childhood Adenotonsillectomy Trial CPAP: continuous positive air pressure DS: Down Syndrome ICSD II: The International Classification of Sleep Disorders II IOTN: Index of Orthodontic Treatment Need OA: oral appliances ODI: oxygen desaturation index OJ: Overjet OSA: obstructive sleep apnea PSQ: pediatric sleep questionnaire RME: rapid maxillary expansion T & A: Tonsillectomy and/or Adenoidectomy SDB: sleep disordered breathing UARS: Upper airway resistance syndrome   xi  Acknowledgements I would like to acknowledge Drs. Edwin Yen, David Kennedy, Benjamin Pliska and the other members of the Graduate Admission Committee for accepting me into the UBC Graduate Orthodontic Program. I have wanted to become an orthodontist since I had braces on my teeth and I am extremely grateful for the opportunity that I was given. I have received a century’s worth of collective knowledge and experience from the instructors in this program. They are my mentors, my colleagues, and my friends; I have the upmost respect and gratitude for each one of them.   I am a clinician at heart, and it was challenging for me to adopt the mindset of a researcher. Fortunately, I have some of the most intelligent and dedicated researchers in the field of sleep medicine on my team. I could not be more grateful of the supervision of wonderful, erudite mentors such as Drs. Fernanda Almeida, Benjamin Pliska, Nelly Huynh, David Wensley and Alan Lowe.   I am so thankful to Dr. Fernanda Almeida for offering me the opportunity to take on this great project. As a supervisor, she is kind, patient, encouraging, and always there for me with an open door (literally). As a researcher, she is passionate, thorough, and bold. I’ve learned not only the methodology of conducting good research, but also important wisdom in life that makes me a better person. The passion she has for her work is contagious, and I am truly blessed and honored to have the chance to work alongside and form a relationship with such a brilliant and dedicated researchers. Thank you, Dr. Almeida!  xii  I want to also thank Dr. Benjamin Pliska for his participation in my committee, helping me to brainstorm and edit my thesis, as well as generously and charmingly sharing his outstanding clinical knowledge and skills in everyday learning and the orthodontic clinics. I also want to thank Dr. Nelly Huynh for helping us to establish the research protocol and all the documentation, sharing her amazing energy and personality whether in person or through Skype, and helping me to edit my thesis. I would also like to thank Dr. David Wensley for allowing us to use his facility and sharing his knowledge of pediatric sleep medicine. Moreover, I would like to thank Dr. Wensley's wonderful and kind staff; this project would not have been possible without their help. Finally, I want to thank Dr. Alan Lowe for his participation in my committee. Dr. Lowe is a pioneer in the research of orthodontic and sleep medicine and his help with this project was invaluable.  And, of course, three wonderful women I will never forget for their great help and kindness are Heather Beal for preparing the patient s for data collection, Kirstie Santos for informing me of the schedules and helping me with secretarial work, and Mary Wong for help with the database and statistical analyses. Thank you to Gail Furlong and Michele Wong for helping me sterilize the equipment for my project. Finally, thank you to Ms. Clare Davies for the editorial work for this thesis.   Lastly, to my fellow residents with whom I shared laughter, tears and sweat for the past three years, I will treasure every moment that we have spent together, from studying embryology to practicing wire bending to enjoying the odd pint at Mahony’s. I prayed for good classmates and was given life-long friends, and I could not be more grateful.  xiii  Dedication First and foremost, praise and thanks goes to my savior Jesus Christ for the many blessings undeservingly bestowed upon me. It is my prayer that this dissertation may be a testimony for you and your glory.  I also dedicate this dissertation to my loving parents. You uprooted yourselves from your home country, so that I could place my root in a better place. You left your work in your prime, so I could grow into my prime with my parents behind me. You changed your careers in late adulthood, so I could pursue my dreams. You gave everything to me, and everything I am, is owed to you. Thank you, Mom and Dad; I love you.   Finally, I dedicate this to my beautiful wife, Sherry. Meeting you was the best gift God has given me, and I am still overwhelmed by the thought that we are now married. I know the past year has been difficult for you as I was kidnapped by the board exams, clinic duty, and research.  Thank you for taking all the loads that are supposed to be shared between husband and wife, and allowing me to concentrate during this critical time. I could not have done this without you; hence, this is dedicated to you. Now that I have been released, I look forward to spending every moment with you and our future children, for the rest of my life.    1  Chapter 1: Introduction  Obstructive Sleep Apnea (OSA) was first described by Guilleminault et al. in 1976 using polysomnography and clinical symptoms (Guilleminault, 1976). Since then there has been increased recognition of  sleep disorders in children, and subsequent research has resulted in the development of many classification systems, including the Diagnostic Classification of Sleep and Arousal Disorders published in 1979, and the International Classification of Sleep Disorders (ICSD) published in 1990 and its revision, ICSD 2, published in 20051.    Sleep-disordered breathing (SDB) is a continuum which encompasses a spectrum of disease of varying severity, ranging from habitual snoring, labored breathing, sleep disruption and/or gas exchange abnormalities 2. Clinically, various forms of SDB can be differentiated using different clinical and polysomnographic presentations 3.   The mildest form is habitual snoring or primary snoring, which was described by the American Academy of Pediatrics (AAP) as “snoring without obstructive apnea, frequent arousals from sleep, or gas exchange abnormalities” 4. This suggests that neuromuscular compensation is able to sustain stable breathing and maintain the breathing effort below the threshold level of arousal3. Nevertheless, primary snoring had been found to be associated with significant neurobehavioral deficits in a subset of children5, suggesting it may not be benign.  The intermediate forms of SDB include obstructive hypoventilation and upper airway resistance syndrome (UARS). Obstructive hypoventilation is habitual snoring without apnea and hypopnea, 2  but with a stable increased respiratory effort and hypercapnia3. In order to maintain stable sleep, there is increased neuromuscular compensation. However, this effort was not enough to maintain baseline minute ventilation, resulting in hypercapnia3. It is hypothesized that these children have moderate anatomical predisposition towards OSA3.  UARS was first described by Guilleminault et al. in 1993 as brief, repetitive respiratory effort related arousals, and daytime sleepiness without overt sleep apnea, hypopnea, or gas exchange abnormalities6. It was observed that compared with children with OSA, children with UARS aroused with less respiratory effort7, suggesting that reduced arousal threshold may be a possible etiology. Nevertheless, as children with UARS have similar daytime neurobehavioral symptoms to those with OSA, and respond similarly as children with OSA do, it is likely that they share common pathophysiology8. However, whether UARS needs to be regarded as a distinct disease is controversial. The American Academy of Sleep Medicine (AASM) concluded that the current clinical and pathophysiological data are not sufficient to specify UARS as a distinct condition; instead it was defined as a mild form of OSA9,10. The International Classification of Sleep Disorders II's (ICSD II) 2005 version is consistent with the AASM in this matter11.   OSA syndrome is the most severe form of SDB. In 2012, it was defined by the AAP as a “disorder of breathing during sleep characterized by prolonged partial upper airway obstruction and/or intermittent complete obstruction (obstructive apnea) that disrupts normal ventilation during sleep and normal sleep patterns” 12. The increased respiratory effort results in a reflex recruitment of upper airway muscles and serves as an arousal trigger (Gozal 2012 3). As in adults, the gold standard for diagnosis of OSA in children is an overnight polysomnography 3  study, which records sleep architecture, respiration, cardiac rhythm, muscle activity, gas exchange, and snoring13. The most important index of polysomnography in defining the severity of OSA is the apnea/hypopnea index (AHI), which is defined as the number of apneas and hypopneas per hour of total sleep time. Apnea in children is scored when a drop in the peak airflow is ≥ 90% of the pre-event baseline, with the drop lasting at least the duration of two breaths during baseline breathing and is associated with the presence of respiratory effort throughout the entire period of absent airflow14. Hypopnea is scored in children when the drop in peak airflow is ≥ 30% of pre-event baseline, for the duration of at least two breaths in association with either ≥ 3% oxygen desaturation or an arousal14,15. It was found that that an apnea/hypopnea index (AHI) greater than 1.5 events per hour is abnormal in a child16-21.  1.1 Epidemiology It is difficult to obtain the prevalence of SDB due to inconsistency in the definition of the disease used by different studies15. Lumeng et al. performed a meta-analysis of the prevalence of SDB in children (defined as age from 0 to 18 years old) by reviewing 48 articles worldwide including studies from USA, Europe, Asia, Middle East, and Australia8. They reported that the overall prevalence of parent-reported snoring in children by any definition was 7.45%, while parental report of apnea varied from 0.2 to 4%8. They also found that prevalence of SDB identified by parent-reported symptoms on questionnaires was estimated between 4 to 11%, while prevalence of OSA diagnosed by diagnostic polysomnography studies was reported to be 1 to 4% by most studies8. In 2009, Bixler et al. investigated the prevalence and risk factors of OSA in a representative sample of elementary school children using full polysomnogram and complete history/physical examination. They found that the prevalence of moderate OSA (AHI ≥ 5) was 4  1.2% in the USA, and waist circumference/BMI, nasal abnormalities, and ethnic minority (non-Caucasian) are the main risk factors22. Li et al in 2009 reported similar numbers. They noted that 9 to 10% of children are habitual snorers, while 1-3% of children were estimated to have UARS13. In the 2012 guideline published by AAP, Marcus et al. reported that prevalence of habitual snoring varied widely, depending on the study and definition used, from 1.5% to 27.6%, while prevalence of OSA is found to be in the range of 1% to 5%21.   It has been reported in various studies in the United States that SDB is more prevalent among African American children than Caucasian children8,15, and Asians have more severe OSA than matched Caucasians23; the difference between races is less clear in other populations. Lumeng et al. also reported that SDB is more common among boys and heavier children8. SDB was reported to present most commonly in 2 to 5 year olds, but it can present in all ages11. OSA does run in families, and it is likely that both genetic and environmental factors play a role 15.   Metabolic and inflammatory factors are also important risk factors for the development of  OSA22. Using questionnaires, Li et al. studied 20,152 Chinese children and found 7.2% had habitual snoring, with male gender, obesity, parental habitual snoring, atopic symptoms, and history of upper respiratory infection being significant risk factors24. Other medical conditions that increase risk of OSA include syndromes with midface hypoplasia (i.e., Pierre Robin sequence, Crouzon Syndrome, Treacher Collins), increased body-mass index (Prader-Willi syndrome), large tongue (i.e., Beckwith Wiedeman syndrome, Trisomy 21), and neuromuscular disorders (i.e., cerebral palsy and myotonic dystrophy)15.    5  1.2 Pathophysiology Apnea or hypopnea occurs when the patency of the airway is diminished, resulting in the reduced effectiveness of the lungs to perform ventilation25. The patency of the airway depends on the balance between the collapsing forces, which include the intraluminal negative pressure and airway anatomy, and the dilating forces from the pharyngeal muscles and changes in lung volume26. These forces are affected by factors such as the anatomical structure, neuromotor tone, and inflammation; hence it has been suggested by many authors that the pathophysiology of OSA should be approached using these categories15,27.   1.2.1 Anatomical Structure Humans are the only mammal in which the hyoid bone, a key anchoring site for pharyngeal dilator muscles, is not rigidly attached to skeletal structures25. As a result, the cross-sectional area of the airway depends on luminal pressure25,28 and the activity of the pharyngeal dilator muscles. Patients with OSA had been shown to have increased upper airway collapsibility when awake29 and it is plausible that these patients may have an anatomically small pharyngeal airway27. Using computerized tomography on awake patients, Haponik et al. observed a reduced cross-sectional area in the nasopharynx, oropharynx, and/or hypo-pharynx of patients with OSA30. CT imaging was also used by Schwab et al., who reported that an enlarged tongue and lateral pharyngeal wall size independently increased the risk for OSA31,32.   Furthermore, the physical size of the craniofacial and dentofacial skeleton and the amount of soft tissue within and surrounding the airway also affect the airway size25,26. As infants and young children are obligate nose breathers, difficulties with nasal breathing in children result frequently 6  from large adenoids 15. It is known that adenotonsillar tissue is largest in relative size in the first few years of life and gradually involutes by adolescence and adulthood15. Using magnetic resonance imaging (MRI), Ni et al. observed that in children with OSA and primary snoring, the upper airway is restricted by both the adenoid and tonsils; the soft palate is also larger in children with OSA, adding further restriction33. Nevertheless, as indicated by the high percentage of patients who suffer from persistent OSA after adenotonsillectomy, adenotonsillar hypertrophy is only one of the anatomical determinants of OSA in children34.  In addition to adenotonsillar hypertrophy, reduced size in craniofacial and dentofacial bony structures compromises the pharyngeal space and also contributes to the development of OSA25. In a cross-sectional study of 604 pediatric patients, Huynh et al. found that SDB symptoms were primarily associated with adenotonsillar hypertrophy, morphologic features related to a long and narrow face (dolichocephalic facial profile, high mandibular plane angle, narrow palate, and severe crowding in the maxilla and the mandible), allergies, frequent colds, and habitual mouth breathing35. Furthermore, Flores-Mir et al. conducted a meta-analysis in 2013 and found from the nine selected studies that pediatric OSA patients, when compared with controls, have a steeper mandibular plane angle (MP-SN = +4.2deg), a more retrusive mandible (SNB = -1.79 deg), and are more likely to show a class II skeletal pattern (ANB = +1.38deg). Similar results were found by Katyal et al. in a meta-analysis conducted in 2013. They found that the sagittal dimension of the airway measured from the posterior nasal spine to the adenoids on cephalomatric radiographs  is on average 2.60-5.60 mm  shorter in children with OSA than it is in children of healthy control groups36, indicating that children with OSA have enlarged soft tissue negatively affecting the lumen size of the upper airway.  