Indian Journal of Sleep Medicine

Register      Login

VOLUME 7 , ISSUE 2 ( April-June, 2012 ) > List of Articles


Predictive Morphometric Model Value Estimation and its Correlation with Severity of Obstructive Sleep Apnoea in a Mixed Indian Population: A Pilot Study

MS Barthwal, B Jayan, Oommen Nainan, SS Chopra, M Mukherjee

Keywords : apnoea/hypopnoea index, clinical rule, morphometric model, polysomnography, predictors,Obstructive sleep apnoea

Citation Information : Barthwal M, Jayan B, Nainan O, Chopra S, Mukherjee M. Predictive Morphometric Model Value Estimation and its Correlation with Severity of Obstructive Sleep Apnoea in a Mixed Indian Population: A Pilot Study. Indian Sleep Med 2012; 7 (2):48-54.

DOI: 10.5958/j.0973-340X.7.2.011

License: CC BY-SA 4.0

Published Online: 00-06-2012

Copyright Statement:  Copyright © 2012; Jaypee Brothers Medical Publishers (P) Ltd.


Background: The morphometric model (MM) provides a rapid, accurate and reproducible method for predicting whether patients in an ambulatory setting are at risk for obstructive sleep apnoea (OSA). Introduction: The aim of this study was to estimate mean MM scores in a mixed Indian population and to investigate its correlation with the severity of OSA as determined by apnoea/ hypopnoea index (AHI). Materials and Methods: A total of 60 subjects were included in the study and were divided into two groups of 30 subjects each; Group 1: Patient group; Group 2: Control group. A comparative cross-sectional study design was employed and MM value as suggested by Kushida et al. was estimated by applying their clinical rule. To determine the correlation between OSA severity as indicated by AHI and MM values, linear and multiple regression models were applied. Results: The comparison of MM values between OSA and non-OSA groups showed an extremely statistically significant difference. There was no significant correlation between the severity of OSA and MM values in this sample of Indian OSA patients. Conclusions: The results of this study could facilitate the early recognition of OSA and support the available diagnostic setup.

PDF Share
  1. Hoffstein V, Szalai JP. Predictive value of clinical features in diagnosing obstructive sleep apnoea. Sleep 1993; 16: 118–22.
  2. Kushida CA, Efron B, Guilleminault C. A predictive morphometric model for the obstructive sleep apnoea syndrome. Ann Intern Med 1997; 127: 581–7.
  3. Dupont WD, Plummer WD. PS power and sample size program available for free on the Internet. Controlled Clin Trials. 1997; available at:
  4. Revicki DA, Israel RG. Relationship between body mass indices and measures of body adiposity. Am J Public Health 1986; 76: 992–4.
  5. Sayin MO, Turkkahraman H. Comparison of dental arch and alveolar widths of patients with Class II division 1 malocclusion and subjects with Class I ideal occlusion. Angle Orthod 2004; 74: 356–60.
  6. Udwadia ZF, Doshi AV, Lonkar SG, Singh CI. Prevalence of sleep-disordered breathing and sleep apnoea in middleaged urban Indian men. Am J Respir Crit Care Med 2004; 169: 168–73.
  7. Lowe AA, Santamaria JD, Fleetham JA, Price C. Facial morphology and obstructive sleep apnea. Am J Orthod Dentofac Orthop 1986; 90: 484–9.
  8. Jayan B, Prasad BNBM, Kotwal A, Kharbanda OP, Roy Chowdhury SK, Gupta SH. The role of cephalometric analysis in obese and non obese urban Indian adults with obstructive sleep apnea syndrome: A Pilot Study. Indian J Sleep Med 2007; 2.2: 59–63.
  9. Richard WW Lee, Andrew SL Chan, Ronald R Grunstein, Peter A Cistulli. Craniofacial phenotyping in obstructive sleep apnoea – A novel quantitative photographic approach. Sleep 2009; 32(1): 37–45.
  10. Ethan M Balk, Denish Moorthy, Ndidiamaka Obadan, et al. Diagnosis and treatment of obstructive sleep apnea in adults. Comparative effectiveness review. Number 32. Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services, Rockville; 2011.
  11. Sharma SK, Malik V, Vasudev C, et al. Prediction of obstructive sleep apnea in patients presenting to a tertiary care center. Sleep Breath 2006; 10: 147–54.
  12. Soares MCM, Bittencourt LR, Zonato AL, Gregorio LC. Application of the Kushida morphometric model in patients with sleep-disordered breathing. Rev Bras Otorrinolaringol 2006; 72(4): 541–8.
  13. Dae Gun Jung, Hae Young Cho, Ronald R Grunstein, Brendon Yee. Predictive value of Kushida Index and acoustic pharyngometry for the evaluation of upper airway in subjects with or without obstructive sleep apnea. J Korean Med Sci 2004; 19: 662–7.
  14. Santoro M, Galkin S, Teredesai M, Nicolay OF, Cangialosi TJ. Comparison of measurements made on digital and plaster models. Am J Orthod Dentofac Orthop 2003; 124: 101–5.
  15. Singh SP, Goyal A. Mesiodistal crown dimensions of the permanent dentition in North Indian children. J Indian Soc Pedod Prev Dent 2006; 24: 192–6.
  16. Knott VB. Longitudinal study of dental arch widths at four stages of dentition. Angle Orthod 1972; 42: 387–94.
PDF Share

© Jaypee Brothers Medical Publishers (P) LTD.