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INTRODUCTION: United States stroke systems are increasingly transitioning from alteplase (TPA) to tenecteplase (TNK). Real-world data on the safety and effectiveness of replacing TPA with TNK before large vessel occlusion (LVO) stroke endovascular treatment (EVT) are lacking. METHODS: Four Pennsylvania stroke systems transitioned from TPA to TNK during the study period 01/2020-06/2023. LVO stroke patients who received intravenous thrombolysis with TPA or TNK before EVT were reviewed. Multivariate logistic analysis was conducted adjusting for age, sex, National Institute of Health Stroke Scale (NIHSS), occlusion site, last-known-well-to-intravenous thrombolysis time, interhospital-transfer and stroke system. RESULTS: Of 635 patients, 309 (48.7%) received TNK and 326 (51.3%) TPA prior to EVT. The site of occlusion was the M1 middle cerebral artery (MCA) (47.7%), M2 MCA (25.4%), internal carotid artery (14.0%), tandem carotid with M1 or M2 MCA (9.8%) and basilar artery (3.1%). A favorable functional outcome (90-day mRS ≤ 2) was observed in 47.6% of TNK and 49.7% of TPA patients (p = 0.132). TNK versus TPA groups had similar rates of early recanalization (11.9% vs. 8.4%, p = 0.259), successful endovascular reperfusion (93.5% vs. 89.3%, p = 0.627), symptomatic intracranial hemorrhage (3.2% vs. 3.4%, p = 0.218) and 90-day all-cause mortality (23.1% vs. 21.5%, p = 0.491). CONCLUSIONS: This U.S. multicenter real-world clinical experience demonstrated that switching from TPA to TNK before EVT for LVO stroke resulted in similar endovascular reperfusion, safety, and functional outcomes.

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BACKGROUND: The M1 middle cerebral artery (MCA) commonly bifurcates into M2 superior and M2 inferior segments. However, MCA anatomy is highly variable rendering classification for mechanical thrombectomy trials difficult. This study explored safety and effectiveness of M2 MCA stroke thrombectomy stratified by M2 MCA anatomy. METHODS: Cases of large vessel occlusion strokes treated by mechanical thrombectomy between February 2016 and August 2022 were reviewed (N = 784). M1 (n = 431) and M2 (n = 118) MCA occlusions were assessed. Among M2 MCA occlusions, only prototypical MCA bifurcation anatomy cases were included (n = 99). Dominance was assessed based on angiography. Procedural and outcome data were compared between M1, M2 superior, and M2 inferior MCA occlusions. RESULTS: Baseline demographics and periprocedural criteria of M2 superior (n = 56) and M2 inferior (n = 43) occlusion mechanical thrombectomies were comparable. The occluded branch was dominant in 41/43 (95.3%) M2 inferior cases, but in only 37/56 (66.1%) M2 superior cases (P < 0.001). The 90-day favorable functional outcome (modified Rankin Scale score 0-2) and mortality (modified Rankin Scale score 6) rates were 60.0% and 8.9% in M2 superior, 42.9% and 32.6% in M2 inferior, and 44.1% and 26.0% in M1 (n = 431) cases. Compared with M2 superior cases, in M2 inferior cases, favorable outcome rates were lower (P = 0.094) and mortality rates were higher (P = 0.003) and resembled M1 rates (P = 0.750 and P = 0.355, respectively). CONCLUSIONS: In the setting of prototypical MCA bifurcation anatomy, thrombectomy of dominant M2 inferior occlusions had outcome rates similar to M1 occlusions. In contrast, M2 superior occlusions had significantly lower mortality rates and a trend toward better favorable functional outcome rates.

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BACKGROUND: Tenecteplase (TNK) is a genetically modified variant of alteplase (TPA) and has been established as a non-inferior alternative to TPA in acute ischemic stroke (AIS). Whether TNK exerts distinct benefits in large vessel occlusion (LVO) AIS is still being investigated. OBJECTIVE: To describe our first-year experience after a healthcare system-wide transition from TPA to TNK as the primary thrombolytic. METHODS: Patients with AIS who received intravenous thrombolytics between January 2020 and August 2022 were retrospectively reviewed. All patients with LVO considered for mechanical thrombectomy (MT) were included in this analysis. Spontaneous recanalization (SR) after TNK/TPA was a composite variable of reperfusion >50% of the target vessel territory on cerebral angiography or rapid, significant neurological recovery averting MT. Propensity score matching (PSM) was performed to compare SR rates between TNK and TPA. RESULTS: A total of 148 patients were identified; 51/148 (34.5%) received TNK and 97/148 (65.5%) TPA. The middle cerebral arteries M1 (60.8%) and M2 (29.7%) were the most frequent occlusion sites. Baseline demographics were comparable between TNK and TPA groups. Spontaneous recanalization was significantly more frequently observed in the TNK than in the TPA groups (unmatched: 23.5% vs 10.3%, P=0.032). PSM substantiated the observed SR rates (20% vs 10%). Symptomatic intracranial hemorrhage, 90-day mortality, and functional outcomes were similar. CONCLUSIONS: The preliminary experience from a real-world setting demonstrates the effectiveness and safety of TNK before MT. The higher spontaneous recanalization rates with TNK are striking. Additional studies are required to investigate whether TNK is superior to TPA in LVO AIS.

