Use of Flow–Volume Curves to Predict Oral Appliance Treatment Outcome in Obstructive Sleep Apnea

AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE VOL 175 2007

1 Centre for Sleep Health and Research, Department of Respiratory Medicine, Royal North Shore Hospital, University of Sydney, Sydney, Australia;2 Department of Respiratory and Sleep Medicine, St. George Hospital, University of New South Wales, Sydney, Australia;3 Discipline of Orthodontics, Sydney Dental Hospital, University of Sydney, Sydney, Australia;4 Department of Statistics, Macquarie University, Sydney, Australia;and 5 Woolcock Institute of Medical Research, Sydney, Australia

Background: It has been recognized that mandibular advancement splint (MAS) treatment is effective in some, but not all, patients
with obstructive sleep apnea (OSA). Hence there is a need for a simple and reliable clinical tool to assist in the differentiation of treatment responses. We hypothesized that abnormalities of flow–
volume curves, together with other clinical variables, may have clinical utility in the prediction of MAS treatment outcome.
Methods: Fifty-four patients with known OSA underwent MAS treatment. Expiratory and inspiratory flow–volume curves were measured in the erect and supine positions to derive midinspiratory
flow (MIF50) and the ratio of expiratory to inspiratory flow at 50% of vital capacity (MEF50:MIF50). Multivariable logistic regression was performed to identify additional significant clinical variables in the prediction of treatment outcome.
Results: The mean ( SD) apnea–hypopnea index (AHI) in 35 responders was significantly reduced from 28.9  13.7 to 6.7  5.8/ hour (p  0.001). In 19 nonresponders there was no significant
change in AHI. MIF50 was lower (6.04  1.80 vs. 6.88  1.08 L/ second; p  0.035) and the MEF50:MIF50 ratio was higher (0.82  0.23 vs. 0.61  0.15; p  0.001) in responders than nonresponders.
Logistic regression analysis revealed that the MEF50:MIF50 ratio was the most important predictive factor for MAS treatment outcome, but that body mass index, age, and baseline AHI were also
contributory.
Conclusions: These data suggest that flow–volume curves, in combination with other factors such as body mass index, age, and baseline AHI, may have a useful clinical role in the prediction of treatment outcome with MAS

Complete article   http://ajrccm.atsjournals.org/cgi/reprint/175/7/726.pdf

Randy Clare

Randy Clare

Randy Clare brings to The Sleep and Respiratory Scholar more than 25 years of extensive knowledge and experience in the sleep and pulmonary function field. He has held numerous management positions throughout his career and has demonstrated a unique view of the alternate care diagnostic and therapy model. He is considered by many an expert in the use of a Sleep Bruxism Monitor in a dental office. He is also very involved with physician office spirometry for the early detection of COPD and Asthma

Mr. Clare’s extensive sleep industry experience assists Sleep Scholar in providing current, relevant, data-proven information on sleep diagnostics and sleep therapies that are effective for the treatment of sleep disorders.

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