Development and internal validation of an equation using anthropometric measures to predict correct endotracheal tube insertion depth

Abstract

Purpose To develop, internally validate, and assess the utility of implementing a regression model for determining endotracheal tube (ETT) insertion depth. Research methods We recorded height, weight, age, sex, ETT internal diameter (ID), lip marking, and tracheal position from the electronic record from a random subset of 2,000 intubated subjects obtained from 1 January 2009 to 5 May 2012. A multivariable linear regression model was constructed and validated by a nonparametric bootstrapping technique using unrestricted random sampling methods. A prospective pilot of subjects admitted to the pediatric intensive care unit requiring invasive mechanical ventilatory support was conducted from 7 January 2019 to 31 May 2019. Those with spinal and/or skeletal malformations, without a post-intubation chest-x-ray (CXR) order, or whose CXR quality impaired visualizing the carina and ETT tip, were excluded. The validated regression equation determined insertion depth. CXR following intubation determined ETT position. Demographic data were summarized. Two-tailed, one-sample binomial test of proportions assessed differences in the proportion of correct position by the equation. Main findings Four hundred and seventy-seven subjects included in model construction yielded 10,000 independent samples for internal validation; 55% were female, and the mean age (SD) was 47 (63) months. Bias between bootstrap coefficients and refined model estimates were negligible (P < 0.01). Eleven subjects in the pilot were female (64%), mean age (SD) of 36.7 (38) months. Four protocol violations (36.4%) resulted in malposition. Subsequent repositioning per protocol resulted in 100% correct positioning (P = 0.01). Conclusion The regression equation [0.8636 * (Ht. 0.6223)] facilitated correct ETT placement. A larger, diverse sample is required for external model validation.