Introduction
In both the elective and emergency settings there is a potential for tracheal intubation to fail, and a consequential failure to provide adequate oxygenation and CO2 removal can lead to life-threatening complications.1,2 Available guidelines provide indices to predict the risk of difficult laryngoscopy but, despite these, unpredicted difficult laryngoscopy complicates 1.5 to 13% of cases.3 Safe management of the airway before tracheal intubation or after failed intubation (i.e. effective mask ventilation) plays a critical role that is sometimes overlooked.4 Despite similarities in predictors, the incidence of difficult mask ventilation (DMV) is distinct from difficult laryngoscopy.5–11 Patients presenting with difficult laryngoscopy associated with DMV, especially if these are unpredicted, represent the highest risk subgroup.
Diagnostic tools that help in predicting patients who are likely to have DMV can contribute to safer airway management and must be considered as an adjunct to the conventional pre-operative clinical assessment. During the last few years ultrasound has been widely used in the operating room for ultrasound-guided procedures such as nerve block or central venous access. Ultrasound provides quick, relatively easy, and accurate information, with diagnostic and therapeutic relevance.12,13 For some considerable time ultrasound has not been taken into consideration as a tool for the evaluation of the airway or as a predictor of difficult laryngoscopy.14–19 Pre-operative ultrasound measurement of the anterior neck soft-tissue thickness at different levels, combined with the commonly used screening tests and risk factor assessment for difficult laryngoscopy might improve the ability to predict difficult laryngoscopy. Research regarding DMV combined with difficult laryngoscopy is extremely limited even though these two aspects of airway management are closely related.20
The aim of this study was to evaluate the accuracy of pre-operative ultrasound assessment of neck anatomy in predicting DMV and difficult laryngoscopy, in mostly ENT (ear, nose and throat) patients undergoing elective tracheal intubation for general anaesthesia.
Methods
The study was approved by the Ethical Committee of Azienda Policlinico Umberto I ‘Sapienza’ University of Rome (Rome, Italy) (Protocol No. 2017-4498) on 30 March 2017, Chairperson Prof. G. Spera. All study participants gave informed written consent and the research was conducted in accordance with the Helsinki Declaration. From April 2018 to July 2018, in Policlinico Umberto I (Rome, Italy), a nonselected series of consecutive patients aged more than 18 years undergoing general anaesthesia for elective ENT-surgery, were prospectively enrolled. Exclusion criteria were any of the following: facial, cervical, pharyngeal and epiglottic cancer or trauma, previous thyroid surgery or tracheotomy, pregnancy. The data collection form included a standard airway physical examination (ASA-PS) and the type of surgery. Data were recorded by two different anaesthetists: one measured ultrasound distances, the other, blinded to ultrasound distances, was in charge of the clinical aspects of the case, undertaking mask ventilation and intubation as well as grading the difficulty of laryngoscopy and mask ventilation.
On arrival in the pre-operative room, with the patient lying supine with the head and neck in a neutral position, the thicknesses of the anterior neck soft tissues were measured with a portable ultrasound machine (SonoSite NanoMaxx; SonoSite, Bothell, Washington, USA) with a linear 6 to 13 MHz ultrasound transducer. After a cranio-caudal sagittal scan of the neck with the probe placed in the transverse axis, ultrasound distances were measured: the minimum distance from the thyroid isthmus to skin surface (DSTI); the minimum distance from the hyoid bone to skin surface (DSHB); the minimum distance from skin to anterior commissure of the vocal cords (DSAC); the minimum distance from skin to the trachea at the level of the jugular notch (DSTJ); and at the thyrohyoid membrane level, with the probe placed on sagittal axis, the minimum distance from the skin to the point of the epiglottis corresponding to half the distance between the hyoid bone and the thyroid cartilage (DSEM)18 (Fig. 1).
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Fig. 1: Ultrasound distances: DSHB, distance from skin to the hyoid bone; DSEM, distance from skin to epiglottis midway; DSTJ, distance from skin to trachea at jugular notch; DSAC, distance from skin to anterior commissure of the vocal cords; DSTI, distance from skin to thyroid isthmus.
