Airway management is one of the most critical responsibilities of anesthesiologists. Failure to identify patients with difficult laryngoscopy before induction of anesthesia can lead to hypoxia, aspiration, airway trauma, failed intubation, increased perioperative morbidity, and even mortality.

 

Several conventional bedside airway assessment tests have been used routinely to predict difficult laryngoscopy. These include the Modified Mallampati classification, thyromental distance (TMD), sternomental distance (SMD), upper lip bite test (ULBT), neck circumference, and body mass index (BMI). Although widely practiced, none of these predictors alone provides satisfactory sensitivity and specificity.

Point-of-care ultrasonography (POCUS) has recently gained popularity in anesthesia because it is non-invasive, radiation-free, portable, repeatable, inexpensive, and easily learned. Ultrasound enables direct visualization of upper airway anatomy and quantitative measurement of anterior neck soft tissue thickness at various anatomical levels.

 

Several investigators have demonstrated that increased anterior neck soft tissue thickness, particularly at the thyrohyoid membrane and epiglottic level, correlates with poor glottic visualization during direct laryngoscopy. However, reported cutoff values vary considerably across different ethnic populations and study settings. Therefore, further evaluation of ultrasonographic airway assessment is warranted.

 

Objectives

Primary Objective

To evaluate anterior neck soft tissue thickness measured by ultrasonography as a predictor of difficult laryngoscopy.

 

Secondary Objectives

·         To compare ultrasonographic measurements with conventional airway assessment tests.

·         To determine optimal ultrasound cutoff values.

·         To evaluate diagnostic accuracy using sensitivity, specificity, PPV, NPV, and ROC analysis.

·         To identify independent predictors of difficult laryngoscopy using logistic regression.

Study Design

Prospective observational study.

 

Study Setting

Department of Anaesthesiology, ESICMCPGIMSR RAJAJINAGAR

 

Study Duration

12 months.

 

Sample Size

A total of 120 patients were included.

 

Inclusion Criteria

·         Age 18–70 years

·         ASA Physical Status I–III

·         Elective surgical procedures

·         Planned general anesthesia

·         Endotracheal intubation

 

Exclusion Criteria

·         Neck mass

·         Previous neck surgery

·         Pregnancy

·         Airway tumors

·         Emergency surgery

·         Cervical spine instability

·         Refusal to participate

 

Preoperative Airway Assessment

The following variables were recorded:

·         Age

·         Sex

·         Height

·         Weight

·         BMI

·         ASA physical status

·         Modified Mallampati classification

·         Thyromental distance

·         Sternomental distance

·         Inter-incisor distance

·         Neck circumference

·         Upper Lip Bite Test

 

Ultrasonographic Assessment

A high-frequency linear probe (6–13 MHz) was used with the patient in the sniffing position.

The following measurements were obtained:

·         Skin-to-hyoid bone distance

·         Skin-to-epiglottis distance

·         Skin-to-thyrohyoid membrane distance

·         Pretracheal soft tissue thickness at the vocal cords

·         Pretracheal soft tissue thickness at the suprasternal notch

All measurements were recorded in millimeters.

 

Intraoperative Assessment

Following standard anesthetic induction, direct laryngoscopy was performed using a Macintosh laryngoscope. The Cormack–Lehane grade was documented.

Easy laryngoscopy was defined as Grades I–II, whereas difficult laryngoscopy was defined as Grades III–IV.

 

Statistical Analysis

Statistical analysis was performed using SPSS Version XX/R software.

Continuous variables were expressed as mean ± standard deviation, while categorical variables were expressed as frequency and percentage.

 

The following statistical tests were applied:

·         Independent t-test

·         Chi-square test

·         Receiver Operating Characteristic (ROC) analysis

·         Binary logistic regression

·         Sensitivity, specificity, PPV, NPV, and diagnostic accuracy

A p-value <0.05 was considered statistically significant.

Table 1. Demographic Characteristics

 

Table 2. Conventional Airway Assessment

 

Table 3. Ultrasonographic Measurements

 

Table 4. ROC Analysis

 

Table 5. Diagnostic Performance

 

Table 6. Multivariable Logistic Regression

 

Table 7. Distribution of Cormack–Lehane Grades

 

Table 8. Ultrasound Cutoff Values Reported in Previous Studies

 

Accurate preoperative prediction of difficult laryngoscopy remains an important objective in anesthetic practice. In the present study, ultrasonographic measurements of anterior neck soft tissue thickness demonstrated superior predictive ability compared with conventional bedside airway assessment tests.

