Establishment of Airway Database for Surgical Patients
Study on the Method of Difficult Airway Prediction Based on Artificial Intelligence
Study Overview
Status
Status
Conditions
Conditions
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
Study Type
Enrollment (Anticipated)
Enrollment
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
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?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / 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
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
the sensitivity of artificial Intelligence to predict difficulty of facemask ventilation and endotracheal intubation
Time Frame: 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.
|
5 years
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Study record dates
Study Major Dates
Study Start (Anticipated)
Study Start
Primary Completion (Anticipated)
Primary Completion
Study Completion (Anticipated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
Other Study ID Numbers
- 2016-076
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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