European Journal of Cardiovascular Medicine

Airway management is an essential component of clinical anaesthesia, and involves maintenance of patent airway to facilitate gas exchange via mask ventilation or airway device. A significant aspect of airway management is assessment of patient’s airway to predict the ease or difficulty with bag mask ventilation or with laryngoscopy and intubation, enabling the anaesthesiologist to prepare for this challenging scenario. A difficult airway.is defined as one, in which.there is difficulty in mask ventilation, laryngoscopy or intubation. The ASA Task force defined difficult mask ventilation as when it is not possible for the anesthesiologist to provide adequate ventilation because of one or more of the following problems: inadequate mask or SGA seal, excessive gas leak, or excessive resistance to the entry and exit of gases. Difficult Laryngoscopy is most commonly defined as Cormack-Lehane (CL) grade 3 or 4 on direct laryngoscopy. It defined difficult intubation as occurring when proper insertion of the ET tube with conventional laryngoscopy required multiple attempts, with or without any tracheal pathology.[1,2]

From the time of introduction of ET intubation, several problems have occurred due to failed intubation. Majority (85%) of airway related events involve brain damage and one third of this mortality was attributable completely to anesthesia. This was related to difficulty in maintaining a patent airway in these patients. Many methods have been introduced since then to overcome these problems and identify the patient who will be difficult to intubate.[3] Various bedside airway assessment tests are available, but are highly subjective and have a moderate sensitivity and specificity. Initially the preoperative airway assessment was done by single factors like Mallampatti’s classification, thyromental distance etc. Higher the Mallampatti score; difficult the mask ventilation. Wilson’s scoring is a.relatively new clinical scoring which includes weight, inter-incisor gap, neck and jaw movements, mandibular recession, absence or presence of buck teeth. However, inspite of these clinical factors, there have been instances when a patient predicted to have an easy intubation had a difficult one and vice versa.[1,3]

The CL grading observed during direct laryngoscopy is a reliable predictor of difficult intubation, but due to its invasive nature, it is difficult to carry it out in an awake patient during pre-anesthetic airway assessment. In the last few years, USG has been gaining popularity and practical applicability in the hands of anesthesiologist as a non invasive painless modality for airway assessment. USG is used to assess tissues in close proximity to the larynx as observed during direct laryngoscopy. It is safe, quick, repeatable, portable, widely available and gives real-time dynamic images. Ultrasound is as efficacious as CT scan in quantifying all dimensions of airway structure. During direct laryngoscopy, introduction of the laryngoscope blade into the mouth displaces pharyngeal structures. Increased anterior.soft tissue.thickness could impair the forward mobility of these pharyngeal structures.[4,5]

Predicting.a difficult.airway in pre-operative period, helps an anesthesiologist to stay well prepared to encounter difficulty during bag and mask ventilation, direct laryngoscopy and ET intubation. Preparation for difficult airway management includes keeping the patient and relatives informed about a suspected difficult airway, availability.of equipment for management of difficult airway (stylet, bougie, SGA, fiberoptic bronchoscope and in worst case scenarios, cricothyrodotomy), an assistant to provide help while managing a difficult airway (e.g. providing external laryngeal manipulation) and  ensuring supplemental oxygen throughout the process of securing a difficult airway.

In this study conducted to.assessed the utility.of USG in predicting.difficult intubation, by measuring the USG_SET at the.level of Thyrohyoid Membrane, and compared it with the classical clinical airway assessment.

The study.was conducted in.the Department of Anaesthesiology at Government General Hospital, Guntur which is a tertiary care teaching hospital affiliated to Guntur Medical College, Guntur., After approval of ethical committee of institution, a total of 80 patients were enrolled for study and informed. consent was obtained from all the patients. It is a descriptive observational study done from February 2023 to February 2024.

Inclusion Criteria: ASA grade I / II, Age 18-60.years of either sex, undergoing elective surgery under General anaesthesia.

