Pre-anesthesia Imaging-based Respiratory Assessment and Analysis
NCT ID: NCT06270797
Last Updated: 2024-02-21
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
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
RECRUITING
30000 participants
OBSERVATIONAL
2024-03-01
2026-12-31
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Machine Learning Model to Predict Postoperative Respiratory Failure
NCT04527094
Optimization of Chest Tube Drainage Management
NCT03791437
Early Oral Hydration After Thoracoscopic Surgery
NCT06297720
Retrospective Study in Patients Who Have Had a Difficult Intubation.
NCT02576756
Establishment of Airway Database for Surgical Patients
NCT03125837
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
Various risk factors have been proposed in past literature for discussion, and corresponding to these risk factors, there is currently no single factor that can predict difficult intubation completely. Existing investigations into difficult intubation factors mostly focus on high-risk populations, including patients with morbid obesity, where significant differences have been identified but not developed into predictive models.
With the rapid development of AI-related technologies in recent years, numerous image-related AI frameworks have been proposed. In recent years, attempts have been made to combine various clinical risk factors using machine learning methods to create automated prediction models for difficult intubation. However, their effectiveness has not met expectations, reflecting the significant clinical problem of difficulty in prediction that remains unresolved.
This study is an observational study aimed at analyzing and establishing patient image data, refining various data engineering techniques, and optimizing existing prediction model frameworks to enhance their medical value. Additionally, the focus of this project will be on establishing more prediction models to improve existing clinical decision support systems.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
COHORT
PROSPECTIVE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
normal intubation
during general anesthesia, normal intubation without any difficult airway or difficult intubation were recorded in the note.
intubation for general anesthesia
routine intubation for general anesthesia
difficult airway or difficult intubation
during general anesthesia, any type of difficult airway or difficult intubation were recorded in the note.
intubation for general anesthesia
routine intubation for general anesthesia
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
intubation for general anesthesia
routine intubation for general anesthesia
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
* Patients who can undergo pre-anesthetic consultation and airway examination.
Exclusion Criteria
* Patients requiring emergency surgery.
* Vulnerable populations.
18 Years
85 Years
ALL
Yes
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
Kaohsiung Medical University Chung-Ho Memorial Hospital
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Principal Investigators
Learn about the lead researchers overseeing the trial and their institutional affiliations.
Kuang-I Cheng, MD,Phd
Role: STUDY_DIRECTOR
Kaohsiung Medical University Chung-Ho Memorial Hospital
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
Kaohsiung Medical University Chung-Ho Memorial Hospital
Kaohsiung City, Sanmin Dist, Taiwan
Countries
Review the countries where the study has at least one active or historical site.
Central Contacts
Reach out to these primary contacts for questions about participation or study logistics.
Facility Contacts
Find local site contact details for specific facilities participating in the trial.
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
KMUHIRB-E(I)-20230184
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.