Author:
Yu Yue,Cao Jingjing,Tang Xinyuan,Dong Zhiyuan,Xu Jianling,Wang Bin,Cheng Pingping,Wang Mingfang,Wu Yue,Yao Weidong,Jiang Xiaogan
Abstract
Abstract
Background
The anatomical characteristics of difficult airways can be analysed geometrically. This study aims to develop and validate a geometry-assisted difficult airway screening method (GADAS method) for difficult tracheal intubation.
Methods
In the GADAS method, a geometric simulated model was established based on computer graphics. According to the law of deformation of the upper airway on laryngoscopy, the expected visibility of the glottis was calculated to simulate the real visibility on laryngoscopy. Validation of the new method: Approved by the Ethics Committee of Yijishan Hospital of Wannan Medical College. Adult patients who needed tracheal intubation under general anaesthesia for elective surgery were enrolled. The data of patients were input into the computer software to calculate the expected visibility of the glottis. The results of tracheal intubation were recorded by anaesthesiologists. The primary observation outcome was the screening performance of the expected visibility of the glottis for difficult tracheal intubation.
Results
The geometric model and software of the GADAS method were successfully developed and are available for use. We successfully observed 2068 patients, of whom 56 patients had difficult intubation. The area under the receiver operating characteristic curve of low expected glottis visibility for predicting difficult laryngoscopy was 0.96 (95% confidence interval [CI]: 0.95–0.96). The sensitivity and specificity were 89.3% (95% CI: 78.1-96.0%) and 94.3% (95% CI: 93.2%-95.3), respectively.
Conclusions
It is feasible to screen difficult-airway patients by applying computer techniques to simulate geometric changes in the upper airway.
Funder
Science and Technology Department of Anhui Province
Natural Science Major Research Project of Anhui Provincial Department of Education
Publisher
Springer Science and Business Media LLC
Subject
Anesthesiology and Pain Medicine