Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
600 participants
OBSERVATIONAL
2021-03-09
2023-04-26
Brief Summary
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Detailed Description
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The study will include patients undergoing imaging for a suspected LVO acute ischemic stroke. The post-Viz LVO intervention group will consist of patients who either presented to or underwent transfer to an interventional center, from a non-interventional center, following image analysis by Viz LVO. Data will be collected retrospectively on consecutive patients meeting eligibility criteria from the date of implementation up to 5 years post implementation.
The control group will consist of patients who either presented to or underwent transfer to an interventional center, from a non-interventional center, for evaluation prior to the implementation of Viz LVO. Data will be collected on consecutive patients from one day prior to implementation, back as far as 2 years prior to implementation
Conditions
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Study Design
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CASE_CONTROL
RETROSPECTIVE
Study Groups
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Pre-Viz
Pre-Viz LVO implementation patient data utilized as a control data set
Baseline Effectiveness Cohort
No Intervention was performed for the pre-Viz group. Record review to establish operational metrics only occurred.
Post-Viz
Patient data collected post-Viz LVO implementation
Viz LVO (De Novo Number DEN170073)
Viz LVO is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to identify and communicate images of specific patients to a specialist, independent of standard of care workflow.
Viz LVO uses an artificial intelligence algorithm to analyze images for findings suggestive of a pre-specified clinical condition and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Identification of suspected findings is not for diagnostic use beyond notification. Specifically, the device analyzes CT angiogram images of the brain acquired in the acute setting and sends notifications to a neurovascular specialist that a suspected large vessel occlusion has been identified and recommends review of those images. Images can be previewed through a mobile application.
Interventions
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Viz LVO (De Novo Number DEN170073)
Viz LVO is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to identify and communicate images of specific patients to a specialist, independent of standard of care workflow.
Viz LVO uses an artificial intelligence algorithm to analyze images for findings suggestive of a pre-specified clinical condition and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Identification of suspected findings is not for diagnostic use beyond notification. Specifically, the device analyzes CT angiogram images of the brain acquired in the acute setting and sends notifications to a neurovascular specialist that a suspected large vessel occlusion has been identified and recommends review of those images. Images can be previewed through a mobile application.
Baseline Effectiveness Cohort
No Intervention was performed for the pre-Viz group. Record review to establish operational metrics only occurred.
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
* Signs and symptoms consistent with the diagnosis of a large vessel occlusive stroke
* Pre-treatment National Institutes of Health Stroke Scale (NIHSS) ≥ 6
* Aspects Score ≥6
* Patient must have a suspected LVO in M1.
* Patient with an intention to treat with mechanical thrombectomy with confirmation of LVO by the CT/CTA radiographic report with the reading diagnosis.
Exclusion Criteria
18 Years
ALL
No
Sponsors
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Viz.ai, Inc.
INDUSTRY
Responsible Party
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Principal Investigators
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Dr. Thomas Devlin
Role: PRINCIPAL_INVESTIGATOR
CHI Memorial
Dr. Ameer Hassan
Role: PRINCIPAL_INVESTIGATOR
Valley Baptist
Locations
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Wellstar Neurosurgery
Atlanta, Georgia, United States
Semmes-Murphey
Memphis, Tennessee, United States
Valley Baptist Medical Center
Harlingen, Texas, United States
Countries
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Other Identifiers
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VIZ-LVO-03
Identifier Type: -
Identifier Source: org_study_id
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