Trends in stroke-related journals: Examination of publication patterns using topic modeling.

Objectives: This study aims to demonstrate the capacity of natural language processing and topic modeling to manage and interpret the vast quantities of scholarly publications in the landscape of stroke research. These tools can expedite the literature review process, reveal hidden themes, and track rising research areas.

Materials And Methods: Our study involved reviewing and analyzing articles published in five prestigious stroke journals, namely Stroke, International Journal of Stroke, European Stroke Journal, Translational Stroke Research, and Journal of Stroke and Cerebrovascular Diseases.

Development of machine learning models for predicting outcome in patients with distal medium vessel occlusions: a retrospective study.

Background: While numerous prognostic factors have been reported for large vessel occlusion (LVO)-acute ischemic stroke (AIS) patients, the same cannot be said for distal medium vessel occlusions (DMVOs). We used machine learning (ML) algorithms to develop a model predicting the short-term outcome of AIS patients with DMVOs using demographic, clinical, and laboratory variables and baseline computed tomography (CT) perfusion (CTP) postprocessing quantitative parameters.

Methods: In this retrospective cohort study, consecutive patients with AIS admitted to two comprehensive stroke centers between January 1, 2017, and September 1, 2022, were screened.

Assessing the Efficacy of Mechanical Thrombectomy in Patients with an NIHSS < 6 Presenting with Proximal Middle Cerebral Artery Vessel Occlusion as Compared to Best Medical Management.

Background And Purpose: Minor acute ischemic stroke (AIS) patients-defined by an NIHSS score < 6-presenting with proximal middle cerebral artery large vessel occlusions (MCA-LVO) is a subgroup for which treatment is still debated. Although these patients present with minor symptoms initially, studies have shown that several patients afflicted with MCA-LVO in this subgroup experience cognitive and functional decline. Although mechanical thrombectomy (MT) is the standard of care for patients with an NIHSS score of 6 or higher, treatment in the minor stroke subgroup is still being explored.

Arterial Spin Labeling Imaging Characteristics of Anti-leucine-rich Glioma-Inactivated 1 Encephalitis: A Qualitative and Quantitative Analysis.

Background And Significance: Autoimmune encephalitis (AE) is a rare group of diseases that can present with stroke-like symptoms. Anti-leucine-rich glioma inactivated 1 (LGI1) encephalitis is an AE subtype that is infrequently associated with neoplasms and highly responsive to prompt immunotherapy treatment. Therefore, accurate diagnosis of LGI1 AE is essential in timely patient management.