Predicting outcome in acute stroke with large vessel occlusion-application and validation of MR PREDICTS in the ESCAPE-NA1 population.
Martha MarkoMayank GoyalJohanna M OspelNishita SinghEsmee VenemaRaul G NogueiraAndrew M DemchukRyan A McTaggartAlexandre Y PoppeBijoy K MenonCharlotte ZernaMaxim MulderDiederik Wj DippelHester F LingsmaBob RoozenbeekMichael TymianskiMichael D HillPublished in: Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences (2023)
Outcome-prediction using models created from HERMES data, based on information available in the emergency department underestimated the actual outcome in patients with acute ischemic stroke and large vessel occlusion receiving endovascular treatment despite overall good model performance, which might be explained by differences in quality of and time to reperfusion. These findings underline the importance of timely and successful reperfusion for functional outcomes in acute stroke patients.
Keyphrases
- acute ischemic stroke
- emergency department
- endovascular treatment
- acute myocardial infarction
- cerebral ischemia
- liver failure
- computed tomography
- big data
- magnetic resonance imaging
- electronic health record
- heart failure
- subarachnoid hemorrhage
- quality improvement
- respiratory failure
- machine learning
- deep learning
- contrast enhanced
- aortic dissection