Development of an Artificial Intelligence-Based Model for Predicting Difficult Intubation Using Video Laryngoscopic Images and Cormack-Lehane Classification
NCT ID: NCT07152093
Last Updated: 2025-11-18
Study Results
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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COMPLETED
132 participants
OBSERVATIONAL
2025-05-01
2025-10-01
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Group 1: Normal Intubation Group
Intubations in patients assessed as Cormack-Lehane (CL) Class 1-2.
No interventions assigned to this group
Difficult Intubation Group
Intubations in patients evaluated as Cormack-Lehane Class 3-4.
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
Elective surgery
ASA I-II
No upper airway pathology
Exclusion Criteria
Morbid obesity (BMI \> 40)
Pregnancy
History of upper airway surgery
18 Years
65 Years
ALL
No
Sponsors
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Duzce University
OTHER
Responsible Party
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Gizem Demir Şenoğlu
Principal Investigator, Assistant Professor of Anesthesiology and Reanimation, Düzce University Faculty of Medicine
Locations
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Duzce University Faculty of Medicine, Department of Anesthesiology and Reanimation
Düzce, Merkez, Turkey (Türkiye)
Countries
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Other Identifiers
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2025/183
Identifier Type: -
Identifier Source: org_study_id
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