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Table of Contents
ORIGINAL ARTICLE
Year : 2020  |  Volume : 4  |  Issue : 4  |  Page : 172-177

An observational study to evaluate the role of ultrasound in the prediction of difficult laryngoscopy


1 Department of Anesthesia, ASCOMS, Jammu, Jammu and Kashmir, India
2 Department of Surgery, Government Medical College, Jammu, Jammu and Kashmir, India

Date of Submission25-Jun-2020
Date of Decision20-Jul-2020
Date of Acceptance19-Aug-2020
Date of Web Publication16-Sep-2020

Correspondence Address:
Dr. Shikha Sharma
H. No. 41, Vikas Lane No. 1, Talab Tillo, Jammu - 180 002, Jammu and Kashmir
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/BJOA.BJOA_119_20

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  Abstract 


Background: Difficult laryngoscopy (DL) is challenging when difficult ventilation occurs during standard laryngoscopy. For airway assessment, the common clinical airway predictors have low sensitivity (Sn) and specificity (Sp) with a limited predictive value. Ultrasound can be a useful tool for predicting such difficulties. We aimed to evaluate the usefulness of several sonographic airway parameters in predicting DL in adults. Patients and Methods: This prospective observational study included 120 patients who underwent elective surgery requiring general anesthesia with direct laryngoscopy (Macintosh blade) and endotracheal intubation. Ultrasonography (USG) assessment included preepiglottic space (PES), hyomental distance (HMD), distance from skin to the hyoid bone-skin (DSHB), and distance from skin-to-epiglottis midway between the hyoid bone and thyroid cartilage distance from skin to epiglottis midway (DSEM). Demographic variables and Cormack-Lehane (CL) grading for laryngoscopy (CL grade 1, 2-easy; 3, 4-difficult). Receiver operating characteristic (ROC) analysis was done, and area under the curve (AUC) was calculated to determine the best predictor of DL. Results: DL was present in 22.50% of patients. Compared to those with easy laryngoscopy, patients with DL had lesser HMD (4.55 vs. 4.96, P = 0.002), and comparable DSHB, DSEM, and PES. Among the various US parameters for predicting DL, we found the highest Sn of DSHB (74.07%); highest Sp of HMD (86.02%); highest positive predictive value of HMD (50%); and highest negative predictive value of HMD (85.1%). ROC curve analysis showed HMD to be the best predictor for DL with the highest AUC of 0.684. Conclusion: DL is common, present in 22.5% patients. US is a novel modality for predicting the DL, especially HMD, which showed the highest AUC among DSHB, DSEM, and PES.

Keywords: Airway, difficult, laryngoscopy, ultrasonography


How to cite this article:
Gupta M, Sharma S, Katoch S. An observational study to evaluate the role of ultrasound in the prediction of difficult laryngoscopy. Bali J Anaesthesiol 2020;4:172-7

How to cite this URL:
Gupta M, Sharma S, Katoch S. An observational study to evaluate the role of ultrasound in the prediction of difficult laryngoscopy. Bali J Anaesthesiol [serial online] 2020 [cited 2020 Nov 30];4:172-7. Available from: https://www.bjoaonline.com/text.asp?2020/4/4/172/299877




  Introduction Top


Difficulty in airway management is a major cause of morbidity and mortality in anesthetic practice. The ability to identify patients at risk of difficult tracheal intubation is important, especially in patients with apparently normal airways. Difficult laryngoscopy (DL) is considered a surrogate indicator of the difficult intubation. Differences in patient characteristics due to race or ethnicity may influence the incidence of the difficult airway.[1] The incidence of DL ranges between 1.5% and 13%.[2],[3],[4],[5],[6],[7] The inability to predict difficult airways is probably due to high interobserver variability and low predictability of commonly used airway assessment screening tests.[8]

Since 1900, the use of Ultrasonography (USG) in airway assessment and management has observed an exponential increase for routine cases, emergency cases, critical care and preoperative settings. Its use has also observed a resurgence among the anaesthetists on account of its accurate visualization of airway structures, easy availability, and safe operationality.[9],[10] Currently, USG has become a part of the anesthesiologists' armamentarium to facilitate various procedures in the operation theatre and critical care areas. Imaging of the airway is a relatively newer application of USG which is extensively used for diagnosis of upper airway pathology.[11],[12],[13] It is also used to assess the size of the tongue, the floor of the mouth musculature, depth of the preepiglottic space (PES), and anterior neck soft (ANS)-tissue thickness.[8],[14],[15],[16]

The basis for the use of ultrasonography for assessing tissues in close vicinity to the larynx is by observing through direct laryngoscopy. It involves using the laryngoscope blade into the mouth and displacing the tongue, epiglottis and hyoid bone into the subglossal space. Increase in ANS-tissue thickness may impair the forward mobility of the pharyngeal structures;[3],[17] and an increase in the PES or a decrease in the distance from the epiglottis to the vocal cords (VCs) could be associated with increasingly DL and intubation.[8]

Although the use of various clinical parameters such as modified Mallampati grading, Wilson scoring system, thyromental distance, mouth opening, and the upper-lip bite test is used for prediction of DL, the diagnostic accuracy of a preanesthetic airway assessment is very low.[18] USG has been evolving as a useful device for airway assessment,[4],[19] but data are scarce on the correlation of USG with laryngoscopy as compared to clinical airway assessment. Thus, the present study was conducted to assess the usefulness of various sonographic airway parameters in predicting DL among adults.


