Evidence map›Paper›PMID 41261298›Full record

ArticleInternal and emergency medicine2025

The implementation of an artificial intelligence-based software for large vessel occlusion stroke improves door-to-puncture time at a comprehensive stroke center.

Murtaza Akhter, Christine Ibrahim, Kara Nolan, Olivia Igoe, Christine Mae Anzardo, Christopher J Love

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Article in Internal and emergency medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Murtaza AkhterPenn State Hershey Medical Center, Hershey, PA, USA. murtazaakhter@gmail.com.ORCID http://orcid.org/0000-0001-9693-6871
Christine IbrahimHCA Healthcare, Miami, FL, USA.
Kara NolanPenn State Hershey Medical Center, Hershey, PA, USA.
Olivia IgoeHCA Healthcare, Miami, FL, USA.
Christine Mae AnzardoHCA Healthcare, Miami, FL, USA.
Christopher J LoveViz.ai, San Francisco, CA, USA.ORCID https://orcid.org/0000-0002-7989-2376

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Endovascular thrombectomy (EVT) is the standard treatment for large vessel occlusion (LVO) acute ischemic stroke (AIS), with a target door-to-device time of under 90 min. While prior reports have indicated that artificial intelligence (AI) software can reduce door-to-procedure times, we set out to study its impact in our own patient population. A retrospective cohort study was conducted at a comprehensive stroke center located in a densely populated, urban region consisting of a majority Hispanic population. Data were analyzed from 222 patients who underwent EVT between July 2018 and July 2022. The study compared workflow and patient outcomes before (n = 84) and after (n = 138) the implementation of an AI software (Viz LVO, Viz.ai, Inc.) in July 2020. The primary outcome was the fraction of EVT patients who received thrombectomy within 90 min. The proportion of patients undergoing thrombectomy within 90 min increased significantly from 26.5% (95% CI 17.9-36.8%) to 68.1% (95% CI 60.0-75.5%, p < 0.001). The median door-to-groin (DTG) time decreased from 109 min pre-Viz to 75 min post-Viz (p < 0.001). An interrupted time-series analysis confirmed a significant reduction in DTG time following the AI software implementation (p = 0.001). The percentage of AIS patients who received EVT went up between pre- and post-AI periods. No differences were found in TICI scores, length of stay, or mortality/hospice rates. Implementation of an AI-powered platform was associated with a significant increase in the fraction of patients who received EVT within 90 min and decrease in DTG time. An AI-based system helped optimize stroke care workflow in an urban center with a diverse patient population.

Indexed as

Artificial intelligenceLarge vessel occlusionStrokeThrombectomy

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.