Laryngeal mask placement in a teaching institution: analysis of difficult placements

Introduction

Since its introduction into clinical practice in 1983¹, the laryngeal mask airway (LMA) has found a place in everyday anesthesia practice^2–4, including its use as a primary airway device in the elective or pre-hospital emergency settings, as well as a rescue airway device in either settings^5,6. Additionally, the LMA placement has become a common airway management technique, particularly in ambulatory surgery^2,3, and is associated with shorter recovery time, earlier patient discharge and lower associated costs^7,8. Even if the LMA is considered a very safe airway device⁹ with a low incidence of complications, there may be situations where it either does not function properly or is difficult to place¹⁰. Importantly, the association between difficult LMA placement and increased incidence of Difficult Mask Ventilation (DMV) has been recognized¹¹.

Appropriate sizing is critical for correct LMA application¹², while the selection of the device type seems to play a less significant role, yet the prediction of the correct size is not easy. This can be attributed to the absence of a coherent and universal standard sizing system¹³. Most of the manufacturers suggest a weight-based size selection, however there is no consistency between weight and oropharyngeal anatomy¹⁴.

Alternative recommendations for the selection of the appropriate size of a LMA, regarding age, height and gender, as well as anatomical landmarks, are still under investigation^15–17.

As a result, the concepts of difficult LMA placement and effective usage have prompted new research, focusing on the prediction of difficult LMA placement¹⁸.

A simple, objective, predictive score to identify patients at risk of difficult LMA placement at the bedside does not currently exist, however to achieve such score a comprehensive airway assessment based analysis of risk identification needs to be accomplished first. Based on recorded outcomes at a major teaching hospital that utilized a comprehensive airway assessment¹⁹ we aimed to identify predictive factors for difficult LMA placement.

Methods

Data for this retrospective analysis were derived from a database of airway assessments, management plans, and outcomes collected prospectively from August, 2008 to May, 2010 at a Level 1 academic trauma center (Memorial Hermann Hospital, Texas Medical Center, Houston, TX, USA)¹¹. The study was sponsored by an educational grant from the Foundation for Anesthesia, Education and Research (FAER), and other educational funds from the Department of Anesthesiology at University of Texas Medical School at Houston. After obtaining IRB approval, (HSC-MS-07-0144) all non-obstetric adult patients presenting for elective surgery requiring general anesthesia were enrolled in this study (n=8364). All uLMA placements were carried out by anesthesiology residents. In the ‘mother study’, residents were randomized into two groups—an experimental group, which used a comprehensive airway assessment form^11,20 in addition to the existing anesthesia record, and a control group, which used only the existing anesthesia record. For the purpose of the present analysis, only the experiment (n=2348) group data was utilized, since the comprehensive airway assessment needed to be linked to the airway device that was utilized. We identified 110 cases-used of LMA, disposable laryngeal mask (uLMA, North America, San Diego, CA), and 69 of those as primary airway device, which we utilized for our analysis. Difficult LMA placement was defined as either inability to physically place a LMA device or inadequacy of ventilation, oxygenation, or airway protection after placement that required conversion to an alternative technique. The level of difficulty and the number of attempts of the uLMA placement were documented by the anesthesiology residents.

Statistical analysis

Sixty nine uLMA placements were completed and an analysis was performed (based on “per protocol” and not intention to treat). The mean and standard deviation were used to summarize continuous variables, and frequency (percentage) was summarized for categorical variables. A two-tailed sample t-test was applied to compare continuous variables and Chi-square or Fisher exact tests as appropriate were performed for categorical variables between patients with or without uLMA placement difficulty. Using multivariate logistic regression models, the variables associated with uLMA placement difficulty were identified. All variables with a p-value ≤0.25 in univariate analysis and variables of known biological importance (e.g., age and BMI) were entered into a full model. A backward selection method was used to identify significant independent predictors. A receiver-operating-characteristic (ROC) area under the curve was also calculated to evaluate the resulting model’s predictive value, (Figure 1) as well as adjusted odds ratios and their 95% confidence intervals. Continuous variables were included after the dichotomization and the best cut-off was determined by maximizing the sum of sensitivity and specificity using the ROC curve. Age distribution for our population was assessed by using descriptive statistics including mean, standard deviation, and median values. All statistical analyses were conducted using SAS 9.3 (SAS Institute, Cary, NC, USA). A p-value <0.05 was considered significant.

Figure 1. A receiver-operating-characteristic (ROC) curve evaluating the sensitivity and specificity of preoperative independent risk factors for LMA difficulty.