  Patients and Methods Top


This prospective, observational study was conducted in the Postgraduate Department of Anesthesiology and Intensive Care, Jammu for 1 year (2018–2019), after obtaining approval from the Institutional Ethical Committee (approval registry number ASCOMS/IEC/RPandT/20/8/296, dated 24/10/2018). A total of 120 patients were enrolled in this study after obtaining the written informed consent from them.

Inclusion criteria included patients of 18–70 years with only the American Society of Anesthesiologists physical status Class I–III underwent elective surgery requiring general anaesthesia with direct laryngoscopy (Macintosh blade) and endotracheal intubation. Exclusion criteria include head and neck anatomical pathology, edentulous patients, smallmouth opening, limitation in head and neck flexion or extension, previous history of difficult intubation, pregnancy, and a body mass index (BMI) of >34.9 kg/m2.

Standard preanesthetic check-up was done 1 day before surgery.[20] Each patient was subjected to complete general physical and systemic examination, and detailed history was taken. Basic demographic characteristics, such as age, height, sex, weight and BMI, were noted. All relevant investigations were done, and the patient was kept 6-h fasting overnight. During this visit, the preanesthetic clinical and ultrasonographic airway assessment was done, include viewing the patient from lateral and anterolateral positions, viewing and palpating the neck anteriorly and laterally, extending and flexing the neck and head maximally, and examining the mouth opening, teeth, and oral cavity.

The USG assessment of the airway of all patients included in the study was done with high-frequency linear probe (GE Logiq E by GE Healthcare ultrasound system HFL 12 LRS/5-13 MHz transducer), and the same anesthesiologist measured the four ultrasonographic parameters. The patients were asked to lie down supine with maximal sniffing position. The probe was then placed longitudinally in the submandibular area in the midline. Without changing the position of the probe, the linear array of the USG probe was moved in the transverse planes from cephalad to caudal, that is, from a plane to see the mouth opening in coronal view to a transverse plane that bisects the epiglottis and posterior-most part of vocal folds with arytenoids obliquely in one two-dimensional view. The further movement of the USG array was ceased at the first simultaneous visualization (in the same ultrasonic frame) of the epiglottis and posterior-most part of vocal folds with arytenoids.

We noted some US-based parameters in this study, including the skin-to-epiglottis distance, i.e., the depth of the PES, the hyomental distance (HMD), the distance between hyoid bone and skin (DSHB), and the distance from skin to epiglottis midway (DSEM) between the hyoid bone and thyroid cartilage (DSEM) [Figure 1], [Figure 2], [Figure 3], [Figure 4].
Figure 1: Ultrasonography showing preepiglottic space (yellow line)

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Figure 2: Ultrasonography showing hyomental distance (yellow line)

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Figure 3: Ultrasonography showing distance between hyoid bone-skin (yellow line)

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Figure 4: Ultrasonography showing distance from skin-to-epiglottis midway (yellow line)

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On the day of surgery, all patients were treated similarly with the same technique and drug administration. The dose was adjusted to the respective body weight. Direct laryngoscopy and endotracheal intubation were carried out by anesthesia providers with considerable experience.[21] All the patients were put in the sniffing position with head extension and neck flexion. The Macintosh blade of appropriate size was used to expose the target larynx, and no external laryngeal pressure was used to facilitate this process.

During the intraoperative direct laryngoscopy, the anesthesia providers recorded the Cormack and Lehane (CL) grading for the VC view during direct laryngoscopy.[22] Outcome measures included the demographic variables and their association with DL and predictive accuracy, which includes sensitivity (Sn), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV) of USG parameters for DL.

The data analysis was carried out using the Statistical Package for Social Sciences (SPSS) version 21.0. (IBM Corp. Released 2012. IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY, USA: IBM Corp.) Categorical variables were presented in number and percentage, and continuous variables were presented as mean ± standard deviation and median. The Kolmogorov–Smirnov was used to test the normality of data. If the normality was rejected, then the nonparametric test was used. Quantitative variables were compared using the independent t-test (or Mann–Whitney test when the data sets were not normally distributed) between the two groups. Qualitative variables were correlated using the Chi-square test. Receiver operating characteristic curve was used to find out the cut off point of parameters for predicting DL. A diagnostic test was used to calculate Sn, Sp, PPV, and NPV. Comparison of receiver operating characteristic (ROC) was performed to find out any significant difference in the area under the curve (AUC) between USG and clinical. A P < 0.05 was considered statistically significant.


