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AI-based Prediction Model of Difficult Tracheal Intubation Using Medical Image Parameters

NCT06982144 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 228

Last updated 2025-05-21

No results posted yet for this study

Summary

Difficult airway is a life-threatening event during anesthesia. Prediction model is helpful to detect high-risk patients and decrease the risk of un-anticipated difficult airway. Present models are usually based on Mallampati grade and the width of mouth open. However, the prediction accuracy is only about 0.7-0.8 in different populations. Present study is designed to investigate if AI-based prediction model using medical imaging parameters (such as CT and MRI) can increase the accuracy of prediction model.

Conditions

  • Difficult Airway

Sponsors & Collaborators

  • Mu Dong Liang

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-05-20
Primary Completion
2026-03-01
Completion
2026-05-30

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06982144 on ClinicalTrials.gov