Optimal tracheal tube rotation patterns for navigating through the glottis: an in-silico quantification.
Schulz, E. B.; Carra Schulz, L. E.
Show abstract
Seeking to unpack some of the anaesthetists "knack" for intubation, this study examines the effect of various orientations of the tracheal tube on the anterior movement of the tube tip using a computerised 3D model of intubation. The model used sets of coordinates for the upper incisor tip, lower incisor tip and vallecula extracted from mean values reported in a study of 16 volunteers predicted to have easy laryngoscopy and 16 predicted to have difficult laryngoscopy during both gentle laryngoscopy and laryngoscopy under 50N of lifting force, yielding a total of four sets of airway geometry. Tube orientation was specified with the standard aviation terms pitch, roll and yaw. Observations were repeated across permutations of tube roll (0{degrees} to 45{degrees}) and yaw (0{degrees} to 15{degrees}) in all four geometric configurations. Across all four geometries, the most favourable tip location was observed with close to 15{degrees} of yaw and 0{degrees} roll with an anterior tip movement at the level of the glottis observed between 19.2 and 26.6mm. Unsurprisingly given the curved shapes of the objects involved, incremental movement of the tip was greatest at extreme values of roll and yaw. Both yaw and roll caused posterolateral movement of the maxillary teeth contact point. The posterior motion at the mouth enables the entire tube to pitch tip up. However, rolling the tube caused the tube tip to move posteriorly and the pivot point on the laryngoscope blade to move cephalad, nearly always negating what should be a favourable change in pitch allowed by the posterolateral maxillary dentition contact point. Our analysis suggests that avoiding tube roll while maximising yaw at the time of glottic entrance may be a previously unrecognised manoeuvre to improve tracheal intubation success rate having implications for intubation teaching and simulation. Understanding the importance of posterolateral movement of the tube at the oral cavity also may provide new insights into the cause of some difficult intubations.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Cardiorespiratory physiological perturbations after acute smoke-induced lung injury and during extracorporeal membrane oxygenation support in sheep 89%
- Findings of a feasibility study of pre-operative pulmonary rehabilitation to reduce post-operative pulmonary complications in people with chronic obstructive pulmonary disease scheduled for major abdominal surgery. 88%
- Retrospective evaluation of a filtering trabeculotomy in comparison to conventional trabeculectomy by exact matching 87%
Similar papers in this journal
- Transformers for rapid detection of airway stenosis and stridor 93%
- Performance of EasyBreath ® Decathlon Snorkeling mask for Delivering Continuous Positive Airway Pressure 92%
- Spatiotemporal droplet dispersion measurements demonstrate face masks reduce risks from singing: results from the COvid aNd FacEmaSkS Study (CONFESS) 92%
Similar papers in this journal
- Preoperative predictions of in-hospital mortality using electronic medical record data 89%
- The impact of female sex on anaesthetic awareness, depth and emergence: A systematic review and meta-analysis 88%
- DALES - a prospective cross-sectional study of incidence of penicillin allergy labels, risk of true allergy and attitudes of patients and anaesthetists to de-labelling strategies 88%
Similar papers in this journal
- A standardized analytics pipeline for reliable and rapid development and validation of prediction models using observational health data 87%
- In Silico Modeling of Transcatheter Heart Valve Oversizing and Ellipticity, Part I: Establishing Credibility of an Advanced Model 87%
- Digitizing ECG image: new fully automated method and open-source software code 87%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.