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Background and Purpose: Hospital readmissions impose a substantial burden on the healthcare system. Reducing readmissions after stroke could lead to improved quality of care especially since stroke is associated with a high rate of readmission. The goal of this study is to enhance our understanding of the predictors of 30-day readmission after ischemic stroke and develop models to identify high-risk individuals for targeted interventions. Methods: We used patient-level data from electronic health records (EHR), five machine learning algorithms (random forest, gradient boosting machine, extreme gradient boosting-XGBoost, support vector machine, and logistic regression-LR), data-driven feature selection strategy, and adaptive sampling to develop 15 models of 30-day readmission after ischemic stroke. We further identified important clinical variables. Results: We included 3,184 patients with ischemic stroke (mean age: 71 ± 13.90 years, men: 51.06%). Among the 61 clinical variables included in the model, the National Institutes of Health Stroke Scale score above 24, insert indwelling urinary catheter, hypercoagulable state, and percutaneous gastrostomy had the highest importance score. The Model's AUC (area under the curve) for predicting 30-day readmission was 0.74 (95%CI: 0.64-0.78) with PPV of 0.43 when the XGBoost algorithm was used with ROSE-sampling. The balance between specificity and sensitivity improved through the sampling strategy. The best sensitivity was achieved with LR when optimized with feature selection and ROSE-sampling (AUC: 0.64, sensitivity: 0.53, specificity: 0.69). Conclusions: Machine learning-based models can be designed to predict 30-day readmission after stroke using structured data from EHR. Among the algorithms analyzed, XGBoost with ROSE-sampling had the best performance in terms of AUC while LR with ROSE-sampling and feature selection had the best sensitivity. Clinical variables highly associated with 30-day readmission could be targeted for personalized interventions. Depending on healthcare systems' resources and criteria, models with optimized performance metrics can be implemented to improve outcomes.

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STUDY OBJECTIVE: The aim of this study is to determine the accuracy of pre-hospital trauma notifications and the effects of inaccurate information on trauma triage. METHODS: This study was conducted at a level-1 trauma center over a two-year period. Data was collected from pre-notification forms on trauma activations that arrived to the emergency department via ambulance. Trauma activations with pre-notification were compared to those without notification and pre-notification forms were assessed for accuracy and completeness. RESULTS: A total of 2186 trauma activations were included in the study, 1572 (71.9%) had pre-notifications, 614 (28.1%) did not and were initially under-triaged. Pre-notification forms were completed for 1505 (95.7%) patients, of which EMS provided incomplete/inaccurate information for 1204 (80%) patients and complete/accurate information for 301 (20%) patients. Missing GCS/AVPU score (1099, 91.3%), wrong age (357, 29.6%), and missing vitals (303, 25.2%) were the main problems. Missing/wrong information resulted in trauma tier over-activation in 25 (2.1%) patients and under-activation in 20 (1.7%) patients. Under-triaged patients were predominantly male (18, 90%), sustained a fall (9, 45%), transported by BLS EMS teams (12, 60%), and arrived on a weekday (13, 65%) during the time period of 11 pm-7 am (9, 45%). A total of 13 (65%) required emergent intubation, 2 (10%) required massive transfusion activation, 7 (35%) were admitted to ICU, 3 (15%) were admitted directly to the OR, and 1 (15%) died. CONCLUSION: EMS crews frequently provide inaccurate pre-hospital information or do not provide any pre-hospital notification at all, which results in over/under triage of trauma patients.

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Neurocritical care aims to improve outcomes in patients with life-threatening neurologic illness. The scope of neurocritical care extends beyond the more commonly encountered and important field of cerebrovascular disease, as described previously. This article focuses on neuromuscular, neuroinfectious, and neuroimmunologic conditions that are significant causes of morbidity and mortality in the acutely neurologically ill patient. As understanding continues to increase regarding the physiology of these conditions and the best treatment, rapid identification, triage, and treatment of these patients in the emergency department is paramount.

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