Artificial Intelligence as A Complementary Tool for Clincal Decision-Making in Stroke and Epilepsy.

Neurology is a quickly evolving specialty that requires clinicians to make precise and prompt diagnoses and clinical decisions based on the latest evidence-based medicine practices. In all Neurology subspecialties-Stroke and Epilepsy in particular-clinical decisions affecting patient outcomes depend on neurologists accurately assessing patient disability. Artificial intelligence [AI] can predict the expected neurological impairment from an AIS [Acute Ischemic Stroke], the possibility of ICH [IntraCranial Hemorrhage] expansion, and the clinical outcomes of comatose patients. This review article informs readers of artificial intelligence principles and methods. The article introduces the basic terminology of artificial intelligence before reviewing current and developing AI applications in neurology practice. AI holds promise as a tool to ease a neurologist's daily workflow and supply unique diagnostic insights by analyzing data simultaneously from several sources, including neurological history and examination, blood and CSF laboratory testing, CNS electrophysiologic evaluations, and CNS imaging studies. AI-based methods are poised to complement the other tools neurologists use to make prompt and precise decisions that lead to favorable patient outcomes.

Endovascular thrombectomy with and without preceding intravenous thrombolysis for treatment of large vessel anterior circulation stroke: A cross-sectional analysis of 50,000 patients.

INTRODUCTION: The safety and efficacy of intravenous thrombolysis (IVT) before endovascular thrombectomy (EVT) for large vessel occlusion stroke remains a highly contested and unanswered clinical question. We aim to characterize the clinical profile, complications, and discharge disposition of EVT patients treated with and without preceding IVT using a large, nationally-representative sample. METHODS: The National Inpatient Sample was queried from 2015 to 2018 to identify adult patients with anterior circulation stroke treated with EVT with and without preceding IVT. Multivariable logistic regression analysis and propensity-score matching were employed to assess adjusted associations with clinical endpoints and to address confounding by indication for IVT, respectively. RESULTS: Among 48,525 patients identified, 40.7% (n = 19,735) received IVT prior to EVT. On unadjusted analysis, patients treated with IVT bridging therapy experienced higher rates of intracranial hemorrhage (26% vs. 24%, p = 0.003) and routine discharge to home with or without services (33% vs. 27%, p < 0.001), a lower frequency of thromboembolic complications (3% vs. 5%, p < 0.001), and lower rates of extended hospital stays (eLOS) (20% vs. 24%, p < 0.001). Multivariable logistic regression analysis adjusting for demographic and baseline clinical characteristics demonstrated independent associations of IVT bridging therapy with intracranial hemorrhage (aOR 1.28, 95% CI 1.15, 1.43; p < 0.001), thromboembolic complications (aOR 0.66, 95% CI 0.53, 0.83; p < 0.001), routine discharge (aOR 1.27, 95% CI 1.15, 1.40; p < 0.001), and eLOS (aOR 0.76, 95% CI 0.68, 0.85; p < 0.001). Sensitivity testing confirmed these findings. CONCLUSION: Preceding IVT was associated with favorable functional outcomes following endovascular therapy. Prospective randomized clinical trials are warranted for further evaluation.