Exclusion Criteria: Patients with, Mouth opening < 3cm, ASA grade III/IV, pregnant females, having any head or neck pathology, restricted neck movement, risk for gastric aspiration, and edentulous patients and patients having artificial denture

Pre Anaesthetic Assessment

After taking the informed written consent from all the patients, the study was proceeded in following manner:

Each patient was visited on the day before surgery. General, physical and systemic examination was carried out. Pre-operative investigations were done according to protocol set by Department of Anaesthesia for routine pre-aesthetic clinical examination.  Patients were assigned an ASA class. Written and informed consent was obtained from all the patients fulfilling the inclusion criteria by explaining the details of study in their own language in the. presence of a witness.

All patients were kept fasting for 6 hours prior to surgery. Pre-medication was given in form of tablet alprazolam (0.25 mg) and tablet ranitidine (150 mg) per oral, a night before and two hours prior to surgery with sips of water. On the day of surgery the patients were explained about the procedure and after obtaining informed written consent, the measurements were made and recorded Height, Weight, Modified Mallampatti's classification, Wilson’s Score and USG measurement of thickness of soft tissue in anterior neck at the level of Thyrohyoid membrane.

The patient was asked to lie down supine with a 10 cm pillow under the neck. Patient was then instructed to keep the mouth closed and to take slow breaths during measurements to minimize errors in recordings due to movements during respiration.

The following controls were set in the USG machine for obtaining the airway assessment measurements and images Transducer - Linear High frequency transducer, Axis/Plane - Short axis/Transverse plane, Frequency - 11 MHz , Depth - 3.0 cms - 4.0 cms, Gain-20-30.

The Epiglottis was identified at Thyrohyoid membrane level as a linear hypoechoic structure followed by a hyperechoic shadow.17,32 Measurement was taken from skin to epiglottis and noted down on the Patient proforma sheet.

Anaesthesia Technique

On arrival in the operative room, intravenous line was secured with appropriate size cannula and crystalloid infusion was started according to fasting status.

Monitoring of NIBP, ECG, HR, SpO2, EtCO2 was done on Blease Sirius Anaesthesia machine, Spacelab monitor UltraviewSL. These recordings were taken as a baseline parameter for the study.

The patient was induced as per the patient profile. After giving muscle relaxant, the patient was positioned on the same 10 cms pillow used earlier for USG assessment.

The operating table was then positioned so that the patient’s face was at the level of the Xiphisternum of the anesthesiologist performing laryngoscopy and intubation.

Preoxygenation was done, followed by laryngoscopy using a Macintosh blade (size 3 for females and size 4 for males). Laryngoscopy was done by an anesthesiologist, with an experience of at least 50 intubations.

The CL grading was noted, without any external laryngeal pressure. Orotracheal intubation was performed after visualizing the glottis. A standard oral tracheal tube was used (size 7 for females and size 8 for males).

Statistical Methods

Our estimated sample size was based on the comparison between USG Guided Airway assessment and Clinical Airway assessment for prediction of difficult airway. With reference to a similar study by Parmeswari et al, we defined a relevant clinical difference of 20% between USG and clinical airway assessment for successful prediction of difficult airway. Thus, a sample size minimum of 80 patients provided a power of 80% for detecting a significant difference at an alpha level of 0.05.

The formula used to calculate sample size was -

n = [z1-α/2.√2P(1-P) + z1-β.√{P1(1-P1) + P2(1-P2)}]2 (P1-P2)2

= [1.645*0.693 + 0.842*0.678] 2 (0.20) 2

= 2.93/0.04 = 73.2

where Zα/2 is the critical value of the Normal distribution at α/2 (e.g. for a confidence level of 95%, α is 0.05 and the critical value is 1.96), Zβ is the critical value of the Normal distribution at β (e.g. for a power of 80%, β is 0.2 and the critical value is 0.842) and P1 and P2 are the expected sample proportions of the two groups.

With an attrition rate of 10%, the final sample size was 80 patients.

