Health Technology/clinical-trials

ERICA Study Develops AI Model to Predict Supraglottic Airway Failure — 44,000-Patient Analysis Offers New Risk Stratification Tool

247 Health News Editorial

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19 May 2026

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4 min read

·clinical-trials

German researchers analysed 44,000 patients to develop a machine learning algorithm predicting supraglottic airway failure. The ERICA study offers new risk stratification tools for anaesthetists planning airway management strategies.

Originally reported by ClinicalTrials.gov

References

  1. 1.University Hospital Ulm. (2024). Can Pre-operative Characteristics Predict Failure of Supraglottic Airway to Tracheal Tube? A Machine Learning Algorithm (ERICA). ClinicalTrials.gov. NCT06617403. https://clinicaltrials.gov/study/NCT06617403
  2. 2.Cook, T. M., Woodall, N., Harper, J., & Benger, J. (2011). Major complications of airway management in the UK: results of the Fourth National Audit Project of the Royal College of Anaesthetists and the Difficult Airway Society. British Journal of Anaesthesia, 106(5), 617-631. https://doi.org/10.1093/bja/aer058
  3. 3.Hernandez, M. R., Klock, P. A., & Ovassapian, A. (2012). Evolution of the extraglottic airway: a review of its history, applications, and practical tips for success. Anesthesia & Analgesia, 114(2), 349-368. https://doi.org/10.1213/ANE.0b013e31823b6748
  4. 4.Ramachandran, S. K., Mathis, M. R., Tremper, K. K., Shanks, A. M., & Kheterpal, S. (2013). Predictors and clinical outcomes from failed Laryngeal Mask Airway Unique™: a study of 15,795 patients. Anesthesiology, 118(6), 1351-1362. https://doi.org/10.1097/ALN.0b013e31827d5c90
  5. 5.Brimacombe, J., & Berry, A. (1995). The incidence of aspiration associated with the laryngeal mask airway: a meta-analysis of published literature. Journal of Clinical Anesthesia, 7(4), 297-305. https://doi.org/10.1016/0952-8180(95)00041-0
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