Mobile Interventional Stroke Teams Improve Outcomes in the Early Time Window for Large Vessel Occlusion Stroke.

BACKGROUND AND PURPOSE: Endovascular thrombectomy for large vessel occlusion stroke is a time-sensitive intervention. The use of a Mobile Interventional Stroke Team (MIST) traveling to Thrombectomy Capable Stroke Centers to perform endovascular thrombectomy has been shown to be significantly faster with improved discharge outcomes, as compared with the drip-and-ship (DS) model. The effect of the MIST model stratified by time of presentation has yet to be studied. We hypothesize that patients who present in the early window (last known well of ≤6 hours) will have better clinical outcomes in the MIST model. METHODS: The NYC MIST Trial and a prospectively collected stroke database were assessed for patients undergoing endovascular thrombectomy from January 2017 to February 2020. Patients presenting in early and late time windows were analyzed separately. The primary end point was the proportion with a good outcome (modified Rankin Scale score of 0-2) at 90 days. Secondary end points included discharge National Institutes of Health Stroke Scale and modified Rankin Scale. RESULTS: Among 561 cases, 226 patients fit inclusion criteria and were categorized into MIST and DS cohorts. Exclusion criteria included a baseline modified Rankin Scale score of >2, inpatient status, or fluctuating exams. In the early window, 54% (40/74) had a good 90-day outcome in the MIST model, as compared with 28% (24/86) in the DS model (P<0.01). In the late window, outcomes were similar (35% versus 41%; P=0.77). The median National Institutes of Health Stroke Scale at discharge was 5.0 and 12.0 in the early window (P<0.01) and 5.0 and 11.0 in the late window (P=0.11) in the MIST and DS models, respectively. The early window discharge modified Rankin Scale was significantly better in the MIST model (P<0.01) and similar in the late window (P=0.41). CONCLUSIONS: The MIST model in the early time window results in better 90-day outcomes compared with the DS model. This may be due to the MIST capturing high-risk fast progressors at an earlier time point. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03048292.

Neighborhood characteristics and psychiatric disorders in the aftermath of mass trauma: A representative study of New York City public school 4th-12th graders after 9/11.

Studies of the relationship between neighborhood characteristics and childhood/adolescent psychopathology in large samples examined one outcome only, and/or general (e.g., 'psychological distress') or aggregate (e.g., 'any anxiety disorder') measures of psychopathology. Thus, in the only representative sample of New York City public school 4th-12th graders (N = 8202) surveyed after the attacks of 9/11/2001, this study examined whether (1) indices of neighborhood Socioeconomic Status, Quality, and Safety and (2) neighborhood disadvantage (defined as multidimensional combinations of SES, Quality and Safety indicators) are associated with eight psychiatric disorders: posttraumatic stress disorder, separation anxiety disorder (SAD), agoraphobia, generalized anxiety disorder (GAD), panic disorder, major depression, conduct disorder, and alcohol use disorder (AUD). (1) The odds ratios (OR) of psychiatric disorders were between 0.55 (AUD) and 1.55 (agoraphobia), in low and intermediate-low SES neighborhoods, respectively, between 0.50 (AUD) and 2.54 (agoraphobia) in low Quality neighborhoods, and between 0.52 (agoraphobia) and 0.65 (SAD) in low Safety neighborhoods. (2) In neighborhoods characterized by high disadvantage, the OR were between 0.42 (AUD) and 1.36 (SAD). This study suggests that neighborhood factors are important social determinants of childhood/adolescent psychopathology, even in the aftermath of mass trauma. At the community level, interventions on modifiable neighborhood characteristics and targeted resources allocation to high-risk contexts could have a cost-effective broad impact on children's mental health. At the individual-level, increased knowledge of the living environment during psychiatric assessment and treatment could improve mental health outcomes; for example, specific questions about neighborhood factors could be incorporated in DSM-5's Cultural Formulation Interview.

Real-World Experience with Artificial Intelligence-Based Triage in Transferred Large Vessel Occlusion Stroke Patients.

BACKGROUND AND PURPOSE: Randomized controlled trials have demonstrated the importance of time to endovascular therapy (EVT) in clinical outcomes in large vessel occlusion (LVO) acute ischemic stroke. Delays to treatment are particularly prevalent when patients require a transfer from hospitals without EVT capability onsite. A computer-aided triage system, Viz LVO, has the potential to streamline workflows. This platform includes an image viewer, a communication system, and an artificial intelligence (AI) algorithm that automatically identifies suspected LVO strokes on CTA imaging and rapidly triggers alerts. We hypothesize that the Viz application will decrease time-to-treatment, leading to improved clinical outcomes. METHODS: A retrospective analysis of a prospectively maintained database was assessed for patients who presented to a stroke center currently utilizing Viz LVO and underwent EVT following transfer for LVO stroke between July 2018 and March 2020. Time intervals and clinical outcomes were compared for 55 patients divided into pre- and post-Viz cohorts. RESULTS: The median initial door-to-neuroendovascular team (NT) notification time interval was significantly faster (25.0 min [IQR = 12.0] vs. 40.0 min [IQR = 61.0]; p = 0.01) with less variation (p < 0.05) following Viz LVO implementation. The median initial door-to-skin puncture time interval was 25 min shorter in the post-Viz cohort, although this was not statistically significant (p = 0.15). CONCLUSIONS: Preliminary results have shown that Viz LVO implementation is associated with earlier, more consistent NT notification times. This application can serve as an early warning system and a failsafe to ensure that no LVO is left behind.