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Ultrasound images for predicting difficult airways: a prospective study based on machine learning

To explore the possibility of predicting difficult airway based on ultrasound images and features of machine learning

Status
Recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400084274
Enrollment
Unknown
Registered
2024-05-14
Start date
2024-05-14
Completion date
Unknown
Last updated
2024-05-21

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

Conditions

Difficult airway

Interventions

Difficult Airway Group:Not applicable
Non-difficult airway group:Not applicable

Sponsors

The Affiliated Hospital of Qingdao University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 90 Years

Inclusion criteria

Inclusion criteria: Age =18 years old, Patients undergoing elective surgery, Tracheal intubation was performed by video laryngoscope, They voluntarily participated and signed informed consent forms

Exclusion criteria

Exclusion criteria: Impaired language communication, Patients with neurological dysfunction and inability to cooperate with examinations, Emergency surgery, Head and neck fractures, Abnormal neck anatomical structure (including congenital malformation, neck surgery and radiotherapy), Patients requiring awake intubation

Design outcomes

Primary

MeasureTime frame
Distance from skin to hyoid bone;Skin to epiglottis distance;The Angle between the chin, hyoid bone and glottis;Distance from skin to anterior commissure;Distance from skin to thyrohyoid membrane;Distance from skin to thyroid cartilage;The videolaryngoscopic intubation and difficult airway classification;

Secondary

MeasureTime frame
Modified Mallampati test;Head and neck mobility classification;Occlusal test of the upper lip;Horizontal length of mandible;Thyromental distance;Interincisor space;

Countries

China

Contacts

Public ContactZejun Niu

Department of Anesthesiology, Affiliated Hospital of Qingdao University

nzj16niu@sina.com+86 186 6180 5522

Outcome results

None listed

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