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BackgroundPrehospital automated large vessel occlusion (LVO) detection in Mobile Stroke Units (MSUs) could accelerate identification and treatment of patients with LVO acute ischemic stroke. Here, we evaluate the performance of a machine learning (ML) model on CT angiograms (CTAs) obtained from 2 MSUs to detect LVO.MethodsPatients evaluated on MSUs in Houston and Los Angeles with out-of-hospital CTAs were identified. Anterior circulation LVO was defined as an occlusion of the intracranial internal carotid artery, middle cerebral artery (M1 or M2), or anterior cerebral artery vessels and determined by an expert human reader. A ML model to detect LVO was trained and tested on independent data sets consisting of in-hospital CTAs and then tested on MSU CTA images. Model performance was determined using area under the receiver-operator curve statistics.ResultsAmong 68 patients with out-of-hospital MSU CTAs, 40% had an LVO. The most common occlusion location was the middle cerebral artery M1 segment (59%), followed by the internal carotid artery (30%), and middle cerebral artery M2 (11%). Median time from last known well to CTA imaging was 88.0 (interquartile range, 59.5-196.0) minutes. After training on 870 in-hospital CTAs, the ML model performed well in identifying LVO in a separate in-hospital data set of 441 images with area under receiver-operator curve of 0.84 (95% CI, 0.80-0.87). ML algorithm analysis time was under 1 minute. The performance of the ML model on the MSU CTA images was comparable with area under receiver-operator curve 0.80 (95% CI, 0.71-0.89). There was no significant difference in performance between the Houston and Los Angeles MSU CTA cohorts.ConclusionsIn this study of patients evaluated on MSUs in 2 cities, a ML algorithm was able to accurately and rapidly detect LVO using prehospital CTA acquisitions.

Background Evidence suggests intracerebral hemorrhage survivors have earlier recovery compared with ischemic stroke survivors. The Centers for Medicare and Medicaid Services prospective payment system instituted documentation rules for inpatient rehabilitation facilities (IRFs) in 2010, with the goal of optimizing patient selection. We investigated whether these requirements limited IRF and increased skilled nursing facility (SNF) use compared with home discharge. Methods and Results Intracerebral hemorrhage discharges to IRF, SNF, or home were estimated using GWTG (Get With The Guidelines) Stroke registry data between January 1, 2008, and December 31, 2015 (n=265 444). Binary hierarchical models determined associations between the 2010 Rule and discharge setting; subgroup analyses evaluated age, geographic region, and hospital type. From January 1, 2008, to December 31, 2009, 45.5% of patients with intracerebral hemorrhage had home discharge, 22.2% went to SNF, and 32.3% went to IRF. After January 1, 2010, there was a 1.06% absolute increase in home discharge, a 0.46% increase in SNF, and a 1.52% decline in IRF. The adjusted odds of IRF versus home discharge decreased 3% after 2010 (adjusted odds ratio [aOR], 0.97; 95% CI, 0.95-1.00). Lower odds of IRF versus home discharge were observed in people aged

Objectives: The benefits of intravenous thrombolysis are time‐dependent, with maximum efficacy when administered within the first "golden" hour after onset. Nevertheless, the impact of golden hour thrombolysis has not been well quantified. Methods: Medline, Embase, and Web of Science databases were systematically searched from inception to August 27, 2023. We included studies that reported safety and efficacy outcomes of ischemic stroke patients treated with intravenous thrombolysis in the golden hour versus later treatment window. The primary outcome was an excellent functional outcome, defined as a modified Rankin Scale score of 0–1 at 90 days. The secondary efficacy outcome was a good functional outcome (defined as modified Rankin Scale score of 0–2). The main safety outcome was symptomatic intracerebral hemorrhage. Results: Seven studies involving 78,826 patients met the selection criteria. Golden hour thrombolysis was associated with higher odds of 90‐day excellent functional outcomes (OR 1.40, 95% CI 1.16–1.67) and 90‐day good functional outcomes (OR 1.38, 95% CI 1.13–1.69) compared with thrombolysis outside the golden hour. The number needed to treat to benefit for golden hour thrombolysis to reduce disability by at least 1 level on the modified Rankin Scale per patient was 2.6. Rates of symptomatic intracerebral hemorrhage and mortality were similar between groups. Interpretation: Golden hour thrombolysis significantly improved acute ischemic stroke outcomes. The findings provide rationale for intensive efforts aimed at expediting thrombolytic therapy within the golden hour window following the onset of acute ischemic stroke. ANN NEUROL 2024;96:582–590 [ABSTRACT FROM AUTHOR]

