Main Article Content
Positional sleep apnea, Clustering, Decision tree, Data mining
Study Objectives: Obstructive sleep apnea syndrome (OSAS) is a common sleep disorder that occurs in approximately 5–10% of the general population, and characterized by excessive daytime sleepiness, disruptive snoring, recurrent episodes of apnea or hypopnea and nocturnal hypoxemia. The subtypes of positional OSAS (PPs) are defined by conventional classification determined by the apnea-hypopnea index (AHI). However, there were not enough studies about the classification and characterization of PPs in the literature. The aim of this study is to determine the new subtypes of PPs by data mining algorithms. Methods: The study was admitted by 514 patients with OSAS with 24 attributes which was analysed by K-means clustering, C&RT and CHAID decision tree algorithms by RStudio programming. Chi-square test was used for crossvalidation and Kappa statistics were used to compare the re-evaluated values with classical values. Results: In all methods, two clusters for PPs were obtained and the CHAID algorithm gave us the most accurate results. The value for AHI nodes in CHAID was considered as a cut-off value, and cross-validated with the cut-off value obtained by AUC-ROC analysis with high accuracy (92%). Conclusion: It can be concluded that specific treatments should be developed for new subtypes of PPs considering the centroids of 14 significant attributes.
2. Punjabi, N. M. The epidemiology of adult obstructive sleep apnea. Proc Am Thorac Soc 2008;5(2):136–143.
3. McNicholas WT, Bonsigore MR. Sleep apnoea as an independent risk factor for cardiovascular disease: current evidence, basic mechanisms and research priorities. Eur Respir J 2007;29(1):156-178.
4. Eckert D J, White DP, Jordan AS, Malhotra A, Wellman A. Defining phenotypic causes of obstructive sleep apnea. Identification of novel therapeutic targets. Am J Respir Crit Care Med 2013;188(8):996–1004.
5. Edwards BA, Wellman A, Sands SA, Owens RL, Eckert JD, White DP, et al. Obstructive sleep apnea in older adults is a distinctly different physiological phenotype. Sleep 2014;37(7):1227–1236.
6. Bonsignore MR, Suarez Giron MC, Marrone O, Castrogiovanni A, Montserrat JM. et al. Personalized medicine in sleep respiratory disorders: focus on obstructive sleep apnea diagnosis and treatment. Eur Respir Rev 2017;26(146):170069.
7. Shahar E, Whitney CW, Redline S, Lee ET, Newman AB, Nieto FJ, et al. Sleep-disordered breathing and cardiovascular disease: cross-sectional results of the Sleep Heart Health Study. Am J Respir Crit Care Med 2001;163(1):19–25.
8. Randerath WJ, Verbraecken J, Andreas S, Bettega G, Boudewyns A, Hamans E, et al. European Respiratory Society task force on non-CPAP therapies in sleep apnea. Non-CPAP therapies in obstructive sleep apnea. Eur Respir J 2011;37(5):1000-1028.
9. Joosten SA, O’Driscoll DM, Berger PJ, Hamilton GS. Supine position related obstructive sleep apnea in adults: pathogenesis and treatment. Sleep Med Rev 2014;18(1):7-17.
10. Joosten SA, Hamza K, Sands S, Turton A, Berger P, Hamilton G. Phenotypes of patients with mild to moderate obstructive sleep apnea as confirmed by cluster analysis. Respirology 2012;17(1):99-107.
11. Cartwright RD. Effect of sleep position on sleep apnea severity. Sleep 1984;7(2):110-14
12. Lee CH, Jung HJ, Lee WH, Rhee CS, Yoon IY, Yun PY, et al. The effect of positional dependency on outcomes of treatment with a mandibular advancement device. Arch Otolaryngol Head Neck Surg 2012;138(5):479-483.
13. Sunwoo WS, Hong SL, Kim SW, Park SJ, Han DH, Kim JW, et al. Association between positional dependency and obstruction site in obstructive sleep apnea syndrome. Clin Exp Otorhinolaryngo 2012;5(4):218-21.
14. Kim KT, Cho YW, Kim DE, Hwang SH, Song ML, Motamedi GK. Two subtypes of positional obstructive sleep apnea: supine-predominant and supine-isolated. Clin Neurophysiol 2016;127(1):565-570.