  Results Top


Mean age of the patients was 50.03 years with a mean weight and BMI were 67.09 kg and 25.96 kg/m2, respectively. As per CL grading, DL was noted in 22.50% patients (Grades 3 and 4) and easy laryngoscopy was seen in 77.5% patients (Grades 1, 2a, and 2b), as presented in [Table 1].
Table 1: Demographic and clinical characteristics

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Mean age of the patients [Table 2] with DL was comparable to that of easy laryngoscopy (54.59 vs. 48.71, P = 0.055). The number of females and males were also similar in both groups (P = 0.668). Mean weight in the patients with DL was comparable to that of easy laryngoscopy (65.63 vs. 67.52, P = 0.423). BMI was also similar in both groups (25.76 vs. 26.02, P = 0.748). [Table 3] shows that compared to patients with easy laryngoscopy, those with DL had lesser HMD (4.55 vs. 4.96, P = 0.002), comparable DSHB (1.51 vs. 1.56, P = 0.826), comparable DSEM (2.24 vs. 2.21, P = 0.8) and comparable PES (1.41 vs. 1.36, P = 0.523).
Table 2: Association of demographic parameters with laryngoscopy

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Table 3: Association of ultrasound parameters with laryngoscopy

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A ROC curve was plotted, showing the performance of all USG parameters at various thresholds to determine true positive rate and false positive rate for DL [Figure 5]. The analysis showed that mean Sn, Sp, PPV, and NPV of HMD was 48.15%, 86.02%, 50%, and 85.1%, respectively; of DSHB was 74.07%, 15.05%, 20.2%, and 66.7%, respectively; of DSEM was 70.37%, 13.98%, 19.2%, and 19.2%, respectively; and of PES was 55.56%, 59.14%, 28.3%, and 82.1%, respectively [Table 4]. The best diagnostic performance in our study was the HMD with the highest AUC of 0.684.
Figure 5: Receiver operating characteristic curve for prediction of difficult laryngoscopy by ultrasonography parameters

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Table 4: Predictive ability of ultrasound parameters for difficult laryngoscopy

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  Discussion Top


The mean age of the patients in our study was 50.03 ± 14.05 years. Majority of the patients (50.00%) were in the age group of 41–60 years. In our study, the baseline characteristics between easy and DL population were comparable. The comparability ensured that differences seen in the measured parameters are subject to the minimal bias.

We used the CL grading and found that 27 (29%) patients had difficult intubation and 93 had easy intubation. As compared to our study, the rates varied among different studies.[3],[4],[5],[6],[7],[22],[23],[24]

We found that patients with difficult intubation had lower HMD (P = 0.002), comparable DSHB (P = 0.826), comparable DSEM (P = 0.800), and comparable PES (P = 0.523) our findings were in line with the study by Yadav et al.[25] where USG measurements of anterior soft tissue neck were found to be significantly higher in DL group with P = 0.0001. Adhikari et al.[3] found that thickness of ANS tissue at the hyoid bone and the thyrohyoid membrane was higher in patients with the DL. Similarly, Wu et al.[19] reported that USG measurement at the level of the hyoid bone, thyrohyoid membrane, and anterior commissure could independently predict DL.

Our study found that the highest Sn to predict DL was DSHB (74.07%) and the highest Sp was HMD (86.02%). The highest PPV and NPV was HMD (50% and 85.1%, respectively) for predicting DL. Compared to our study, Parameswari et al.[5] found that the skin-to-epiglottis distance was the most sensitive (75%) and most specific (63.6%) in predicting DL.[5] Yadav et al.[25] reported that the highest Sn was tongue-thickness. In another study, Reddy et al.[18] reported that the ANS-VC had the highest Sn. Yao and Wang[7] reported that the highest Sn, Sp, PPV, and NPV were the inter-incisor distance, the ratio of tongue thickness to thyromental distance, the ratio of tongue thickness to thyromental distance, and inter-incisor distance, respectively. Senapathi et al.[26] reported that the skin-to-epiglottis distance of >26.05 is a risk factor for difficult intubation.

Since there is always a trade-off between Sn and Sp, it is reasonable to take AUC in the account. In the present study, the area under the ROC curve (AUC) was highest for HMD (cutoff ≤4.34). Previous publications reported different results for AUC of the most reliable predictive parameter.[5],[25],[26] Thus, no single USG parameter can be suggested as an alternative to clinical tests for predicting DL. Rather a combination of USG measurements of soft tissue thickness of anterior neck at the hyoid and thyrohyoid level and tongue thickness may impart a better prediction.

Our results must be interpreted with some limitations. The experience of the person performing laryngoscopy can influence the view and grading of laryngoscopy. In addition, the amount of pressure that was applied by the USG probe can lead to a difference in value.


  Conclusion Top


DL is common, as seen in 22.5% of our patients. US is a novel modality for predicting the DL, especially HMD, which showed the highest AUC among DSHB, DSEM, and PES. The USG measurements of soft-tissue thickness of the anterior neck and tongue thickness along with the clinical assessment of airway can be useful in predicting DL.

Acknowledgment

We would like to thank Dr Ketan Garg and Dr Anchal Kaushik for assistance in medical writing and editing. We thank Ms Bhawna Garg for assistance in statistical analysis.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

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