AnaesthesiaNCT07411495
To Create an Artificial Intelligence-enabled Device for Airway Assessment (AINFAS) to Identify Patients With Difficult Airway Pre-operatively.
An observational study of Anaesthesia, run by National University Hospital, Singapore at 1 site in Singapore.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 21 to 100 years
- Conditions the study is for
- Anaesthesia
- What is being tested?
- AI-Assisted Preoperative Airway Risk Assessment
- Type of treatment
- Pill or oral medicine
- How many people
- 1,000 participants
- Where
- 1 siteSingapore
- Study dates
- 17 May 2022to Dec 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 21 to 100 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients that undergoing surgery in National University Hospital Singapore Only.
Who may be able to join
- Undergoing surgery under general anaesthesia requiring endotracheal intubation or supraglottic airway
- 21-100 years old
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Artificial INtelligence eNabled 3D Facial Scanner for Airway Assessment (AINFAS)
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.
Read the detailed description
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.
- Conditions
- Anaesthesia
- Being tested
- AI-Assisted Preoperative Airway Risk Assessment
- Keywords
- difficult airway, General anaesthesia
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-Assisted Preoperative Airway Risk AssessmentOther
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.
| Study group | Role | What they receive |
|---|---|---|
| General anaesthesia surgery | Not described Receives: Other: AI-Assisted Preoperative Airway Risk Assessment |
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy of AINFAS in Predicting Difficult Airways
To identify and characterize the key predictive parameters that contribute to the AI system's overall ability to detect difficult airways.
Measured: Assessment will occur from the time of preoperative AI analysis through to the completion of the intubation procedure, typically within 48 hours.
Secondary outcomes (1)
Identification of Novel Predictors of Difficult Airways
To identify and characterize new predictive parameters that contribute to the AI system's overall ability to determine the likelihood of a difficult airway.
Measured: Data analysis will be conducted after completion of all participant procedures, typically within 2 years of the last participant's assessment.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Feb 2026
- Study start17 May 2022
- Primary completion24 Jan 2025
- Study completionDec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for AnaesthesiaStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,000 participants (actual)
Sponsor and investigators
- Lead sponsor
- National University Hospital, Singapore
- Sponsor type
- University, hospital or other
- Collaborators
- National University of Singapore
- Responsible party
- Sponsor
- Investigators
- Will Ne-Hooi Loh, Principal investigator, National University Hospital, Singapore
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07411495
- Sponsor's protocol ID
- 2021/00908
- Status last verified
- Dec 2025
- First submitted
- 21 Dec 2025
- Last updated
- 13 Feb 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 13 Feb 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial INtelligence eNabled 3D Facial Scanner for Airway Assessment (AINFAS)
- ClinicalTrials.gov ID
- NCT07411495
- Acronym / sponsor ID
- 2021/00908
- Conditions
- Anaesthesia
- Keywords
- difficult airway, General anaesthesia
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 1,000 participants (actual)
- Lead sponsor
- National University Hospital, SingaporeUniversity, hospital or other
- Collaborators
- National University of Singapore
- Study start
- 17 May 2022 (actual)
- Primary completion
- 24 Jan 2025 (actual)
- Study completion
- Dec 2026 (estimated)
- First posted
- 13 Feb 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| General anaesthesia surgery | – | Other: AI-Assisted Preoperative Airway Risk Assessment |
Who may qualify
- Ages
- 21 to 100 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients that undergoing surgery in National University Hospital Singapore Only.
Key inclusion criteria (2 listed)
- Undergoing surgery under general anaesthesia requiring endotracheal intubation or supraglottic airway
- 21-100 years old
Key exclusion criteria (7 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-Assisted Preoperative Airway Risk Assessmentparticipants 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. | Other | General anaesthesia surgery |
Primary outcome
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.
To identify and characterize the key predictive parameters that contribute to the AI system's overall ability to detect difficult airways.
1 secondary outcome
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.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Feb 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Will Ne-Hooi Loh principal investigator
National University Hospital, Singapore
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Anaesthesia, run by National University Hospital, Singapore at 1 site in Singapore.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 13 Feb 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Singapore. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
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.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 Feb 2026; AzTrials last refreshed its copy on 28 Oct 2026.