Anaesthesia was induced with propofol 2 to 2.5 mg kg−1, fentanyl 2 to 4 μg kg−1, and cisatracurium 0.15 mg kg−1 and mask ventilation was performed using a clear disposable plastic mask. The grade of DMV was evaluated using the four level Han scale: first, ventilated by mask; second, ventilated by mask with oral airway/adjuvant, with or without muscle relaxant; third, difficult ventilation (inadequate, unstable or requiring two providers), with or without muscle relaxant; fourth, unable to mask ventilate, with or without muscle relaxant.20,21 After adequate relaxation had been achieved, tracheal intubation was attempted by direct laryngoscopy using an appropriately sized Macintosh blade. Tracheal intubation was performed by an experienced anaesthetist (>5 years of clinical practice) blinded to the results of the ultrasound assessment. The laryngoscopic view was graded according to the Cormack–Lehane scale.22 Difficult laryngoscopy was considered difficult if the Cormack–Lehane grade was at least 2B and DMV if the Han scale was at least III. The primary endpoint of this study was to evaluate if DSHB can be predictive of DMV. Secondary endpoints were the relationship between DSTI, DSEM, DSAC, DSTJ and DMV. We also investigated the relationship between ultrasound-recorded measures and Cormack–Lehane scale.
Statistical analysis
Based on the primary endpoint and assuming a correlation of 0.2, we expected the inclusion of 194 patients to guarantee a power of 80%, with a level of significance of 5%. Continuous data were expressed as mean (SD), whereas categorical data were expressed as frequencies (%). Pearson correlation coefficients were calculated to evaluate the dependence between the variables. Receiver-operating characteristic curves (ROC) were used to determine the sensitivity and specificity of the measured ultrasound distances.
Results
A total of 194 eligible patients (76 female, 118 male) were included in this study. Their personal and clinical characteristics are summarised in Table 1. In our study population, 135 (69.6%) patients presented with a DMV-I, 51 (26.3%) patients DMV-II and eight (4.1%) patients DMV-III. No patient had a DMV-IV; 91 (47%) patients had a Cormack–Lehane 1, 69 (36%) 2A, 21 (11%) 2B, 10 (5%) 3A and three (1%) 3B. No patient had a Cormack–Lehane 4.
Table 1: Patient demographics and pre-operative variables
Table 2 shows the summary statistics of the ultrasound distances graded for DMV and difficult laryngoscopy. Mask ventilation was difficult in eight patients and easy in 186, while direct laryngoscopy was difficult in 34 patients and easy in 160. Ultrasound measures (DSTI, DSHB, DSEM, DSTJ, DSAC), were positively correlated (Fig. 2). However, the DSHB seemed better correlated with both DMV and difficult laryngoscopy than the other ultrasound measures: The median [IQR] Pearson correlation coefficient was 0.61 [0.5 to 0.69] for DMV and 0.34 [0.21 to 0.46] for difficult laryngoscopy: the greater the distance the higher the DMV grade (Table 3).
Table 2: Ultrasound distances graded for DMV and DL
Fig. 2: Scatter Plot and Pearson's Correlation Coefficient Matrix for comparisons among the five ultrasound measurements. The five ultrasound measurements are labelled diagonally from top left to bottom right. The intersections of the rows and columns above the diagonal show the Pearson's correlation coefficients (r) with their P values. The intersections of the rows and columns below the diagonal illustrates their respective scatter plots. All ultrasound distances are expressed in centimetres. DSAC, distance from skin to anterior commissure of the vocal cords; DSEM, the distance from the skin to the point of the epiglottis corresponding to half the distance between the hyoid bone and the thyroid cartilage; DSHB, distance from skin to the hyoid bone; DSTI, distance from skin to thyroid isthmus; DSTJ, distance from skin to trachea at jugular notch.
Table 3: Pearson correlation indices (95% confidence interval) between ultrasound distances and the grade scales difficult mask ventilation and difficult laryngoscopy
In Fig. 3, the correlation between ultrasound distances and Han scale grade for mask ventilation is shown by comparison of the area under the ROC curves The best predictor of DMV (Han scale >3) was the DSHB [Area Under the Curve (AUC) 0.93; 95% confidence interval 0.87 to 0.93)] (Fig. 3).
Fig. 3: Receiver operating characteristic curve analyses of the five ultrasound measurements and Han Scale at least III (top row) and Cormack–Lehane at least 2B (bottom row). DSAC, distance from skin to anterior commissure of the vocal cords; DSEM, the distance from the skin to the point of the epiglottis corresponding to half the distance between the hyoid bone and the thyroid cartilage; DSHB, distance from skin to the hyoid bone; DSTI, distance from skin to thyroid isthmus; DSTJ, distance from skin to trachea at jugular notch.
Discussion
Data analysis from this prospective observational study in 194 patients, confirms and extends available evidence on the relationship between ultrasound assessment of the anterior neck soft tissues and difficult laryngoscopy and DMV. DSHB was a better predictor of DMV than other distance measurements.
