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ARTICLE

A Predictive Morphometric Model for the Obstructive Sleep Apnea Syndrome

Clete A. Kushida, MD, PhD; Bradley Efron, PhD; and Christian Guilleminault, MD

15 October 1997 | Volume 127 Issue 8 Part 1 | Pages 581-587

Background: Mathematical formulas have been used to clinically predict whether patients will develop the obstructive sleep apnea syndrome (OSAS). However, these models do not take into account the disproportionate craniofacial anatomy that accompanies OSAS independently of obesity.

Objective: To determine the accuracy of a morphometric model, which combines measurements of the oral cavity with body mass index and neck circumference, in predicting whether a patient has OSAS.

Design: 6-month prospective study.

Setting: University-based tertiary referral sleep clinic and research center.

Participants: 300 consecutive patients evaluated for sleep disorders for the first time.

Measurements: Body mass index, neck circumference, and oral cavity measurements were obtained, and a model value was calculated for each patient. Polysomnography was used to determine the number of abnormal respiratory events that occurred during sleep. Sleep apnea was defined as more than five episodes of apnea or hypopnea per hour of sleep.

Results: The morphometric model had a sensitivity of 97.6% (95% CI, 95% to 98.9%), a specificity of 100% (CI, 92% to 100%), a positive predictive value of 100% (CI, 98.5% to 100%), and a negative predictive value of 88.5% (CI, 77% to 96%). No significant discrepancies were revealed in tests of intermeasurer and test-retest reliability.

Conclusions: The morphometric model provides a rapid, accurate, and reproducible method for predicting whether patients in an ambulatory setting have OSAS. The model may be clinically useful as a screening tool for OSAS rather than as a replacement for polysomnography.

Author and Article Information

From Stanford University, Stanford, California.
Acknowledgments: The authors thank Rolfe LaForge, PhD, for his contribution to the statistical analyses; Anstella Robinson, MD, for her contribution to the interrater reliability measurements; and Ann Mack, Julianne Lemons, Evangeline Roldan-Fong, Ray Kubisiak, Mike Bilberry, Doug Yost, Lars Black, and Angela Giacomini for technical assistance.
Grant Support: In part by grants NIA AG07772 and NIA AG00164-07 from the National Institutes of Health.
Requests for Reprints: Clete A. Kushida, MD, PhD, Stanford University Sleep Disorders Clinic and Research Center, 401 Quarry Road, Suite 3301-A, Stanford, CA 94305-5730.
Current Author Addresses: Drs. Kushida and Guilleminault: Stanford University Sleep Disorders Clinic and Research Center, 401 Quarry Road, Suite 3301-A, Stanford, CA 94305-5730.

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