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The major take-away from our presentation at the HIMSS20 is that an EEG-based machine learning device detects stroke and LVO better than current prehospital stroke and LVO detection exams. The first potential advantage of the device is increased accuracy. Current prehospital LVO detection exams perform with unacceptably low sensitivity, resulting in tens of thousands of LVO patients sent to hospitals that cannot treat them. The second advantage of the device is that it makes the stroke and LVO detection process more objective. Instead of relying on the skill of EMS personnel, an unbiased intelligent device assesses stroke and LVO status.
The current prehospital LVO diagnostic exams consistently perform with unacceptably low accuracy. The American Heart Association’s “Guidelines for the Early Management of Patients with Acute Ischemic Stroke: 2019 Update” emphasized the need for better alternatives to current LVO diagnostic exams. Several groups, including Forest Devices, are already hard at work on novel devices for LVO detection. In the next year, I foresee the emergence of new research on novel approaches to prehospital LVO triage that incorporate new ideas and technologies.
The session: A Novel Device for Stroke and LVO Detection
March 9 – 13, 2020 | Orange County Convention Center | Orlando, Florida
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