7   Down Syndrome (DS) is an example of how anatomical structural deformities can lead to development of OSA. These deformities include macroglossia, glossoptosis, hypopharyngeal collapse, tracheal stenosis, laryngomalacia and recurrent enlarged adenoids15. Studies done by Marcus et al. and Dyken et al. showed that OSA was found in 63% and 79% children with DS, respectively37,38, which demonstrates higher prevalence than in the general pediatric population (see section 1.1). Also using polysomnography (PSG) but on a younger group of patients, Shott et al. found that 80% of the children diagnosed with DS showed abnormal PSG results39.   1.2.2 Neuromuscular The clinical observations that 1) apnea is observed mainly during rapid eye movement (REM) and stage 2 sleep but not in wakefulness or slow wave sleep40; 2) there is considerable overlap in airway size in both OSA and control children who were sedated and anesthetized28,41; and 3) most OSA children were able to intermittently obtain a stable breathing pattern during sleep, suggest that neuromuscular compensation below arousal level is possible and that anatomic properties are not the only determinants of airway patency34.  The pharyngeal dilator muscles are secondary respiratory muscles that “modulate” ventilation by maintaining the patency of the airway during respiration34,42. These muscles experience inspiratory phasic activation approximately 200ms prior to the diaphragm to prepare the airway to resist the subsequent negative intraluminal pressure during inspiration42. This suggests coordination at the level of the central nervous system (CNS) between the upper airway muscles and diaphragm27.  8   In addition to anatomic factors, the stability of the upper airway is determined by neuromuscular activation, which is affected by sleep state, negative pressure reflex, and ventilatory control34.   During wakefulness, there is strong activation of the pharyngeal dilator muscles and a stable ventilation pattern7. As sleep begins, airway muscle activation is significantly reduced, accompanied by increased ventilator variability, especially in REM sleep43. Katz et al. observed that most children with severe OSA have a rebound increase in genioglossus muscle activity as shown by electromyography (EMGgg) during stage 2 sleep. The genioglossus stabilizes and enlarges the portion of the upper airway that is most vulnerable to collapse. A greater reduction of EMGgg activity in OSA patients during sleep onset results in increased airway resistance to the point where a reflex of the pharyngeal dilator muscle is necessary to maintain airway patency43.   Negative pressure reflex occurs when a large negative luminal pressure change is detected by the airway mucosal mechanoreceptor, which induces the activation of pharyngeal dilator muscles and respiratory effort in the face of collapse of the upper airway34. Marcus et al. observed that normal children are able to perform negative pressure reflex without arousal44 and are also able to restore minute ventilation without significant overshoot34. By contrast, this negative pressure reflex is substantially diminished or completely lost in patients with OSA34. This results in intermittent obstructive cycling and these patients must depend on the arousal mechanism to sustain minute ventilation44.   9  Ventilation control is determined by blood carbon dioxide (CO2) level, which is the main determinant of central respiratory drive34. During non-REM sleep, ventilation control is robust and hypercapnea may lead to a ventilatory overshoot. Since the apneic CO2 threshold level is reduced to that of the eupneic level during non-REM sleep, this will result in a decrease in central respiratory drive and innervation of pharyngeal musculature, predisposing the airway to an obstructive event34.  In contrast, chemical ventilatory control is least important in REM sleep, where the highest density of obstructive events in children occurs. An obstructive event is likely a result of paroxysmal reduction in pharyngeal dilator activity interrupting its baseline tonic activity related to central REM sleep process3,34. Children with OSA have blunted ventilator responses to hypercapnia45 and higher end-tidal CO2 when anesthetized46, suggesting that ventilation control is affected in this population34.  With the above knowledge, it is understandable how children with neurological disorders such as cerebral palsy may present with SDB and OSA3. These neurological disorders contribute to OSA by reducing upper airway motor control with pharyngeal hypotonia, reduced ventilator responses, and reduced ventilator muscle strength3. They may also have additional craniofacial anomalies, obesity, central hypoventilation and central sleep apnea, compounding their risk for OSA and the severity of it3. Using validated sleep questionnaires, Elsayed et al. observed a 50% prevalence of SDB among 48 school aged children with cerebral palsy47. In another retrospective study using overnight polysomnography on children with cerebral palsy, Kotagal et al. found 5 out of 9 were diagnosed with OSA48.      10  1.2.3 Inflammatory The association between inflammatory measures of the upper airway and development of OSA in adults led several investigators to examine these in children, and associations of both systemic and local inflammation in the upper airway have been found3,49.   Studies have shown inflammatory changes in upper airway samples from children with OSA, and higher levels of cysteinyl leukotrienes (CYS LT) have been found15,49. CYS LT are major inflammatory mediators and potent chemoattractant and neutrophil activators49,50. The expression of their receptors has been shown to be higher in children with OSA compared to children with recurrent infectious tonsillitis, suggesting an inflammatory process involving LT expression and regulation occurs in children with OSA. It is plausible that mucosal inflammation or edema could impair the afferent limb of the negative pressure reflex. Blunted respiratory perception in children with OSA has been reported by measuring respiratory-related evoked potentials51.   Systemic inflammation, as indicated by C-reactive protein (CRP) levels, has been shown to increase in patients with SDB, independent of obesity3,52. Furthermore, CRP levels have been shown to decrease in children with OSA three months after adenotonsillectomy, and there is a significant correlation between the changes in CRP and reduction in the severity of OSA3,52,53.  This elevation of systemic inflammation was thought to be triggered by episodic hypoxia and arousal, which may also lead to endothelia dysfunction, increased blood pressure, and insulin resistance50,54-56).   11  Anti-inflammatory treatments for children with mild OSA are associated with major improvements in symptoms, polysomnographic respiratory values, and radiologic measures of adenoid size3,49. Inflammation is correlated to some extent with OSA-related neurocognitive morbidity, but the role of inflammatory markers in the diagnosis and management of OSA, and the role of anti-inflammatory treatments, remains to be clarified3,49.  There is continued effort to understand whether local and systemic inflammation is a component or the cause of OSA49. Most current evidence shows that adenotonsillectomy reduces the inflammation in OSA at the local or systemic level49. There is, however, no data to confirm that pre-existing inflammation is present in children with newly diagnosed OSA49. Therefore, further research is needed before routine use of inflammatory markers as an evaluator of disease severity can be justified49.     1.2.4 Obesity Obesity is a known risk factor for OSA in adults3,57, and the prevalence of OSA is tripled by each increase in body mass index (BMI) of one standard deviation. From the results of some epidemiological studies, the prevalence of OSA in obese children is in the range of 46% to 55%3,58,59. The mechanism on how obesity contributes to development of OSA is both mechanical and functional. Using volumetric analysis of the upper airway in obese children with OSA, Arens et al. noted larger adenoid, tonsils, and parapharyngeal fat pads in OSA children as compared to matched controls3,60. Additionally, obese children may have excess deposition of adipose tissue within the muscles and tissue surrounding the airway, altered chest wall 12  mechanics, and reduced lung volumes3,61-63. All of these lead to decreased airway size and increased airway resistance, contributing to the development of OSA.  Additionally, obesity can be considered as a state of low-grade, systemic inflammation64, and increased inflammatory markers, such as white blood cell count, have been shown in obese children65,66. In the presence of obesity, OSA has significant effects on lipid homeostasis and affects glycemic regulation through changes in insulin sensitivity49. Complete normalization of polysomnographic findings occurred in only 25% of patients treated by adenotonsillectomy, with obesity and AHI at diagnosis being the major determinants for surgical outcome49,67. Furthermore, Verhulst et al. in 2008 demonstrated that intermittent hypoxia and nocturnal desaturation during sleep are associated with increased white blood cell and neutrophil levels, independent of obesity and its related metabolic abnormalities 64. Therefore, obesity should be considered as its own mechanism contributing to OSA64.   1.3 Diagnosis It is recommended in the AAP clinical practice guidelines that clinicians should inquire whether a child or adolescent snores as screening for OSA during any routine health maintenance visit12. Almost all children with OSA snore, thus asking about snoring is a sensitive, though non-specific, screening measure12. As mentioned above, snoring is more common in children and adolescents than OSA, therefore, an affirmative answer should be followed by a detailed history and physical examination for symptoms and signs of OSA (Table 1-1) to determine if further evaluation is necessary.   13  Table 1-1 Symptoms and Signs of OSA 12  History Frequent snoring (≥3 nights/wk) Labored breathing during sleep Gasps/snorting noises/observed episodes of apnea Sleep enuresis (especially secondary enuresis)a Sleeping in a seated position or with the neck hyperextended Cyanosis Headaches on awakening Daytime sleepiness Attention-deficit/hyperactivity disorder Learning problems Physical examination Underweight or overweight Tonsillar hypertrophy Adenoidal faces Micrognathia/retrognathia High-arched palate Failure to thrive Hypertension a Enuresis after at least 6 months of continence  14  Although taking a history and conducting a physical examination may comprise a good screening tool to determine whether a child should receive further clinical evaluation for OSA, physical examination when a child is awake may lead a physician to assess a child as normal4,68-71. Mitchell et al. in 2015 analyzed baseline data from the Childhood Adenotonsillectomy (CHAT) study to assess whether a combination of demographics, physical examination findings, and caregiver reports from validated questionnaires could predict OSA severity in children. Four hundred and fifty-three children between 5.0 to 9.9 years of age with PSG-diagnosed OSAS were included and it was found that information on demographics, physical findings, and questionnaire responses did not reliably discriminate different levels of OSAS severity72. Therefore, it can be concluded that such information alone is not sufficient for establishing diagnosis and determining who requires treatment4,12.  For a child or adolescent who snores on a regular basis and who shows any of the signs and symptoms in Table 1, it is recommended that either (1) a polysomnogram be performed on the patient; or (2) the patient be referred to a sleep specialist or otolaryngologist for a more extensive evaluation12.   1.3.1 Portable Monitoring Nocturnal pulse oximetry had been suggested as an alternative method to PSG for the diagnosis of OSA in children21. Brouillette et al. (2000) developed a scoring algorithm for overnight home oximetry which was compared to PSG in a study sample with a median age of 4 years73. The oximetry score correlated with the AHI obtained from PSG as well as with the presence of postoperative complications, but the positive predictive value for major postoperative respiratory 15  complications was only 13%. Furthermore, 80% of the 223 children had normal, inconclusive, or technically unsatisfactory oximetry results, requiring either repeat oximetry or PSG. Kirk et al. (2003) compared over-night home oximetry with laboratory PSG in 58 children aged ≥4 years who had suspected OSA74. They found poor agreement between the desaturation index on the basis of oximetry and the PSG-determined AHI, with 67% sensitivity and 60% specificity in identifying moderate OSA (AHI >5/hour). These results may be due to the fact that children may have OSA that results in arousals and subsequent sleep fragmentation but little desaturation; also children tend to move a lot during sleep, which can result in a movement artifact. Marcus et al. (2012) hence concluded that oximetry alone is insufficient for the diagnosis of OSA because of the high rate of inconclusive test results and the poor sensitivity and specificity compared with PSG21.  Ambulatory PSG refers to unattended sleep studies conducted in the home, frequently consisting of cardiorespiratory recordings alone21. Although the use of ambulatory PSG is considered appropriate under certain circumstances in adults75, there is contradictory data from the literature regarding its use in a pediatric population. Marcus et al. (2012) identified three studies comparing ambulatory PSG with overnight laboratory PSG. There were vast differences in the samples, with the patients’ ages ranging from 3 to 6 years in one study52, to 8 to 11 years in another41. The parameters included in the ambulatory PSG also have marked variations, with one study using an abbreviated PSG at the laboratory, which included inductance plethysmography, oximetry, heart rate, and position only, while the other used a full PSG test at home21,41,52,76.  Based on these studies, ambulatory PSG seems to be technically feasible in school-aged children, as greater than 90% of the time the researchers were able to collect adequate data. Nevertheless, 16  data are not available for younger children. Also, due to these studies being done on different age groups, wide discrepancies in the specifications for diagnosis of moderate OSA were found. Clearly, additional studies are needed22,77-79  1.3.2 Polysomnography An overnight, attended, in-laboratory polysomnogram is the gold standard for diagnosing OSA as it is the only diagnostic test able to quantitate the respiratory and sleep abnormalities associated with OSA in children4,21. This non-invasive test, also called Type I sleep diagnostic testing, is performed in a sleep laboratory and attended by specialized technologists throughout the duration of the study27. It measures complex polygraphic signals from three channels of measurements of physiological functions15,27:  (1) Sleep channels  Electroencephalogram (EEG), electrooculogram (EOG), submental and extremity electromyogram (EMG), and audio/video taping.  (2) Cardiovascular channels  Electrocardiogram (ECG), pulse transit time (3) Respiratory channels  Airflow determined by oronasal thermistor or nasal pressure transducer, Thoracoabdominal effort by piezoelectric effect, respiratory inductive plethysmography, or chest and abdominal excursion belts, intercostal muscle or diaphragmatic EMG, pulse oximetry, capnography, limb leads, end tidal or transcutaneous CO2, esophageal manometry.  17  Using the information of sleep architecture, breathing events during sleep (apnea, hypopnea, flow limitation, respiratory effort related arousals), desaturation and periodic limb movements, autonomic changes and respiratory effort can be evaluated15. OSA is diagnosed if frequent arousals with increased respiratory effort, hypercapnia, apnea with desaturation or markedly negative esophageal pressure swings are seen11,15. Pediatric studies in infants and children of all ages should utilize appropriate equipment and experienced technicians, and the result should be scored and interpreted using the age-appropriate criteria outlined in the new American Academy of Sleep Medicine (AASM) scoring manual80, which is the first to clearly delineate pediatric scoring criteria16. The AASM mandates the use of this manual in all accredited sleep labs. Unfortunately, individual sleep laboratories establish their own thresholds for diagnosis differently by modifying adult sleep-scoring criteria or using the American Thoracic Society’s suggested pediatric criteria, resulting in a lack of consensus of diagnostic criteria for OSA81,82. Although an AHI of greater than 1 event per hour has been considered abnormal in a child more than one-month old by many authors18,83-85, Beck et al. reported that the an AHI ≤ 1.4 events per hour is statistically normal in children 16-21. Commonly an AHI or RDI ranging from 1-5 events per hour is used to diagnose OSA in children8,86, and many centers will treat children with an AHI in the 2–5 events per hour range16.  