Revision of Estimation Method for an Established Morphometric Model for Prediction of Obstructive Sleep Apnea: A Pilot Study
|Oommen Nainan1*, Jayan B2, Chopra SS3 and Mukherjee M4|
|1 Graded Specialist-Orthodontics & Dentofacial Orthopedics, Naval Institute of Dental Sciences, India|
|2 Department of Dental Surgery, Armed Forces Medical College, India|
|3 Classified Specialist-Orthodontics & Dentofacial Orthopedics, Corps Dental Unit, India|
|4 Classified Specialist-Periodontology, Military Dental centre, India|
|Corresponding Author :||Oommen Nainan
Graded Specialist-Orthodontics & Dentofacial Orthopedics
Naval Institute Of Dental Sciences
INHS Asvini Campus
Colaba, Mumbai 400005, Maharashtra, India
E-mail: [email protected]
|Received February 20, 2014; Accepted February 22, 2014; Published February 24, 2014|
|Citation: Nainan O, Jayan B, Chopra SS, Mukherjee M (2014) Revision of Estimation Method for an Established Morphometric Model for Prediction of Obstructive Sleep Apnea: A Pilot Study. J Sleep Disord Ther 3:156 doi:10.4172/2167-0277.1000156|
|Copyright: © 2014 Nainan O, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.|
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 apnea (OSA).
Introduction: The aim of this study was to estimate mean MM scores in a mixed Indian population and to test a
revision of the method for making intraoral measurements.
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 was estimated by applying their clinical rule. The measurements in our study were
made on study models to ensure precise and accurate measurement of these anatomic distances, thus ensuring a
greater accuracy for the morphometric model.
Results: The comparison of morphometric model values between OSA and non OSA groups showed an
extremely statistically significant difference. The average predictive morphometric model value for OSA in this
sample of Indian patients is only slightly lesser than that observed by Kushida
Conclusions: The results of this study could facilitate the early recognition of OSA and support the available
diagnostic setup. This revised methodology may be used to widen the reach of the morphometric model from the
sleep physician’s clinic to the Dental operatory.