Liu Bingchuan, Song Yanan, Liu Kaixi, Zhou Fang, Ji Hongquan, Tian Yun, Han Yong Zheng
Department of Orthopaedics, Peking University Third Hospital, Beijing, China.
Beijing Key Laboratory of Spinal Disease Research, Beijing, China.
BMC Anesthesiol. 2020 Sep 17;20(1):238. doi: 10.1186/s12871-020-01153-0.
We aimed to distinguish the preoperative radiological indicators to predict the application of assistant techniques during intubation for patients undergoing selective cervical surgery.
A total of 104 patients were enrolled in this study. According to whether intubation was successfully accomplished by simple Macintosh laryngoscopy, patients were divided into Macintosh laryngoscopy group (n = 78) and Assistant technique group (n = 26). We measured patients' radiographical data via their preoperative X-ray and MRI images, and compared the differences between two groups. Binary logistic regression model was applied to distinguish the meaningful predictors. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to describe the discrimination ability of indicators. The highest Youden's index corresponded to an optimal cut-off value.
Ten variables exhibited significant statistical differences between two groups (P < 0.05). Based on logistic regression model, four further showed correlation with the application of assistant techniques, namely, perpendicular distance from hard palate to tip of upper incisor (X2), atlanto-occipital gap (X9), angle between a line passing through posterior-superior point of hard palate and the lowest point of the occipital bone and a line passing through the anterior-inferior point and the posterior-inferior point of the second cervical vertebral body (Angle E), and distance from skin to hyoid bone (MRI 7). Angle E owned the largest AUC (0.929), and its optimal cut-off value was 19.9° (sensitivity = 88.5%, specificity = 91.0%). the optimal cut-off value, sensitivity and specificity of other three variables were X2 (30.1 mm, 76.9, 76.9%), MRI7 (16.3 mm, 69.2, 87.2%), and X9 (7.3 mm, 73.1, 56.4%).
Four radiological variables possessed potential ability to predict the application of assistant intubation techniques. Anaesthesiologists are recommended to apply assistant techniques more positively once encountering the mentioned cut-off values.
我们旨在鉴别术前影像学指标，以预测选择性颈椎手术患者插管过程中辅助技术的应用情况。
本研究共纳入104例患者。根据单纯麦氏喉镜插管是否成功，将患者分为麦氏喉镜组（n = 78）和辅助技术组（n = 26）。我们通过患者术前的X线和MRI图像测量其影像学数据，并比较两组之间的差异。应用二元逻辑回归模型鉴别有意义的预测因素。采用受试者工作特征（ROC）曲线和曲线下面积（AUC）来描述指标的鉴别能力。最大约登指数对应的是最佳截断值。
10个变量在两组之间存在显著统计学差异（P < 0.05）。基于逻辑回归模型，另外4个变量与辅助技术的应用相关，即硬腭至上门齿尖端的垂直距离（X2）、寰枕间隙（X9）、经过硬腭后上点与枕骨最低点的直线和经过第二颈椎椎体前下点与后下点的直线之间的夹角（E角）以及皮肤至舌骨的距离（MRI 7）。E角的AUC最大（0.929），其最佳截断值为19.9°（灵敏度 = 88.5%，特异度 = 91.0%）。其他三个变量的最佳截断值、灵敏度和特异度分别为X2（30.1 mm，76.9，76.9%）、MRI7（16.3 mm，69.2，87.2%）和X9（7.3 mm，73.1，56.4%）。
4个影像学变量具有预测辅助插管技术应用的潜在能力。建议麻醉医生一旦遇到上述截断值，更积极地应用辅助技术。
