Department of Anesthesiology, All India Institute of Medical Sciences, Rishikesh, India.
Korean J Anesthesiol. 2021 Apr;74(2):134-141. doi: 10.4097/kja.20114. Epub 2020 Jun 15.
Predicting difficult intubation (DI) is a key challenge, as no single clinical predictor is sufficiently valid to predict the outcome. We evaluated the effectiveness of four upper airway ultrasonographic parameters in predicting DI. The validity of the models using combinations of ultrasonography-based parameters was also investigated.
This prospective, observational, double-blinded cohort trial enrolled 1,043 surgical patients classified as American Society of Anesthesiologists physical status I-III without anticipated difficult airway. Preoperatively, their tongue thickness (TT), invisibility of hyoid bone (VH), and anterior neck soft tissue thickness from the skin to thyrohyoid membrane (ST) and hyoid bone (SH) were measured by sublingual and submandibular ultrasonography. The logistic regression, Youden index, and receiver operator characteristic analysis results were reported.
Overall, 58 (5.6%) patients were classified as DI. The TT, SH, ST, and VH had accuracies of 78.4%, 85.0%, 84.7%, and 84.9%, respectively. The optimal values of TT, SH, and ST for predicting DI were > 5.8 cm (sensitivity: 84.5%, specificity: 78.1%, AUC: 0.880), > 1.4 cm (sensitivity: 81%, specificity: 85.2%, AUC: 0.898) and > 2.4 cm (sensitivity: 75.9%, specificity: 85.2%, AUC: 0.885) respectively. VH had a sensitivity and specificity of 72.4% and 85.6% (AUC: 0.790). The AUC values of the five models (with combinations of three or four parameters) ranged from 0.975-0.992. ST and VH had a significant impact on the individual models.
SH had the best accuracy. Individual parameters showed limited validity. The model including all four parameters offered the best diagnostic value.
预测困难插管(DI)是一个关键挑战,因为没有单一的临床预测指标足以准确预测结果。我们评估了四种上呼吸道超声参数在预测 DI 中的有效性。还研究了使用基于超声的参数组合的模型的有效性。
这是一项前瞻性、观察性、双盲队列研究,共纳入 1043 例美国麻醉医师协会身体状况 I-III 级、无预期困难气道的手术患者。术前通过舌下和下颌下超声测量舌厚(TT)、舌骨不可见(VH)以及从皮肤到甲状舌骨膜(ST)和舌骨(SH)的前颈部软组织厚度。报告了逻辑回归、Youden 指数和接收者操作特征分析结果。
共有 58 例(5.6%)患者被归类为 DI。TT、SH、ST 和 VH 的准确率分别为 78.4%、85.0%、84.7%和 84.9%。预测 DI 的 TT、SH 和 ST 的最佳值分别为>5.8cm(灵敏度:84.5%,特异性:78.1%,AUC:0.880)、>1.4cm(灵敏度:81%,特异性:85.2%,AUC:0.898)和>2.4cm(灵敏度:75.9%,特异性:85.2%,AUC:0.885)。VH 的灵敏度和特异性分别为 72.4%和 85.6%(AUC:0.790)。五个模型(三个或四个参数的组合)的 AUC 值范围为 0.975-0.992。ST 和 VH 对个体模型有显著影响。
SH 的准确率最高。单独的参数显示出有限的有效性。包含所有四个参数的模型具有最佳的诊断价值。