Two independent predictors for LMA difficulty were identified using logistic regression: Female and NeckCirc of 44 or greater. The area under the curve was 0.69. The area under the curve was calculated to evaluate the resulting model’s predictive value. The adjusted odds ratios and their 95% confidence interval were calculated. Continuous variables were included after the dichotomization and the best cut-off was determined by maximizing the sum of sensitivity and specificity using the ROC curve. Analyses were conducted using SAS 9.3 (SAS Institute, Cary, NC, USA).

Results

Patient demographics are presented in Table 1 and Table 2. Of the airway evaluations performed using a comprehensive airway assessment tool 69 LMAs were utilized as a primary airway device (Table 3). Of these, 67 were successful (97.1%) and 2 were unsuccessful (2.9%), with 17 (24.6%) uLMA placements considered as difficult (Table 4). Multivariate logistic regression models identified two independent predictors of difficult airway: gender and neck circumference (Table 5). The risk of difficult LMA placement was significantly higher for female patients and patients with a neck circumference (≥44 cm). The model’s c-statistic score is 0.69 (Table 6). When at least one of two identified risk factors as a cut-off for predicting difficult LMA placement is present, the sensitivity is 87.5% and the specificity is 50%. If we use two risk factors as a cut-off, the specificity increases to the level of 98% and sensitivity is 63% (Table 5).

Discussion

In the present investigation, risk factors in 69 LMA primary airway management placements were assessed. The incidence of difficult LMA placement in our study was 24.6% and the LMA failure rate was 2.9%. Moreover, the incidence of failed LMA placement in our study is consistent with previous studies^{9,13,18,21,22}, ranging from 0.19 to 4.7%.

Although from a large database, the study resulted only in a few placements, which is consistent with the practice of our teaching academic center and that could give a possible explanation to the increased incidence of difficult LMA placement in our study. Beside the limited number of uLMAs utilized electively, the study provides an interesting perspective on predictive factors pertaining laryngeal mask placement: indeed, two independent risk factors were found, neck circumference ≥44 cm and female gender. A predictive score that would assist the clinician in identifying difficult LMA placement was also developed, resulting in a model with low sensitivity but specificity of 98% and a negative likelihood ratio of 95.6% (for instance, excluding difficult LMA placement in male patients with neck circumference <44 cm).

The current study supports previous findings regarding the correlation of obesity and difficult airway^23–26, since increased neck circumference is also an independent risk factor for difficult mask ventilation (DMV) and difficult intubation. The most interesting finding of this study is that female gender, rather than male gender is associated with difficult LMA placement in this study population. In contrast, Ramachandran et al. found that male gender was a predictive factor for failed LMA placement^13,18.

Age distribution of our population was considered as a cause for this difference. Indeed, age distribution of our female population could be associated with an increased proportion of postmenopausal women. Previous studies have demonstrated that the prevalence and severity of Obstructive Sleep Apnea (OSA) is increased in postmenopausal women, as compared to pre-menauposal women, which may be related to functional changes²⁷. However, history of OSA was not an independent predictive factor in our population. This can be attributed to the retrospective nature of our study, where OSA assessment was assessed only by patient history. Of interest, a recent but unpublished study has highlighted that the female gender was a predictor for difficult LMA placement in a study population of more than 400 patients, where LMA placement was performed by a single skilled clinician²⁸.

Of the other airway variables that were evaluated in our study, none was identified as an independent predictor of LMA failure: this finding differs from that of Ramachandran et al., who recognized the absence of teeth as an independent predictor of LMA failure, and the differences could be attributed to population included in the two studies, particularly the limited number of outcomes of our study, possible underutilization of the LMA as a primary airway device, as compared to other airway devices, the increased incidence of difficult LMA placements in our population, and the placements by trainees. Discussing the limitations of the present investigation, it is necessary to mention the retrospective nature as well the stepwise selection that may contribute to bias the study, and the subjective nature of the definition of difficult LMA placement. Additionally, we assumed that all anesthesiology residents had similar educational skills based on a previous study¹⁹, which also could have affected our findings.

In conclusion, two risk factors for LMA placement difficulty were identified: female gender and large neck circumference. Considering the airway as an entity, neck circumference is being increasingly recognized as a significant predictive factor for difficulty with airway management, especially when it is considered across the spectrum of difficulties.

Data availability

Data have been obtained from databases at the Memorial Hermann Hospital, Texas Medical Center, Houston, IRB approval HSC-MS-07-0144. The author can support applications to the Institutional Board to make the data accessible upon individual request. Please forward your requests to Davide Cattano.