Kyle P O'Connor1, Mausaminben Y Hathidara2, Gopichandh Danala3, Chao Xu4, Tressie M McCoy1, Evgeny V Sidorov2, Bin Zheng3, Bradley N Bohnstedt1, Bappaditya Ray5. 1. Department of Neurosurgery, College of Medicine, College of Public Health, Oklahoma University Health Sciences Center, Oklahoma City Oklahoma, USA. 2. Department of Neurology, College of Medicine, College of Public Health, Oklahoma University Health Sciences Center, Oklahoma City Oklahoma, USA. 3. Department of Electrical Engineering, University of Oklahoma, Norman, Oklahoma, USA. 4. Department of Biostatistics and Epidemiology, College of Public Health, Oklahoma University Health Sciences Center, Oklahoma City; Oklahoma, USA. 5. Department of Neurology, College of Medicine, College of Public Health, Oklahoma University Health Sciences Center, Oklahoma City Oklahoma, USA. Electronic address: Bappaditya.Ray@utsouthwestern.edu.
Abstract
OBJECTIVE: To investigate predictive factors and develop an outcome assessment tool to determine clinical outcome after endovascular mechanical thrombectomy (EMT) in patients presenting with large vessel occlusion (LVO). METHODS: A retrospective analysis was carried out of a prospective cohort of patients presenting with LVO who underwent EMT after adoption of an expanded time window of ≤24 hours. Final cerebral infarction volume (CIV) after EMT was estimated using magnetic resonance imaging segmentation software. Stepwise linear regression models were used to identify factors that determined clinical outcome and to develop a predictive scale. RESULTS: Ninety patients underwent EMT over 19 months (68 within 6 hours and 22 between 6 and 24 hours). Clinical outcome determined using modified Rankin Scale (mRS) score at discharge and 3 months was no different among these subcohorts. A threshold of 16.99 mL of CIV, using the Youden index, resulted in a sensitivity of 90.5% and specificity of 58.1% for predicting mRS score of 0-2. A regression model identified gender, age, diabetes mellitus status, CIV, and smoking status as outcome determinants, which were used to develop the GADIS (Gender, Age, Diabetes Mellitus History, Infarct Volume, and Sex) scoring system to predict good clinical outcome. Using the GADIS score, <6 predicted mRS score 0-2 at discharge with a sensitivity of 83.3% and specificity of 80.6%. CONCLUSIONS: The GADIS score for patients with LVO-related acute ischemic stroke includes CIV after EMT and helps in early short-term prognostication. It is not intended to predict preintervention patient selection or outcome prediction.
OBJECTIVE: To investigate predictive factors and develop an outcome assessment tool to determine clinical outcome after endovascular mechanical thrombectomy (EMT) in patients presenting with large vessel occlusion (LVO). METHODS: A retrospective analysis was carried out of a prospective cohort of patients presenting with LVO who underwent EMT after adoption of an expanded time window of ≤24 hours. Final cerebral infarction volume (CIV) after EMT was estimated using magnetic resonance imaging segmentation software. Stepwise linear regression models were used to identify factors that determined clinical outcome and to develop a predictive scale. RESULTS: Ninety patients underwent EMT over 19 months (68 within 6 hours and 22 between 6 and 24 hours). Clinical outcome determined using modified Rankin Scale (mRS) score at discharge and 3 months was no different among these subcohorts. A threshold of 16.99 mL of CIV, using the Youden index, resulted in a sensitivity of 90.5% and specificity of 58.1% for predicting mRS score of 0-2. A regression model identified gender, age, diabetes mellitus status, CIV, and smoking status as outcome determinants, which were used to develop the GADIS (Gender, Age, Diabetes Mellitus History, Infarct Volume, and Sex) scoring system to predict good clinical outcome. Using the GADIS score, <6 predicted mRS score 0-2 at discharge with a sensitivity of 83.3% and specificity of 80.6%. CONCLUSIONS: The GADIS score for patients with LVO-related acute ischemic stroke includes CIV after EMT and helps in early short-term prognostication. It is not intended to predict preintervention patient selection or outcome prediction.
Authors: Arne Potreck; Matthias A Mutke; Charlotte S Weyland; Johannes A R Pfaff; Peter A Ringleb; Sibu Mundiyanapurath; Markus A Möhlenbruch; Sabine Heiland; Mirko Pham; Martin Bendszus; Angelika Hoffmann Journal: Transl Stroke Res Date: 2021-01-11 Impact factor: 6.829