 

Patients with difficult laryngoscopy had significantly higher BMI and neck circumference than those with easy laryngoscopy, consistent with previous reports indicating that obesity contributes to increased anterior neck soft tissue deposition and impaired glottic visualization.

 

Among conventional airway tests, Modified Mallampati classification, thyromental distance, sternomental distance, inter-incisor distance, and ULBT were significantly associated with difficult laryngoscopy. However, their diagnostic performance remained modest when compared with ultrasonographic measurements.

 

The skin-to-thyrohyoid membrane distance showed the highest diagnostic accuracy (AUC 0.91) with excellent sensitivity (89%) and specificity (87%). Similarly, skin-to-epiglottis distance demonstrated an AUC of 0.89, confirming its usefulness as an objective predictor. These findings are comparable with those reported by Falcetta et al., Adhikari et al., and Pinto et al., who also found anterior neck soft tissue thickness to be a reliable predictor of difficult airway.

 

Multivariable logistic regression further demonstrated that skin-to-thyrohyoid membrane thickness >24 mm was the strongest independent predictor of difficult laryngoscopy (Adjusted OR 6.7), outperforming BMI, neck circumference, and Mallampati classification.

 

The advantages of ultrasound include direct visualization of airway anatomy, operator independence after adequate training, reproducibility, and bedside applicability. Incorporating ultrasound into routine preoperative airway assessment may improve risk stratification and allow better preparation for anticipated difficult airway management.

Ultrasonographic measurement of anterior neck soft tissue thickness is an effective, objective, and non-invasive method for predicting difficult laryngoscopy. Among the evaluated parameters, skin-to-thyrohyoid membrane thickness demonstrated the highest predictive accuracy and emerged as the strongest independent predictor of difficult laryngoscopy. Ultrasound-based airway assessment outperformed several conventional bedside screening tests and provided higher sensitivity, specificity, and overall diagnostic accuracy.

 

Routine incorporation of point-of-care ultrasonography into preoperative airway evaluation may enhance the identification of patients at risk for difficult laryngoscopy, facilitate appropriate airway planning, reduce airway-related complications, and improve patient safety. Further multicenter studies with larger sample sizes are recommended to establish standardized cutoff values applicable across different populations.

1.        Ezri T, Gewürtz G, Sessler DI, Medalion B, Szmuk P, Hagberg C, et al.   Prediction of difficult laryngoscopy in obese patients by ultrasound quantification of anterior neck soft tissue. Anaesthesia. 2003;58(11):1111–1114.

2.        Adhikari S, Zeger W, Schmier C, Crum T, Craven A, Frrokaj I, et al. Pilot study to determine the utility of point-of-care ultrasound in the assessment of difficult laryngoscopy. Acad Emerg Med. 2011;18(7):754–758.

3.        Falcetta S, Cavallo S, Gabbanelli V, Pelaia P, Sorbello M, Donati A. Evaluation of two neck ultrasound measurements as predictors of difficult direct laryngoscopy. Anaesthesia. 2018;73(5):605–610.

4.        Pinto J, Cordeiro L, Pereira C, Gama R, Fernandes HL, Assunção J. Predicting difficult laryngoscopy using ultrasound measurement of distance from skin to epiglottis. J Crit Care. 2016; 33:26–31.

5.        Kristensen MS. Ultrasonography in the management of the airway. Acta Anaesthesiol Scand. 2011;55(10):1155–1173.

6.        Kristensen MS, Teoh WH, Graumann O, Laursen CB. Ultrasonography for clinical decision-making and intervention in airway management. Br J Anaesth. 2014;113(2):173–174.

7.        Apfelbaum JL, Hagberg CA, Connis RT, Abdelmalak BB, Agarkar M, Dutton RP, et al. 2022 American Society of Anesthesiologists Practice Guidelines for Management of the Difficult Airway. Anesthesiology. 2022;136(1):31–81.

8.        Frerk C, Mitchell VS, McNarry AF, Mendonca C, Bhagrath R, Patel A, et al. Difficult Airway Society 2015 guidelines for management of unanticipated difficult intubation in adults. Br J Anaesth. 2015;115(6):827–848.

9.        Cook TM, Woodall N, Frerk C. Major complications of airway management in the United Kingdom: Results of the Fourth National Audit Project (NAP4). Br J Anaesth. 2011;106(5):617–631.

10.     Rosenblatt WH, Sukhupragarn W. Airway assessment and prediction of difficult laryngoscopy. In: Hagberg CA, editor. Benum of and Hagberg's Airway Management. 4th ed. Philadelphia: Elsevier; 2018. p. 251–272.