Upper Airway Areas, Volumes, and Linear Measurements Determined on Computed Tomography During Different Phases of Respiration Predict the Presence of Severe Obstructive Sleep Apnea.

Autor:	Chousangsuntorn K; Biomedical Engineer, Department of Radiological Technology, Faculty of Medical Technology, Mahidol University, Phutthamonthon, Nakhon Pathom, Thailand., Bhongmakapat T; Assistant Professor, Department of Otolaryngology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand., Apirakkittikul N; Otolaryngologist, Department of Otolaryngology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand., Sungkarat W; Biomedical Engineer, Department of Radiology and Advanced Diagnostic Imaging Center, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand., Supakul N; Assistant Professor, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Riley Hospital for Children, Indianapolis, IN., Laothamatas J; Professor, Advanced Diagnostic Imaging Center and Chakri Naruebodindra Medical Institute, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand. Electronic address: laothamatas@gmail.com.
Jazyk:	angličtina
Zdroj:	Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons [J Oral Maxillofac Surg] 2018 Jul; Vol. 76 (7), pp. 1524-1531. Date of Electronic Publication: 2017 Dec 09.
DOI:	10.1016/j.joms.2017.11.041
Abstrakt:	Purpose: The objective of this study was to analyze the potential of using low-dose volumetric computed tomography (CT) during different phases of respiration for identifying patients likely to have severe obstructive sleep apnea (OSA), defined as a respiratory disturbance index (RDI) higher than 30. Patients and Methods: A prospective study was undertaken at the Ramathibodi Hospital (Bangkok, Thailand). Patients with diagnosed OSA (N = 82) were recruited and separated into group 1 (RDI, ≤30; n = 36) and group 2 (RDI, >30; n = 46). The 2 groups were scanned by low-dose volumetric CT while they were 1) breathing quietly, 2) at the end of inspiration, and 3) at the end of expiration. Values for CT variables were obtained from linear measurements on lateral scout images during quiet breathing and from the upper airway area and volume measurements were obtained on axial cross-sections during different phases of respiration. All CT variables were compared between study groups. A logistic regression model was constructed to calculate a patient's likelihood of having an RDI higher than 30 and the predictive value of each variable and of the final model. Results: The minimum cross-sectional area (MCA) measured at the end of inspiration (cutoff point, ≤0.33 cm 2 ) was the most predictive variable for the identification of patients likely to have an RDI higher than 30 (adjusted odds ratio [OR] = 5.50; 95% confidence interval [CI], 1.76-17.20; sensitivity, 74%; specificity, 72%,), followed by the MCA measured at the end of expiration (cutoff point, ≤0.21 cm 2 ; adjusted OR = 3.28; 95% CI, 1.05-10.24; sensitivity, 70%; specificity, 68%). Conclusion: CT scanning at the ends of inspiration and expiration helped identify patients with an RDI higher than 30 based on measurement of the MCA. Low-dose volumetric CT can be a useful tool to help the clinician rapidly identify patients with severe OSA and decide on the urgency to obtain a full-night polysomnographic study and to start treatment. (Copyright © 2018. Published by Elsevier Inc.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu