Study on the Method of Difficult Airway Prediction Based on Artificial Intelligence
试验速览
- 阶段
- 不适用
- 发起方
- 入组人数
- 50,000
- 主要终点
- the sensitivity of artificial Intelligence to predict difficulty of facemask ventilation and endotracheal intubation
研究概览
简要总结
Difficult airway is a major reason of anesthesia related injuries with latent life threatening complications. Foresee difficult airway in the preoperative period is vital for the patient's safety. The aim of this study is to develop a computer algorithm that can detect whether the patient is a difficult airway based on photographs form six aspects. This method will be decreased potential complication related to difficult airway and increased patient safety.
详细描述
Introduction
The primary purpose of the study is to develop a computer algorithm that can detect whether the patient is a difficult airway based on photographs from six different aspects.
Methods:
This study is divided into two parts. In the first part, we collected the patients' airway assessment score who underwent general anesthesia with endotracheal intubation assessed by an experienced attending anesthesiologists before and after intubation. Evaluation of airway score after tracheal intubation as the gold standard for airway assessment. Digital photographs of the face of each patient in frontal neutral view and in profile neutrals were obtained. Details of the photographs, each corresponding to a facial motion: (1) Frontal, neutral. (2) Frontal, mouth open. (3)Frontal, extreme mouth open and tongue out. (4)Frontal, extreme upper lip bite (5)Profile, neutral. (6) Profile, neutral, maximum head back. The patient's photographs and the airway evaluation score after intubation were input to the computer to train the computer. In the second part, the trained computer was used to evaluate the airway score of the new patient compared with that of the patient after intubation, and calculated the sensitivity.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •General anesthesia-induced tracheal intubation in patients who undergoing elective surgical patients
排除标准
- •Patients with multiple facial injuries Patients who had undergone head or neck surgery Patients who need emergency operation
结局指标
主要结局
the sensitivity of artificial Intelligence to predict difficulty of facemask ventilation and endotracheal intubation
时间窗: 5 years
The outcome will be a computer algorithm that can detect whether the patient is a difficult airway based on photographs from six different aspects.Details of the photographs, each corresponding to a facial motion: (1) Frontal, neutral. (2) Frontal, mouth open. (3)Frontal, extreme mouth open and tongue out. (4)Frontal, extreme upper lip bite (5)Profile, neutral. (6) Profile, neutral, maximum head back.
次要结局
未报告次要终点