Available evidence reports mixed results on the value of ultrasound neck screening to predict difficult laryngoscopy.3,6,18,23 In one study, the relationship between ultrasound-measured anterior neck soft-tissue thickness at the hyoid bone and thyrohyoid membrane levels predicted difficult laryngoscopy but there was no relationship between the ultrasound measurements and clinical screening tests.3 A similar study showed that both ultrasound quantification of anterior neck soft tissues and general bedside screening tests failed to predict difficult laryngoscopy in obese patients.6 In another study of obese patients, an ultrasound-detected abundance of fat tissue at the anterior neck region was an independent predictor of difficult laryngoscopy and was more specific than the BMI.23 The sensitivity of ultrasound in predicting difficult laryngoscopy is proven by the strong positive linear correlation among the thicknesses of anterior neck soft tissue measured by ultrasound at the hyoid bone, thyrohyoid membrane, and anterior commissure levels.18
To date no evidence is available on ultrasound measurement of the anterior soft tissues of the neck and DMV. Although the Han scale is neither objective nor validated, it is the most commonly used method for grading DMV. We investigated five different distances by adding DSTI and DSTJ to the three measures proposed by Wu et al.,18 and investigated their relationship with DMV. Our data are in agreement with previous evidence in that there is was a statistically positive association between the increased thickness of the anterior neck soft tissues at all five levels and not only the incidence of difficult laryngoscopy, but also the incidence of DMV. This is especially so for DSHB which showed a higher correlation. Results of the comparison of the five distances are consistent.
The study was performed in ENT patients and airway management is often difficult in this population. Thus, this choice of patient should allow us to study the ultrasound measurements as independent predictive assessments of a difficult airway, and to identify difficult laryngoscopy and DMV in patients with no clinically predictable difficulty. Patients with abnormal airways were excluded as our intention was to provide an additional tool to increase the detection of unpredicted DMV and difficult laryngoscopy.
DSHB is perhaps the more stable distance. In a study by Adhikari et al.15 DSEM and DSHB were evaluated and both were considered predictive of difficult airway management. However, DSEM is too dependent on the length of the epiglottis. In the study of Wu et al.,18 DSHB had a higher specificity and sensitivity in detecting difficult laryngoscopy, possibly because the hyoid is the fulcrum of the upper airway: it is connected to the tongue by genioglossus muscle and to the larynx through the hyoepiglottic and thyrohyoid membranes and thus can affect every aspect of airway management.
The study is a first attempt to find new ultrasound parameters to improve the specificity and sensitivity of anthropometric parameters for the pre-operative evaluation of the upper airway. Computed tomography, MRI and other imaging techniques can measure the thickness of the soft tissues of the neck, but are expensive and not available in the operation room. Ultrasound is bedside, radiation-free, cheap, fast and as accurate as MRI.24,25
There are several limitations in our study. First, we have not defined a cut-off value for the DSHB that is useful to quantify DMV or difficult laryngoscopy. Another aspect for further study is the comparison between ultrasound distances and anthropometric parameters currently considered as a reference: in particularly it would be very interesting to evaluate the relationship with neck circumference, which is related to DMV.26 Finally, it should be remembered that patients with predicted difficult airway management were excluded as the study aim was to investigate the use neck ultrasound in patients for whom the potential for DMV and difficult laryngoscopy was not predictable pre-operatively.
In summary, the growing interest in the use of ultrasound to assist airway management and the study of the anatomy of the anterior region of the neck as revealed by ultrasound, will be helpful in developing new predictors for DMV and difficult laryngoscopy. Longer distances from skin to larynx, appear predictive of both DMV and difficult laryngoscopy, and DSHB seems to be better than the other distances, however further studies are needed to identify the most accurate and easy parameter to predict difficult laryngoscopy and DMV.
Acknowledgements relating to this article
Assistance with the study: none.
Financial support and sponsorship: none.
Conflicts of interest: none.
Presentation: none.
References
1. Law JA, Broemling N, Cooper RM, et al. The difficult airway with recommendations for management – Part 1 – Difficult tracheal intubation encountered in an unconscious/induced patient.
Can J Anaesth 2013; 60:1089–1118.
2. Cook TM, Woodall N, Harper J, et al. Major complications of airway management in the UK: results of the fourth national audit project of the royal college of anaesthetists and the difficult airway society. Part 2: Intensive care and emergency departments.
Br J Anaesth 2011; 106:632–642.
3. Apfelbaum JL, Hagberg CA, Caplan RA, et al. American Society of Anesthesiologists Task Force on Management of the Difficult Airway. Practice guidelines for management of the difficult airway: an updated report by the American Society of Anesthesiologists Task Force on Management of the Difficult Airway.
