Evaluation of Double Lumen Tube Intubation Difficulty With Photo-Based Artificial Intelligence Algorithms
Efficacy and Reliability of Photo-Based Artificial Intelligence Algorithms in Assessing Difficulty of Intubation With a Double-Lumen Tube
The complexity and difficulty of intubation with double lumen tubes requires the use of advanced technologies in the management of this procedure. The potential of photo-based artificial intelligence algorithms to predict and minimize the difficulties encountered during intubation is the main motivation for this study.
The utilization of artificial intelligence algorithms within the domain of airway management holds considerable promise in providing real-time feedback to anesthesiologists, enhancing the efficacy of intubation procedures, and reducing the occurrence of complications. Specifically, photo-based AI systems can facilitate a more comprehensive understanding of airway anatomy by analyzing images captured prior to and during intubation, thereby enhancing the management of complex cases.The objective of this study is to examine the efficacy and reliability of photo-based artificial intelligence algorithms in evaluating the complexity of intubation with a double lumen tube.The integration of artificial intelligence into the intubation process is intended to enhance patient outcomes and establish a new benchmark for anesthesia practice. This study aims to address the existing gap in the literature and provide innovative approaches to clinical practice.
Informed consent was obtained from patients undergoing thoracic surgery operations, and demographic data (age, height, body weight, body mass index, gender), American Society of Anesthesiologists (ASA) score, type of operation, and comorbid diseases (diabetes mellitus, hypertension, coronary artery disease, chronic kidney disease, chronic obstructive pulmonary disease, asthma, obstructive sleep apnea) were obtained. Thoracic and/or extrath oracic malignancy history), parameters considered as risk factors for difficult intubation (history of previous difficult intubation, LEMON criteria (look externally, evaluate, mallampathy, obstruction, neck mobility), upper lip bite test) and photographs of the patients (including head and neck region) will be recorded in six different directions and ways with a professional camera (actively used in our hospital) in the preoperative period. During the intraoperative phase, the Cormack-Lehane scoring system will be employed, and the intubation process with a double-lumen tube will be evaluated for ease or difficulty. Intraoperative complications related to the operation will also be documented.The data will then be processed using Python 3 programming language and open-source libraries to calculate artificial intelligence algorithms. In the event of incomplete patient data, data imputation techniques will be employed to supplement the artificial intelligence program.
The primary outcome variable of the study is the rate at which the photo-based artificial intelligence algorithm predicts whether intubation with a double lumen tube is easy or difficult.The secondary outcome variable is the comparison of the rate of prediction of intubation with double lumen tube by photo-based artificial intelligence algorithms and the rate of prediction of intubation with double lumen tube by conventional methods.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Onur Küçük, Specialist
- Phone Number: +905358543333
- Email: dr.okucuk@gmail.com
Study Locations
-
-
Keçiören
-
Ankara, Keçiören, Turkey (Türkiye), 06290
- Ankara Atatürk Sanatoryum Training and Research Hospital
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Undergoing thoracic surgery
- Giving informed consent
- Over 18 years of age
- Double lumen tube used for intubation
- ASA (American Society of Anesthesiologist)1-2-3
Exclusion Criteria:
- Emergency surgeries
- ASA 4 and above
- Head and neck tumor, history of surgery/RT related to tumor
- Presence of syndrome that will cause difficult intubation
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Intubation - Difficult
According to the Intubation Difficulty Scale (IDS), a score of > 5 was defined as difficult intubation.
|
The Intubation Difficulty Scale (IDS) is an objective way to classify easy and difficult intubation.
A score ≤ 5 indicates an easy or mildly difficult intubation, while IDS > 5 suggests difficult intubation, requiring additional techniques or attempts.
The program made with Python 3 programming language using open source libraries.
It will be developed to predict difficult intubation with 6 different photo data of patients, this process will be taught with a learning process and then tested.
|
|
Intubation - Easy
According to the Intubation Difficulty Scale (IDS), a score of ≤ 5 was defined as easy intubation.
|
The Intubation Difficulty Scale (IDS) is an objective way to classify easy and difficult intubation.
A score ≤ 5 indicates an easy or mildly difficult intubation, while IDS > 5 suggests difficult intubation, requiring additional techniques or attempts.
The program made with Python 3 programming language using open source libraries.
It will be developed to predict difficult intubation with 6 different photo data of patients, this process will be taught with a learning process and then tested.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Intubation Difficulty Scale (IDS)
Time Frame: During the operation
|
The Intubation Difficulty Scale (IDS) is an objective way to classify easy and difficult intubation.
A score ≤ 5 indicates an easy or mildly difficult intubation, while IDS > 5 suggests difficult intubation, requiring additional techniques or attempts.
|
During the operation
|
Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Onur Küçük, Specialist, Ankara Atatürk Sanatoryum Training and Research Hospital
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Estimated)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 2024-KAEK-24/07
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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