Momany Suleiman M, AlJamal Ghaida, Shugaa-Addin Bassam, Khader Yousef S
Department of Internal Medicine, King Abdullah University Hospital, Jordan University of Science and Technology, Irbid, Jordan.
Faculty of Dentistry, Department of Oral Medicine and Surgery, Jordan University of Science and Technology, Irbid, Jordan.
Am J Med Sci. 2016 Oct;352(4):376-384. doi: 10.1016/j.amjms.2016.07.014. Epub 2016 Aug 5.
To explore the validity of cone beam computed tomography (CBCT) as one of many predictive tools that can be used (alone or in conjunction) to help in identifying high-risk cases of obstructive sleep apnea (OSA) that should get the earliest possible referral to a sleep specialist for standard diagnostic polysomnography, and to identify imaging airway parameters that may be predictive of OSA severity.
Using a case-control design, 45 subjects matched by age and sex (22 OSA cases and 23 controls) were included in this study. Subjects were assigned as cases depending on a sleep study with apnea-hypopnea index (AHI)>5 and as controls depending on a Berlin questionnaire score identifying low risk or no risk of OSA. All subjects had CBCT scans. Airway and craniofacial parameters as assessed by CBCT were compared between the 2 groups. Significant CBCT variables were entered into a logistic regression model to identify risk factors of OSA and the correlations of variables with AHI were evaluated using multiple linear regression. For all tests P ≤ 0.05 was considered statistically significant.
OSA cases had larger body mass index and neck circumference than controls. OSA cases showed significantly smaller airway narrowest cross-sectional areas (CSAs) (P < 0.05) and larger posterior nasal spine and the second cervical vertebrae distances (P < 0.001) than those in controls. Airway narrowest CSA showed a significant negative correlation with AHI (r = -0.653, P = 0.001) and was a significant variable for predicting the AHI of OSA cases in multiple regression analysis.
The importance of the narrowest CSA and posterior nasal spine and the second cervical vertebrae distance in the pathogenesis of OSA has been highlighted in the present study. We can conclude that CBCT can provide findings that entail earlier referral of suspected patients with OSA for further assessment.
探讨锥形束计算机断层扫描(CBCT)作为众多预测工具之一(单独使用或联合使用)的有效性,以帮助识别阻塞性睡眠呼吸暂停(OSA)的高危病例,这些病例应尽早转诊至睡眠专科医生处进行标准诊断性多导睡眠图检查,并识别可能预测OSA严重程度的影像学气道参数。
采用病例对照设计,本研究纳入了45名年龄和性别匹配的受试者(22例OSA病例和23例对照)。根据呼吸暂停低通气指数(AHI)>5的睡眠研究将受试者分配为病例组,根据柏林问卷评分确定为OSA低风险或无风险的受试者作为对照组。所有受试者均接受了CBCT扫描。比较两组之间通过CBCT评估的气道和颅面参数。将具有显著意义的CBCT变量纳入逻辑回归模型以识别OSA的危险因素,并使用多元线性回归评估变量与AHI的相关性。对于所有测试,P≤0.05被认为具有统计学意义。
OSA病例的体重指数和颈围均大于对照组。与对照组相比,OSA病例的气道最窄横截面积(CSA)显著更小(P<0.05),后鼻棘与第二颈椎的距离更大(P<0.001)。气道最窄CSA与AHI呈显著负相关(r=-0.653,P=0.001),并且在多元回归分析中是预测OSA病例AHI的显著变量。
本研究强调了最窄CSA以及后鼻棘与第二颈椎距离在OSA发病机制中的重要性。我们可以得出结论,CBCT能够提供相关结果,从而促使疑似OSA患者更早转诊以进行进一步评估。