SAFEAIR: Secure Airway Prediction through Flexible Endoscopy and Artificial Intelligence Recognitio
Recruiting
- Conditions
- T88.4Failed or difficult intubation
- Registration Number
- DRKS00033992
- Lead Sponsor
- niversitätsklinikum des Saarlandes
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Recruiting
- Sex
- All
- Target Recruitment
- 1000
Inclusion Criteria
Surgery at HNT-Department with endotracheal intubation
Exclusion Criteria
Minor patients
Patients undergoing emergency surgery
Patients with known intubation difficulties who need to be intubated while awake
Patients who do not require intubation due to surgery
Study & Design
- Study Type
- observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method prediction of a difficult airway
- Secondary Outcome Measures
Name Time Method adverse events while securing airway
Related Research Topics
Explore scientific publications, clinical data analysis, treatment approaches, and expert-compiled information related to the mechanisms and outcomes of this trial. Click any topic for comprehensive research insights.
What anatomical or physiological biomarkers does AI in SAFEAIR identify for predicting difficult intubation?
How does AI-guided flexible endoscopy compare to traditional Mallampati scoring in airway assessment accuracy?
What adverse events are associated with AI-based airway prediction in observational studies like SAFEAIR?
Are there specific laryngeal or pharyngeal features linked to failed intubation in the SAFEAIR trial dataset?
How do machine learning models in SAFEAIR enhance preoperative airway risk stratification compared to video laryngoscopy?