Session ID: 
80

A Novel Device for Prehospital Stroke and LVO Detection

4:15pm - 5:15pm Tuesday, March 10
Orlando - Orange County Convention Center
W207C

Description

Accurate prehospital stroke detection is essential for getting stroke patients to treatment quickly and promoting positive patient outcomes. Currently, inaccurate clinical exams are used for prehospital detection of stroke.  We sought to develop a more sensitive and objective method of prehospital stroke detection. We created an experimental electroencephalogram (EEG)-based diagnostic device using artificial intelligence (AI) as a potential tool for detection of acute stroke and large vessel occlusion (LVO) among patients with neurological deficits. Both device performance and feasibility in the emergent setting were assessed. The diagnostic device performed well in identifying stroke and LVO in patients presenting with suspected stroke. The accurate performance of the device in the acute setting indicates that it may be able to support prehospital decision making when triaging patients suspected of having stroke.

Learning Objectives

  • Explain why accurate prehospital stroke triage is important for optimal stroke patient outcome
  • Compare artificial intelligence (AI)-based stroke detection devices with the current standard of care (brief clinical exam)
  • Outline why hospitals are monetarily interested in improving prehospital stroke triage
  • Diagram the steps involved in an EEG-based diagnostic device arriving at a diagnosis
  • Analyze the setup of the clinical studies that allowed data collection and algorithm refinement

Speaker(s)

CEO,
Forest Devices
Professor, Vice Chair for Research,
Henry JN Taub Department of Emergency Medicine, Ba

Continuing Education Credits

ABPM
1.00
CAHIMS
1.00
CME
1.00
CNE
1.00
CPHIMS
1.00

Audience

Healthcare Financial Professionals
Nurse or Nurse Practitioner
Physician or Physician’s Assistant

Level

Advanced