Indian Journal of Sleep Medicine

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

ORIGINAL ARTICLE

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.


Abstract

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.


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