Statistical testing was conducted with the statistical package for the social science system version SPSS 17.0. Continuous variables were presented as mean±SD or median (IQR) for non normally distributed data. Categorical variables were expressed as frequencies and percentages. The comparison of normally distributed continuous variables were performed using paired t test. Nominal categorical data between the groups were compared using Chi-squared test or Fisher’s exact test as appropriate. Non-normal distribution continuous variables were compared using Mann Whitney U test. A receiver operating characteristics (ROC) analysis was calculated to determine the area under the curve and its standard deviation (AUC _ SD), the sensitivity, and the specificity, PPV, NPV to analyze the diagnostic value of USG Guided Airway assessment and Clinical Airway assessment in prediction of difficult airway. For all statistical tests, a p value less than 0.05 was taken to indicate a significant difference.

During the study period 80 patients who met the inclusion criteria were selected for this study. These patients were aged between 18 and 60 years of which 58 were females and 22 were males. 40 patients had CL.grade 1, 21 patients had CL grade 2, 19 patients had CL Grade 3.and 0 patients had CL grade 4. Using the CL grade during direct laryngoscopy, the patients were divided in two groups – 61/patients in the easy group (Group E) and 19 patients.in the difficult group (Group D).

There. Was a higher relative percentage of males in the difficult laryngoscopy group as compared to easy laryngoscopy group. However, this difference was not statistically significant. (p value 0.141)

Table-1: Patient Demographics

Hence Age, Height, Weight, BMI, and Neck circumference had no statistically significant association with difficult laryngoscopy and they were divided in both groups equally.

Regarding the USG measurements, patients with difficult laryngoscopy had significantly greater USG_SET (1.82 ± 0.32 vs 1.46 ± 0.20 p=<0.001)

Based on ROC curve the cut off point that delineates Group E and Group D for USG_SET is 1.67 cm. Area under the curve is 0.852

Out of the total number of cases in the study the number of cases above the cut off point are 21 and less than cut off are 59. This states that on the basis of cut off point 21 cases are predicted to be difficult intubation but based on CL grading, only 19 cases were categorized in Group D.

Similarly 59 cases were predicted in easy intubation group (Group E) but based on CL grading 61 cases belonged to Group E. Based on this data Sensitivity and Specificity were calculated for USG SET. Cut off point 1.67 cm. AUC = 0.852 Sensitivity = 78.9% Specificity  = 90.2% .

Table-3: MMPC correlation with CL grade

Statistically.significant differences were found in classic preoperative.airway assessment test MMPC, which was higher.in patients with difficult laryngoscopy (p =0.019). The optimal cut. Off value (with specificity and sensitivity in parentheses) for MMPC was 2 (42.1%,86.9%). 

Table-4: Wilson’s score correlation with CL Grade

On the other hand, the association of difficult laryngoscopy with clinical preoperative airway assessment Wilson’s score did not turn out significant (p value 0.294). The optimal cutoff values (with specificity and sensitivity in parentheses) Wilson’s score to predict difficult laryngoscopy more than 4 (21%,83.6%) respectively.

Table-5: Correlation of Age, BMI, Neck Circumference, MMPC and Wilson’s score with USG SET

The correlation between USG SET and age is 0.402. This means the correlation is positive. P value is <0.001 which is significant.

The correlation between USG SET and age is 0.303. This means the correlation is positive. P value is 0.006 which is significant.

Despite recent developments, anaesthesiologists face a significant problem when dealing with unanticipated difficult airways. There are a number of traditional approaches for predicting difficult laryngoscopy, but none of them are 100 percent sensitive or specific for predicting a difficult airway.  Airway ultrasound imaging is a relatively new addition to anaesthetists’ toolkit and it has improved care in a number of ways. It is useful in diagnosing upper airway diseases, confirming placement of an ET tube, predicting double lumen tube size, paediatric ET size, percutaneous tracheostomy or cricothyroidotomy guidance, nerve blocks to enable awake intubation, and also for airway assessment to predict difficult laryngoscopy. With no recognized USG standard parameters to predict difficult laryngoscopy, its role in airway assessment is still primitive. Hence this study was conducted to determine the usefulness of USG in predicting a difficult airway.

