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

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Total Enrollment

228 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-05-20

Study Completion Date

2026-05-30

Brief Summary

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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.

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Detailed Description

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Conditions

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Difficult Airway

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Adult patients scheduled for selective surgery

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

1. age ≥18 years old;
2. surgical patients undergoing general anesthesia with endotracheal intubation;
3. with head and neck CT examination results
4. Consent to participate in the study.

Exclusion Criteria

1. The presence of laryngeal edema;
2. The presence of airway stenosis, including internal airway stenosis (such as foreign body or tumor) or stenosis caused by external tracheal mass compression;
3. tracheo-esophageal fistula;
4. severe gastroesophageal reflux;
5. previous upper airway surgery, such as laryngeal cancer radical surgery, snoring surgery, etc.

6）participating in other research projects

Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No