Despite general belief of a positive correlation between PSG score and risk for complications of OSA, this has not been proven and it is not known which PSG criteria predict morbidity4. Additionally, PSG requires time, effort, and expense from both patient and health care professionals, and use of a sleep study laboratory is only readily available in some parts of the 18  world. Considering these limitations, it was estimated that less than 10% of all children have been diagnosed using PSG, leading primary care physicians to look for other alternatives15.   1.3.3 Questionnaires Questionnaires are generally considered as screening tools to identify patients who are at higher risk of developing OSA3,15. Phase I screening tools generally include specific preliminary questions to be asked during health-care maintenance visits. These are developed to help pediatricians recognize the symptoms of snoring and other sleep problems in children. Two such screening tools include BEARS87 and the ten-item sleep screener (TISS)88. (Table 1-2)   Table 1-2 Phase I Screening Questionnaires  3 BEARS TISS 1. Bedtime problems  2. Excessive daytime sleepiness  3. Awakenings during the night  4. Regularity of sleep  5. Snoring  1. Does the child snore lightly or loudly at night?  2. Does the child exhibit excessive daytime sleepiness?  3. Does the child have difficulty falling asleep at night?  4. Does the child roll, kick, or move around frequently in sleep?  5. Does the child wake up frequently in the night?  6. Is the child difficult to awaken in the morning?  7. Does the child gasp, choke, or snort in sleep?  8. Does the child stop breathing during sleep?  9. Does the child get enough sleep at night compared with peers of the same age? 10. Does the child have a difficult temperament (irritable or easily frustrated)?  Phase II screening tools are described by Bandla et al. as more comprehensive and “capable of predicting the probability of sleep disorder with high accuracy”3. Several such validated 19  questionnaires have been developed to improve the accuracy of distinguishing OSA from primary snoring3.   Brouilette et al. was among the pioneers in this field. In 1981, they developed a questionnaire for OSA using a score calculated from a designed formula using three discriminant variables: difficulty during sleep, apnea observed during sleep, and snoring. In their study in 1984 to evaluate the effectiveness of the questionnaire against PSG, they were able to correctly identify all OSA children from controls. Nevertheless, a large proportion of the children fell into the intermediate score group, which may or may not indicate OSA89. This questionnaire was subsequently used by others in a cumulative larger sample of 765 patients; the combined sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV) was found to be 59%, 51%, 65%, and 46% respectively73,90-92. Therefore, it is obvious that this questionnaire is not a substitute for PSG for the diagnosis of OSA.  Schechter et al. in 2002 performed a systemic review and evaluated the questionnaires developed to substitute PSG and concluded that “clinical evaluation, including the use of questionnaires such as the one published by Brouilette et al., has unacceptably low sensitivity and specificity for predicting OSA”90.  Chervin et al. in 2000 developed and validated a 22-item parent-reported pediatric sleep questionnaire (PSQ). The PSQ has four subscales for SDB, snoring, sleepiness, and behaviour, and the total score provides an evaluation of all sleep problems. Using children aged 2-18 years who had PSG-confirmed SDB or appointments at either of two general pediatric clinics, the PSQ 20  was able to correctly classify 86% of the subjects with overall sensitivity and specificity of 85% and 87%, respectively. The scale showed good internal consistency and, in a separate sample, good test-retest stability91.  Li et al. in 2006 also developed a parent-reported, 54-item HK-CSQ (Hong Kong Children Sleep Questionnaire) for identification of OSA; reported overall sensitivity, specificity, positive predictive values, and negative predictive values were 75.4, 80.5, 61.3, and 88.9, respectively.  Test-retest with a separate sample showed that measurement of agreement (Kappa value) was 0.693.  Spruyt et al. in 2012 was able to delineate a severity hierarchy of parent-reported complaints based on commonly used subjective respiratory symptoms. A set of six ordered questions was used: shake child to breathe, apnea during sleep, struggle to breathe when asleep, and breathing concerns while asleep, followed by loudness of snoring and snoring while asleep. It was found to aid in the screening of children at high risk for SDB, but it cannot be used as a sole diagnostic approach as it has a sensitivity of 59.03%, specificity of 82.85%, positive predictive value of 35.4, and negative predictive value of 92.794.  Finally, De Luca Canto et al. in 2014 performed a systematic review evaluating the diagnostic capability of various questionnaires and clinical examinations for pediatric SDB. They concluded that only the Pediatric Sleep Questionnaire (PSQ) had enough diagnostic accuracy to warrant its use as a screening method for pediatric SDB, but not enough to be considered a true diagnostic tool for pediatric SDB95. 21   Taken together, the overall performance of questionnaires seems to support their use more as a screening tool, such that in most cases a negative score could correctly identify a healthy child. Nevertheless, a positive score would be unlikely to accurately diagnose a particular child with OSA, hence it should not be used as a diagnostic tool21.   1.4 Treatment of OSA Depending on the underlying etiology and the severity of the disease, treatment of SDB in children can be surgical or non-surgical13.   1.4.1 Watchful Waiting: Watchful waiting with regular follow ups was proposed by a few authors as a possible treatment option for children with habitual or primary snoring14,96-98. Marcus et al conducted PSG on 20 children (mean age of 6.4 years old) and reported that primary snoring did not progress to OSA in the majority of the children over a 2-year period, although two children (10%) developed mild OSA96. Topol et al. followed up 19 children (mean age 5.5 years) for three years and concluded that children with primary snoring are not likely to develop PSG-confirmed OSA, and it is safe to defer treatment97. Anuntaseree et al. gave a snoring questionnaire to the parents of 1008 Thai children in 1999 and again in 2002. They found that 65% of children who snored habitually no longer did so when they got older, while 9% of children had developed OSA98. Overall, it is suggested that regular follow-ups in children with habitual snoring may be needed, but additional research is required to determine the indications for PSG, neurobehavioral and cardiovascular assessments14,96,98.  22   Watchful waiting is not recommended for children with diagnosed OSA. In the study mentioned above, Anuntaseree et al. found that children with mild OSA could develop more severe disease if left untreated14,98. Li et al. assessed 45 children aged 6-13 diagnosed consecutively with mild OSA (AHI 1-5) and assessed the children again two years later; they found that mild OSA in the majority of children did not resolve spontaneously99. Marcus et al. randomly assigned 464 children with OSA, 5 to 9 years of age, to early adenotonsillectomy or a strategy of watchful waiting and performed re-assessment in 7 months. They found that surgical intervention did not significantly improve attention or executive function as measured by neuropsychological testing, but did reduce symptoms and improve secondary outcomes of behavior, quality of life, and polysomnographic findings100. Even though a higher proportion (79%) of children in the early adenotonsillectomy group showed normalization of polysomnographic findings, normalization occurred in 46% of patients who received only watchful waiting100.   Overall, it has been found that even mild OSA may develop into a worse disease if left untreated and early treatment has proven a benefit to patients.   1.4.2 Adenotonsillectomy: Tonsillectomy and adenoidectomy (T & A) is the accepted first line of treatment for children diagnosed with OSA15, and it has been shown that removing both the tonsils and adenoids is more effective than either on its own15. The rationale is that adenoid and tonsillar hypertrophy occurs most frequently between 2-6 years of age, when the pharyngeal lymphoid tissue outgrows the structures of the surrounding airway, leading to pharyngeal obstruction during sleep13,101. It 23  was reported that only 9% of OSA secondary to adenotonsillar hypertrophy within a 1-year observation period displayed spontaneous resolution13,102, indicating treatment is needed for this condition.   T & A had been shown to significantly improve obstructive symptoms in 80% of the cases13,103. Based on parental reported questionnaires, T & A had been shown to have an efficacy of around 91% for snoring13,104. Lim et al. in their systemic review in 2003 concluded that the cure rate of OSA from T&A determined by AHI < 5 events/hr was between 78.4% and 100%105. Quality of life based on the OSA-18 questionnaire, and the behaviour of children evaluated both subjectively and objectively, all showed significant improvement after the surgery106. Nevertheless, T&A in children with underlying airway abnormalities (such as craniofacial anomalies, neuromuscular deficits, and pathological obesity) is more likely to fail as a treatment than T & A performed on children without the abnormalities13,58. Furthermore, Guilleminault et al. (1989) reported that 13% of children who were successfully treated with T&A showed recurrence of symptoms when they reached  adolescence89. Therefore, regular monitoring is necessary for these patients even if they had a good response to the procedure13.  1.4.3 CPAP: Continuous positive airway pressure (CPAP) produces an air splint to prevent airway collapse by continuously blowing pressured air into the larynx13. It is useful for children with other underlying medical disorders who cannot benefit from recurrent surgeries, who need temporary treatment until definitive surgery is done, or who have residual SDB post operatively13,15. Marcus et al. in 2012 reported that several studies have demonstrated that nasal CPAP is 24  effective in the treatment of both symptoms and polysomnographic evidence of OSA, even in young children21. However, CPAP is cumbersome to wear, yet full cooperation from the patient and parents is required for effectiveness of the treatment13. For this reason, Marcus et al. does not recommend CPAP as first-line therapy for OSA when adenotonsillectomy is an option21. Complications of CPAP include nasal congestion and dry mouth15, and the long-term effects of CPAP, particularly on the development of the face, jaw, and teeth, is an area that requires future research21.  1.4.4 Orthodontic Treatments: For those children with OSA who have a constricted maxilla, an anterior open bite, and a long lower facial height, orthodontic treatment may be necessary, especially if they do not experience significant improvement in their dentofacial features and OSA symptoms even after removal of the adenoid and tonsils at an early age107,108.   Orthodontic therapy at an early age in OSA children may permanently modify their nasal breathing and respiration and consequently reduce obstruction of the upper airway108,109. In a recent study by Villa et al., it is suggested that orthodontic appliances such as a rapid maxillary expansion (RME), a lower jaw positioner, or a modified monoblock are effective for treating OSA in children with malocclusions110.  Rapid maxillary expansion (RME) in an orthodontic procedure that applies orthopedic force to open the midpalatal suture via a tooth-born device13. It is able to achieve widening of the maxilla and the base of the nose, hence increasing the nasal passage and reducing the resistance to 25  airflow15. Children with OSA who have maxillary constriction, BMI < 24kg/m2, and no adenotonsillar hypertrophy are considered to have the most favorable response to RME13,111. Cistulli et al. showed that RME treatment on young adults was able to reduce AHI from 12.2 to 0.4 events/hour13,112.   Distraction osteogenesis is another accepted procedure for treatment of OSA in children with maxillomandibular deficiency who do not require maxillomandibular advancement surgery but for whom T&A is inadequate13,15. Using a distraction device, the mandible or midface can be slowly moved in the anteroposterior direction desired13. Currently, there is still insufficient data to demonstrate the efficiency of distraction osteogenesis for treatment of OSA as most reports did not demonstrate PSG data before and after the procedure13.   Function mandibular advancement appliances are considered a moderately effective treatment for snoring and mild to moderate OSA in adult patients113-117. The concern that such appliances may alter occlusion in children prevents this treatment from being widely used15. Nevertheless, both the Herbst and the Twin Block are functional appliances that could be used in patients with retruded mandibles based on patient-specific dentoalveolar conditions and the orthodontic need for treatment118.  Research on these appliances in children is still lacking. Most studies involving children are non-randomized, non-controlled, or undertaken with only a small sample size and short follow up times. Nevertheless, as shown in a randomized controlled study of a small group of children by Villa et al. (2012) , the results are promising119. These researchers found that jaw-positioning 26  appliances were able to induce a significant improvement in OSA symptoms compared with the control group. They concluded that treatment of OSA with an oral appliance (OA) in children with malocclusions is an effective and well-tolerated method119.  1.4.5 Occlusal Indices for Need for Orthodontic Treatment: A variety of clinical-based indices have been developed to classify various types of malocclusion and to determine the orthodontic treatment need120-123. The most commonly employed malocclusion indices are the Dental Aesthetic Index (DAI), Index of Orthodontic Treatment Need (IOTN), Peer Assessment Rating(PAR) 6,112 and Index of Complexity, Outcome and Need (ICON)124,125. IOTN, DAI and ICON are used to assess the orthodontic treatment needs while ICON and PAR are used to assess the treatment outcome120. The indices of IOTN, DAI and ICON are similar. All include two components – morphological and esthetic– and all measure similar traits such as overjet, reverse overjet, open bite, overbite, antero-posterior molar relationship, and displacement. They differ in the weighing of these traits by each index124,125, and by the fact that in IOTN the aesthetic component (AC) and dental health component (DHC) are separated120.   Shaw et al. (1995) assessed the validity and reproducibility of the IOTN and PAR indices by inviting a panel of 74 dentists to evaluate treatment need and treatment changes of 234 cases with 16 duplicated casts123. They found that the correlation between DHC of IOTN and collective view of the panel was reasonably high, and agreement is higher between AC of IOTN and the panel. Agreement between the panel and PAR index was also high, and improved after applying weightings to the individual components. For reproducibility, they found almost perfect 27  inter-examiner agreement for DHC (Kappa coefficient = 0.83) and substantial agreement for AC (Kappa = 0.72) for IOTN, while the PAR index has a value of 0.83123.  Hagg et al.