Analysis of imaging features of upper airway in obstructive sleep apnea patients with epiglottic collapse
10.3760/cma.j.cn115330-20250104-00008
- VernacularTitle:伴会厌塌陷阻塞性睡眠呼吸暂停患者的上气道影像学特征分析
- Author:
Ying ZHANG
1
;
Zhenyuan WEI
;
Xunyan OU
;
Yunxiu WANG
;
Zhihong LIN
;
Di ZHAO
Author Information
1. 浙江大学医学院附属第二医院耳鼻咽喉科，杭州 310000
- Publication Type:Journal Article
- Keywords:
Sleep apnea,Obstructive;
Epiglottic collapse;
Computerized tomography
- From:
Chinese Journal of Otorhinolaryngology Head and Neck Surgery
2025;60(9):1119-1126
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze and summarize the characteristics and rules of upper airway computerized tomography (CT) in obstructive sleep apnea (OSA) patients with epiglottic collapse.Methods:As a cross-sectional study, OSA patients (all were male, aged 18 to 60) who received Han-uvulopalatopharyngoplasty (H-UPPP) surgery at Second Affiliated Hospital of Zhejiang University School of Medicine from April 2023 to February 2024 were continuously selected. All patients underwent physical examination, polysomnography (PSG) and three-dimensional CT plain scan of upper airway before surgery. Preoperative drug-induced sleep endoscopy (DISE) was performed on the day of surgery. According to the findings of DISE, all patients were divided into two groups: epiglottic collapse group and non-epiglottic collapse group. The relevant data were collected, and the measured data included epiglottic length, epiglottic width, epiglottic curvature, epiglottic angle, distance between epiglottis and posterior pharyngeal wall, distance between epiglottis and tongue base, angle between epiglottis and tongue base, the lymph tissue classification of the tongue base, airway length, mandibular - hyoid bone distance, soft palate length and soft palate - hard palate Angle. Statistical analysis was performed using SPSS 25.0.Results:There were a total of 104 patients with OSA, consisting of 27 patients with epiglottic collapse and 77 patients with non-epiglottic collapse. In this study, the incidence of epiglottic collapse was 25.96%. There were no significant differences in apnea hyponea index (AHI), minimum blood oxygen saturation and the time ratio of blood oxygen saturation below 90% (TS90) between the two groups (all P>0.05). Compared with the non-epiglottic collapse group, the epiglottic length [(19.77±2.42)mm vs. (18.54±2.62)mm, t=2.162, P=0.033] and the lymph tissue classification of the tongue base [4(1,4) vs.2(1,3), Z=-2.968, P=0.003] in the epiglottic collapse group increased. Distance between epiglottis and tongue base reduced [2.70(0,5.88) mm vs. 5.45(2.15,6.98)mm, Z=-2.385, P=0.017]. According to Logistic regression analysis, epiglottic collapse and epiglottic width ( OR: 1.201; 95% CI: 1.009-1.430, P=0.039) were positively correlated, epiglottic curvature ( OR: 0.979; 95% CI: 0.961-0.998, P=0.030) was negatively correlated, and with the grade of lymph tissue of tongue root ( OR: 1.936; 95% CI: 1.294-2.896, P=0.001) was positively correlated. Conclusion:CT examination in awake OSA patients with epiglottic collapse can reveal its characteristic indicators. The wider the epiglottic width, the smaller the epiglottic curvature, and the larger the lymph tissue grade of the base of tongue were effective predictors of epiglottic collapse.
