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计算机断层扫描对阻塞性睡眠呼吸暂停的特征描述及与多导睡眠图的比较用于评估

Computed Tomography Characterization and Comparison With Polysomnography for Obstructive Sleep Apnea Evaluation.

作者信息

Chousangsuntorn Khaisang, Bhongmakapat Thongchai, Apirakkittikul Navarat, Sungkarat Witaya, Supakul Nucharin, Laothamatas Jiraporn

机构信息

Biomedical Engineer, Department of Radiological Technology, Faculty of Medical Technology, Mahidol University, Phutthamonthon, Nakhon Pathom, Thailand.

Assistant Professor, Department of Otolaryngology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.

出版信息

J Oral Maxillofac Surg. 2018 Apr;76(4):854-872. doi: 10.1016/j.joms.2017.09.006. Epub 2017 Sep 12.

Abstract

PURPOSE

We hypothesized that computed tomography (CT) combined with portable polysomnography (PSG) might better visualize anatomic data related to obstructive sleep apnea (OSA). The present study evaluated the CT findings during OSA and assessed their associations with the PSG data and patient characteristics.

PATIENTS AND METHODS

We designed a prospective cross-sectional study of patients with OSA. The patients underwent scanning during the awake state and apneic episodes. Associations of the predictor variables (ie, PSG data, respiratory disturbance index [RDI]), patient characteristics (body mass index [BMI], neck circumference [NC], and waist circumference [WC]), and outcome variables (ie, CT findings during apneic episodes) were assessed using logistic regression analysis. The CT findings during apneic episodes were categorized regarding the level of obstruction, single level (retropalatal [RP] or retroglossal [RG]) or multilevel (mixed RP and RG), degree of obstruction (partial or complete), and pattern of collapse (complete concentric collapse [CCC] or other patterns).

RESULTS

A total of 58 adult patients with OSA were scanned. The mean ± standard deviation for the RDI, BMI, NC, and WC were 41.6 ± 28.55, 27.80 ± 5.43 kg/m, 38.3 ± 4.3 cm, and 93.8 ± 13.6 cm, respectively. No variables distinguished between the presence of single- and multilevel airway obstruction in the present study. A high RDI (≥30) was associated with the presence of complete obstruction and CCC (odds ratio 6.33, 95% confidence interval 1.55 to 25.90; and odds ratio 3.77, 95% confidence interval 1.02 to 13.91, respectively) compared with those with a lesser RDI.

CONCLUSIONS

An increased RDI appears to be an important variable for predicting the presence of complete obstruction and CCC during OSA. Scanning during apneic episodes, using low-dose volumetric CT combined with portable PSG provided better anatomic and pathologic findings of OSA than did scans performed during the awake state.

摘要

目的

我们推测计算机断层扫描(CT)结合便携式多导睡眠监测(PSG)可能能更好地显示与阻塞性睡眠呼吸暂停(OSA)相关的解剖学数据。本研究评估了OSA患者的CT表现,并评估了这些表现与PSG数据及患者特征之间的关联。

患者与方法

我们设计了一项针对OSA患者的前瞻性横断面研究。患者在清醒状态和呼吸暂停发作期间接受扫描。使用逻辑回归分析评估预测变量(即PSG数据、呼吸紊乱指数[RDI])、患者特征(体重指数[BMI]、颈围[NC]和腰围[WC])与结果变量(即呼吸暂停发作期间的CT表现)之间的关联。呼吸暂停发作期间的CT表现根据阻塞水平(单水平[腭后[RP]或舌后[RG]]或多水平[混合RP和RG])、阻塞程度(部分或完全)以及塌陷模式(完全同心塌陷[CCC]或其他模式)进行分类。

结果

共对58例成年OSA患者进行了扫描。RDI、BMI、NC和WC的平均值±标准差分别为41.6±28.55、27.80±5.43kg/m²、38.3±4.3cm和93.8±13.6cm。在本研究中,没有变量能够区分单水平和多水平气道阻塞的存在情况。与RDI较低的患者相比,高RDI(≥30)与完全阻塞和CCC的存在相关(优势比分别为6.33,95%置信区间为1.55至25.90;以及优势比为3.77,95%置信区间为1.02至13.91)。

结论

RDI升高似乎是预测OSA期间完全阻塞和CCC存在的一个重要变量。与清醒状态下的扫描相比,在呼吸暂停发作期间使用低剂量容积CT结合便携式PSG进行扫描能提供更好的OSA解剖学和病理学表现。

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