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Abstract Details

RAPIDTM Based Treatment Algorithms Lead to Faster Activation of Neurointervention Team and Reduce Recanalization Times
Cerebrovascular Disease and Interventional Neurology
P1 - Poster Session 1 (5:30 PM-6:30 PM)
3-020
We aimed to compare the activation time of our neurointervention team before and after implementing using the RAPID software at our institution.

Delay in recognition and treatment of acute ischemic stroke patients has been shown to worsen outcome.  The recent use of an automated CT perfusion analysis tool (RAPIDTM) has been demonstrated to provide rapid and accurate prediction of core stroke volumes and therefore early recognition of large vessel acute ischemic stroke (AIS) patient’s that can potentially benefit from endovascular treatment.  

We reviewed the IRB approved stroke registry of patients who presented to our community based, university affiliated comprehensive stroke center with ischemic strokes during January 2014-July 2018. Patients who underwent neuroendovascular interventions were included.  Patients were divided into three groups based on which imaging modality was used by our stroke team in deciding to activate the neurointervention team.  (Group A-CT ASPECT, Group B-CT Perfusion, Group C-RAPIDTM).    Stroke team activation (Code Stroke) to neurointervention team activation (Code Neurointervention) mean times were analyzed and compared.

There were total of 2423 patients with ischemic strokes.  Of those, 262 patients underwent neuroendovascular interventions. The three groups of patients were: Group A (n=232);  Group B (n=22); and  Group C (n=8). Mean times from Code Stroke to Code Neurointervention were Group A=77 minutes (SD=55, 95% CI= 69-84), Group B=78 minutes (SD=53, 95% CI=53-100), Group C=53 minutes (SD=40, 95% CI=25-80). These groups were statistically significant and there was a definitive suggestion of improved response times from assessment based on RAPIDTM vs the other two modalities (CT ASPECT and CT Perfusion).

Implementation of RAPIDTM software has significantly reduced the time to activate the neurointervention team. Multifactorial time delays may have been reduced with ease of algorithmic decision node. Larger ‘real-life’ practical studies are required to corroborate our findings. 

Authors/Disclosures
Siddhart K. Mehta, MD
PRESENTER
Dr. Mehta has nothing to disclose.
Spozhmy Panezai, MD (JFK Medical Center) Dr. Panezai has nothing to disclose.
Sara Strauss, DO (JFK Medical Center Neuroscience Department) Dr. Strauss has nothing to disclose.
No disclosure on file
Ashish Kulhari, MD (JFK Medical Center) No disclosure on file
Amrinder Singh, MD (Hackensack Meridian Health JFK Medical Center) No disclosure on file
Jawad F. Kirmani, MD Dr. Kirmani has nothing to disclose.