Ignite Creation Date:
2026-03-26 @ 3:14 PM
Ignite Modification Date:
2026-03-30 @ 3:16 AM
Study NCT ID:
NCT07411495
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
2026-02-13
First Post:
2025-12-21
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
To Create an Artificial Intelligence-enabled Device for Airway Assessment (AINFAS) to Identify Patients With Difficult Airway Pre-operatively.
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2026-03-25'}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'COHORT'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 1000}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'ACTIVE_NOT_RECRUITING', 'startDateStruct': {'date': '2022-05-17', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2025-12', 'completionDateStruct': {'date': '2026-12', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2026-02-08', 'studyFirstSubmitDate': '2025-12-21', 'studyFirstSubmitQcDate': '2026-02-08', 'lastUpdatePostDateStruct': {'date': '2026-02-13', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2026-02-13', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-01-24', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Accuracy of AINFAS in Predicting Difficult Airways', 'timeFrame': 'Assessment will occur from the time of preoperative AI analysis through to the completion of the intubation procedure, typically within 48 hours.', 'description': "To identify and characterize the key predictive parameters that contribute to the AI system's overall ability to detect difficult airways."}], 'secondaryOutcomes': [{'measure': 'Identification of Novel Predictors of Difficult Airways', 'timeFrame': "Data analysis will be conducted after completion of all participant procedures, typically within 2 years of the last participant's assessment.", 'description': "To identify and characterize new predictive parameters that contribute to the AI system's overall ability to determine the likelihood of a difficult airway."}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['difficult airway', 'General anaesthesia'], 'conditions': ['Anaesthesia']}, 'descriptionModule': {'briefSummary': "We're developing a new AI, which uses advanced computer technology to help doctors identify patients who might have a difficult airway before surgery or emergency procedures. Sometimes, when a person needs help breathing, doctors have to insert a tube into their airway. This can be challenging for some people due to the shape of their mouth, throat, or neck. We hope that AI will look at a patient's facial features to predict if there might be any difficulties.", 'detailedDescription': "AINFAS (Artificial Intelligence-enabled system for airway assessment) is an innovative AI system we're developing to revolutionize airway management in healthcare. This advanced artificial intelligence is designed to analyze patient characteristics and predict potential difficulties in airway management before any medical procedure that might require breathing assistance. Using sophisticated machine learning algorithms, AINFAS processes data such as facial structure and neck anatomy to assess the likelihood of a difficult airway. This non-invasive, rapid assessment tool has potential applications across various healthcare settings, including pre-operative assessments, emergency departments, intensive care units, and even pre-hospital care. By providing early identification of potential airway challenges, AINFAS aims to enhance patient safety, improve resource allocation, and provide a standardized, objective method of airway assessment. Currently in development and testing, this AI system represents a significant step forward in using technology to enhance clinical decision-making and patient safety in critical aspects of medical care."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '100 Years', 'minimumAge': '21 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'Patients that undergoing surgery in National University Hospital Singapore Only.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Undergoing surgery under general anaesthesia requiring endotracheal intubation or supraglottic airway\n* 21-100 years old\n\nExclusion Criteria:\n\n* Age less than 21 years\n* Patients with prior surgery with altered facial appearance\n* Patients with tracheostomy\n* Patients with any oropharyngeal pathology\n* Patients with nasopharyngeal carcinoma post radiotherapy or chemotherapy\n* Pregnant females\n* Patients whose physicians did not use a laryngoscope or supraglottic airway'}, 'identificationModule': {'nctId': 'NCT07411495', 'briefTitle': 'To Create an Artificial Intelligence-enabled Device for Airway Assessment (AINFAS) to Identify Patients With Difficult Airway Pre-operatively.', 'organization': {'class': 'OTHER', 'fullName': 'National University Hospital, Singapore'}, 'officialTitle': 'Artificial INtelligence eNabled 3D Facial Scanner for Airway Assessment (AINFAS)', 'orgStudyIdInfo': {'id': '2021/00908'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'General anaesthesia surgery', 'interventionNames': ['Other: AI-Assisted Preoperative Airway Risk Assessment']}], 'interventions': [{'name': 'AI-Assisted Preoperative Airway Risk Assessment', 'type': 'OTHER', 'description': '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.', 'armGroupLabels': ['General anaesthesia surgery']}]}, 'contactsLocationsModule': {'locations': [{'zip': '119074', 'city': 'Singapore', 'country': 'Singapore', 'facility': 'National University Hospital Singapore', 'geoPoint': {'lat': 1.28967, 'lon': 103.85007}}], 'overallOfficials': [{'name': 'Will Ne-Hooi Loh', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'National University Hospital, Singapore'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'National University Hospital, Singapore', 'class': 'OTHER'}, 'collaborators': [{'name': 'National University of Singapore', 'class': 'OTHER'}], 'responsibleParty': {'type': 'SPONSOR'}}}}