Difficult Airway IntubationNCT07278232
Research on a Machine Learning-Based Predictive Model for Difficult Intubation Using Specific Vocal Characteristics
An observational study of Difficult Airway Intubation, run by Shanghai Jiao Tong University Affiliated Sixth People's Hospital at 1 site in China.
Trial summary
1. Study Purpose This research aims to develop a novel, non-invasive, and simple method to predict difficult intubation before surgery. The core idea is that the anatomy of a person's throat and mouth, which determines the ease of intubation, also uniquely shapes their voice. Read more about this study
- Who is it for?
- Ages 15 to 70 years
- Conditions the study is for
- Difficult Airway Intubation
- How many people
- 300 participants
- Where
- 1 siteChina
- Study dates
- 20 Dec 2025to 31 Dec 2026
- How long will I take part?
- 1 Day
- 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 15 to 70 years
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: Patients of 15-70 years scheduled for elective general anesthesia with tracheal intubation
Who may be able to join
- Patients scheduled for elective general anesthesia with tracheal intubation.
Who cannot join
- Patients with speech and pronunciation disorders (vocal cord diseases, cleft palate, craniofacial deformities, extensive tooth defects, cleft lip).
- Hearing impairment (difficulty in communication, inaccurate repetition).
- Patients with central nervous system diseases causing significant pronunciation abnormalities.
- Patients contraindicated for direct laryngoscopy (e.g., post-chemotherapy in the pharynx, diseases prone to mucosal bleeding, etc.) that affect group allocation, as well as those unable to complete the recording or temporarily reassigned to other anesthesia methods.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
Shanghai Sixth People's Hospital Affiliated with Shanghai Jiao Tong University School of Medicine
Shanghai
Jun Yao, +86 18930173671, guoxinger@126.com
About this study
- Study Purpose This research aims to develop a novel, non-invasive, and simple method to predict difficult intubation before surgery. The core idea is that the anatomy of a person's throat and mouth, which determines the ease of intubation, also uniquely shapes their voice. By analyzing the acoustic features of specific vowel sounds using machine learning, we seek to identify voice patterns associated with difficult airways. The ultimate goal is to create a tool that allows for a quick, painless pre-operative risk assessment, enhancing patient safety by better preparing anesthesiologists.
- Study Design This is a prospective, observational, single-center study. It is purely observational and does not involve any changes to standard medical care or anesthesia procedures.
- Participants We plan to enroll 300 patients. Who can join: Patients aged 15-70 scheduled for elective surgery requiring general anesthesia with tracheal intubation. Who cannot join: Individuals with speech/hearing impairments, significant neurological diseases affecting speech, or conditions contraindicating standard laryngoscopy.
- Study Procedures For participants, the study involves one key procedure in addition to standard care:Voice Recording: Before surgery, participants will be asked to lie down and pronounce the vowels "a," "e," and "i" steadily for 1-2 seconds. This will be done twice: once with the head in a normal position and once with the head tilted back. A high-quality recorder will capture the sounds. This process is painless and takes only a few minutes. Standard anesthesia and intubation will then proceed as usual. The anesthesiologist will record the laryngeal view obtained during intubation, which will be used to classify the case as "difficult" or "non-difficult" for analysis.
- Data Analysis The primary goal is to determine if there are statistically significant differences in the key voice resonance frequencies (F1, F2, F3) between the difficult and non-difficult intubation groups. Advanced machine learning models will be built to create the predictive algorithm.
- Risks and Benefits Benefits: There is no direct medical benefit to participants. The contribution is to future medical knowledge and patient safety. Risks: The study involves minimal risk. The voice recording is non-invasive and safe. The main risk is the potential loss of confidentiality, which is mitigated by strict data protection protocols.
- Confidentiality \& Ethics All patient data will be de-identified and stored securely. The study protocol and informed consent form have been approved by the Institutional Ethics Committee of Shanghai Sixth People's Hospital. Participation is voluntary, and participants may withdraw at any time without affecting their medical care. Written informed consent will be obtained from every participant before any study procedures.
- Conditions
- Difficult Airway Intubation
- Being tested
- No Intervention: Observational Cohort
- Keywords
- Difficult Airway Intubation
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
No Intervention: Observational CohortOther
No Intervention
What is being measured
The primary outcome is the main question the study is designed to answer.
The corresponding differences in average F1, F2, and F3 between the two sets of speech signals.
Measured: Preoperative Phase
Differences in F1, F2, and F3 of the same pronunciation before and after changing head position.
Measured: Preoperative Phase
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 Dec 2025
- Study start20 Dec 2025
- Primary completion31 Dec 2026 (estimated)
- Study completion31 Dec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Difficult Airway IntubationStudies 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
- Ecologic or community
- Time perspective
- Prospective
- Enrolment
- 300 participants (estimated)
- Target duration
- 1 Day
Sponsor and investigators
- Lead sponsor
- Shanghai Jiao Tong University Affiliated Sixth People's Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Xi Liu, Shanghai Jiao Tong University Affiliated Sixth People's Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07278232
- Sponsor's protocol ID
- Difficult Intubation
- Status last verified
- Nov 2025
- First submitted
- 29 Nov 2025
- Last updated
- 24 Aug 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 24 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Research on a Machine Learning-Based Predictive Model for Difficult Intubation Using Specific Vocal Characteristics
- ClinicalTrials.gov ID
- NCT07278232
- Acronym / sponsor ID
- Difficult Intubation
- Conditions
- Difficult Airway Intubation
- Keywords
- Difficult Airway Intubation
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 300 participants (estimated)
- Lead sponsor
- Shanghai Jiao Tong University Affiliated Sixth People's HospitalUniversity, hospital or other
- Study start
- 20 Dec 2025 (actual)
- Primary completion
- 31 Dec 2026 (estimated)
- Study completion
- 31 Dec 2026 (estimated)
- First posted
- 11 Dec 2025 (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.
