[Study on the association of imaging and clinical anatomic data in the prediction of difficult intubation]

Difficult intubation is a serious challenge for emergency doctors and anesthesiologists.

This study was aimed at investigating the effectiveness of imaging methods combined with clinical anatomic data in predicting difficult intubation by developing a score as thorough and easy to use as possible.

This prospective study was carried out on a series of 121 patients (51 males and 70 females), aged between 18 and 85 years (mean age 45.5 years) in the interval September 2010 0 June 2011. The patients, scheduled for various surgical interventions requiring general anesthesia by oral tracheal intubation, were randomly selected and gave a written consent. Children and pregnant women were excluded. The criteria for clinical anatomic assessment and cerebral and cervical imaging methods were used in all patients. By corroborating these data, a difficult intubation prediction score, named OMLET, was developed. It included 5 parameters: obesity (IMC), Mallampati score (modified), position of the larynx as to the spine, cervicothoracic angle (CTA), and head extension (DTM). Each variable was attributed 0 or 2 points, the highest score being 10 points, the obtained score being directly proportional with the expected difficulty during oral tracheal intubation.

Of the 121 patients, 9 were difficult cases, the incidence of difficult intubation being 7.43%. The Cormack-Lehane score predicted a difficult intubation in 11 of the 121 cases (sensitivity 77.78%, specificity 96.43%), while the OMLET score predicted 6 of the 9 difficult intubations (sensitivity of 66.67%, specificity of 95.43%. positive predictive value 54.55%, and negative predictive value 97.27%).

The OMLET score proved effective in predicting difficult intubation expressed in its high specificity and sensitivity, and could be used especially in patients with conditions of the cephalic extremity and neck inevitably requiring before surgery investigation of these areas.