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Data-driven Development of a Core Dataset for Difficult Airway Alerts
Sponsor: Universitätsklinikum Hamburg-Eppendorf
Summary
Previous difficult airway management is the most accurate predictor of future difficulty. Consistent documentation is paramount for future airway planning, but requires reliable, reproducible and easily accessible information. Currently, anaesthesia alert cards are often based on analogue hard copies while they lack a clinically meaningful core data set allowing structured reproducible documentation and risk estimation. Further, existing alert cards are often inconsistently used and clear triggers for issuing of airway alert cards are widely undefined. The FingAIRprint project aims to develop a justifiable core data set using a data-driven approach in patients undergoing tracheal intubation with videolaryngoscopy or direct laryngoscopy, that is intended to be used for documentation of digital airway alerts.
Official title: Data-driven Development of a Core Dataset for Documentation of Difficult Airway Alerts - a Secondary Analysis of Pooled Database From Three Prospective Studies - the FingAIRprint Project
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
1785
Start Date
2019-04-01
Completion Date
2025-11-30
Last Updated
2025-12-10
Healthy Volunteers
No
Locations (1)
Department of Anesthesiology, Center for Anesthesiology and Intensive Care Medicine, University Medical Center Hamburg-Eppendorf
Hamburg, Germany