Background and purposeAlthough the modified Rankin Scale (mRS) is the most commonly used primary end point in acute stroke trials, its power is limited when analyzed in dichotomized fashion and its indication of effect size challenging to interpret when analyzed ordinally. Weighting the 7 Rankin levels by utilities may improve scale interpretability while preserving statistical power.MethodsA utility-weighted mRS (UW-mRS) was derived by averaging values from time-tradeoff (patient centered) and person-tradeoff (clinician centered) studies. The UW-mRS, standard ordinal mRS, and dichotomized mRS were applied to 11 trials or meta-analyses of acute stroke treatments, including lytic, endovascular reperfusion, blood pressure moderation, and hemicraniectomy interventions.ResultsUtility values were 1.0 for mRS level 0; 0.91 for mRS level 1; 0.76 for mRS level 2; 0.65 for mRS level 3; 0.33 for mRS level 4; 0 for mRS level 5; and 0 for mRS level 6. For trials with unidirectional treatment effects, the UW-mRS paralleled the ordinal mRS and outperformed dichotomous mRS analyses. Both the UW-mRS and the ordinal mRS were statistically significant in 6 of 8 unidirectional effect trials, whereas dichotomous analyses were statistically significant in 2 to 4 of 8. In bidirectional effect trials, both the UW-mRS and ordinal tests captured the divergent treatment effects by showing neutral results, whereas some dichotomized analyses showed positive results. Mean utility differences in trials with statistically significant positive results ranged from 0.026 to 0.249.ConclusionsA UW-mRS performs similar to the standard ordinal mRS in detecting treatment effects in actual stroke trials and ensures the quantitative outcome is a valid reflection of patient-centered benefits.

Background and purposeIntra-arterial therapy (IAT) promotes recanalization of large artery occlusions in acute ischemic stroke. Despite high recanalization rates, poor clinical outcomes are common. We attempted to optimize a score that combines clinical and imaging variables to more accurately predict poor outcome after IAT in anterior circulation occlusions.MethodsPatients with acute ischemic stroke undergoing IAT at University of Texas (UT) Houston for large artery occlusions (middle cerebral artery or internal carotid artery) were reviewed. Independent predictors of poor outcome (modified Rankin Scale, 4-6) were studied. External validation was performed on IAT-treated patients at Emory University.ResultsA total of 163 patients were identified at UT Houston. Independent predictors of poor outcome (P≤0.2) were identified as score variables using sensitivity analysis and logistic regression. Houston Intra-Arterial Therapy 2 (HIAT2) score ranges 0 to 10: age (≤59=0, 60-79=2, ≥80 years=4), glucose (

BackgroundMinorities have an increased incidence of early-onset, obesity-related cerebrovascular disease. Unfortunately, effective weight management in this vulnerable population has significant barriers. ObjectiveOur objective was to determine the feasibility and preliminary treatment effects of a smartphone-based weight loss intervention versus food journals to monitor dietary patterns in minority stroke patients. MethodsSwipe out Stroke was a pilot prospective randomized controlled trial with open blinded end point. Minority stroke patients and their caregivers were screened for participation using cluster enrollment. We used adaptive randomization for assignment to a behavior intervention with (1) smartphone-based self-monitoring or (2) food journal self-monitoring. The smartphone group used Lose it! to record meals and communicate with us. Reminder messages (first 30 days), weekly summaries plus reminder messages on missed days (days 31-90), and weekly summaries only (days 91-180) were sent via push notifications. The food journal group used paper diaries. Both groups received 4 in-person visits (baseline and 30, 90, and 180 days), culturally competent counseling, and educational materials. The primary outcome was reduced total body weight. ResultsWe enrolled 36 stroke patients (n=23, 64% African American; n=13, 36% Hispanic), 17 in the smartphone group, and 19 in the food journal group. Mean age was 54 (SD 9) years; mean body mass index was 35.7 (SD 5.7) kg/m2; education, employment status, and family history of stroke or obesity did not differ between the groups. Baseline rates of depression (Patient Health Questionnaire-9 [PHQ-9] score median 5.5, IQR 3.0-9.5), cognitive impairment (Montreal Cognitive Assessment score median 23.5, IQR 21-26), and inability to ambulate (5/36, 14% with modified Rankin Scale score 3) were similar. In total, 25 (69%) stroke survivors completed Swipe out Stroke (13/17 in the smartphone group, 12/19 in the food journal group); 1 participant in the smartphone group died. Median weight change at 180 days was 5.7 lb (IQR –2.4 to 8.0) in the smartphone group versus 6.4 lb (IQR –2.2 to 12.5; P=.77) in the food journal group. Depression was significantly lower at 30 days in the smartphone group than in the food journal group (PHQ-9 score 2 vs 8; P=.03). Clinically relevant depression rates remained in the zero to minimal range for the smartphone group compared with mild to moderate range in the food journal group at day 90 (PHQ-9 score 3.5 vs 4.5; P=.39) and day 180 (PHQ-9 score 3 vs 6; P=.12). ConclusionsIn a population of obese minority stroke survivors, the use of a smartphone did not lead to a significant difference in weight change compared with keeping a food journal. The presence of baseline depression (19/36, 53%) was a confounding variable, which improved with app engagement. Future studies that include treatment of poststroke depression may positively influence intervention efficacy. Trial RegistrationClinicalTrials.gov NCT02531074; https://www.clinicaltrials.gov/ct2/show/NCT02531074