(2007) reported that there was a significant but weak-moderate correlation between the various occlusal indices (IOTN, DAI, and ICON), except for correlation between AC and ICON. This suggests that different results can be obtained by using different indices in deciding whether a subject has an orthodontic treatment need or not120. Hagg et al. also reported that there was a significant but weak correlation between oral health quality of life (OHQoL) and the occlusal indices9,10. Patients determined by occlusal indices as having an orthodontic treatment need had poorer OHQoL than those ascribed as not having an orthodontic treatment need10.   In summary, although there is only weak-moderate correlation between different malocclusion indices, they have been validated and proved to be reproducible when utilized to assess orthodontic treatment needs and treatment outcome.   This type of assessment approach is important in the initial decision of patient selection to treatment. In the context of our study, although there is not enough evidence that orthodontic treatment may fully treat OSA, if a patient is categorized as have significant need of orthodontic treatment according to IOTN, he or she would still benefit from receiving orthodontic treatment.  1.5 Sequelae of Untreated Pediatric OSA  The causes of comorbidity of untreated OSA may be compromised respiration, sleep fragmentation, and local and systemic inflammation15,49. These comorbidities include 28  hypertension, cardiovascular failure, and frequent upper airway infections, as well as disturbances of growth and mood15. As children are sensitive to both gas exchange abnormalities and disrupted sleep, it was suggested in a preliminary epidemiology study that even mild pediatric sleep disorders negatively impact growth and development81,91. Disrupted sleep causes children to have an increased resting energy expenditure and abnormal release of growth-related hormones, both of which have been linked with a failure to thrive in these children81,86. In the review study done by Au and Li in 2008, conflicting results were found regarding the cardiovascular consequences in children with OSA. Some hypothesize that children with OSA are at an increased risk for elevated blood pressure as well as for changes in ventricular geometry and endothelial dysfunction86,96, while others have found children with OSA to be hypotensive and to have lower diastolic blood pressure than normal controls. 86,126,127. Au et al. concluded that there is inadequate evidence to demonstrate that children with SDB are at an increased risk for elevated blood pressure and more research is warranted86. Additionally, Ross et al. found that children with SDB have about a 3.6 times higher chance of having severe asthma128.  Unlike adults with OSA, most children with OSA do no present with daytime sleepiness, but rather have hyperactive or inattentive behaviour and are often misdiagnosed with attention deficit hyperactivity disorder129. Left untreated, OSA has been shown to affect school performance and intellectual function, especially short term memory and concentration ability15,129. OSA children had three times more behavioral problems and neurocognitive abnormalities than those without90, and the prevalence of hyperactivity behaviors is higher in younger children with OSA130.   29  1.6 Obstructive Sleep Apnea and Craniofacial and Dentofacial Development Craniofacial refers to the structures of the cranium, including the skeletal and neuromuscular structures of the skull, the brain, and the face. Dentofacial refers to the skeletal and neuromuscular structures of the face and the mouth, including the teeth and their relationship to each other. There are craniofacial and dentofacial morphological changes secondary to upper airway obstruction131. Craniofacial and dentofacial anomalies result from both genetic and environmental determinants. Studies in monkeys and children have shown that upper airway obstruction with mouth breathing can induce craniofacial and dentofacial anomalies, which can be improved or normalized after OSA treatments such as T&A95,131-133. Guilleminault et al. (2005) hypothesized that these changes mainly result from the mouth breathing exhibited by children with OSA. The lowered tongue position results in a constricted maxillary arch, while the extended head posture lowers the mandibular posture134. These are supported by two systematic reviews conducted by Flores-Mir et al. and Katyal et al. who in 2013 compared cephalometric radiograph findings between healthy children and children with OSA. It was found that children with OSA have a more retrusive chin (SNB = -1.79º135; P<0.001), steeper mandibular plane (MP-SN = 4.2º135 and 2.43º36; P<0.001), and a tendency toward Class II malocclusion (ANB = 1.38º135 and 1.64º36; P<0.001).   In addition to cephalometric findings, dentofacial anomalies also present as malocclusion that can be identified during clinical orthodontic examination. A literature review was performed using “malocclusion” and “sleep disordered breathing OR obstructive sleep apnea” and “children” as search keywords in PUBMED. The inclusion criteria were: pediatric population, SDB and OSA diagnosed with questionnaire and/or PSG, malocclusion diagnosed with cast 30  and/or clinical examination. The exclusion criteria were: adult population and malocclusion diagnosed with cephalometric radiograph only. Overall, 42 studies were initially found; among these, 10 studies remained after application of the inclusion and exclusion criteria. With the exception of the case-controlled study by Pirilä-Parkkinen et al. in 2009 136, Ikävalko et al. in 2012 137, and Katyal et al in 2013 92, and the longitudinal study by Hultcrantz et al. in 2009 77, all remaining articles were cross-sectional studies without a control group. Only four studies used laboratory overnight PSG for the diagnosis of SDB75,78,136,138; a parent-reported sleep questionnaire and clinical ENT examination was employed as method of diagnosis for the remainder of the studies35,77,79,92,137.   All of the studies have found an increased prevalence of posterior crossbite (PXB) among children with SDB. The reported prevalence of PXB in SDB children was 10.4% 35, 12.2% 136, 16.7% 138, 28.3% 137, 42.9% 75 48% 139, 68.2% 92. The prevalence of PXB in the reported control groups was 2.4% 136, 7% 138, 12.9 137%, and 23.2% 92. This is comparable to the results from the National  Health and Nutrition Estimates Survey III (NHANES III) conducted in United States in 1989 - 1994, which showed the prevalence of PXB to be 7.1% and 8.8% in 8-11 year olds and 12-17 year olds, respectively 140,141.   Class II skeletal and dental patterns were also found to be more prevalent in children with SDB, with the reported prevalence of 29.3% 136, 33% 138, 46% 137, and 88% 138. In comparison, the reported prevalence of Cl II pattern in the control samples was 4.9%136, 26%138, and 28%137. From NHANES III, the prevalence of Class II malocclusion was 23% and 15% in 8-11 year olds and 12-17 year olds in the general U.S. population, respectively140,141. 31   Four studies found that reduced overbite or anterior open bite occurred more frequently among children with SDB. The reported prevalence was 5%35, 17.1%136, 20%138 in permanent dentition and 30%138 and 42.9% 75 in primary dentition,. In the general population, this malocclusion has a prevalence of 0% (control group) 136 and 3.6% as reported in NHANES III140,141.  Dental crowding was evaluated by Huynh et al. and Pirilä-Parkkinen et al. Moderate dental crowding (≥ 4mm) was found to be more prevalent in children with SDB, with a prevalence of 16.1% 35 to 17.1%136. Nevertheless, results from NHANES III showed the prevalence of incisor crowding of 4mm or greater in children from 8-11 years to be 22% in the maxillary arch and 20.6% in the mandibular arch140,141.   Table 1-3 summarizes the result of the literature review.  32  Table 1-3 Summary of Literature Review        Pirilä-Parkkinen  2009 Lofstrand-Tidestrom 2009 Souki 2009 Caprioglio 2011 Huynh 2011 Kim 2011 Ikävalko  2012 Sauer 2012 Carvalho 2014 Study Design PCC L (CC) CS CS PC CS CC  PC CS Sample size 123 31 401 197 604 378 466 60 50 Sample Type Referred General Mouth Breath Referred Ortho Post T&A  General Referred General Age 7.2 ±1.9  12 6.5 ± 2.6 4.12 ± 2.08  13.01±2.28  2–17 7.6 ± 0.2 6.3 ± 0.78  7, 8, 9 OSA Dx PSG  Q + ENT Q Q and A-PSG Q Q & PSG* Q Q & PSG Q + PSG* Malocclusion DX COE + Model COE + Model COE COE COE COE COE COE COE AOB/Red OB 17.1*        11.1  12.2 11.1 30-29-20% 18% 5% 6.5 10 30* 0 3.2    2.4  0 PXB 12.2        55  12.2 33.3* 28.1-28.6-48 25% 10.40% 28.3* 16.7 30* 2.4 9.7    12.9  0 Cl II 29.3*         88.9  36.6** 14.8 27-32.8-25% 22% 32.6 33.3 42.5 4.9 9.6   29.5  30 OJ 3.5*              3.7* 2.6 Retrud Md        81.4        45.7*  74.8 27.6 ICW 29.6 **              30.4* 28.6* 31.2 30.9 IMW 30.1*              30.4 40.7* 31.3 43.2 33   Table 1-4 Summary of Literature Review    Study Design: PCC = Prospective Case Controlled CC = Case Controlled CS = Cross-Sectional L (CC) = Longitudinal Cross-Sectional Sample Type: Referred = Sample was comprised of patients who were referred for snoring, symptoms of OSA, and for mouth breathing. General = Sample was comprised of school age students representative of general population of the area. Mouth Breath = Sample was comprised of patient who are mouth breathers Ortho = Sample was comprised of patients of orthodontic clinic.  Post T&A = Sample was comprised of patients who received adenotonsillectomy surgery. OSA Dx (Obstructive Sleep Apnea Diagnosis): PSG = Overnight, in laboratory polysomnography study; * signifies studies that followed the 2007 AASM guideline.80 APSG = Ambulatory (at home) polysomnography study. Q = Questionnaire ENT = clinical ear nose throat examination Malocclusion Dx (Diagnosis): COE = Clinical Orthodontic Examination Model = Dental cast models Malocclusion categories: AOB/Red OB = Percentage of patient with Anterior openbite / Reduced overbite. PXB = Percentage of patient with posterior crossbite Cl II = Percentage of patient with Class II molar classification Inc. OJ           11.1  29 35.4-43.7% 11.7 30    10 Convex             81.4%  52.2*   31.3 Narrow Mx         74.9      8.70%  17.4  67.8 10.8 Crowding 17.1*        7.3 16.1% 35 2.4  50 34  OJ = Overjet (mm)  Retrud Md = Percentage of patient with retruded mandible ICW = Intercanine width IMW = Intermolar width Inc OJ = Percentage of patient with increased overjet. Convex = Percentage of patient with convex facial profile  Narrow Mx = Percentage of patient with narrow maxilla Values in Black represent patients diagnosed with OSA; values in Green represent patients diagnosed with SDB, values in Blue represent patients in control group, values in Red represent patients who showed improvement after adenotonsillectomy surgery (no symptoms, AHI ≤ 2). * p<0.05; ** p<0.01 Significant differences between OSA or SDB patients and the control patients.35    In summary, the literature review showed that the evidence currently available on the relationship between SDB and malocclusion is limited, highlighting the need for further research on this topic. Furthermore, the reported occlusion characteristics varied significantly among children with SDB. Posterior crossbite is the only malocclusion that was found to be consistently more prevalent in all the included studies, while some studies reported that a Cl II skeletal and dental pattern, reduced overbite (OB), and dental crowding may also be more prevalent in children with SDB.  1.7 Hypothesis Children with OSA may have craniofacial and dentofacial features associated with their disease. In addition to improving esthetics and occlusion, orthodontic therapy may also reduce the risk of development of OSA by permanently modifying nasal breathing and respiration. Orthodontists are specialists in malocclusion, as well as neuromuscular and skeletal abnormalities of the developing or mature orofacial structures. Therefore we are interested in finding out how dentofacial morphology is related to OSA, specifically, the prevalence of dentofacial morphology among children with diagnosed OSA.   Despite the limitations of the currently available studies on this topic, there is evidence supporting that the prevalence of abnormal dentofacial morphology is higher in children diagnosed with OSA when compared to children without OSA.  36  The null hypothesis of the current study is that the prevalence of dentofacial morphology is the same between children who were diagnosed with OSA and children without OSA.   1.8 Objectives The objective of this study was to assess the prevalence of dentofacial morphology, determined by dentist/orthodontists evaluating a standardized set of dentofacial features, in children from age 4 to 16 with a diagnosis of OSA using overnight PSG.  The following topics are the specific aims of the study:  To collect a sample group that can represent the population of children with OSA.  To devise a clinical examination protocol to define and determine the presence of malocclusion that can be reproduced for future use.  The data of this examination should also be used to determine the need for orthodontic treatment.  To establish the prevalence of dentofacial morphology in children with OSA. 37  Chapter 2: Material and Methods 2.1 Subjects Children referred to the Department of Respirology of BC Children’s Hospital for overnight polysomnography (PSG) study during the months of January to June 2014 were invited to participate in the study (n=104). The subjects were selected according to the inclusion and exclusion criteria listed in Table 2-1. Informed consent was obtained from the parents of 64 children, and an orthodontic examination was performed on the same 64 children. Among these children, 17 had syndromes affecting craniofacial development; these syndromes included Pierre-Robin Sequence, De George Syndrome, Cleft Palate, Coffin-Siris Syndrome, Cerebral Palsy, Treacher-Collin Syndrome, Q15 Deletion, Prader-Willi Syndrome, Down Syndrome, Quadriplegia Cerebral Palsy, Ohdo Syndrome, Fetal Alcohol Syndrome, and left facial plexiform neurofibroma. All children were evaluated by overnight polysomnography. One child was excluded at this stage because of unsuccessful registration of the PSG.  On the basis of the PSG findings, the study group was divided into an OSA group (AHI ≥ 2 events per hour; n=17) and a non-OSA group (AHI ≤ 2 events per hour; n=22). The OSA group was further divided into a low AHI group (AHI between 2-5; n=9) and a higher AHI group (AHI ≥ 5; n=8).   The study was conducted in accordance with the ethical standards of the University of British Columbia and BC Children’s Hospital (ethical approval # H12-03285).  38   Table 2-1 Inclusion and Exclusion Criteria Inclusion Criteria: Exclusion Criteria: o Age is between 4 to 16 years o Completion of an overnight polysomnography study at the sleep laboratory of the BC Children’s Hospital  o Who are currently going through CPAP treatment o Children and parents who are not proficient in English because the informed consent form and all the documents are printed in English and we do not have the necessary means to translate the forms     2.2 Methods 2.2.1 6-Item Sleep Questionnaire (Spruyt and Goyal, 2012) 94: After obtaining informed consent, the parents or guardians present for the clinical examination were asked to complete the sleep questionnaire comprised of the following 6 questions: For the  preceding  6-month  time  frame, (1) Do you shake your child to breathe; (2) have you witnessed an apnea during sleep; (3) does your child struggle to breathe when asleep; (4) do you have concerns about your child’s breathing while asleep; (5) how loud does your child snore; (6) does your child snore while asleep (Spruyt and Goyal, 201294).  All questions were answered using a Likert-type response scale including: 0 = “never”, 1 = “rarely” (once  per  week), 2 =  “occasionally”  (twice  per  week), 3 = “frequently” (three  to  four  times  per  week) and 4 = 39  “almost  always” (>4  times per  week); except the fifth question, which was answered using the following scale: mildly quiet  =  0, medium  loud  =  1,  loud  =  2,  very loud  =  3,  extremely loud  =  4). The  cumulative  score of  the  questionnaire  represented the average score of all six questions, according to the following formula (where Q1  =  response  to question 1, Q2  =  response  to question 2, and so forth): A  =  (Q1  +  Q2)/2;  B  =  (A  +  Q3)/2;  C  =  (B  +  Q4)/2;  D  =  (C  +  Q5)/2; and the cumulative score  =  (D  +  Q6)/2. Based on the original assessment, a score greater or equal to 2.72 out of 4 was used as indicative of a high risk for OSA (Spruyt and Goyal, 201294).   