Predicting Acute Brain Injury in Venoarterial Extracorporeal Membrane Oxygenation Patients with Tree-Based Machine Learning: Analysis of the Extracorporeal Life Support Organization Registry.
Andrew KalraPreetham BachinaBenjamin L ShouJaeho HwangMeylakh BarshayShreyas KulkarniIsaac SearsCarsten EickhoffChristian A BermudezDaniel BrodieCorey E VentetuoloBo Soo KimGlenn J R WhitmanAdeel AbbasiSung-Min ChoPublished in: Research square (2024)
This is the largest study predicting neurological complications on sufficiently powered international ECMO cohorts. Longer ECMO duration and higher 24h pump flow were associated with ABI in both non-ECPR and ECPR VA-ECMO.
Keyphrases
- extracorporeal membrane oxygenation
- brain injury
- respiratory failure
- acute respiratory distress syndrome
- machine learning
- subarachnoid hemorrhage
- cardiopulmonary resuscitation
- cerebral ischemia
- liver failure
- cardiac arrest
- mechanical ventilation
- risk factors
- intensive care unit
- big data
- drug induced
- blood brain barrier