The patients in our study were on average 41 years old. The majority of the patients were between the ages of 35 and 45. The mean age of patients in Group E was 41.31 ± 10.27 years and in Group D was 41.37 ± 13.48 years (p value = 0.937) Hence the difference is statistically insignificant. The average weight of the patients in Group E was 63.13 ± 8.67 kgs and in that of Group D was 63.89 ± 10.35 kgs (p value =-0.750). The average height of patients both in Group E and Group D in our study was 1.60 m. (p value = 0.765. BMI in Group E was 34.70 ± 3.45 kg/m2 and in Group D was 34.82 ± 3.86 kg/m2 with a p value of 0.900. The average neck circumference of patients in Group E was 36.80 cm and in Group D was 37.04 cm with a p value of 0.511 . There was a higher relative percentage of males in the difficult laryngoscopy group as compared to easy laryngoscopy group. (23% Males in Group E and 42% Males in Group D). Hence, in our study, the demographic and anthropometric distribution of patients in easy and difficult laryngoscopy patients, such as age, weight, height and BMI were comparable. This guaranteed that the differences seen in the measured parameters were free of bias.

In our research, we discovered a strong correlation of USG_SET with CL grade on direct laryngoscopy. The USG SET cutoff limit for difficult laryngoscopy was > 1.67 cm, with a sensitivity of 78.9% and a specificity of 90.2 percent, according to our findings. Our findings were in line with those of Wu[6], Nazir[7], and Abdelhady[8], who used a similar cut-off point. The USG SET cutoff point > 1.77 cm in Nazir's study on 90 Indian patients with 19 difficult laryngoscopies exhibited a sensitivity of 78.9% and specificity of 76.3 percent.

They included measurement of pre-epiglottic space(PES), distance between epiglottis and vestibular ligaments(EVL) distance from skin to hyoid bone(DSHB) and distance from skin to epiglottis at level of Thyrohyoid membrane(DSEM) as their ultrasound parameters. Only DSHB and DSEM (USG_SET) exhibited significant correlation with CL grading. They found a weak positive correlation of DSEM with MMPC which was similar to our study.[1]

Wu's research included 203 Chinese patients and had 28 difficult laryngoscopies. They concluded that Anterior neck soft tissue thicknesses measured by USG at the hyoid bone, Thyrohyoid membrane (USG_SET) and anterior commissure levels are independent predictors of difficult laryngoscopy and a USG_SET >1.78 cm can be used to predict difficult laryngoscopies. Abdelhady et al[8] studied an Egyptian population of 80 patients who had undergone 15 difficult laryngoscopies, with a specificity of 70.8 percent and sensitivity of 80 percent for a USG SET value >1.85 cm. They also used a single USG parameter i.e. USG_SET in their study, similar to our study.

In our study, we used the optimal sniffing posture during USG to reproduce the settings during laryngoscopy, which had not been explored in prior studies. These results were however much lower than results from other studies. Mirunalini et al[9] included 150 Indian patients with 11 difficult laryngoscopies. They included MMPC, Thyromental distance and inter-incisor gap as their clinical parameters of airway assessment and anterior cervical soft tissue at hyoid bone, Thyrohyoid membrane(USG_SET) and suprasternal notch as their USG parameters. They demonstrated that the USG_SET has cutoff point of 2.33 cm for difficult laryngoscopy with 100% sensitivity and 99.3% specificity which was a much higher cut off than in our study. Shi et al[10] studied 71 Chinese patients and found that the USG-SET had a cutoff point of 2.36 cm for difficult laryngoscopy, with 96.43 percent specificity and 60% sensitivity.

Adhikari’s[11] study included 51 African-American patients, of which six were categorized as difficult laryngoscopy. He used USG measurements of anterior neck tissue at level of hyoid and Thyrohyoid membrane and concluded that USG_SET cut off point for difficult laryngoscopy was 2.8 cm. Martinez-Garcia et al[12] did their research in 2020 on 50 Spanish patients who had 16 difficult laryngoscopies (32%). Clinical airway assessment tests were compared with ultrasound measurements of the neck soft tissue from skin to hyoid (DSH), epiglottis (DSE) and glottis (DSG) were obtained, as well as two measurements derived from the above: DSH + DSE and DSE − DSG They discovered that out of all the parameters DSE(USG_SET) of 3 cm had 56.3 percent sensitivity and 88.2 percent specificity in predicting a difficult laryngoscopy. This value was much higher than our cut off value.