Anesthesiology 2013; 118:251–270.
4. Adnet F. Difficult mask ventilation: an underestimated aspect of the problem of the difficult airway?
Anesthesiology 2000; 92:1217–1218.
5. Kim WH, Ahn HJ, Lee CJ, et al. Neck circumference to thyromental distance ratio: a new predictor of difficult intubation in obese patients.
Br J Anaesth 2011; 106:743–748.
6. El-Orbany M, Woehlck HJ. Difficult mask ventilation.
Anesth Analg 2009; 109:1870–1880.
7. Kheterpal S, Han R, Tremper K, et al. Incidence and predictors of difficult and impossible mask ventilation.
Anesthesiology 2006; 105:885–891.
8. Kheterpal S, Healy D, Aziz MF, et al. Multicenter Perioperative Outcomes Group (MPOG) Perioperative Clinical Research Committee. Incidence, predictors, and outcome of difficult mask ventilation combined with difficult laryngoscopy: a report from the multicenter perioperative outcomes group.
Anesthesiology 2013; 119:1360–1369.
9. Cattano D, Killoran PV, Iannucci D, et al. Anticipation of the difficult airway: preoperative airway assessment, an educational and quality improvement tool.
Br J Anaesth 2013; 111:276–285.
10. Kheterpal S, Martin L, Shanks AM, et al. Prediction and outcomes of impossible mask ventilation: a review of 50,000 anesthetics.
Anesthesiology 2009; 110:891–897.
11. Roberts S, Cyna AM, Walsh JP, et al. Assessment of anaesthetists’ ability to predict difficulty of bag-mask ventilation.
Br J Anaesth 2013; 111:676–677.
12. Manno E, Navarra M, Faccio L, et al. Deep impact of ultrasound in the intensive care unit: The ‘ICU-sound’ protocol.
Anesthesiology 2012; 117:801–809.
13. Pelosi P, Corradi F. Ultrasonography in the intensive care unit: looking at the world through colored glasses.
Anesthesiology 2012; 117:696–698.
14. Kristensen MS. Ultrasonography in the management of the airway.
Acta Anaesthesiol Scand 2011; 55:1155–1173.
15. Adhikari S, Zeger W, Schmier C, et al. Pilot study to determine the utility of point-of-care ultrasound in the assessment of difficult laryngoscopy.
Acad Emerg Med 2011; 18:754–758.
16. Ezri T, Gewurtz G, Sessler DI, et al. Prediction of difficult laryngoscopy in obese patients by ultrasound quantification of anterior neck soft tissue.
Anaesthesia 2003; 58:1111–1114.
17. Komatsu R, Sengupta P, Wadhwa A, et al. Ultrasound quantification of anterior soft tissue thickness fails to predict difficult laryngoscopy in obese patients.
Anaesth Intensive Care 2007; 35:32–37.
18. Wu J, Dong J, Ding Y, et al. Role of anterior neck soft tissue quantifications by ultrasound in predicting difficult laryngoscopy.
Med Sci Monit 2014; 20:2343–2350.
19. Falcetta S, Cavallo S, Gabbanelli V, et al. Evaluation of two neck ultrasound measurements as predictors of difficult direct laryngoscopy: a prospective observational study.
Eur J Anaesthesiol 2018; 35:605–612.
20. Green L. Can’t intubate, can’t ventilate! A survey of knowledge and skills in a large teaching hospital.
Eur J Anaesthesiol 2009; 26:480–483.
21. Han R, Tremper KK, Kheterpal S, et al. Grading scale for mask ventilation (letter).
Anesthesiology 2004; 101:267.
22. Cormack RS, Lehane J. Difficult tracheal intubation in obstetrics.
Anaesthesia 1984; 39:1105–1111.
23. Khan ZH, Kashfi A, Ebrahimkhani E. A comparison of the upper lip bite test (a simple new technique) with modified Mallampati classification in predicting difficulty in endotracheal intubation: a prospective blinded study.
Anesth Analg 2003; 96:595–599.
24. Prasad A, Yu E, Wong DT, et al. Comparison of sonography and computed tomography as imaging tools for assessment of airway structures.
J Ultrasound Med 2011; 30:965–972.
25. Abe T, Kawakami Y, Sugita M, et al. Use of B-mode ultrasound for visceral fat mass evaluation: comparisons with odds ratio imaging.
Appl Human Sci 1995; 14:133–139.
26. Riad W, Vaez MN, Raveendran R, et al. Neck circumference as a predictor of difficult intubation and difficult mask ventilation in morbidly obese patients: a prospective observational study.
Eur J Anaesthesiol 2016; 33:244–249.