2.3 Clinical Orthodontic Examination: Prior to initiation of the overnight PSG study, all subjects underwent a clinical screening evaluation by the same orthodontist (K.L.), blinded to the outcome of the questionnaires, using an orthodontic evaluation form covering the various standard dental, skeletal, functional, and esthetic characteristics. The examination has four components: (1) Frontal View, (2) Profile View, (3) Functional, (4) Intra oral. Details of the examination are described below.    2.3.1 Frontal View (Table 2-2): Face height was assessed and facial types were categorized as brachycephalic if the lower third was shorter than the average, mesocephalic if the lower third was longer than the average, or dolichocephalic if the lower third was much larger than the average. Asymmetries of the dental midline to the facial mid-line were noted to evaluate the relationship of the dentition to the face. Incisor and gingival display is measured clinically using a plastic ruler with 1mm accuracy.   40  Table 2-2 Frontal View Front View 1. Type facial (if borderline, choose mesocephalic)  Mesocephalic   Brachycephalic   Dolichocephalic 2. Lower Face Height  Normal  Increased   Decreased 3. Symmetry  Symmetric  Mandible shift to the Right          Mandible shift to the Left 4. Dental Midlines (midline – use cusp of upper lip) Upper : on with facial midline  shift to Right  shift to Left; Amount : ____mm Lower : on with facial midline  shift to Right  shift to Left; Amount : ____mm 5. Incisor display at rest ____mm 6. Gingival display on smile ____mm 7. Incisor display on smile ____mm   2.3.2 Profile View (Table 2-3) A facial profile is convex when a line dropped from the bridge of the nose to the base of the upper lip and the second line extending from that point downward to the chin forms an acute angle, or if it is straight or concave when the angle is obtuse. Lip position is determined relative to a straight line drawn from the tip of the nose to the most anterior curvature of the soft tissue chin. Lip strain on closing is determined by the activity of the mentalis muscle. Table 2-3 Profile View Profile View 8. Facial Profile  Straight  Concave  Convex  9. Skeletal position - Maxilla  Retrognathic   Normal  Prognathic  10. Skeletal position - Mandible  Retrognathic   Normal  Prognathic  11. Nasolabial Angle  Normal 90º-100 º  Acute (< 90 º)   Obtuse (>100 º) Lip Position  12. With respect to esthetic line : Upper lip    Normal  Retrusive   Protrusive  41  Table 2-4 Profile View 13. With respect to esthetic line : Lower lip   Normal  Retrusive   Protrusive 14. Lip strain to close (mentalis strain only, slight opening without strain is “No”)  Yes   No   2.3.3 Functional  (Table 2-4) Tonsil size is evaluated according to the Standardized Tonsillar Hypertrophy Grading Scale99.  Table 2-5 Functional assessment Functional 15. Tonsils  Removed  1+       2+        3+               4+ (kissing tonsils) 16. History of Mouth Breathing  Yes :  During Day Time             During Night Time                      No  2.3.4 Intra-Oral (Table 2-6) Visual clinical evaluation of the dental component of the malocclusion included horizontal and vertical discrepancies, molar and canine Angle’s classifications, number and location of crossbites, and maxillary and mandibular dental arch crowding or spacing. Angle classification was performed separately for each side of the jaw. Occlusion of the molars was classified as Class I (the mesiobuccal cusp of the permanent upper first molar occluded into the buccal fossa of the lower first permanent molar or was less than half cusp mesial or distal), Class II (the mesiobuccal cusp of the permanent upper first molar occluded from half to a full cusp or more than a full cusp mesially relative to the buccal fossa of the lower first permanent molar), or Class III (the mesiobuccal cusp of the permanent upper first molar occluded from half to a full cusp or more than a full cusp distally relative to the buccal fossa of the lower first permanent molar). Children with an asymmetric canine or molar relationship were classified as having 42  malocclusions. The antero-posterior relationship was also determined for the second primary molars if they were erupted and in occlusion.  Occlusal discrepancies, such as deep-bites, open-bites, crossbites, and scissor-bites as well as crowding, were recorded and classified modifying the method of Björk et al. (1964) 142. Incisor occlusion was judged by taking the average measurement of both central incisors. Overbite measures the percentage of the lower incisors that is overlapped by the upper incisors. Posterior crossbites were recorded if the buccal cusp of the upper tooth occluded edge-to-edge, or lingually, to the buccal cusp of the corresponding lower tooth. Posterior crossbites included cross bites of the primary or permanent molars and canines as well as permanent premolars. Crowding or spacing of the arch was evaluated by calculating the amount of overlap or space between the interproximal contacts of erupted teeth. In mixed dentition, this was done with the assumption that unerupted permanent canines, first premolars and second premolars will occupy 7mm of the mesio-distal arch dimension. The overall crowding or spacing was divided into mild (1-3 mm), moderate (4-9 mm), or severe (>10 mm). Intercanine width and intermolar width was measured using a Boley gauge with 0.01mm accuracy. Intercanine width was measured from the cusp tips of the maxillary right and left primary and permanent canines. Intermolar width was measured from the junction of the lingual groove at the gingival margin between the maxillary left and right primary second molars and permanent first molars.   The need for orthodontic treatment was determined for the study population using the Index of Orthodontic Treatment Need (IOTN), which ranks malocclusion in terms of the significance of various occlusal traits for the person's dental health and perceived esthetic impairment in order to 43  identify those who would most likely to benefit from orthodontic treatment (Shaw, 1995 123).  The IOTN has two components: Dental Health Component (Table 2-5), and Esthetic Component (Table 2-6, #36).  Table 2-6 Dental Health Component of Index of Orthodontic Treatment Need Grade 1: No treatment need 1. Extremely minor malocclusion with contact point displacements of less than 1 mm Grade 2: Minor anomaly, no treatment need 2.a Overjet > 3.5 mm and ≤ 6 mm (with competent lip closing) 2.b Reverse overjet between 0 and ≤ 1 mm 2.c Anterior or posterior crossbite with 1 mm discrepancy between RCP and ICP 2.d Contact point displacements > 1 mm and ≤ 2 mm 2.e Anterior or posterior open bite > 1 mm and ≤ 2 mm 2.f Increased overbite of ≥ 3.5 mm (without gingival contact) 2.g Class II or class III occlusion without other anomalies (up to half a premolar width) Grade 3: Borderline treatment need 3.a Overjet > 3.5 mm and ≤ 6 mm (incompetent lip closing) 3.b Reverse overjet between 1 and ≤ 3.5 mm 3.c Anterior or posterior crossbite with > 1 mm and ≤ 2 mm discrepancy between RCP and ICP 3.d Contact point displacements > 2 mm and ≤ 4 mm 3.e Lateral or anterior open bite > 2 mm and ≤ 4 mm 3.f Deep overbite with gingival contact or contact with palatal mucosa (but without trauma) Grade 4: Treatment need 4.h Less severe hypodontia requiring prerestorative orthodontics or orthodontic space closure to obviate the need for prosthetic restoration 4.a Overjet > 6 mm and ≤ 9 mm 4.b Reverse overjet > 3.5 mm (without masticatory or speech problems) 4.m Reverse overjet > 1 mm and ≤ 3.5 mm (without masticatory or speech problems) 4.c Anterior or posterior crossbite with > 2 mm discrepancy between RCP and ICP 4.l Posterior lingual crossbite with no functional occlusal contact in one or both buccal segments 4.d Major contact point displacements > 4 mm 4.e Extreme lateral or anterior open bite > 4 mm 4.f Increased and complete overbite with gingival or palatal trauma 4.t Partially erupted teeth, tipped and impacted against adjacent teeth 4.x Existence of supernumerary teeth    44  Table 2-7 Dental Health Component of Index of Orthodontic Treatment Need Grade 5: Treatment need 5.i Impeded tooth eruption (3rd molars) attributable to crowding, displacements, supernumerary teeth, retained deciduous teeth and all pathological reasons 5.h Extensive hypodontia with restorative impact (more than 1 congenitally missing tooth in any quadrant) requiring prerestorative orthodontics 5.a Increased overjet > 9 mm 5.m Reverse overjet > 3.5 mm with masticatory problems and speech disorders 5.p Cleft lip and palate and other craniofacial anomalies 5.s Retained deciduous teeth  Table 2-8 Intra-Oral Examination Intra oral 17. Oral Habits  Yes  No                Since When :____________years Which?  Nail Biting                       Biting lip/cheek               Bruxism   Sucking Thumb/finger                   Other :______________________ 18. Horizontal Excess (taken at average of both central incisors, labial to labial) Overjet :  mm 19. Vertical Excess (taken at average of both central incisors, labial to labial) Overbite :  % 20. Anterior OpenBite Open bite:  mm 21. Posterior OpenBite Right  mm 22. Posterior OpenBite Left  mm 23. Odontogram 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8    E D C B A A B C D E       E D C B A A B C D E    8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8  24. Dental crossbite (including edge-to-edge bite) Anterior crossbite :  Yes ; IF YES Number of maxillary teeth involved : ____                                    No  Posterior crossbite :  Yes                                              Unilateral ; IF YES Number of maxillary teeth involved : ____                                         Bilateral                                  No  45  Table 2-9 Intra-Oral Examination 25. Narrow Palate  Yes  No 26. CR/CO shift  Yes, Specify:  Posterior - anterior : __________ Vertically: __________ To the right : __________ To the left : __________  No 27. Intermolar distance (measured from mid-palatal groove @ gingival margin) mm  28. Intercanine distance (measured from cusp tip) mm 29. Tongue size  Normal   Microglassia             Macroglossia 30. Arch Shape Upper:    U shape   V shape Lower :  U shape   V shape 31. Palatal Depth mm  32. Stage of dentition  Primary  Mixed  Permanent (No primary teeth present) 33. Molar Classification (according to R and L sides) Permanent : (<1/2 cusp = cl.1)    Right :    I       II     III Left :      I      II     III Primary/mixed :        Right :    Mesial step       Flush    Distal Step Left :      Mesial step       Flush    Distal Step 34. Canine Classification (<1/2 cusp = cl.1) Right :    I       II     III Left :      I      II     III  35. Space Analysis  crowding Upper  :          <3 mm              4-9 mm            >10mm    Lower :          <3 mm              4-9 mm            >10mm     spacing Upper  :          <3 mm              4-9 mm            >10mm    Lower :          <3 mm              4-9 mm            >10mm       46  Table 2-10 Intra-Oral Examination 36. IOTN esthetic scale  (match for overall occlusal attractiveness)   The need for maxillary expansion was indicated by the presence of a posterior crossbite. The need for growth modification treatment was indicated in those patients who had Class II molar occlusion, whether on both side or one side only, in combination of one of the following occlusal characteristics: increased overjet of greater or equal to 5mm, convex facial profile, and a retrognathic mandible. 47  2.4 Overnight Polysomnography  A one night, in-laboratory PSG was conducted for every child by trained and certified respiratory technologists. Each study lasted 8–10 hours and included overnight monitoring of an electroencephalogram, electro-oculogram, electro-cardiogram, chin and anterior tibial electromyogram, nasal pressure transducer, oral thermistor, a snore sensor, respiratory inductive plethysmography, pulse oximetry, and end-tidal capnography, as well as continuous video monitoring. The studies were scored according to the American Academy of Sleep Medicine manual for the scoring of sleep and associated events with a computerized system (XL-TEK, Oakville, Ontario, Canada) 80. The study reports were assessed and approved by a pediatric sleep physician (DW). The staff performing, scoring and approving the PSG study and report were blinded to the score on the questionnaire and clinical examination data.   Apnea in children is scored when a drop in the peak airflow is ≥ 90% of the pre-event baseline, with the drop lasting at least the duration of two breaths during baseline breathing, and it is associated with the presence of respiratory effort throughout the entire period of absent airflow 14. Hypopnea is scored in children when the drop in peak airflow is ≥ 30% of the pre-event baseline, for the duration of at least two breaths in association with either ≥ 3% oxygen desaturation or an arousal. (Sinha 2010 15, 14). The severity of OSA was expressed using the obstructive apnea – hypopnea index (AHI), which was the sum of apneas and hypopneas per hour of sleep during polysomnographic registration. An AHI of two events per hour or higher was considered abnormal for this study as it was found that an AHI value of ≤ 1.4 events per is normal for children (Section 1.3). 48  The weight and height was measured and recorded for every patient. Each patient’s body mass index (BMI) was calculated using the formula BMI = Weight (kg)/ Height2 (m2). Each patient's  BMI was then converted into a percentile for the population according to the patient’s age and gender using the published data by the Center of Disease Control and Prevention (CDC) 143. Weight status category was determined from each patient’s BMI percentile according to the CDC’s guidelines (Table 2-7)144. Table 2-11 CDC Weight Categories Weight Status Category Percentile Range Underweight Less than the 5th percentile Normal or Healthy Weight 5th percentile to less than the 85th percentile Overweight 85th to less than the 95th percentile Obese Equal to or greater than the 95th percentile   2.5 Statistical Analysis Data are presented as the mean, the standard deviation for continuous variables, and as percentages for categorical variables. Categorical variables were presented as percentage and analyzed using the Pearson chi-square test and the Fisher exact test. Continuous variables were analyzed using the t- test and Kruskal-Wallis statistics if not normally distributed. Statistical significance was assessed at P<0.05. Data were analyzed with SPSS software (version 15; SPSS, Chicago, Ill).  49  Associations between AHI, age, gender, and dentofacial variables were tested using multiple regression analyses, with AHI as the dependent variable.  2.6 Analysis of Error Twelve patients of the Graduate Orthodontic Clinic of University of British Columbia were randomly selected as the sample for error analysis. Orthodontic examination was performed on these patients during the initial appointment using the standardized form described above. These measurements were repeated clinically in six patients 3-6 months later, and repeated using full orthodontic records (photograph and radiograph) in 12 patients 7 months later. Intra-rater reliability was analyzed using the student’s t-test for linear measurements and percentage agreement for categorical measurements.    50  Chapter 3: Results 3.1 Error Analysis Repeated clinical orthodontic examination was carried out on six patients with a 2 to 6 month interval between measurements. The average differences in linear measurements ranged from 0.08mm (intermolar width) to 0.5mm (incisor display at rest and during smiling). There was no statistical significant difference between the repeated measurements. Percentage agreement ranged from 67% to 100%.  The average accuracy from the 41 variables recorded was 87%. The results are summarized in Table 3-1. Table 3-1 Percentage agreement of repeated clinical orthodontic examination measurements recorded 2-6 months apart.  