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

Abstract

Background: Laryngeal mask airway (LMA) placement is now considered a common airway management practice. Although there are many studies which focus on various airway techniques, research regarding difficult LMA placement is limited, particularly for anesthesiologist trainees. In our retrospective analysis we tried to identify predictive factors of difficult LMA placement in an academic training program.

Methods: This retrospective analysis was derived from a research airway database, where data were collected prospectively at the Memorial Hermann Hospital, Texas Medical Center, Houston, TX, USA, from 2008 to 2010. All non-obstetric adult patients presenting for elective surgery requiring general anesthesia, were enrolled in this study: anesthesiology residents primarily managed the airways. The level of difficulty, number of attempts, and type of the extraglottic device placement were retrieved.

Results: Sixty-nine unique Laryngeal Mask Airways (uLMAs) were utilized as a primary airway device. Two independent predictors for difficult LMA placement were identified: gender and neck circumference. The sensitivity for one factor is 87.5% with a specificity of 50%. However with two risk factors, the specificity increases to the level of 93% and the sensitivity is 63%.

Conclusion: In a large academic training program, besides uLMA not been used routinely, two risk factors for LMA difficulty were identified, female gender and large neck circumference. Neck circumference is increasingly being recognized as a significant predictor across the spectrum of airway management difficulties while female gender has not been previously reported as a risk factor for difficult LMA placement.

Keywords: LMA; airway management; anesthesia; neck circumfrence.

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).