Abstract

Introduction: Automated Large Vessel Occlusion (LVO) detection and software-based care team integration may improve treatment times. Their effect on likelihood to perform Endovascular Thrombectomy (EVT) in LVO Acute Ischemic Stroke (AIS) patients remains undetermined. Methods: We performed a cluster randomized stepped wedge clinical trial across 4 comprehensive stroke centers in the greater Houston area from January 1st 2021 - February 24th 2022. This trial design was chosen due to the impracticality of randomizing at the patient level. An automated LVO detection and workflow manager software (Viz.AI) was implemented at the 4 hospitals in a stepped fashion, with a randomly determined order (Figure 1) . Patients were included if they were diagnosed with LVO AIS based on CT angiogram. Patients who presented during the 2-week transition period at the time of LVO detection software activation were excluded. The primary outcome was proportion of LVO AIS patients treated with EVT adjusted for age, sex and NIHSS and was determined using a mixed-effect logistic regression, with a random effect for cluster (hospital site) and fixed effect for exposure status. Results: Among 834 patients that met inclusion criteria, the median age was 68 [58-79] years, NIHSS 13 [5-20], and 50% were female. Median time from last known well to arrival was 298 [102- 754] minutes. A total of 575 patients were evaluated in the unexposed period and 259 in the exposed. In univariable analysis, there was no significant increase in the proportion of LVO AIS treated with EVT (40.5% vs. 45.6%, unexposed vs. exposed, p=0.17) . In multivariable adjusted mixed-effects model, EVT rates did not change due to software implementation [OR 1.18, p=0.45]. Discussion: In a multi-center cluster randomized trial, implementation of an automated LVO detection software with care team-wide communication did not significantly alter rates of EVT in patients with LVO AIS.

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