Predictive factors for difficult XXXX ventilation in the @entity28 surgical population.

@entity1 @entity28 @entity26 @entity18296 @entity40236
Background Difficult @entity40236 Ventilation ( @entity18296 ), is a situation in which it is impossible for an unassisted anesthesiologist to maintain @entity26 saturation >90% using 100% @entity26 and positive pressure ventilation to prevent or reverse signs of inadequate ventilation during @entity40236 ventilation.   The incidence varies from 0.08 - 15%. @entity1 -related anatomical features are by far the most significant cause.   We analyzed data from an @entity28 surgical population (BMI> 30 kg/m (2)) to identify specific risk and predictive factors for @entity18296 . Methods Five hundred and fifty seven @entity28 @entity1 were identified from a database of 1399 cases associated with preoperative airway examinations where @entity40236 ventilation was attempted. Assessment of @entity40236 ventilation in this group was stratified by a severity score (0-3), and a step-wise selection method was used to identify independent predictors.   The area under the curve of the receiver-operating-characteristic was then used to evaluate the model's predictive value. Adjusted odds ratios and their 95% confidence intervals were also calculated. Results @entity18296 was observed in 80/557 (14%) @entity1 . Three independent predictive factors for @entity18296 in @entity28 @entity1 were identified: age 49 years, short neck, and neck circumference   43 cm. In the current study th sensitivity for one factor is 0.90 with a specificity 0.35. However, the specificity increased to 0.80 with inclusion of more than one factor. Conclusion According to the current investigation, the three predictive factors are strongly associated with @entity18296 in @entity28 @entity1 . Each independent risk factor alone provides a good screening for @entity18296 and two factors substantially improve specificity. Based on our analysis, we speculate that the absence of at least 2 of the factors we identified might have a significant negative predictive value and can reasonably exclude @entity18296 , with a negative likelihood ratio 0.81.