This difference in range of cut off value may be due to the ethnicity of the subjects being studied. Our study was done on Indian subjects, in contrast, Shi et al[10] conducted their study on Chinese patients while Adhikari et al[11] studied Whites and African Americans.

More disparities were found in Parameswari's [13]results, which were inconsistent with those of the others. 130 Indian patients with 12 difficult laryngoscopies were included in Parameswari's [13] study. Patients with a USG SET of less than 1.8 cm were observed to be difficult, while those with a distance of more than 1.8 cm were easy, according to the study, which had a sensitivity of 75 percent and a specificity of 63.6 percent.

As a result, there are large differences in study outcomes, which could be attributable to a lack of defined USG scanning techniques and differences in USG experience among investigators. Furthermore, the CL grade may be influenced by the skill of the person performing laryngoscopy, as well as any external laryngeal manipulation used to improve the CL grade. The CL grade was determined, in our study. based on the view obtained prior to any external laryngeal manipulation.

In terms of clinical airway screening tests, we found that MMPC > 2 was a good predictor of difficult laryngoscopy (p value = 0.019) while Wilson Scoring was not (p value 0.294). Our findings were consistent with those of Reddy et al[14] who found out that MMPC > 3 could reliably predict difficult intubation (p value <0.001) and Yadav et al [15] who found MMPC > 3 was a good predictor of difficult laryngoscopy (p value 0.005). However, according to two recent systematic reviews, the most commonly used tests, such as MMPC and TMD measurement, have limited to moderate accuracy and inconsistent ability to distinguish between patients with difficult and easy airways. The large variation could be attributable to the groups' demographics as well as anthropometric variations between populations.

In our study, variables like experience of anaesthesia providers, laryngoscopy equipments used, external laryngeal manipulation and view of glottis, were controlled. These variables were standardized by implementing the following: anaesthesia providers with experience of more than 50 intubations intubated all the patients, standard Macintosh blade size 3 was used for all female patients and size 4 for all male patients and first view of glottis before any external laryngeal manipulation was used to record CL grade.

There were some limitations in our research. Only one ultrasonographic parameter was measured, and the sample size was small. One investigator obtained the USG measurements, which could have resulted in some bias. The easy and difficult laryngoscopy groups were uneven, with no patient in CL grade IV. Future research needs to address these limitations. A greater sample size, paired with a documented USG scanning methodology that specifies the measures to be acquired as well as the optimal technique for obtaining the measurements, would improve predictive value and increase the accuracy of the results. As a result, consistent research is needed to link USG to the prediction of difficult airway.

In conclusion, our research found that USG SET has a strong link with CL grading and that it is superior to clinical airway tests (such as MMPC and Wilson's score) in predicting a difficult laryngoscopy. Incorporating this parameter into clinical practice could improve our capacity to predict a difficult laryngoscopy.

Pre-operative evaluation of the patient's airway to forecast potential difficulties during bag and mask ventilation, laryngoscopy, or intubation is an important part of clinical anaesthesia. When compared to traditional clinical airway evaluation tests like the MMPC or Wilson's score, USG is gaining favour as a non-invasive, rapid, repeatable, and reliable technique for airway assessment.

This was a descriptive observational study conducted on 80 patients undergoing elective surgery under general anaesthesia. Preoperative clinical and ultrasonographic airway assessments were carried out to predict difficult airway and were correlated with CL grade noted at direct laryngoscopy.

In conclusion, USG can be used to predict difficult airway preoperatively by measuring soft tissue thickness at neck and Skin to epiglottis distance at the level of Thyrohyoid membrane on USG is a potential predictor of difficult intubation. 

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