Clinical trial NCT04458220: Research on Early Warning and Solution System of Difficult Airway in Perioperative Period Based on Artificial Intelligence
Official title: Research on Early Warning and Solution System of Difficult Airway in Perioperative Period Based on Artificial Intelligence
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Difficult Airway
Lead sponsor: Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University
Sponsor class: OTHER
First posted: 2020-07-07
Enrollment: 16000
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The study is performed in Shanghai Ninth People's Hospital Affiliated with Shanghai Jiao Tong University School of Medicine . According to inclusion and exclusion criteria ,We are expected to enroll 16000 participants who performed endotracheal intubation under general anesthesia.

Brief summary: The study is performed in Shanghai Ninth People's Hospital Affiliated with Shanghai Jiao Tong University School of Medicine . According to inclusion and exclusion criteria ,the investigators are expected to enroll 16000 participants who performed endotracheal intubation under general anesthesia. All enrolled participants must sign a written informed consent.In the preset studio,The 3D face scanner and camera is used to obtain 3D or 2-dimensional portrait images of patients in different positions and from different angles.The Hi-Fi Recorder is used to obtain sound samples of patients in different word.Then,Statistical experts use quantitative software to quantify the data.The investigators will put all the data and images into a confidential database in order to build a large database of difficult airways.

Anesthesiologist will give every patient an endotracheal intubation as planned. After that the anesthesiologist will be asked to fill out the questionnaire immediately.This questionnaire allows obtaining a ground truth for the intubation difficulty.All data will be used for AI deep learning and intelligent analysis,Several of the most relevant landmarks will be selected to build an early warning model.The overall study did not involve any intervention in the process of anaesthesia and operation of the patients, only the three-dimensional facial images of the patients were obtained, without any trauma or injury.


Eligibility criteria: Inclusion Criteria:

* Patients to be intubated under general anesthesia.

Exclusion Criteria:

* Patients with deaf-mutism or communication disorders.
* Patients with language deficiency or non-native language.
* Patients with mental or central nervous system disease.
* Patients with stupefaction or disturbance of consciousness.
* Patients with terrible injury.
* Patients cannot follow instructions to perform standard actions.
* Patients participated in other relevant clinical investigation in the past 3 months.

Primary outcomes:
measure: Diagnosed as a difficult airway
timeFrame: Just after intubation
Secondary outcomes:
measure: Difficult mask ventilation
timeFrame: 2 minutes after administration of Rocuronium
Other outcomes:
Locations:
city: Shanghai
country: China
facility: The Ninth People's Hospital of Shanghai Jiaotong University School of Medicine
state: Shanghai
Study officials:
affiliation: The Ninth People's Hospital of Shanghai Jiaotong University School of Medicine
name: Hong Jiang, Dr
role: STUDY_CHAIR
References: