Establishment of Airway Database for Surgical Patients

Study on the Method of Difficult Airway Prediction Based on Artificial Intelligence

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.

Study Overview

• Status: Unknown
• Conditions: Artificial Intelligence; Difficult Airway

Detailed Description

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.

• Study Type: Observational
• Enrollment (Anticipated): 50000

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

the patients who underwent general anesthesia with endotracheal intubation

Description

Inclusion Criteria:

• General anesthesia-induced tracheal intubation in patients who undergoing elective surgical patients

Exclusion Criteria:

• Patients with multiple facial injuries Patients who had undergone head or neck surgery Patients who need emergency operation

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort
general anesthesia; Digital photographs of the face of each patient undergoing general anesthesia with endotracheal intubation

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
the sensitivity of artificial Intelligence to predict difficulty of facemask ventilation and endotracheal intubation	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.	5 years

Collaborators and Investigators

• Sponsor: Second Affiliated Hospital, School of Medicine, Zhejiang University
• Collaborators: Zhejiang University

Study record dates

Study Major Dates

• Study Start (Anticipated): May 1, 2017
• Primary Completion (Anticipated): May 1, 2022
• Study Completion (Anticipated): May 1, 2022

Study Registration Dates

• First Submitted: March 13, 2017
• First Submitted That Met QC Criteria: April 19, 2017
• First Posted (Actual): April 24, 2017

Study Record Updates

• Last Update Posted (Actual): April 24, 2017
• Last Update Submitted That Met QC Criteria: April 19, 2017
• Last Verified: April 1, 2017

More Information

Terms related to this study

• Other Study ID Numbers: 2016-076

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No