Abstract
BackgroundAccurate prediction of the difficult airway (DA) could help to prevent catastrophic consequences in emergency resuscitation, intensive care, and general anesthesia. Until now, there is no nomogram prediction model for DA based on ultrasound assessment. In this study, we aimed to develop a predictive model for difficult tracheal intubation (DTI) and difficult laryngoscopy (DL) using nomogram based on ultrasound measurement. We hypothesized that nomogram could utilize multivariate data to predict DTI and DL.MethodsA prospective observational DA study was designed. This study included 2254 patients underwent tracheal intubation. Common and airway ultrasound indicators were used for the prediction, including thyromental distance (TMD), modified Mallampati test (MMT) score, upper lip bite test (ULBT) score temporomandibular joint (TMJ) mobility and tongue thickness (TT). Univariate and the Akaike information criterion (AIC) stepwise logistic regression were used to identify independent predictors of DTI and DL. Nomograms were constructed to predict DL and DTL based on the AIC stepwise analysis results. Receiver operating characteristic (ROC) curves were used to evaluate the accuracy of the nomograms.ResultsAmong the 2254 patients enrolled in this study, 142 (6.30%) patients had DL and 51 (2.26%) patients had DTI. After AIC stepwise analysis, ULBT, MMT, sex, TMJ, age, BMI, TMD, IID, and TT were integrated for DL nomogram; ULBT, TMJ, age, IID, TT were integrated for DTI nomogram. The areas under the ROC curves were 0.933 [95% confidence interval (CI), 0.912–0.954] and 0.974 (95% CI, 0.954–0.995) for DL and DTI, respectively.ConclusionNomograms based on airway ultrasonography could be a reliable tool in predicting DA.Trial registrationChinese Clinical Trial Registry (No. ChiCTR-RCS-14004539), registered on 13th April 2014.
Highlights
Accurate prediction of the difficult airway (DA) could help to prevent catastrophic consequences in emergency resuscitation, intensive care, and general anesthesia
Results for restricted cubic spline (RCS) and Receiver operating characteristic (ROC) curves for continuous variables segmentation of difficult laryngoscopy (DL) and difficult tracheal intubation (DTI) were presented in Fig. S1, S2, S3, S4, S5, S6, S7, S8 and S9
According to the results of univariate logistic regression analysis, upper lip bite test (ULBT), Mallampati test (MMT), sex, temporomandibular joint (TMJ), age, BMI, thyromental distance (TMD), interincisor distance (IID), and tongue thickness (TT) were included in multivariate logistic regression analysis
Summary
Accurate prediction of the difficult airway (DA) could help to prevent catastrophic consequences in emergency resuscitation, intensive care, and general anesthesia. Even though the assessment of DA is necessary before intubation, the At present, methods such as interincisor distance (IID), thyromental distance (TMD), modified Mallampati test (MMT) score, and upper lip bite test (ULBT) score are mostly used in clinical practice [12]. Methods such as interincisor distance (IID), thyromental distance (TMD), modified Mallampati test (MMT) score, and upper lip bite test (ULBT) score are mostly used in clinical practice [12] These indicators have limited performance, low sensitivity and specificity, and low positive predictive values [13, 14]. To overcome the predicting inability of single factor, some studies combined multiple indicators to improve DA prediction, for examples, the “3–3-2” rule [21], modified “look, evaluate, Mallampati score, obstruction, and neck mobility” (LEMON) criteria [22], and “Wilson” scores [23]. Even in ultrasonography-guided methods, the absence of valuable information is still a major drawback of DA risk prediction
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