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Prediction of tracheal tube diameter based on artificial intelligence ultrasound recognition technology

Prediction of tracheal tube diameter based on artificial intelligence ultrasound recognition technology

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300069902
Enrollment
Unknown
Registered
2023-03-29
Start date
2023-03-29
Completion date
Unknown
Last updated
2023-05-29

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

Conditions

difficult airway

Interventions

Case series:none

Sponsors

Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine
Lead Sponsor

Eligibility

Sex/Gender
All
Age
No minimum to 12 Years

Inclusion criteria

Inclusion criteria: (1) Age <= 12 years (2) Children intended for general anesthesia with tracheal intubation; (3) ASA classification of grade I-III;

Exclusion criteria

Exclusion criteria: (1) The child's parents have speech communication and cooperation difficulties; (2) Patients with open trauma to the head and neck (3) Patients with cervical fractures, neck surgery, or a history of cervical spine disease (4) Emergency surgery; (5) Patients who are allergic to relevant medications.

Design outcomes

Primary

MeasureTime frame
tracheal tube diameter;—

Secondary

MeasureTime frame
ultrasound image;Baseline Data;—

Countries

China

Contacts

Public ContactMing Xia

Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine

shxiaming1980@163.com+86 150 2130 6970

Outcome results

None listed

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