Categories  Percentage Agreement  Lower Face Height; Upper Dental Midline; Nasolabial Angle; Lower Arch Shape; Canine Classification – Left; IOTN esthetic scale 66.67 Body Type; Type Facial; Symmetry; Lower Dental Midline; Lower Amount of Shift; With respect to esthetic line: Upper lip; With respect to esthetic line: Lower lip; Lip strain to close; Upper Arch Shape; Molar Classification - Permanent – Right; Molar Classification - Permanent – Left; Molar Classification - Primary/Mixed – Right; Molar Classification - Primary/Mixed – Left; Crowding – Upper; Crowding - Lower 83.33 Facial Profile; Skeleton position – Maxilla; Skeleton position – Mandible; Anterior crossbite; Posterior crossbite; Narrow Palate; CR/CO shift; Tongue size; Stage of dentition; Mixed dentition sub-categories; Canine Classification – Right; Spacing – Upper; Spacing - Lower 100%   For 12 patients, clinical orthodontic examination was carried out and repeated measurements were performed using intra-oral and extra-oral photographs. Percentage agreement ranged from 51  67% (upper dental midline, upper crowding), to 100%. The average accuracy from the 38 variables recorded was 89.7%. The results are summarized in Table 3-2. Table 3-2 Percentage agreement between measurements recorded with clinical examination and orthodontic photographic records.  Categories  Percentage Agreement Upper Dental Midline; Crowding - Upper 66.67 Lower Amount of Shift; Skeleton position – Mandible; IOTN esthetic scale 75.00 Type Facial; Symmetry; Skeleton position – Maxilla; Dental crossbite; Number of maxillary teeth involved; Lower Arch Shape 83.33 Canine Classification – Left; Crowding – Lower; Lower Face Height; Lower Dental Midline; With respect to esthetic line: Upper Lip; With respect to esthetic line: Lower Lip; Narrow Palate; Upper Arch Shape; Stage of dentition; Mixed dentition sub-categories; Molar Classification - Primary/Mixed – Right; Molar Classification - Primary/Mixed - Left 91.67 Canine Classification – Right; Spacing – Lower; Facial Profile; Nasolabial Angle; Lip strain to close; Dental Crossbite: Posterior crossbite; Molar Classification - Permanent – Right; Molar Classification - Permanent – Left; Spacing - Upper 100.00  3.2 Subjects During the study period of January 07, 2014 to June 18, 2014, 64 children and their legal guardian agreed to participate in the study (38 male, 26 female). One patient did not complete the PSG study. Seven patients were currently going through or had history of orthodontic treatment, including full or partial fixed edgewise appliance (braces) and rapid maxillary expander. Since the objective of orthodontic treatment is to alter dentofacial morphology, these patients were excluded from data analysis.  52  Additionally, 17 children were diagnosed with craniofacial syndromes, including Pierre-Robin Sequence, De George Syndrome, Cleft Palate, Coffin-Siris Syndrome, Cerebral Palsy, Treacher, Collin Syndrome, Q15 Deletion, Prader-Willi Syndrome, Trisomy 21 (Down Syndrome), Quadriplegia Cerebral Palsy, Ohdo Syndrome, Fetal Alcohol Syndrome, and left facial plexiform neurofibroma.  The mean age of OSA children (12 males and 5 females) was 8.0 years [standard deviation (SD) 2.31; range 4.4 – 14.7]. The mean age of the non-OSA group (13 males and 9 females) was 8.4 years (SD 3.16; range 4.3 – 16.9). A history of adenoidectomy was found in 35.3 per cent of the OSA subjects and in 45.4 per cent of the non-OSA subjects.   To better understand if we could analyze the whole sample together, we evaluated the differences between the syndromic and non-syndromic patients. When compared to patients without craniofacial syndromes, patients with craniofacial syndromes were found to have significantly greater AHI (12.4 vs. 3.5 events/hr), and a significantly greater prevalence of a dolichocephalic face type (35.3%  vs. 10.9%), convex profile (82.4% vs. 43.5%), retrognathic mandible (70.6% vs. 23.9%), posterior crossbite (41.2% vs. 13.3%), narrow palate (62.5% vs. 26.7%), and narrower intermolar width (31.7mm vs. 35.9mm). Table 3-3 summarizes these findings. Therefore, syndromic patients were assessed separately from the non-syndromic patients. Since there were only 17 syndromic patients, only descriptive statistical analysis was performed. Further analysis was only done on the non-syndromic patients.    53  Table 3-3 Comparison of dentofacial morphology between children with and without craniofacial syndromes              The remaining 39 patients had a mean age of 8.2 years and 64% were male. They were divided into an OSA group (AHI ≥ 2; n=17) and a non-OSA group (AHI < 2; n=22). Although there was no statistical difference between the two groups for these variables, when compared to the children in the non-OSA group, children in the OSA group were slightly younger (8.0yr vs. 8.4yr), and there were more males (70.6% vs. 59.1%), more patients with increased tonsillar size (58.8% vs. 40.9%) and fewer thumb suckers (10% vs. 20%).Table 3-4 summarizes these findings.    Syndromic Non-Syndromic P-Value N 17 46  Loud Snorers 5/16 (31.3%) 10/46 (21.7%) .333 Frequent Snorers 11/16 (68.8%) 30/45 (66.7%) .267 AHI 12.4 3.5 .001 AHI ≥ 2 13/16 (76.5%) 19/46 (41.3%) .022 Dolichocephalic 6/17 (35.3%) 5/46 (10.9%) .016 Increased LFH 5/17 (29.4%) 5/46 (10.9%) .056 Convex Profile 14/17 (82.4%) 20/46 (43.5%) .009 Retrognathic Md 12/17 (70.6%) 11/46 (23.9%) .000 Mouth Breather 12/17 (76.5%) 31/46 (67.4%) .552 Posterior Crossbite 7/17 (41.2%) 6/45 (13.3%) .032 Narrow Palate 10/16 (62.5%) 12/45 (26.7%) .016 Intermolar width  31.7mm 35.9mm .022 54   Table 3-4 Demographic distribution of children in Non-OSA and OSA group  Non-OSA AHI < 2 (n=22) OSA AHI >2 (n=17) Total (n=39) Age  8.4 8.0 8.2 Male Gender  13/22 (59.1%) 12/17 (70.6%) 25/39 (64.1%) BMI  19.8 20.8 20.3 Overweight and Obese   12/22 (54.6) 9/17 (52.9%) 21/39 (53.9%) Increased Tonsillar Size  9/22 (40.9%) 10/17 (58.8%) 19/39 (48.7%) Mouth Breather  15/22 (68.2%) 10/17 (58.8%) 25/39 (64.1%) Thumb Sucker  3/22 (13.6%) 1/16 (6.2%)  4/38 (10.5%)   To better understand the relationship between the severity of OSA disease and a patient’s dentofacial characteristics, we further divided the OSA group into a lower AHI group (AHI between 2-5; n=9) and a higher AHI group (AHI ≥ 5; n=8). There was no significant difference among these groups in the distribution of age, gender, BMI, tonsil size, and whether subjects were mouth breathers and/or thumb suckers. Subjects in the higher AHI group were slightly younger (7.1 years old), had increased tonsillar size (75% had tonsil size of 3 or greater), and none were thumb suckers. A summary of the demographic data is provided in Table 3-5.   55  Table 3-5 Demographic Data  Normal AHI < 2 (n=22) Lower AHI OSA AHI 2-5 (n=9) Higher AHI OSA AHI > 5 (n=8) Age  8.4 8.7 7.1 Male Gender  13/22 (59.1%) 7/9 (77.8%) 5/8 (62.5%) BMI  19.8 23.3 17.8 Overweight and Obese   12/22 (54.6%) 5/9 (55.5%) 4/8 (50%) Increased Tonsillar Size  9/22 (40.9%) 4/9 (44.4%) 6/8 (75%) Mouth Breather  15/22 (68.2%) 6/9 (66.7%) 4/8 (50%) Thumb Sucker  3/22 (13.6%) 1/9 (11.1%)  0/7 (0%)   3.3 Questionnaire and PSG results The result of the sleep questionnaire showed that 82.4% of children in the OSA group snored more than 3-4 nights per week, which was higher than children in the non-OSA group (63.3%), but the difference was not significant. The OSA groups on average have a higher questionnaire score when compared with the non-OSA group, but the difference was not statistically significant. When the OSA sample was divided into higher and lower AHI groups, the children with higher AHI had a significantly greater number of very loud or extremely loud snores (62.5%), and higher mean heart rate (86.5 bpm). A summary of these findings is provided in Table 3-6; the differences in AHI and OSA related PSG findings were different between groups as these groups were divided based on AHI variables.   56  Table 3-6 Sleep Questionnaire and PSG results of OSA patients compared with non-OSA patients  Non-OSA AHI < 2 (n=22) OSA AHI ≥2 (n=17) Lower AHI OSA AHI 2-5 (n=9) Higher AHI OSA AHI > 5 (n=8) Total (n=39)       Total questionnaire score 1.97 2.37 2.44 2.30 2.15 High Risk of SDB (% patient) 22.2% 41.2% 33.3% 50% 30.8% 1. Frequent need to shake child to breathe  9.1% 11.8% 11.1% 12.5% 10.3% 2. Frequent witnessed apnea 18.2% 29.4% 22.2% 37.5% 23.1% 3. Frequent struggle to breathe when asleep 31.8% 35.3% 33.3% 37.5% 33.3% 4. Frequent concern with child’s breathing when asleep 50.0% 35.3% 33.3% 37.5% 43.6% 5. Snores Very Loudly  13.6% ¥  35.3% 11.1%¥ 62.5% ¥ 23.1% 6. Frequent Snores  63.6% 82.4% 88.8% 75% 71% Total Sleep Time (hours)  6.76 6.37 6.22 6.53 6.59 Sleep Efficiency  84.4% 80.8% 78.8% 83.0% 82.8% Sleep Onset (min) 35.3 41.3 43.5 38.8 37.9 Mean O2 Sat  96.0% 96.6% 96.2% 96.9% 96.3% Mean HR  76.9¶ 80.8 74.3†† 86.5††¶ 78.3 Total Apnea Index 0.2¶¶ 1.4 0.4† 2.6¶¶† 0.8 Total Hypopnea Index 0.7**££¶¶ 6.1** 2.8££† 9.8¶¶† 3.1 AHI  0.9*££¶¶ 7.5* 3.3†£ 12.4†¶¶ 3.8 For questions 1-4 and 6, Percentage of patient who answered “Frequent” and “Almost Always” were reported. For question 5, Percentage of patient who answered “very strong” and “extreme strong” were reported.  “Frequent” indicates a frequency of more than 3-4 nights per week.  O2 Sat = Arterial Blood Oxygen Saturation (%) 57  HR = Heart Rate (Beats/Min) AHI = Apnea/Hypopnea Index (event/hr)  * p<0.05; ** p<0.01 Significant differences between Non-OSA and OSA group  £ p<0.05; ££ p<0.01 Significant differences between Non-OSA and Lower AHI OSA group  ¶ p<0.05; ¶¶ p<0.01 Significant differences between Non-OSA and Higher AHI OSA group  † p<0.05; †† p<0.01 Significant differences between Lower and Higher AHI OSA group  ¥Significant differences between Non-OSA group and Lower and Higher AHI OSA groups    Out of the maximum score of 4, Spruyt and Goyal suggested that an overall score of 2.72 or higher from the 6-question questionnaire is indicative of a patient who is at high risk of having sleep disordered breathing. It was found that this method is able to predict children who have obstructive sleep apnea (AHI ≥ 2) with 40.6% sensitivity and 83.9% specificity. We also evaluated the ability of each question to predict patients with OSA. Out of the maximum score of 4 for each question, we used the score of 3 or higher as the cut off and found that frequency of snoring had the highest sensitivity (81.3%), while the need to shake the children to breathe had the highest specificity (93.5%). Figure 3-1 summarizes the sensitivity and specificity of each question and the total score.  58   Figure 3-1 Sensitivity and Specificity of the 6-Questions Questionnaire in predicting patients with AHI≥2  3.4 Dentofacial Morphology Dentofacial characteristics were grouped into variables describing anterior-posterior, transverse, vertical, and perimeter characteristics of the patient’s morphology. Table 3-7 presents the prevalence of altered dentofacial morphology of the study sample, the Non-OSA group, the OSA group, and the lower and higher AHI OSA groups.    0.0%10.0%20.0%30.0%40.0%50.0%60.0%70.0%80.0%90.0%100.0%Shake Child tobreathWitnessedApneaStruggle tobreathConcern withchild'sbreathingLoud snoring FrequentsnoringQuestionnaireScoreSensitivitySpecificity59  Table 3-7 Prevalence of dentofacial morphology characteristics of patients of the study sample, non-OSA group, OSA group, lower AHI OSA group, and higher AHI OSA group.                           There was no statistically significant difference in all measurements between the two groups. Nevertheless, when compared to children in the non-OSA group, children diagnosed with OSA      OSA Group   Total Non OSA OSA Group Lower AHI  Higher AHI  Anterior-Posterior Convex Profile  46.2% 50.0% 41.2% 55.6% 25.0% Retrognathic Mandible  23.1% 18.2% 29.4% 33.3% 25.0% Anterior Crossbite  12.8% 9.1% 17.6% 11.1% 25.0% Overjet (mm) 3.4 3.6 3.2 3.4 2.9 Overjet ≥ 5mm  30.8% 36.4% 23.5% 22.2% 25.0% Class II Molar Relationship  33.3% 40.9% 23.5% 22.2% 25.0% Class II Canine Relationship  31.6% 33.3% 29.4% 33.3% 25.0% Transverse and Vertical Dolichocephalic Facial Pattern  10.3% 9.1% 11.8% 11.1% 12.5% Increased Lower Face Height  10.3% 4.5% 17.6% 11.1% 25.0% Overbite (% overlap of incisors) 43.0% 40.0% 46.0% 45.6% 47.5% Overbite ≥ 50%  38.5% 36.4% 41.2% 55.6% 25.0% Anterior Openbite  10.3% 9.1% 11.8% 11.1% 12.5% Posterior Crossbite  10.5% 9.1% 12.5% 22.2% 0.0% Narrow Palate  26.3% 31.8% 18.8% 22.2% 14.3% Maxillary Intermolar width (mm) 36.0 36.4 35.6 36.1 34.8 Maxillary Intercanine width (mm) 31.3 31.6 31.0 30.9 31.1 Perimeter Maxillary Crowding ≥4mm  28.0% 25.0% 30.8% 50.0% 14.3% Mandibular Crowding ≥4mm  26.7% 23.5% 30.8% 50.0% 14.3% 60  displayed a higher prevalence of anterior crossbite (9.1% vs. 17.6%), increased lower face height (4.5% vs. 17.6%), deep bite of more than 50% (36.4% vs. 41.2%), posterior crossbite (9.1% vs. 12.5%), and maxillary and mandibular crowding of 4mm or greater (25% vs. 30.8%, 23.5% vs. 30.8%, respectively). On the other hand, the incidence of a convex facial profile (50% vs 41.2%), increased overjet of 5mm or greater (36.4% vs. 29.4%), and a Cl II molar relationship (40.9% vs. 23.5%) were found to be slightly greater in the non-OSA group when compared with the OSA group. These findings are summarized in figure 3-2.   Figure 3-2  A comparison of  the percentage of patients in the non-OSA and OSA groups that presented with altered dentofacial morphology including convex profile, anterior crossbite, increased OJ of ≥5mm, Class II molar relationship, increased lower face height, deep bite of ≥50% OB, anterior openbite, posterior crossbite, and maxillary and mandibular crowding of ≥4mm.  When the OSA group was divided into lower and higher AHI groups, there was again no statistically significant difference between the groups. However, children in the higher AHI OSA 0.0%10.0%20.0%30.0%40.0%50.0%60.0%Convex ProfileAnterior CrossbiteOverjet >= 5mmClass II Molar RelationshipIncreased Lower Face HeightOverbite >= 50%Anterior OpenbitePosterior CrossbiteMaxillary Crowding >=4mmMandibular Crowding >=4mmAnterior-Posterior Vertical & Transverse PerimeterNon-OSAGroupOSAGroup61  group showed less prevalence of a convex profile (25% vs. 55.9%), a deep bite of 50% or more (25% vs. 55.6%), posterior crossbite (0% vs. 22.2%), and maxillary and mandibular crowding of 4mm or greater (14.3% vs. 50% for both maxillary and mandibular teeth), but they showed an increased prevalence of anterior crossbite (25% vs. 11.1%), and increased lower face height (25% vs. 11.1%)  when compared with children in the lower AHI OSA group.  These findings are summarized in figure 3-3.    Figure 3-3 A comparison of the percentage of patients in the non-OSA, lower AHI OSA, and higher AHI OSA group that presented with convex profile, anterior crossbite, increased OJ of ≥5mm, increased lower face height, deep bite of ≥50% OB, posterior crossbite, and maxillary and mandibular crowding of ≥4mm.  Linear measurements such as overbite, overjet, maxillary intercanine width, and maxillary intermolar width were compared using the t-test with two groups at a time. Although there was no statistically significant difference between groups, intermolar width was the largest in the 0.0%10.0%20.0%30.0%40.0%50.0%60.0%ConvexProfileAnteriorCrossbiteOverjet >=5mmClass IIMolarRelationshipIncreasedLower FaceHeightOverbite >=50%AnteriorOpenbitePosteriorCrossbiteMaxillaryCrowding>=4mmMandibularCrowding>=4mmAnterior-Posterior Vertical & Transverse PerimeterNon-OSAGroupLower AHIOSAGroupHigher AHIOSA group62  non-OSA group followed by the lower AHI OSA group, and lowest in the higher AHI OSA group. This result is presented as a box plot in figure 3-4.    63  Figure 3-4 Box plot presentation of measurements of (a) overjet, (b) overbite, (c) maxillary intercanine width, and (d) maxillary intermolar width in non-OSA, lower AHI OSA, and higher AHI OSA children. Each box plot represents the median and 25th and 75th percentile.   3.5 Need for Orthodontic Treatments The need for orthodontic treatment was determined by use of the Index of Orthodontic Treatment Need (IOTN) classification. The Dental Health Component (DHC) was determined using overjet, crossbite, and overbites only. Missing teeth data were omitted as they could not be evaluated accurately without radiographs. Richmond et al. stated that displacement should not be measured between contacts of permanent and primary teeth 145. Instead, crowding was measured as the tooth size to arch length discrepancy and was recorded as mild (0-3mm), moderate (4-9mm), and severe (>10mm). The need for maxillary expansion and growth modification treatment were also evaluated for the study sample. Although there was no statistically significant difference between the groups in the need for the evaluated orthodontic treatments, more patients in the higher AHI OSA group were determined to require orthodontic treatment as defined by IOTN. The result is summarized in Figure 3-5. 