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Published on: April 7, 2023
Three-Dimensional Imaging-Based Web Application for Predicting Tracheal Tube Depth in Preterm Neonates
Raksa Tupprasoot1, Dean Langan, J Ciaran Hutchinson
1Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK.
Background:
Positioning a tracheal tube (TT) to the correct depth in preterm infants is challenging. Currently, there is no reliable single-predictor model for neonates applicable to the whole range of size or age.
Objective:
In this study, we used post-mortem magnetic resonance imaging (PMMRI) of preterm infants to measure tracheal dimensions and to develop a clinical guide for TT positioning.
Methods:
We measured tracheal length (TL) and tracheal diameter (TD) in a cohort of normal neonates and foetuses that underwent PMMRI (cause of death unexplained). The distance between the lips and the mid-tracheal point, i.e., the mid-tracheal length (mid-TL), and the TD measurement were obtained. We produced univariate prediction models of mid-TL and TD, using gestational age (GA), foot length (FL), crown-rump length (CRL) and body weight (BW) as potential predictors, as well as multiple prediction models for mid-TL.
Results:
Tracheal measurements were performed in 117 cases, with a mean GA of 28.8 weeks (range 14-42 weeks). The best linear association was between mid-TL and FL (mid-TL = FL × 0.914 + 1.859; R2 = 0.94), but was improved by multivariate regression models. We developed a prediction tool using only GA and BW (R2 = 0.92), and all four predictors (GA, BW, FL and CRL; R2 = 0.94) which is now available as a web-based application via the Internet.
Conclusion:
Post-mortem imaging data provide estimates of TT insertion depth. Our prediction tool based on age and BW can be used at the bedside and is ready to be tested in clinical practice.
