To Create an Artificial Intelligence-enabled Device for Airway Assessment (AINFAS) to Identify Patients With Difficult Airway Pre-operatively.
Artificial INtelligence eNabled 3D Facial Scanner for Airway Assessment (AINFAS)
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Locations
-
-
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Singapore, Singapore, 119074
- National University Hospital Singapore
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-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Undergoing surgery under general anaesthesia requiring endotracheal intubation or supraglottic airway
- 21-100 years old
Exclusion Criteria:
- Age less than 21 years
- Patients with prior surgery with altered facial appearance
- Patients with tracheostomy
- Patients with any oropharyngeal pathology
- Patients with nasopharyngeal carcinoma post radiotherapy or chemotherapy
- Pregnant females
- Patients whose physicians did not use a laryngoscope or supraglottic airway
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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General anaesthesia surgery
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participants having their photograph taken using a tablet device following a standardized protocol to capture relevant facial and neck features.
These photographs will then be analyzed using software, which assesses the images for potential indicators of a difficult airway.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Accuracy of AINFAS in Predicting Difficult Airways
Time Frame: Assessment will occur from the time of preoperative AI analysis through to the completion of the intubation procedure, typically within 48 hours.
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To identify and characterize the key predictive parameters that contribute to the AI system's overall ability to detect difficult airways.
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Assessment will occur from the time of preoperative AI analysis through to the completion of the intubation procedure, typically within 48 hours.
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Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Identification of Novel Predictors of Difficult Airways
Time Frame: Data analysis will be conducted after completion of all participant procedures, typically within 2 years of the last participant's assessment.
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To identify and characterize new predictive parameters that contribute to the AI system's overall ability to determine the likelihood of a difficult airway.
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Data analysis will be conducted after completion of all participant procedures, typically within 2 years of the last participant's assessment.
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Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Principal Investigator: Will Ne-Hooi Loh, National University Hospital, Singapore
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Estimated)
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
Keywords
Other Study ID Numbers
Other Study ID Numbers
- 2021/00908
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
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