Orthodontic interventions as a management option for children with residual obstructive sleep apnea: a cohort study protocol

Nathalia Carolina Fernandes Fagundes, Arnaldo Perez-Garcia, Daniel Graf, Carlos Flores-Mir, Giseon Heo, Nathalia Carolina Fernandes Fagundes, Arnaldo Perez-Garcia, Daniel Graf, Carlos Flores-Mir, Giseon Heo

Abstract

Introduction: Obstructive sleep apnoea (OSA) is a sleep-breathing disorder that seems likely to have long-term negative social and health consequences in children and adolescents. There are no established standard management approaches when the first line of therapy, the tonsillectomy and adenoidectomy (T&A), is not indicated or fails to address paediatric OSA (residual paediatric OSA). This protocol describes a prospective cohort study that aims to assess the effectiveness of orthodontic interventions for managing residual paediatric OSA in patients with concomitant craniofacial issues.

Methods and analysis: Children aged 6-16 years who with an OSA diagnosis and did not benefit from previous T&A or qualified for T&A will be recruited. Orthodontic intervention(s), when adequately indicated (maxillary expansion, mandibular advancement or maxillary complex advancement with skeletal anchored headgear), and a control (orthodontic intervention declined) cohorts will be involved. A sample size of 70 participants (n=35 per cohort) is planned. Effectiveness data will be assessed through nocturnal polysomnography, a craniofacial index, sleep questionnaires and medical records. Additionally, the association of residual OSA and two comorbidities, obesity and asthma, will be investigated through assessing blood, urine and saliva metabolites. The changes on body mass index will also be investigated as a secondary outcome. Other additional outcomes, including association between residual paediatric OSA and periodic limbs movement, restless leg syndrome, insomnia, and the use of abiometric shirt to sleep monitoring purposes will also be considered. All participants will be followed up for 12 months after treatment allocation. The effectiveness of the intervention will be analysed by the assessment of sleep parameters, medical history (from medical chart reviews), questionnaire responses, craniofacial characteristics and metabolomic markers using an algorithm to be developed.

Ethics and dissemination: This study was approved by the Health Research Ethics Board-Health Panel, University of Alberta, Edmonton, Canada (Pro00084763). The findings will be shared with scientific and patient content-specific social network communities to maximise their impact on clinical practice and future research in the study topic.

Trial registration number: NCT03821831; Pre-results.

Keywords: paediatric otolaryngology; respiratory medicine (see thoracic medicine); sleep medicine.

Conflict of interest statement

Competing interests: None declared.

© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

References

    1. Guilleminault C, Tilkian A, Dement WC. The sleep apnea syndromes. Annu Rev Med 1976;27:465–84. 10.1146/annurev.me.27.020176.002341
    1. Bixler EO, Vgontzas AN, Lin H-M, et al. . Sleep disordered breathing in children in a general population sample: prevalence and risk factors. Sleep 2009;32:731–6. 10.1093/sleep/32.6.731
    1. Chang SJ, Chae KY. Obstructive sleep apnea syndrome in children: epidemiology, pathophysiology, diagnosis and sequelae. Korean J Pediatr 2010;53:863–71. 10.3345/kjp.2010.53.10.863
    1. Sánchez T, Castro-Rodríguez JA, Brockmann PE. Sleep-Disordered breathing in children with asthma: a systematic review on the impact of treatment. J Asthma Allergy 2016;9:83–91. 10.2147/JAA.S85624
    1. Kheirandish-Gozal L, Gozal D. Genotype-Phenotype interactions in pediatric obstructive sleep apnea. Respir Physiol Neurobiol 2013;189:338–43. 10.1016/j.resp.2013.03.016
    1. Ng DK, Chan C, Chow AS, et al. . Childhood sleep-disordered breathing and its implications for cardiac and vascular diseases. J Paediatr Child Health 2005;41:640–6. 10.1111/j.1440-1754.2005.00751.x
    1. Tarasiuk A, Greenberg-Dotan S, Simon-Tuval T, et al. . Elevated morbidity and health care use in children with obstructive sleep apnea syndrome. Am J Respir Crit Care Med 2007;175:55–61. 10.1164/rccm.200604-577OC
    1. Jennum P, Rejkjær-Knudsen M, Ibsen R, et al. . Long-Term health and socioeconomic outcome of obstructive sleep apnea in children and adolescents. Sleep Med 2020;75:441–7. 10.1016/j.sleep.2020.08.017
    1. Marcus CL, Brooks LJ, Draper KA, Ward SD, et al. . Diagnosis and management of childhood obstructive sleep apnea syndrome. Pediatrics 2012;130:e714–55. 10.1542/peds.2012-1672
    1. Lee C-H, Hsu W-C, Chang W-H, et al. . Polysomnographic findings after adenotonsillectomy for obstructive sleep apnoea in obese and non-obese children: a systematic review and meta-analysis. Clin Otolaryngol 2016;41:498–510. 10.1111/coa.12549
    1. Brietzke SE, Gallagher D. The effectiveness of tonsillectomy and adenoidectomy in the treatment of pediatric obstructive sleep apnea/hypopnea syndrome: a meta-analysis. Otolaryngol Head Neck Surg 2006;134:979–84. 10.1016/j.otohns.2006.02.033
    1. Huynh NT, Desplats E, Almeida FR. Orthodontics treatments for managing obstructive sleep apnea syndrome in children: a systematic review and meta-analysis. Sleep Med Rev 2016;25:84–94. 10.1016/j.smrv.2015.02.002
    1. Li W, Xiao L, Hu J. The comparison of CPAP and oral appliances in treatment of patients with OSA: a systematic review and meta-analysis. Respir Care 2013;58:1184–95. 10.4187/respcare.02245
    1. Brockbank JC. Update on pathophysiology and treatment of childhood obstructive sleep apnea syndrome. Paediatr Respir Rev 2017;24:21–3. 10.1016/j.prrv.2017.06.003
    1. Fagundes NCF, Flores-Mir C. Pediatric obstructive sleep apnea-Dental professionals can play a crucial role. Pediatr Pulmonol 2021:ppul.25291. 10.1002/ppul.25291
    1. Nazarali N, Altalibi M, Nazarali S, et al. . Mandibular advancement appliances for the treatment of paediatric obstructive sleep apnea: a systematic review. Eur J Orthod 2015;37:618–26. 10.1093/ejo/cju101
    1. Machado AJ, Crespo AN, Pauna HF. Rapid maxillary expansion in pediatric patients with obstructive sleep apnea: current and future perspectives. Sleep Med 2018;51:7–8. 10.1016/j.sleep.2018.06.002
    1. Siriwat R, Wang L, Shah V, et al. . Obstructive sleep apnea and insulin resistance in children with obesity. J Clin Sleep Med 2020;16:1081–90. 10.5664/jcsm.8414
    1. Narayanan A, Yogesh A, Mitchell RB, et al. . Asthma and obesity as predictors of severe obstructive sleep apnea in an adolescent pediatric population. Laryngoscope 2020;130:812–7. 10.1002/lary.28029
