ImagingPredicting difficult laryngoscopy using ultrasound measurement of distance from skin to epiglottis
Introduction
Airway management is one of the main concerns for anesthesiologists, and unpredictable difficult airway intubation remains one of the most important challenges in routine practice. Adverse outcomes and severe complications related with difficult airway are rare but may have catastrophic consequences to the patient [1].
Airway assessment can help to provide an appropriate management of an expected difficult airway. Prescreening airway evaluation can include consultation of previous medical history, physical examination, and performing additional bedside tests. Presently, bedside tests such as Mallampati test, thyromental distance (TMD), sternomental distance, neck circumference, and interincisor distance (IID), are used in daily clinical practice to predict difficult intubation. Most of these common tests, however, have limited predictive value when used on their own [2]. This is partially due to lack of standardized measurements, subjectivity, and lack of agreed-upon cutoff values. To overcome this, some multivariable risk scores have been proposed [2] to improve the predictive capability of bedside tests. However, these composite scores tend to be time consuming and difficult to use in clinical practice.
Advances in airway devices, patient monitoring, clinical protocols, and education have reduced the risks associated with an unpredicted difficult airway, but not the incidence of unexpected difficult airway [3], [4], [5], [6]. Ultrasound (US) has recently emerged as a simple, portable, noninvasive, and safe method for rapid airway assessment and management in the operating room, emergency department, and intensive care unit [7], [8].
Recent studies suggest that US-based airway assessment may be a useful adjunct to clinical methods of bedside airway assessment [9], [10], [11], [12]. In morbidly obese patients, anterior soft neck tissue was an independent predictor of difficult laryngoscopy [9]. Another pilot study [11] analyzed three US-based measurements including the distance from skin to epiglottis (DSE) for difficult laryngoscopy prediction. The results suggested that DSE gives good predictive results, but no useful cutoff for clinical practice was validated. Although these results are promising, more systematic studies are needed before US measurements can be validated for reliable use in routine clinical practice [2].
In this regard, our main objective was to evaluate the capability of DSE in predicting difficult laryngoscopy and whether it can be used, alone or combined with other standard clinical preintubation screening tests, in daily clinical practice.
Section snippets
Materials and methods
This prospective double-blind study was conducted in Hospital Center Tondela-Viseu, Portugal.
Results
The goal of this study was to determine the feasibility of including an US-based measurement—the DSE—as a standard variable in prescreening tests for predicting difficult laryngoscopy. The 74 patients involved in the study were divided in 2 groups—easy and difficult laryngoscopy—by an anesthesiologist performing the intubation (using the Cormack-Lehane grade; see “Materials and methods” section). Using these 2 groups, we asked which variables were associated with difficult laryngoscopy (see
Discussion
Here, we have proposed methods to predict difficult laryngoscopy using DSE, a US measurement (DSE, a measure of anterior soft neck tissue width at the level of thyrohyoid membrane). We showed that this measure can significantly improve the predictive power of current standard preintubation screening tests when combined with the standard modified Mallampati score in a simple easy-to-implement decision tree.
Previous studies have used anterior soft neck tissue width at the level of thyrohyoid
Conclusions
This study demonstrated that the sonographic measurement of DSE can be used as a stand-alone screening test to predict a difficult laryngoscopy. Furthermore, combined with Mallampati score in a decision tree algorithm, it can considerably improve difficult airway prediction. The proposed models are also easy to understand and use, making them a useful tool for clinical practice in airway management.
Acknowledgments
The authors thank Nuno Ribeiro, MD (Department of Imagiology, Hospital Center Tondela-Viseu, Portugal), for his suggestions and support and CI&DETS - Polytechnic Institute of Viseu for the financial support.
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