Use of Anthropomorphic Measures to Predict Correct Tracheal Tube Placement Following Intubation

Background:

Endotracheal tubes (ETT) must be properly placed to protect airways, avoid accidental dislodgment, and provide ventilatory support. Infants and small children have short tracheal length complicating proper initial ETT positioning. We sought to develop, internally validate and establish safety, and feasibility of a regression model to determine depth of ETT insertion. We hypothesized that the predictive equation will facilitate correct initial ETT placement compared to PALS guidelines.

Methods:

We recorded height, weight, age, gender, ETT internal diameter (ID) and cm marking at lip from the electronic record from a random subset of 2,000 initial chest radiographs (CXR) obtained 01/01/09 - 05/05/12. A multivariable linear regression model was constructed, refined and validated by non-parametric bootstrapping technique using unrestricted random sampling methods. A prospective pilot study of subjects age 0 – 18 years admitted to pediatric intensive care unit, requiring invasive mechanical ventilatory support from 1/7/19 – 5/31/19 was conducted. Subjects with spinal and/or skeletal malformations, for whom a post-intubation CXR was not ordered, or whose CXR quality impaired visualizing the carina and ETT tip were excluded. The validated regression equation, Lip Mark ∼ 0.8636 * Height 0.6223 determined insertion depth. Initial CXR following intubation determined ETT position. Demographic data was summarized and a One Sided, One-Sample Binomial Test of Proportions was used to assess if proportion of correct position was greater by predicted lip mark calculation than by lip mark. Analyses completed using R and SAS for this IRB approved protocol.

Results:

450 subjects were included in the random subset for model construction. Unrestricted random sampling created 10,000 independent samples used for internal validation. Bias between the bootstrap coefficients and refined model estimates were negligible (< 0.01), indicating they are stable and appropriately reflect the original sample data structure. 11 subjects were included in safety and feasibility testing. When predicted lip mark was not strictly adhered to, 4 (36.4%) were malpositioned, subsequent repositioning to predicted lip mark resulted in 100% correct positioning (P = .01), Table 1.

Conclusions:

Use of regression equation is safe, feasible and facilitated correct ETT placement. A larger, diverse sample is required to externally validate the model.

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