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Development and validation of a deep learning-based airway evaluation system for predicting difficult airway in patients undergoing cervical spine surgery: a multicenter prospective cohort study

Development and validation of a deep learning-based airway evaluation system for predicting difficult airway in patients undergoing cervical spine surgery: a multicenter prospective cohort study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600120169
Enrollment
Unknown
Registered
2026-03-10
Start date
2026-03-22
Completion date
Unknown
Last updated
2026-03-16

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

Conditions

Cervical spondylosis

Interventions

Observation group:N/A

Sponsors

Peking University Third Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. undergoing cervical spine surgery with general anesthesia 2. age: >=18y 3. American Society of Anesthesiologists Classification (ASA) I~I.

Exclusion criteria

Exclusion criteria: 1. pregnancy 2. cervical spine immobilization 3. Oropharyngeal mass 4. unable to cooperation 5. refused to sign the informed consent

Design outcomes

Primary

MeasureTime frame
Physical examination tests;Craniofacial phenotypic characteristics;Radiological indicators;—

Countries

China

Contacts

Public ContactHan Yongzheng

Peking University Third Hospital

hanyongzheng@bjmu.edu.com+86 152 0130 4460

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Mar 20, 2026