- Study Purpose This research aims to develop a novel, non-invasive, and simple method to predict difficult intubation before surgery. The core idea is that the anatomy of a person's throat and mouth, which determines the ease of intubation, also uniquely shapes their voice. By analyzing the acoustic features of specific vowel sounds using machine learning, we seek to identify voice patterns associated with difficult airways. The ultimate goal is to create a tool that allows for a quick, painless pre-operative risk assessment, enhancing patient safety by better preparing anesthesiologists.
- Study Design This is a prospective, observational, single-center study. It is purely observational and does not involve any changes to standard medical care or anesthesia procedures.
- Participants We plan to enroll 300 patients. Who can join: Patients aged 15-70 scheduled for elective surgery requiring general anesthesia with tracheal intubation. Who cannot join: Individuals with speech/hearing impairments, significant neurological diseases affecting speech, or conditions contraindicating standard laryngoscopy.
- Study Procedures For participants, the study involves one key procedure in addition to standard care:Voice Recording: Before surgery, participants will be asked to lie down and pronounce the vowels "a," "e," and "i" steadily for 1-2 seconds. This will be done twice: once with the head in a normal position and once with the head tilted back. A high-quality recorder will capture the sounds. This process is painless and takes only a few minutes. Standard anesthesia and intubation will then proceed as usual. The anesthesiologist will record the laryngeal view obtained during intubation, which will be used to classify the case as "difficult" or "non-difficult" for analysis.
- Data Analysis The primary goal is to determine if there are statistically significant differences in the key voice resonance frequencies (F1, F2, F3) between the difficult and non-difficult intubation groups. Advanced machine learning models will be built to create the predictive algorithm.
- Risks and Benefits Benefits: There is no direct medical benefit to participants. The contribution is to future medical knowledge and patient safety. Risks: The study involves minimal risk. The voice recording is non-invasive and safe. The main risk is the potential loss of confidentiality, which is mitigated by strict data protection protocols.
- Confidentiality \& Ethics All patient data will be de-identified and stored securely. The study protocol and informed consent form have been approved by the Institutional Ethics Committee of Shanghai Sixth People's Hospital. Participation is voluntary, and participants may withdraw at any time without affecting their medical care. Written informed consent will be obtained from every participant before any study procedures.
Study design
- Observational model
- Ecologic or community
- Time perspective
- Prospective
- Target follow-up
- 1 Day
Who may qualify
- Ages
- 15 to 70 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Patients of 15-70 years scheduled for elective general anesthesia with tracheal intubation
Key inclusion criteria (1 listed)
- Patients scheduled for elective general anesthesia with tracheal intubation.
Key exclusion criteria (4 listed)
- Patients with speech and pronunciation disorders (vocal cord diseases, cleft palate, craniofacial deformities, extensive tooth defects, cleft lip).
- Hearing impairment (difficulty in communication, inaccurate repetition).
- Patients with central nervous system diseases causing significant pronunciation abnormalities.
- Patients contraindicated for direct laryngoscopy (e.g., post-chemotherapy in the pharynx, diseases prone to mucosal bleeding, etc.) that affect group allocation, as well as those unable to complete the recording or temporarily reassigned to other anesthesia methods.
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 |
|---|---|---|
| No Intervention: Observational CohortNo Intervention | Other | – |
Primary outcome
The corresponding differences in average F1, F2, and F3 between the two sets of speech signals.
Time frame: Preoperative Phase
Differences in F1, F2, and F3 of the same pronunciation before and after changing head position.
Time frame: Preoperative Phase
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 24 Aug 2026.
- Individual participant dataSharing planned: Undecided
Related trials for Difficult Airway Intubation
Not yet recruitingObservational study
A Novel Score for Procedural Difficulty During Videolaryngoscopic Intubation
Intubation, Intratracheal, Airway Management
RecruitingObservational study
Comparison of Two Sedation Regimens for Awake Fiberoptic Intubation
Awake Fiberoptic Intubation, Difficult Airway
Not yet recruitingObservational study
Modified El-Ganzouri Risk Index for Predicting Difficult Intubation in Obese Patients
Difficult Intubation, Obesity
Enrolling by invitationObservational study
Difficult Airway Management in Oncology: An International Delphi Consensus Study (DAMO)
Neoplasms, Airway Obstruction Upper
Not yet recruitingObservational study
Correlation Between Bedside Anatomical Indicators and Lifting Force and Glottic Exposure Under Different Video Laryngoscopy Techniques
Difficult Airway, Intubation, Intratracheal
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.
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 Difficult Airway Intubation, run by Shanghai Jiao Tong University Affiliated Sixth People's Hospital at 1 site in China.
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 1 inclusion and 4 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: looking for participants now, as of the sponsor's last update on 24 Aug 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 China. 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?
Contact Jun Yao (+86 18930173671, guoxinger@126.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The corresponding differences in average F1, F2, and F3 between the two sets of speech signals. (time frame: Preoperative Phase). The study lists 2 primary outcomes in all. 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 24 Aug 2026.