64   Figure 3-5 Comparison of the need for orthodontic treatment as indicated using IOTN criteria and need for maxillary expansion and growth modification treatment between non-OSA group and OSA groups.   3.6 Correlations between dentofacial morphology and OSA diagnosis There was no statistically significant association between OSA diagnosis and increased lower face height, dolichocephalic facial type, Class II molar relationship, convex profile, retrognathic mandible, deep-bite, increased overjet, anterior openbite, posterior crossbite, lower crowding, need for growth modification treatment, IOTN required treatment, obese or overweight status. The results are summarized in table 3-8.    Need for MaxillaryExpansionNeed for GrowthModification TxIOTN - Tx Required IOTN - BorderlineControl Group 9.1% 13.6% 18.2% 31.8%OSA Group 11.8% 23.6% 35.3% 29.4%OSA Lower AHI 22.2% 22.2% 22.2% 44.4%OSA Higher AHI 0.0% 25.0% 50.0% 12.5%0.0%10.0%20.0%30.0%40.0%50.0%60.0%Percentage of Patient Need for Orthodontic Treatment 65  Table 3-8 Association between evaluated dentofacial morphology, weight status, and diagnosis of OSA (AHI ≥2)  P-Value Odds Ratio Increased LFH 0.21 4.50 Dolichocephalic 0.59 1.33 Cl II molar  0.30 0.54 Convex Profile 0.41 0.70 Retrog Md 0.33 1.88 OB > 50%  0.51 1.24 OJ>4mm  0.14 0.37 AOB  0.59 1.33 PXB  0.57 1.43 Lower crowding  0.11 0.35 Need for Growth Modification 0.54 0.82 IOTN Req Tx 0.20 2.46 Obese & Overweight 0.09 3.06    66  Chapter 4: Discussion  Although the relationship between adenotonsillar hypertrophy and dentofacial morphology with mouth-breathing in children has been reported in many studies95,131-133, the literature review showed that the evidence currently available on the relationship between malocclusion and SDB is limited (Section 1.6). There have been only nine studies to date investigating the association between dentofacial morphology and dental occlusion in children with diagnosed SDB or OSA. Only four studies diagnosed OSA from PSG75,78,136,138, with only one of which included non-OSA sample as a control group. Not every study recorded the extra-oral features of the patients, and the occlusion characteristics reported varied significantly between studies (Table 1-3). Furthermore, these studies had vastly different sample populations: children from the general population, referred patients with suspected SDB, or patients from an orthodontic clinic. Additionally, the methodologies employed by the studies for diagnosis of SDB and definition of abnormal dentofacial morphology also varied, which makes direct comparisons between studies difficult. Therefore, more research is needed in order to establish the association between dentofacial morphology and pediatric OSA. Specifically, the prevalence of abnormal dentofacial morphology in children with diagnosed OSA needs to be established.   The above mentioned limitations could be addressed in a multi-centered study across Canada using the same study design and protocol. The sample will include patients who are referred to a children’s hospital for an overnight PSG study, and one center will include a matched control sample from the general population. All subjects will receive the same questionnaire and undergo an overnight PSG for diagnosis of OSA. A standardized orthodontic examination form 67  will be used for all subjects to record their dentofacial morphology; this will be performed with the examiners blinded to the OSA diagnosis. The examiners for the clinical orthodontic examination will be calibrated using 12 cases with various gender, age, ethnicity, and malocclusion types.   4.1 Error Analysis High intra-observer agreement (100%) was observed for diagnosis of facial profile, skeletal position of the maxilla and mandible, anterior and posterior crossbite, narrow palate, and dental spacing. Good intra-observer agreement (83.3%) was shown for diagnosis of facial type, molar classification, and dental crowding. This finding is similar to that found by Pirilä-Parkkinen et al., who reported strong inter-observer agreement of linear dental arch measurements (ICC = 0.990 – 0.997), openbite estimate (Kappa = 1.000), and Angle’s Classification (Kappa = 0.889)136. Carvalho et al. also reported that strong inter- and intra-observer agreement is possible for diagnosis of dental malocclusion, with reported Cohen’s kappa coefficients ranging from 0.808 (overbite ≥ 4mm, yes or no), to 1.000 (openbite, yes or no)74.   The average differences in linear measurements for the current study ranged from 0.08mm (intermolar width) to 0.5mm (incisor display at rest and on smile). There was no statistically significant difference between the repeated measurements. This is similar to what was reported by Lofstrand-Tidestrom et al., who found the average differences in repeated linear measurements to be less than 0.6mm108.   68  The intra-observer agreement was moderate (66.67%) for the diagnosis of lower face height, upper dental midline, nasolabial angle, lower arch shape, canine classification, and IOTN esthetic scale. One possible explanation could be that there was a 3-6 month interval between the two clinical examinations, resulting in changes in the patient’s dentition between the examinations.  The fact that the intra-observer agreement for diagnosis of the canine relationship was 91.7% between the clinical examination and orthodontic photographic record, which were performed on the same day, supports this hypothesis. Another possible explanation is that the diagnostic criteria for some variables were not clearly defined. This could be the case for the IOTN esthetic scale, which was designed to be used for the full permanent dentition and upper dental midline only.   4.2 Subjects Seventeen children in our sample pool were diagnosed with genetic syndromes which affect craniofacial development. When compared with children without craniofacial syndromes, children with craniofacial syndromes have significantly different dentofacial morphology. Furthermore, these syndrome patients also have a significantly higher prevalence of OSA (AHI ≥ 2; 76.5% vs. 41.3%, p = 0.022) and a significantly higher mean AHI (12.4 vs. 3.5, p = 0.001). This finding is supported by the literature as Anderson et al. in 2011 found that 85% of infants with Pierre Robin Sequence had OSA with a mean AHI of 33.5 events per hour146. Marcus et al. and Dyken et al. documented that OSA was found in 63% and 79% children with Down Syndrome, respectively37,38. This result illustrates the importance of screening for OSA in children diagnosed with genetic syndromes that affect craniofacial development.   69  The remaining 39 children in our sample pool were divided into a non-OSA group and an OSA group based on the AHI index. There was no statistically significant differences between the two groups in age, gender, BMI, weight status category, tonsil size, and percentage of mouth breathers. In an epidemiology study done in 2008 by Lumeng et al. in children with OSA, the available data appeared insufficient to prove that SDB differs systematically by age8,147. This supports our finding that the two groups were only 0.4 years different in age and the p value was 0.591. Lumeng et al reported that the prevalence of childhood SDB does differ by sex, with boys being affected at rates that are 50 to 100% higher than those for girls8,147. The prevalence of OSA in the current study was higher in males (48%) than in females (35.7%), but the difference was not significant. Lumeng et al. also evaluated the association between weight status and pediatric OSA. They concluded that weight status is probably a significant etiological factor affecting the prevalence of OSA, but the evidence is difficult to interpret as a normal distribution of body fat (and BMI) across a population varies by both age and sex.  Indexing of weight status is also extremely variable8. This may explain why in the current sample the OSA group had a higher BMI but had fewer patients who were defined as overweight or obese. A better weight status index is needed. Mitchell et al. reported that tonsillar size and Friedman palate position were not associated with increased AHI72, supporting the lack of significant differences in tonsil size between the non-OSA and the OSA groups in this study. Finally, the prevalence of OSA among mouth breathing children in the current sample was 40%. This is similar to what Izu et al. found in 2010 among 248 mouth breathing children where 42% had OSA148.   70  4.3 Questionnaire & PSG results When comparing the results of the 6-question questionnaire between the non-OSA and OSA groups, children with OSA showed a higher, but not statistically significant, prevalence of frequent snoring of more than 3-4 nights per week. Additionally, the study sample as a whole had a 71% prevalence of frequent snorers, which is much higher than the reported 7-28% prevalence of primary snoring in the literature 8,21. This is expected as our sample was referred to the children’s hospital for an overnight PSG study because of suspected SDB. On the other hand, it was reported that 63.6% of children in the non-OSA group were frequent snorers, yet their PSG results suggested that they do not have OSA. It was calculated that snoring frequency as a diagnostic test showed 81.3% sensitivity but only 48.4% specificity. This supports the literature which reported that assessing patients’ complaints of snoring alone is insufficient to discriminate apneic and non-apneic snorers149-151.  Children with AHI above 5 events per hour showed a significantly higher prevalence of having very strong or extremely strong snoring when compared to children with AHI between 2-5 and children in the non-OSA group. Snoring loudness was able to identify children with OSA with 37.5% sensitivity and 90% specificity. This is in agreement with the finding from Spruyt et al. who described loudness of snoring as exhibiting moderate specificity as a diagnostic test, and which adds specificity to snoring frequency alone 94. Nevertheless, Spruyt et al. concluded that neither of these questions is powerful enough to discriminate across the SDB spectrum.   Finally, the OSA group had a higher, but not statistically significant, average overall questionnaire score than the non-OSA group. Using 2.72 as a cutoff as suggested by Spruyt et al, 71  the overall score was able to identify children with OSA with 40.6% sensitivity and 83.9% specificity. This is comparable to the sensitivity, 59.03%; and specificity, 82.85%, reported by Spruyt et al 94.   The PSG studies were conducted and scored following the latest guidelines published by the AASM in 2007. Only two of the four studies in the literature review incorporated PSG for the diagnosis of OSA and used the AASM guidelines. Pirilä-Parkkinen et al. followed the older guidelines published by the American Thoracic Society in 1996, while Sauer et al. did not describe the guidelines that they used. The use of different guidelines for scoring may result in over- or under-diagnosis of OSA.   An AHI of 2 events per hour or higher was considered abnormal for this study as Marcus et al. in their 2012 guidelines suggested that an AHI value of ≤ 1.4 events per is normal for children16,21. Most studies in the literature review used AHI ≥ 1 for the diagnosis of OSA. This may over-estimate the amount of patients who has the disease.   4.4 Dentofacial morphology  The main finding of this study was that there was no statistically significant difference in dentofacial morphology between children diagnosed with OSA and the non-OSA sample. This result is similar to that reported in the systematic review conducted by Katyal et al. in 2013 on craniofacial and upper airway morphology in pediatric sleep-disordered breathing. From the nine studies that met their inclusion criteria, Katyal et al. found children with OSA and primary 72  snoring show increased weighted mean differences in the ANB angle of 1.64 degrees (P<0.0001) and 1.54 degrees (P<0.00001), respectively, compared with the controls. They concluded that an increased ANB angle of less than 2 degrees in children with OSA and primary snoring, compared with the controls, could be regarded as having marginal clinical significance, and that evidence for a direct causal relationship between craniofacial structure and pediatric sleep-disordered breathing is unsupported by this meta-analysis36.   To better understand the relationship between the severity of OSA disease and a patient’s dentofacial characteristics, we further divided the OSA group into lower AHI and higher AHI groups. Although there was no statistically significant difference between the non-OSA, lower AHI, and high AHI groups, it was noticed that children in the higher AHI group displayed a trend of dentofacial morphology that is different from the non-OSA and lower AHI group, and from what was presented in the literature.   Our literature review showed that that children diagnosed with OSA were found to have a significantly higher prevalence of posterior crossbite, anterior openbite, class II occlusion, and crowding, when compared with the control groups. Nevertheless, only three studies compared OSA children with a control group75,136,138, and the reported prevalence also had very wide ranges. The following ranges of prevalence were reported for children with OSA: posterior crossbite – 12.2% - 55%, with two studies showing significant differences; anterior openbite – 11.1% - 30%, with two studies showing significant differences; Class II occlusion – 29.3% - 88.9%, with one study showing significant differences; and crowding – 17.1% - 35%, reported in two studies, with one showing statistically significant differences.  73  The result of the current study was compared with four studies from the literature review that had the most similar patient population and diagnostic criteria75,136-138. The prevalence of posterior crossbite of the OSA group is similar to what was reported by Ikävalko et al. in their SDB patients, higher than what Pirilä-Parkkinen et al. reported in their snoring and OSA patients, and lower than what Sauer et al. reported in their OSA patients (Appendix A.1).  The prevalence of an anterior openbite in the OSA group is similar to what was reported by Pirilä-Parkkinen et al. in their snoring patients, and Sauer et al. in their OSA and SDB patients. The prevalence of an anterior openbite is higher than what Ikävalko et al. reported in their SDB patients, and lower than what Carvalho et al. and Sauer et al. reported in their SDB patients, and lower than what Pirilä-Parkkinen et al. reported in their OSA patients (Appendix A.2).  The prevalence of Class II occlusion of the OSA group is lower than what was reported by all of the included studies (Appendix A.3).  The prevalence of crowding of the OSA group is similar to what was reported by Carvalho et al. in their SDB patients, but higher than what Pirilä-Parkkinen et al. reported in their snoring patients and OSA patients. Prevalence of crowding was not reported in other studies (Appendix A.4).  It is important to note that each of the included studies in the literature review had specific limitations, making a direct comparison difficult. For example, Pirilä-Parkkinen et al. and Sauer et al. did not utilize the latest AASM guidelines in the scoring of the PSG results; hence the AHI 74  values in their studies may not be comparable with other studies. Caprioglio et al., Ikävalko et al., and Sauer et al. did not perform error analyses for the clinical measurements of the orthodontic examinations. Furthermore, the diagnostic criteria for the various dentofacial characteristics were either defined differently or not defined at all. Therefore, it is possible that the differences noticed between the studies could be due to differences in the methodologies and definitions for the various characteristics of malocclusion used in these studies.  