Pre-operative Characteristics for Prediction of Supraglottic Airway Failure Using Machine Learning (ERICA)
Launched by UNIVERSITY HOSPITAL ULM · Sep 25, 2024
Trial Information
Current as of April 04, 2025
Active, not recruiting
Keywords
ClinConnect Summary
An intraoperative change of procedure not only leads to time delays but also time delays, but also involves measures that are stressful for the patient, such as deepening the anaesthesia and manipulating the airway again.
Therefore, the objective of ERICA is to develop a machine learning algorithm based on preoperative information 1) that can accurately predict the risk of an unplanned SGA conversion and 2) identifies characteristics leading to conversion from SGA to tracheal tube.
I. Developing the model
• The final dataset will be split in a training, testing, and validation cohort. Fi...
Gender
ALL
Eligibility criteria
- Inclusion Criteria:
- • Adult patients (≥18 years) receiving general anaesthesia for non-cardiac surgery with a supraglottic airway device
- Exclusion Criteria:
- • None
About University Hospital Ulm
University Hospital Ulm is a leading academic medical center dedicated to advancing healthcare through innovative research and clinical excellence. Affiliated with the University of Ulm in Germany, the hospital integrates cutting-edge medical education, pioneering research initiatives, and comprehensive patient care. With a strong emphasis on interdisciplinary collaboration, University Hospital Ulm actively participates in clinical trials aimed at developing new therapeutic strategies and improving patient outcomes. Its commitment to ethical standards and rigorous scientific methodology positions it as a trusted sponsor in the realm of clinical research.
Contacts
Jennifer Cobb
Immunology at National Institute of Allergy and Infectious Diseases (NIAID)
Locations
Munich, Bavaria, Germany
Ulm, Baden Württemberg, Germany
Patients applied
Timeline
First submit
Trial launched
Trial updated
Estimated completion
Not reported
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