New Data on Stroke Care Show the Impact of Viz.ai’s Artificial Intelligence-Powered Platform on Patient Outcomes

Data presented at International Stroke Conference 2021 demonstrate reduced door-in door-out times, improved door-in-to-puncture times and higher rates of good reperfusion

Viz.ai announced new data supporting the use of its technology to coordinate care for acute ischemic stroke, hemorrhagic stroke, and clinical trial recruitment at the 2021 International Stroke Conference. Dr. Ameer E. Hassan of the Valley Baptist Medical Center in Texas presented two studies utilizing Viz LVO to improve care coordination for ischemic stroke patients requiring treatment across health systems and at a stand-alone center. The data demonstrated reduced door-in door-out times at primary stroke centers (PSCs), improved door-in-to-puncture times at comprehensive stroke centers (CSCs), and improved reperfusion rates. Dr. Brian Jankowitz of Cooper University Health Care in New Jersey shared how Viz.ai’s clinical trial enrollment software, Viz RECRUIT, has led to faster patient detection and increased enrollment velocity in the AI ENRICH trial.

The first study presented by Dr. Hassan, “The Implementation of Artificial Intelligence Significantly Reduces Door-in Door-out Times in Primary Care Center Prior to Transfer,” compared the time interval between entering and leaving one of Valley Baptist’s 12 PSCs before being transferred to the CSC for an emergent operation. The study showed a significant 45%, or 102.3-minute, average reduction in door-in door-out time for patients whose care was coordinated through the Viz application. In addition, there was an 11.4% improvement in modified Rankin Scale (mRS) scores, which measure stroke outcomes.

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The second study presented by Dr. Hassan, “Implementation of Artificial Intelligence Stroke Software Significantly Improves Door-In to Puncture Time Interval and Reperfusion Rates,” evaluated the impact of Viz LVO on the time interval at the CSC between door-in to puncture time for non-transfer patients. Again, patients treated using Viz LVO showed significant improvements, this time in terms of treatment time and revascularization. The software shaved an average of 86.7 minutes from each procedure and delivered a 10.8 percent improvement in the rate of good revascularization.

“Our two studies show that the incorporation of Viz LVO to coordinate care for ischemic stroke patients is associated with significant time savings across a hub and spoke model and also at comprehensive stroke centers.” said Dr. Hassan. “Because we know that ‘time is brain,’ these improvements in the PSC and CSC settings could lead to significant advances in functional outcomes, reduced mortality and shorter hospital stays.”

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Dr. Brian Jankowitz presented results from “Large Scale, CT Evaluation Can Improve Screening For Multi-Center Stroke Trials.” The data demonstrated that artificial intelligence can automate the detection and triage of ICH patients and subsequently increase enrollment velocity in clinical trials. AI ENRICH is a prospective trial that utilizes Viz RECRUIT to identify potentially eligible study subjects. The utilization of Viz.ai’s technology was associated with a 41% increase in screening rate and a 213% increase in enrollment rates.

“Viz ICH and Viz RECRUIT have increased enrollment in the AI ENRICH trial,” said Dr. Jankowitz. “Increasing enrollment velocity will enable a faster completion of the trial and ultimately help improve our understanding of this devastating condition.”

“We are so grateful to Dr. Hassan and Dr. Jankowitz and their teams, and to all the healthcare providers around the world who have dedicated their careers to improving the lives of stroke patients,” said Dr. Chris Mansi, co-founder and CEO of Viz.ai. “At, that mission is at the core of our work. We want to improve how healthcare is delivered, reducing time to treatment and improving access to care. The magnitude of time saved in studies conducted by Dr. Hassan and his team demonstrates how intelligent software can be harnessed to significantly reduce disability from stroke.”

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