An interesting finding of the current study was that prevalence of a posterior crossbite, a convex profile, and a narrow palate, and mandibular crowding greater or equal to 4mm was highest among children in the lower AHI group, but was lowest among children in the higher AHI group. When compared to the non-OSA group, the lower AHI and higher AHI groups had less prevalence of class II occlusion and less prevalence of increased overjet of greater or equal to 5mm.  One possible explanation of this finding is that pediatric OSA is a multifactorial disease and anatomical malformation is frequently not the only etiological factor contributing to the disease process10,18. Mitchell et al. in 2015 examined the baseline data from 453 children from the Childhood Adenotonsillectomy (CHAT) study to assess whether a combination of factors, including demographics, physical examination findings, and caregiver reports from questionnaires, could predict different levels of OSA severity in children. They found that race (African American), obesity (body mass index z score > 2), and the Pediatric Sleep Questionnaire (PSQ) total score were associated with higher levels of AHI and ODI (P = 0.05)72. More importantly, anatomical landmarks such as tonsillar size and Friedman palate position were 75  not associated with increased AHI and provided only limited information on the severity of OSA72. A similar result was found by Howard and Brietzke when they compared tonsil size, Friedman palate position scores, and preoperative AHI in 34 children and found no correlations between these findings and the PSG results152. It was reported that some patients with size 1+ tonsils had severe OSA, while others had size 4+ tonsils without evidence of OSA152. The findings of Mitchell et al. and Howard and Brietzke’s studies suggest that children with OSA tend to have highly variable anatomical features, and this is in agreement with the results of the current study. This may also be a possible explanation for the wide range of prevalence reported in the literature for the prevalence of various dentofacial morphologies of OSA children. Overall, the results suggest that pediatric OSA is a multifactorial disease, and may present with highly variable anatomical characteristics.   Another possible explanation of why the OSA group showed less prevalence of malocclusion than the non-OSA group could be that 63.6% of patients in the non-OSA group were frequent snorers. This prevalence is much higher than the reported prevalence of primary snorers for the general population (7.5-27.6%), indicating that the non-OSA sample may not represent a healthy population. To determine if this is true, the prevalence of various dentofacial morphologies of the non-OSA group was compared to five different epidemiological studies surveying children between ages 5-17 of different populations 141,153-156. The third National Health and Nutrition Examination Survey (NHANES-III) represented prevalence of malocclusion in the U.S. population in the 1990s141,157. Data from Tausche et al. represented children between ages 6 year and 8 years 11 months old from the city of Dresden, Germany 155. Data from Karaiskos et al. represented 6 year old and 10 year old children of inner city Winnipeg, Canada156. Data from 76  Carvalho et al. represented children between ages of 60 to 71 months from the Belo Horizonte, Brazil154. Finally, data from Prabhakar et al. represented children between ages 7-13 from Chennai, India 153.  When compared to these populations, the non-OSA group in our study had the highest prevalence of increased overjet, and the second highest prevalence of class II occlusion, crowding, and posterior crossbite (Appendix A.5). This result indicates that these children may display a different dentofacial morphology from the general population.   Among the frequent snorers, 14 (50%) had a normal PSG result, 8 (28.6%) had AHI between 2-5 events per hour, and 6 (21.4%) had AHI of more than 5 events per hour. Pirilä-Parkkinen et al. is the only study that included a matched non-snoring, non-OSA control group, a non-OSA snoring group, and a PSG diagnosed OSA group. When compared to controls, the snoring group had significantly increased Class II malocclusion (36.6% vs. 4.9%) and OJ (3.6 vs. 3.2)136. Nevertheless, when we compared snoring children (n=28) with non-snoring children (n=11) in our population, we found that snoring children showed a tendency for less Class II occlusion (25% vs. 54.5%) and less prevalence of increased overjet of 5mm or more (25% vs. 45.5%). Such conflicting results suggests that children with SDB and OSA display highly variable anatomical features. Furthermore, the fact that only 21.4% of children who snore frequently have an AHI of greater than 5 events per hour suggests that snoring alone is not sufficient to distinguish patients who have OSA or not.  4.5 Need for orthodontic treatment The need for orthodontic treatment was evaluated in the current study using the index of orthodontic treatment need (IOTN) as it is the most commonly used index for malocclusion 77  assessment158,159. Ovsenik et al. compared three different occlusal indices using 100 pretreatment study casts of adolescents in the permanent dentition and found the IOTN to be valid (area under the ROC curve = 0.68), reliable (inter-examiner agreement ICC = 0.904), and quick to perform (1.97 minutes)160. Given that no statistically significant difference between dentofacial morphology was found between children with or without OSA, it was not surprising to find that there was no significant difference between these two groups in their need for orthodontic treatment determined using the IOTN guidelines.   When evaluated as a whole, 10/39 (25.6%) children in this study were determined to have an urgent orthodontic treatment need using IOTN-DHC. Tausche et al., evaluated 1975 randomly selected school children between ages 6 to 17 using IOTN and found 26.2% displayed an urgent treatment need155. Birkeland et al. examined 359 school age children with a mean age of 10.6 years and found that 26.1% displayed an urgent treatment need161. It is important to note, however, that the Dental Health Component (DHC) was determined using overjet, crossbite, and overbites only in the current study. Missing teeth data was omitted as it could not be evaluated accurately without a radiograph. Richmond et al. stated that displacement should not be measured between contacts of permanent and primary teeth145. Instead, crowding was measured as the tooth size to arch length discrepancy and was recorded as mild (0-3mm), moderate (4-9mm), and severe (>10mm). Therefore, the reported need for orthodontic treatment in the current study may be an underestimation as missing teeth and contact displacement data were not available.   78  4.6 Limitations of the study: A major limitation of this study was the limited sample size of only 39 patients. This is because every patient included in the study had a laboratory, overnight PSG study done to establish the diagnosis of OSA. To our knowledge, this is the first study where the entire study sample received a PSG study. We were limited by the capacity of the sleep study center at BC’s Children’s Hospital, which had a maximum capacity of five children per week with a three-month waiting list. Also, as this is the pilot study for a future multi-center study to evaluate dentofacial morphology of children with OSA, a portion of the study period was spent on developing and refining a clinical examination protocol that can be reproduced for all other centres.   Furthermore, we did not perform a power analysis from the literature review nor from the result of the current study. We were unable to perform power analysis from literature review because these studies had vastly different sample populations and the methodologies employed by the studies for diagnosis of SDB and definition of abnormal dentofacial morphology also varied significantly. Since we did not find statistically significant differences between the study groups, we did not perform a power analysis as estimating effect sizes based on non-significant results will have an increased error. This may lead to an erroneous estimation of sample size.    Another limitation of the current study was the lack of a true control group. 63.6% of the non-OSA group was reported to be frequent snorers, and the non-OSA group displayed a higher prevalence of increased overjet, class II occlusion, crowding, and posterior crossbite when 79  compared with epidemiological data of the general population of similar age, both suggesting that there may be a lack of a true control sample in the current study.    Finally, diagnosis of dentofacial morphology was established using clinical examination only, which is relatively subjective. Although the addition of radiograph imaging such as lateral cephalometry adds an objective way to evaluate the craniofacial features of a patient, it was omitted in this study. Two recent systematic reviews were conducted and a total of 14 studies that examined the craniofacial morphology of children with OSA using imaging (lateral cephalometry and MRI) were evaluated 36,135. Although children with OSA had statistically significant differences from children without OSA, these differences were not of clinical significance. Diagnosis of an abnormality of craniofacial morphology is always done using a clinical examination first, with radiography imaging as a supplement only when the diagnosis from the clinical examination indicates an abnormality. There appears to be no indication and/or justification for radiation exposure for OSA children as a screening tool for abnormal craniofacial morphology, and the result of this study supports this. Furthermore, an orthodontic clinical examination has been shown to have strong intra-and inter-observer reliability74,136; similar intra-observer reliability was shown with the current study.  80  Chapter 5: Potential Future Studies An increase in sample size would be the most important area of improvement for a future study. A larger sample size will not only provide more power in the statistics to distinguish true differences between groups, but also provide greater diversity of the included sample. Specifically, it was demonstrated that children with craniofacial syndromes such as Down Syndrome display a different dentofacial morphology and have high prevalence of OSA. This population should be separated from the rest of the patient pool in order to study if different craniofacial syndromes and phenotypes have different relative risks for OSA; a larger sample is needed to achieve this.   Alternatively, another way to increase the power of the study is to be more specific in our sample selection and in the number variable we choose to test in the future study. For example, instead of evaluating more than 40 different variables of dentofacial morphology, the future study should be limited to 5 most important variables, such as convex profile and/or retrognathic mandible, posterior crossbite, class II dental and skeletal occlusion, overbite, and dental crowding, as suggested by literature review and the result of the current study. Furthermore, we may also consider limiting the included sample to narrower age and ethnicity group to reduce the amount of confounding factors. This would make it possible to discern any differences between groups with statistical confidence using a smaller sample size.  Since the sample population future study will compose of patients who are referred to the children’s hospital for overnight, in-laboratory PSG study, some of these patients may be referred because they show signs of recurrent or residual disease after they have received 81  treatment. These patients may have different etiology responsible for their OSA disease, and it will be worthwhile to separate them from the rest of the population and analyze them independently.    A true control group would be one of the most important additions needed for the future studies, but could also be one of the most difficult to achieve. As mentioned, PSG laboratories are few in number and require highly specialized personnel to administer, score, and interpret the studies. It is difficult to justify using this resource on healthy children when there are many children with signs and symptoms waiting to be diagnosed.   Objective measurement of dentofacial morphology is another improvement that could be implemented to future studies. Ideally, the measurement should be valid, reproducible, and minimally invasive. Additionally, since the target sample population is children, it should also be easy and quick to conduct to reduce the burden of care for the children and their parents. One possibility of such measurement method is digital photography126,128,132. It is ubiquitously available today, it imposes no harm to the patient, and the procedure can be done within minutes. It could be added to aid in the diagnosis of facial proportions and facial profile.  Finally, since there will be children in whom orthodontic treatment may improve their OSA, there is a need for future studies to allow better evaluation of orthodontic treatment need in children with OSA. Specifically, there is a need for an orthodontic treatment need index that could be used by the non-dental health care professionals. This would allow children with OSA who display an altered dentofacial morphology to be readily identified and referred for proper 82  treatment. Furthermore, more studies are needed to determine how many children are eligible for maxillary expansion treatment and mandibular advancement treatment, and the effectiveness of these treatment in reducing the signs and symptoms of children with OSA.   83  Chapter 6: Conclusions 1. In the sample population of 39 children between ages 4-16 who were referred to BCCH for an overnight sleep study, there were no significant difference in the dentofacial morphology between OSA children and those without OSA.   2. It is likely that children with OSA have a highly variable presentation of anatomical features, and future studies with a larger sample size and a true control group is needed to establish the dentofacial morphology of this population. 3. The 17 children who were diagnosed with craniofacial syndromes displayed a dolichocephalic face type, convex profile, retrognathic mandible and posterior crossbite. 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Overjet (mm) 94  Appendix A Appendix A   A.1 Prevalence of posterior crossbite in the current study compared with that reported in the literature.     8.0% 9.1% 22.2% 0.0% 2.4% 12.2% 12.2% 12.9% 28.3% 16.7% 55.0% 0.0% 30.0% Control Control2 LowerAHIHigherAHIControl Snorer OSA Control SDB SDB2 OSA Control SDBNHANESIIILee 2015 Pirilä-Parkkinen  2009 Ikävalko  2012 Sauer 2012 Carvalho 2014Posterior Crossbite 95  A.2 Prevalence of anterior openbite in the current study compared with that reported in the literature.    3.6% 9.1% 12.5% 0.0% 0.0% 12.2% 17.1% 2.4% 6.5% 10.0% 11.1% 0.0% 30.0% ControlControl2Lower AHIHigher AHIControlSnorerOSAControlSDBSDB2OSAControlSDBNHANES III Lee 2015 Pirilä-Parkkinen  2009 Ikävalko  2012 Sauer 2012 Carvalho 2014Anterior Openbite 96  A.3 Prevalence of class II occlusion in the current study compared with that reported in the literature.    15.0% 40.9% 22.2% 25.0% 4.9% 36.6% 29.3% 29.5% 32.6% 33.3% 88.9% 30.0% 42.5% ControlControl2Lower AHIHigher AHIControlSnorerOSAControlSDBSDB2OSAControlSDBNHANES III Lee 2015 Pirilä-Parkkinen  2009 Ikävalko  2012 Sauer 2012 Carvalho 2014Class II molar classification 97  A.4 Prevalence of crowding in the current study compared with that reported in the literature.   25.8% 18.2% 33.3% 12.5% 2.4% 7.3% 17.1% 50.0% 35.0% ControlControl2Lower AHIHigher AHIControlSnorerOSAControlSDBSDB2OSAControlSDBNHANES III Lee 2015 Pirilä-Parkkinen  2009 Ikävalko  2012 Sauer 2012 Carvalho 2014crowding 98  A.5 Prevalence of some dentofacial morphology in the non-OSA group compared with the general population using data from epidemiology studies.   40.9% 36.4% 18.2% 45.5% 9.1% 9.1% 25.4% 8.9% 16.9% 6.9% 18.9% 44.3% 17.5% 23.2% 8.8% 6.7% 10.5% 19.7% 13.1% 7.9% 6.1% 14.3% 46.2% 8.2% 17.7% 15.0% 19.1% 25.8% 53.9% 8.0% 3.6% 36.2% 29.7% 13.0% 16.6% 5.9% 2.4% Class II molarclassificationIncreased OJ crowding Deepbite Posterior Crossbite AOBPrevalence of Malocclusion of control group vs. general population Lee 2015 (4-16yo) Karaiskos 2006 (6yo) Karaiskos 2006 (9yo)Carvalho 2011 (5-6yo) Tausche 2004 (6-17yo) NHANES III (8-17yo) Prabhakar 2014 (7-13yo)

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