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Background: Andexanet alfa (AA), a factor Xa-inhibitor (FXi) reversal agent, is given as a bolus followed by a 2-hour infusion. This long administration time can delay EVD placement in intracerebral hemorrhage (ICH) patients. We sought to evaluate the safety of EVD placement immediately post-AA bolus compared to post-AA infusion., Methods: We conducted a retrospective study that included adult patients admitted with FXi-associated ICH who received AA and underwent EVD placement The primary outcome was the occurrence of a new hemorrhage (tract, extra-axial, or intraventricular hemorrhage). Secondary outcomes included mortality, intensive care unit and hospital length of stay, and discharge modified Rankin Score. The primary safety outcome was documented thrombotic events., Results: Twelve patients with FXi related ICH were included (EVD placement post-AA bolus, N = 8; EVD placement post-AA infusion, N = 4). Each arm included one patient with bilateral EVD placed. There was no difference in the incidence of new hemorrhages, with one post-AA bolus patient had small, focal, nonoperative extra-axial hemorrhage. Morbidity and mortality were higher in post-AA infusion patients (mRS, post-AA bolus, 4 [4-6] vs. post-AA infusion 6 [5,6], p = 0.24 and post-AA bolus, 3 (37.5 %) vs. post-AA infusion, 3 (75 %), p = 0.54, respectively). One patient in the post-AA bolus group had thrombotic event. There was no difference in hospital LOS (post-AA bolus, 19 days [12-26] vs. post-AA infusion, 14 days [9-22], p = 0.55) and ICU LOS (post-AA bolus, 10 days [6-13] vs. post-AA infusion, 11 days [5-21], p = 0.86)., Conclusion: We report no differences in the incidence of tract hemorrhage, extra-axial hemorrhage, or intraventricular hemorrhage post-AA bolus versus post-AA infusion. Larger prospective studies to validate these results are warranted., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background and Purpose: As "time is brain" in acute stroke triage, the need for automated prognostication tools continues to increase, particularly in rapidly expanding tele-stroke settings. We aimed to create an automated prognostication tool for anterior circulation large vessel occlusion (LVO) stroke based on admission CTA radiomics., Methods: We automatically extracted 1116 radiomics features from the anterior circulation territory on admission CTAs of 829 acute LVO stroke patients who underwent mechanical thrombectomy in two academic centers. We trained, optimized, validated, and compared different machine-learning models to predict favorable outcome (modified Rankin Scale ≤ 2) at discharge and 3-month follow-up using four different input sets: "Radiomics", "Radiomics + Treatment" (radiomics, post-thrombectomy reperfusion grade, and intravenous thrombolysis), "Clinical + Treatment" (baseline clinical variables and treatment), and "Combined" (radiomics, treatment, and baseline clinical variables)., Results: For discharge outcome prediction, models were optimized/trained on n = 494 and tested on an independent cohort of n = 100 patients from Yale. Receiver operating characteristic analysis of the independent cohort showed no significant difference between best-performing Combined input models (area under the curve, AUC = 0.77) versus Radiomics + Treatment (AUC = 0.78, p = 0.78), Radiomics (AUC = 0.78, p = 0.55), or Clinical + Treatment (AUC = 0.77, p = 0.87) models. For 3-month outcome prediction, models were optimized/trained on n = 373 and tested on an independent cohort from Yale (n = 72), and an external cohort from Geisinger Medical Center (n = 232). In the independent cohort, there was no significant difference between Combined input models (AUC = 0.76) versus Radiomics + Treatment (AUC = 0.72, p = 0.39), Radiomics (AUC = 0.72, p = 0.39), or Clinical + Treatment (AUC = 76, p = 0.90) models; however, in the external cohort, the Combined model (AUC = 0.74) outperformed Radiomics + Treatment (AUC = 0.66, p < 0.001) and Radiomics (AUC = 0.68, p = 0.005) models for 3-month prediction., Conclusion: Machine-learning signatures of admission CTA radiomics can provide prognostic information in acute LVO stroke candidates for mechanical thrombectomy. Such objective and time-sensitive risk stratification can guide treatment decisions and facilitate tele-stroke assessment of patients. Particularly in the absence of reliable clinical information at the time of admission, models solely using radiomics features can provide a useful prognostication tool., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Although statins have been associated with increased risk of spontaneous intracerebral hemorrhage, their relationship with cerebral microbleeds (CMBs) formation is poorly understood. We systematically reviewed previously published studies reporting on the association between CMBs presence and current statin use. We performed a systematic search in MEDLINE and SCOPUS databases on October 24, 2019 to identify all cohorts from randomized-controlled clinical trials or observational studies reporting on CMB prevalence and statin use. We extracted cross-sectional data on CMBs presence, as provided by each study, in association to the history of current statin use. Random effects model was used to calculate the pooled estimates. We included 7 studies (n = 3734 participants): unselected general population [n = 1965], ischemic stroke [n = 849], hemorrhagic stroke [n = 252] and patients with hypertension over the age of 60 [n = 668]. Statin use was not associated with CMBs presence in either unadjusted (OR = 1.15, 95%CI: 0.76-1.74) or adjusted analyses (OR = 1.09, 95%CI: 0.64-1.86). Statin use was more strongly related to lobar CMB presence (OR = 2.01, 95%CI: 1.48-2.72) in unadjusted analysis. The effect size of this association was consistent, but no longer statistically significant in adjusted analysis that was confined to two eligible studies (OR = 2.26, 95%CI: 0.86-5.91). Except for the analysis on the unadjusted probability of lobar CMBs presence, considerable heterogeneity was present in all other analyses (I 2  > 60%). Our findings suggest that statin treatment seems not to be associated with CMBs overall, but may increase the risk of lobar CMB formation. This hypothesis deserves further investigation within magnetic resonance imaging ancillary studies of randomized trials., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Objective: The counseling of patients with idiopathic normal pressure hydrocephalus (iNPH) is difficult; there is variability in the diagnostic criteria, and a definitive diagnosis can be made only postoperatively. A patient's clinical response to shunting is also difficult to predict. This study examines the subjective experience of patients treated for iNPH, to identify the challenges patients face and to improve patient outcomes and satisfaction., Methods: We reviewed a consecutive series of patients diagnosed with iNPH who underwent ventriculoperitoneal shunt surgery between January 2012 and March 2016 at our institution. Semistructured telephone interviews were conducted with 31 patients. Interviews were analyzed using the principles of grounded theory., Results: Thirty-one patients who underwent shunt surgery for iNPH were interviewed to reach saturation of themes. Seven themes were identified: 1) long preoperative course causes morbidity; 2) the decision to have shunt surgery is easy to make; 3) patients primarily desire to gain independence; 4) patients show variable levels of anxiety; 5) comorbid conditions interfere with postoperative assessment; 6) patients stand by their decision to have shunt surgery; and 7) outside information is used before surgery., Conclusions: Patients often present to the neurosurgeon frustrated and desperate after a long preoperative course. It is important to acknowledge the uncertainty regarding diagnosis and response to shunting when counseling patients. Comorbid conditions interfere with the ability to assess progression of iNPH and the effectiveness of the shunt. Patient caregivers play a large role in decision making and clinical course and should be included when counseling patients., (Copyright © 2018 Elsevier Inc. All rights reserved.)