Pre-operative Characteristics for Prediction of Supraglottic Airway Failure Using Machine Learning (ERICA) (ERICA)

May 8, 2026 updated by: Flora Scheffenbichler, University Hospital Ulm

Can Pre-operative Characteristics Predict Failure of Supraglottic Airway to Tracheal Tube? A Machine Learning Algorithm (ERICA)

Supraglottic airway devices (SGA) are a safe and well-established technique for airway management. Nowadays, up to 60% of general anaesthetics performed in European countries use SGA. In 0.2-4.7% SGA fail and require conversion to tracheal tubes.

The ERICA study will use artificial intelligence methods to develop a model that can predict the risk of an unplanned SGA conversion based on pre-operative characteristics available during the premedication visit.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

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. Five models will be created to predict intraoperative conversion from SGA to tracheal tube including generalized linear models (GLM), deep learning, distributed random forest (DRF), xgboost and gradient boosting machine (GBM). Then, a stacked ensemble model will be constructed through combination of the five models. Finally, the best artificial intelligence model will be chosen.

II. Identify characteristics leading to the airway conversion and categorisation.

  • Intraoperative changes of the patient's position can alter the risk of conversion, therefore operations with positional changes should be considered
  • Identify patient- and procedure-dependent characteristics that lead to conversion from SGA to tracheal tube and their importance.

Study Type

Observational

Enrollment (Actual)

44000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Germany
    • Baden-Wurttemberg
      • Ulm, Baden-Wurttemberg, Germany, 89073
        • University Hospital Ulm
    • Bavaria
      • Munich, Bavaria, Germany, 81675
        • Technical University Munich

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Adult patients (≥18 years) receiving non-cardiac surgery using a supraglottic airway device

Description

Inclusion Criteria:

  • Adult patients (≥18 years) receiving general anaesthesia for non-cardiac surgery with a supraglottic airway device

Exclusion Criteria:

  • None

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Time Frame
Risk of unplanned SGA conversion
Time Frame: intraoperative
intraoperative

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

University Hospital Ulm

Collaborators

Technical University of Munich

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

December 1, 2022

Primary Completion (Actual)

November 30, 2024

Study Completion (Actual)

December 31, 2024

Study Registration Dates

First Submitted

September 25, 2024

First Submitted That Met QC Criteria

September 25, 2024

First Posted (Actual)

September 27, 2024

Study Record Updates

Last Update Posted (Actual)

May 13, 2026

Last Update Submitted That Met QC Criteria

May 8, 2026

Last Verified

September 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • ERICA

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

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.

Clinical Trials on Postoperative Complications

Clinical Trials on non

Search Similar Trials

Sponsors and Collaborators

Medical Conditions

Drug Interventions

CROs by country

CROs in Mexico

Conditions

Rare Diseases

Drug Interventions

Dietary Supplements

Sponsor/Collaborators

Locations

Subscribe