Se Uk Lee 1 , Jae Yun Jung 2 , Do Kyun Kim 2 , Young Ho Kwak 2 , Hyuksool Kwon 3 , Jun Hwi Cho 4 , Joong Wan Park 2 , Yoo Jin Choi 3 Show Affiliations »
Abstract
INTRODUCTION: The purpose of this study was to construct a prediction model for endotracheal tube depth using neck CT images. METHODS: A retrospective image review was conducted that included patients who had undergone neck CT. Using sagittal neck CT images, we calculated the length between upper incisor and mid-trachea and then derived the model via regression analysis. The model was validated externally using chest radiographs of patients who had undergone endotracheal intubation. We compared performance of our model with that of other methods (Broselow tape and APLS formula) via Bland-Altman analysis and the percentage of estimations within 10% of the measured values. RESULTS: A total of 1111 children were included in this study. The tube depth obtained from CT images was linearly related to body weight (tube depth (cm)=5.5+0.5×body wt (kg)) in children younger than 1 year and to height (tube depth (cm)=3+0.1×height (cm)) in children older than 1 year. External validation demonstrated that our new model showed better agreement with the desired tube depth than Broselow tape and APLS formula. The mean differences in children younger than 1 year were 0.61 cm and -1.24 cm for our formula and Broselow tape, respectively. The mean differences in children older than 1 year were -0.43 cm, -1.98 and -1.64 cm for our formula, Broselow tape and APLS formula, respectively. The percentages of estimates within 10% of the measured values were 52.7% and 35.8% for our formula and Broselow tape in children younger than 1 year, respectively, and 54.3%, 33.8% and 37.2% for our formula, Broselow tape and APLS formula in children older than 1 year, respectively (P<0.01). CONCLUSION: Our new formula is useful and more accurate than the currently available methods. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
INTRODUCTION: The purpose of this study was to construct a prediction model for endotracheal tube depth using neck CT images. METHODS: A retrospective image review was conducted that included patients who had undergone neck CT. Using sagittal neck CT images, we calculated the length between upper incisor and mid-trachea and then derived the model via regression analysis. The model was validated externally using chest radiographs of patients who had undergone endotracheal intubation. We compared performance of our model with that of other methods (Broselow tape and APLS formula) via Bland-Altman analysis and the percentage of estimations within 10% of the measured values. RESULTS: A total of 1111 children were included in this study. The tube depth obtained from CT images was linearly related to body weight (tube depth (cm)=5.5+0.5×body wt (kg)) in children younger than 1 year and to height (tube depth (cm)=3+0.1×height (cm)) in children older than 1 year. External validation demonstrated that our new model showed better agreement with the desired tube depth than Broselow tape and APLS formula. The mean differences in children younger than 1 year were 0.61 cm and -1.24 cm for our formula and Broselow tape, respectively. The mean differences in children older than 1 year were -0.43 cm, -1.98 and -1.64 cm for our formula, Broselow tape and APLS formula, respectively. The percentages of estimates within 10% of the measured values were 52.7% and 35.8% for our formula and Broselow tape in children younger than 1 year, respectively, and 54.3%, 33.8% and 37.2% for our formula, Broselow tape and APLS formula in children older than 1 year, respectively (P<0.01). CONCLUSION: Our new formula is useful and more accurate than the currently available methods. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Entities: Disease
Species
Keywords:
Ct/mri; airway; paediatric resuscitation
Mesh： See more »
Year: 2018
PMID： 29437848 DOI： 10.1136/emermed-2017-206795
Source DB: PubMed Journal: Emerg Med J ISSN： 1472-0205 Impact factor: 2.740