15. Lee SA, Paek JH, Chung YS, Kim WS. Clinical features in patients with positional obstructive sleep apnea according to its subtypes. Sleep Breath 2017;21(1):109-117.
16. Saygin M, Ozturk O, Ozguner MF, Akkaya A, Varol E. Hematological Parameters as Predictors of Cardiovascular Disease in Obstructive Sleep Apnea Syndrome Patients. Angiology 2015;67(5):461-470.
17. Kayatas S, Boza A, Api M, Eroglu M, Arıkan SS. Body composition: A predictive factor of cycle fecundity. Clin Exp Reprod Med 2014;42(2):75-79.
18. National Heart, Lung and Blood Institute. https://www.nhlbi.nih.gov/health/educational/lose_wt/BMI/bmi_dis.htm. Accessed May 5, 2020.
19. Rechtschaffen A, Kales A. A manual of standardized terminology, techniques, and scoring system for sleep stages in human subjects. 1th ed. Los Angeles: UCLA Brain
Information Service/Brain Research Institute US Government Printing Office, 1968.
20. Berry RB, Brooks R, Gamaldo CE, Harding SM, Marcus CL, Vaughn BV. The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology, and Technical Specifications. Darien, Illinois: American Academy of Sleep Medicine 2012;67(3):8-16.
21. Ng Y, Joosten SA, Edwards BA, Turton A, Romios H, Samarasinghe T, et al. The oxygen desaturation index differs significantly between types of sleep software. J Clin Sleep Med 2017;13(4):599–605.
22. Pallayova M, Donic V, Gresova S, Peregrim I, Tomori Z. Do Differences in Sleep Architecture Exist between Persons with Type 2 Diabetes and Nondiabetic Controls? J Diabetes Sci Technol 2010;4(2):344–352.
23. The Report of an American Academy of Sleep Medicine Task Force. Sleep-related breathing disorders in adults: recommendations for syndrome definition and measurement techniques in clinical research. Sleep 1999;22(5):667–689.
24. Oksenberg A, Silverberg DS, Arons E, Radwan H. Positional versus non-positional obstructive sleep apnea patients. Chest 1997;112(3):629–639.
25. Teerapraipruk B, Chirakalwasan N, Simon R, Hirunwiwatkul P, Jaimchariyatam N, Desudchit T, et al. Clinical and polysomnographic data of positional sleep apnea and its predictors. Sleep Breath 2012;16(4):1167-1172.
26. Mo JH, Lee CH, Rhee CS, Yoon IY, Kim JW. Positional dependency in Asian patients with obstructive sleep apnea and its implication for hypertension. Arch Otolaryngol Head Neck Surg 2011;137(8):786-790.
27. Richard W, Kox D, den Herder C, Laman M, van Tinteren H, de Vries N. The role of sleep position in obstructive sleep apnea syndrome. Eur Arch Otorhinolaryngol 2016;263(10):946-950.
28. Lloyd SR, Cartwright RD. Physiologic basis of therapy for sleep apnea. Am Rev Respir Dis 1987;136(2):525-556.
29. George CF, Millar TW, Kryger MH. Sleep apnea and body position during sleep. Sleep 1988;11(1):90-99.
30. Sunnergren O, Brostrom A, Svanborg E. Positional sensitivity as a confounder in diagnosis of severity of obstructive sleep apnea. Sleep Breath 2013;17(1):173-179.
31. Chang ET, Shiao GM. Craniofacial abnormalities in Chinese patients with obstructive and positional sleep apnea. Sleep Med 2008;9(4):403–410.
32. Janssen I, Katzmarzyk PT, Ross R. Waist circumference and not body mass index explains obesity-related health risk. Am J Clin Nutr 2004;79(3):379-384.
33. Mador MJ, Kufel TJ, Magalang UJ, Rajesh SK, Watwe V, Grant BJ. Prevalence of positional sleep apnea in patients undergoing polysomnography. Chest 2005;128(4):2130–2137.
34. Oulhaj A, Al Dhaheri S, Su BB, Al-Houqani M. Discriminating between positional and non-positional obstructive sleep apnea using some clinical characteristics. Sleep Breath 2017;21(4):877-884.