    1. Gingras JL, Gaultney JF, Picchietti DL. Pediatric periodic limb movement disorder: sleep symptom and polysomnographic correlates compared to obstructive sleep apnea. J Clin Sleep Med 2011;7:603–9. 10.5664/jcsm.1460
    1. Cho YW, Kim KT, Moon H-J, et al. . Comorbid insomnia with obstructive sleep apnea: clinical characteristics and risk factors. J Clin Sleep Med 2018;14:409–17. 10.5664/jcsm.6988
    1. Delrosso LM, Lockhart C, Wrede JE, et al. . Comorbidities in children with elevated periodic limb movement index during sleep. Sleep 2020;43:zsz221. 10.1093/sleep/zsz221
    1. Rubens SL, Patrick KE, Williamson AA, et al. . Individual and socio-demographic factors related to presenting problem and diagnostic impressions at a pediatric sleep clinic. Sleep Med 2016;25:67–72. 10.1016/j.sleep.2016.06.017
    1. Katz SL, Witmans M, Barrowman N, et al. . Paediatric sleep resources in Canada: the scope of the problem. Paediatr Child Health 2014;19:367–72. 10.1093/pch/19.7.367
    1. Pesonen A-K, Kuula L. The validity of a new Consumer-Targeted wrist device in sleep measurement: an overnight comparison against polysomnography in children and adolescents. J Clin Sleep Med 2018;14:585–91. 10.5664/jcsm.7050
    1. Kirk V, Baughn J, D'Andrea L, et al. . American Academy of sleep medicine position paper for the use of a home sleep apnea test for the diagnosis of OSA in children. J Clin Sleep Med 2017;13:1199–203. 10.5664/jcsm.6772
    1. Lin S-W, Sutherland K, Liao Y-F, et al. . Three-Dimensional photography for the evaluation of facial profiles in obstructive sleep apnoea. Respirology 2018;23:618–25. 10.1111/resp.13261
    1. Boe AJ, McGee Koch LL, O'Brien MK, et al. . Automating sleep stage classification using wireless, wearable sensors. NPJ Digit Med 2019;2:131. 10.1038/s41746-019-0210-1
    1. Zhao MY, Barber T, Cistulli P. Predicting the treatment response of oral appliances for obstructive sleep apnea using computational fluid dynamics and fluid-structure interaction simulations. In: Proceedings of the Asme international mechanical engineering Congress and exposition, 2013. Vol 3a, 2014.
    1. An H-J, Baek S-H, Kim S-W, et al. . Clustering-based characterization of clinical phenotypes in obstructive sleep apnoea using severity, obesity, and craniofacial pattern. Eur J Orthod 2020;42:93–100. 10.1093/ejo/cjz041
    1. Gozal D, Tan H-L, Kheirandish-Gozal L. Treatment of obstructive sleep apnea in children: handling the unknown with precision. J Clin Med 2020;9:888. 10.3390/jcm9030888
    1. Pirelli P, Saponara M, Guilleminault C. Rapid maxillary expansion (RME) for pediatric obstructive sleep apnea: a 12-year follow-up. Sleep Med 2015;16:933–5. 10.1016/j.sleep.2015.04.012
    1. von Elm E, Altman DG, Egger M, et al. . The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med 2007;147:573–7. 10.7326/0003-4819-147-8-200710160-00010
    1. Sateia MJ. International classification of sleep disorders-third edition: highlights and modifications. Chest 2014;146:1387–94. 10.1378/chest.14-0970
    1. Altalibi M, Saltaji H, Roduta Roberts M, et al. . Developing an index for the orthodontic treatment need in paediatric patients with obstructive sleep apnoea: a protocol for a novel communication tool between physicians and orthodontists. BMJ Open 2014;4:e005680. 10.1136/bmjopen-2014-005680
    1. Chervin RD, Hedger K, Dillon JE, et al. . Pediatric sleep questionnaire (PSQ): validity and reliability of scales for sleep-disordered breathing, snoring, sleepiness, and behavioral problems. Sleep Med 2000;1:21–32. 10.1016/S1389-9457(99)00009-X
    1. Stewart MG, Witsell DL, Smith TL, et al. . Development and validation of the nasal obstruction symptom evaluation (nose) scale. Otolaryngol Head Neck Surg 2004;130:157–63. 10.1016/j.otohns.2003.09.016
