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Predictive modeling of difficult airway useing machine learning approach with AI

Predictive modeling of difficult airway useing machine learning approach with AI

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500108658
Enrollment
Unknown
Registered
2025-09-03
Start date
2024-07-15
Completion date
Unknown
Last updated
2025-09-08

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Difficult airway

Interventions

Gold Standard:A difficult airway includes the clinical situation in which anticipated or unanticipateddifficulty or failure is experienced by a physician trained in anesthesia care, including butnot l

Sponsors

West China Hospital of Sichuan University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 65 Years

Inclusion criteria

Inclusion criteria: 1.Age between 18 and 65 years; 2.Undergoing elective general anaesthetic tracheal intubation; 3.ASA <=III; 4.Signed informed consent;

Exclusion criteria

Exclusion criteria: 1.Patients with head and neck oral and maxillofacial trauma or deformity, subacoustic stenosis, cervical spine disease; 2.Patients with central nervous system diseases or mental disorders; 3.Patients with communication disorders, speech disorders, or severe visual or hearing impairments; 4.Patients who are unable to communicate due to coma, severe dementia, speech impediment or serious illness; 5.Participants in relevant clinical studies within the past three months;

Design outcomes

Primary

MeasureTime frame
facial image;Chinese Pronunciation;

Secondary

MeasureTime frame
opening;Mallampati classification;mandibular protraction;Neck parameters;nail-chin distance (TMD);BMI;snoring;

Countries

China

Contacts

Public ContactLi Xiaoqiang

West China Hospital of Sichuan University

39006900@qq.com+86 189 8060 1475

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026