PrediSuisse: Automatized Assessment of Difficult Airway Using Three Videolaryngoscopes with the Help of Facial Recognition Techniques and Neural Network
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 1,800
- 试验地点
- 1
- 主要终点
- Software creation
研究概览
简要总结
In the "PrediSuisse" research project, the investigators aim to create a reliable, reproducible, ultra-portable and radiation-free automatized software, able to identify automatically collected features, facial characteristics, and range of movements, to predict intubation difficulty. The software will generate a difficulty intubation score tailored to three commercially available videolaryngoscopes with different type of blades, corresponding to the predicted endotracheal intubation difficulty while providing the anaesthesiologist a reliable and non-subjective tool to assess individual patient's risks with regards to airway management.
详细描述
The Swiss multi-institutional research project "PrediSuisse" aims to automatically predict and classify the difficulty of intubation and airway management using three commercially available videolaryngoscopes (VL) by acquiring face/profiles photos and sequences on a training set of 900 patients during the pre-anaesthesia consultation. For each patient, with the help of recently developed Machine Learning (ML), Artificial Intelligence (AI) and Convolutional Neural Network (CNN) techniques, a specially developed software will be trained to provide a predicted airway management difficulty index. This will be performed by correlating those photos/sequences and the real difficulty level of intubation, determined by three experts by reviewing the recordings of the intubations of the training set patients. The software will then be used in routine on a set of 900 other patients to validate the prediction performance.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 100 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Adult patients (≥ 18 years old) presenting at the pre-anesthesia consult for an elective general anesthesia necessitating a tracheal intubation
- •Signed informed consent.
排除标准
- •Patients not speaking French (in Geneva and Lausanne) or Italian (in Lugano).
- •Patients previously operated on the airway with anatomical modifications (ENT Flaps, tracheotomies).
- •Patients unable to follow procedures or to give consent will also be excluded.
结局指标
主要结局
Software creation
时间窗: 18 months
The primary outcome is to create a reliable, reproducible, ultra-portable and radiation-free automated software, capable of identifying automatically collected features such as facial characteristics, mouth opening, range of motion while moving the neck and thyromental distance to predict intubation difficulty. The identification of the difficult intubation score will be compared by the one goven independantly by three airway experts.
次要结局
- Team Communication(18 months)
研究者
Patrick Schoettker
Professor
Centre Hospitalier Universitaire Vaudois