    1. Owens JA, Spirito A, McGuinn M. The children's sleep habits questionnaire (CSHQ): psychometric properties of a survey instrument for school-aged children. Sleep 2000;23:1043–51.
    1. Varni JW, Seid M, Rode CA. The PedsQL: measurement model for the pediatric quality of life inventory. Med Care 1999;37:126–39. 10.1097/00005650-199902000-00003
    1. Arbuckle R, Abetz L, Durmer JS, et al. . Development of the pediatric restless legs syndrome severity scale (P-RLS-SS): a patient-reported outcome measure of pediatric RLS symptoms and impact. Sleep Med 2010;11:897–906. 10.1016/j.sleep.2010.03.016
    1. Drake C, Nickel C, Burduvali E, et al. . The pediatric daytime sleepiness scale (PDSS): sleep habits and school outcomes in middle-school children. Sleep 2003;26:455-8.
    1. Pion-Massicotte J, Godbout R, Savard P, et al. . Development and validation of an algorithm for the study of sleep using a biometric shirt in young healthy adults. J Sleep Res 2019;28:e12667. 10.1111/jsr.12667
    1. McCann JR, Bihlmeyer NA, Roche K, et al. . The pediatric obesity microbiome and metabolism study (POMMS): methods, baseline data, and early insights. Obesity 2021;29:569–78. 10.1002/oby.23081
    1. Tao J-L, Chen Y-Z, Dai Q-G, et al. . Urine metabolic profiles in paediatric asthma. Respirology 2019;24:572–81. 10.1111/resp.13479
    1. Bouatra S, Aziat F, Mandal R, et al. . The human urine metabolome. PLoS One 2013;8:e73076. 10.1371/journal.pone.0073076
    1. Psychogios N, Hau DD, Peng J, et al. . The human serum metabolome. PLoS One 2011;6:e16957. 10.1371/journal.pone.0016957
    1. Dame ZT, Aziat F, Mandal R, et al. . The human saliva metabolome. Metabolomics 2015;11:1864–83. 10.1007/s11306-015-0840-5
    1. Nowak N, Engler A, Thiel S, et al. . Validation of breath biomarkers for obstructive sleep apnea. Sleep Med 2021;85:75–86. 10.1016/j.sleep.2021.06.040
    1. Li S, ed. Computational Methods and Data Analysis for Metabolomics. New York, NY: Springer US, 2020.
    1. Shelgikar AV, Anderson PF, Stephens MR. Sleep tracking, wearable technology, and opportunities for research and clinical care. Chest 2016;150:732–43. 10.1016/j.chest.2016.04.016
    1. Heo G, Leonard K, Wang X. Interdisciplinary Approaches to Automated Obstructive Sleep Apnea Diagnosis Through High-Dimensional Multiple Scaled Data Analysis. In: Gasparovic E, Domeniconi C, eds. Research in data science. Association for women in mathematics series. Cham: Springer, 2019: 81–107.
    1. Su P, Ding X-R, Zhang Y-T. Long-Term blood pressure prediction with deep recurrent neural networks.
    1. Szegedy C, Vanhoucke V, Ioffe S. Rethinking the inception architecture for computer vision.
    1. Sucar LE. Probabilistic graphical models. London: Springer London, 2015.
    1. MacDonald IL, Langrock R, Zucchini W. Hidden Markov Models for Time Series: An Introduction Using R. Second Edi. Chapman and Hall/CRC, 2009.
    1. Carvalho FR, Lentini-Oliveira DA, Prado LB, et al. . Oral appliances and functional orthopaedic appliances for obstructive sleep apnoea in children. Cochrane Database Syst Rev 2016;10:Cd005520. 10.1002/14651858.CD005520.pub3
    1. Watach AJ, Xanthopoulos MS, Afolabi-Brown O, et al. . Positive airway pressure adherence in pediatric obstructive sleep apnea: a systematic scoping review. Sleep Med Rev 2020;51:101273. 10.1016/j.smrv.2020.101273
    1. Won CHJ,. When will we ditch the AHI? J Clin Sleep Med 2020;16:1001–3. 10.5664/jcsm.8594
    1. Gulotta G, Iannella G, Vicini C, et al. . Risk factors for obstructive sleep apnea syndrome in children: state of the art. Int J Environ Res Public Health 2019;16:3235. 10.3390/ijerph16183235
    1. Hoffman JM, Lyu Y, Pletcher SD, et al. . Proteomics and metabolomics in ageing research: from biomarkers to systems biology. Essays Biochem 2017;61:379–88. 10.1042/EBC20160083

Source: PubMed

Sponsor e collaboratori

Condizioni mediche

Interventi farmacologici

3
Sottoscrivi