{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T11:30:12Z","timestamp":1787311812732,"version":"build-2736575974"},"reference-count":17,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"3","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["SVIN"],"published-print":{"date-parts":[[2024,5]]},"abstract":"<jats:sec xml:lang=\"en\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p xml:lang=\"en\">Artificial intelligence platforms, like Viz.ai with large vessel occlusion detection, have been used for disease detection and interprovider communication. Whether this software expedites patient transfer and evaluation for treatment needs further exploration.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec xml:lang=\"en\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p xml:lang=\"en\">A single\u2010center retrospective registry was queried for patients with acute large vessel occlusion of the intracranial internal carotid, middle cerebral M1 or M2 segments, or basilar artery treated in a comprehensive stroke network (8 spokes, 1 hub) for 6 months pre\u2010 and post\u2010implementation of the Viz large vessel occlusion platform (excluding a 1\u2010month \u201cwashout\u201d period). Robust regression was used to summarize time from initial hospital contact to arterial puncture (primary outcome) between periods, with prespecified subgroup analyses, which were assessed using interaction terms.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec xml:lang=\"en\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p xml:lang=\"en\">\n                      Of the 132 patients (n\u00a0=\u00a058 preintervention), there were nonsignificantly fewer patients undergoing endovascular therapy in the postintervention period (86.2% preintervention versus 73.0% postintervention;\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0=\u00a00.07). Among patients who underwent endovascular therapy (n\u00a0=\u00a050 preintervention, n\u00a0=\u00a054 postintervention), there was a nonsignificant reduction in time from first contact to arterial puncture (median 155 minute preintervention versus 116 minute postintervention;\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0=\u00a00.10); however, this became significant in adjusted robust regression accounting for stroke severity, age, Alberta Stroke Program Early Computed Tomography Scale score, daytime versus nighttime and weekend versus weekday arrival, and use of perfusion imaging (\u03b2 \u221220.9 [95% CI, \u221240.5 to \u22121.4)]. There was also a significant interaction observed for the association between spoke versus hub arrival and the Viz large vessel occlusion period, with shorter intervals observed for transferred patients (n\u00a0=\u00a032 preintervention with a median of 169 versus 142 minutes for n\u00a0=\u00a033 postintervention;\n                      <jats:italic>P<\/jats:italic>\n                      <jats:sub>interaction<\/jats:sub>\n                      &lt;0.01).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec xml:lang=\"en\">\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p xml:lang=\"en\">Implementation of the artificial intelligence platform was not associated with shorter intervals between initial hospital contact and neurointervention among all\u2010comers. A meaningful difference in time to treatment was observed among transferred patients. Larger data sets are needed to validate these observations.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1161\/svin.123.001306","type":"journal-article","created":{"date-parts":[[2024,3,9]],"date-time":"2024-03-09T08:52:06Z","timestamp":1709974326000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":8,"title":["Door to Puncture in Large Vessel Occlusions Pre\u2010 and Postimplementation of an Automated Image Interpretation and Communication Platform: A Single Center Study"],"prefix":"10.1161","volume":"4","author":[{"given":"Emma","family":"Frost","sequence":"first","affiliation":[{"name":"Cooper Neurological Institute Cooper University Hospital Camden NJ"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mary","family":"Penckofer","sequence":"additional","affiliation":[{"name":"Cooper Medical School of Rowan University Camden NJ"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linda","family":"Zhang","sequence":"additional","affiliation":[{"name":"Cooper Medical School of Rowan University Camden NJ"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kenyon","family":"Sprankle","sequence":"additional","affiliation":[{"name":"Cooper Medical School of Rowan University Camden NJ"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicholas","family":"Vigilante","sequence":"additional","affiliation":[{"name":"Cooper Medical School of Rowan University Camden NJ"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Omnea","family":"Elgendy","sequence":"additional","affiliation":[{"name":"Cooper Medical School of Rowan University Camden NJ"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiyoun","family":"Ackerman","sequence":"additional","affiliation":[{"name":"Cooper Medical School of Rowan University Camden NJ"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abyson","family":"Kalladanthyil","sequence":"additional","affiliation":[{"name":"Cooper Medical School of Rowan University Camden NJ"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manisha","family":"Koneru","sequence":"additional","affiliation":[{"name":"Cooper Medical School of Rowan University Camden NJ"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zixin","family":"Yi","sequence":"additional","affiliation":[{"name":"Cooper Medical School of Rowan University Camden NJ"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jane","family":"Khalife","sequence":"additional","affiliation":[{"name":"Cooper Neurological Institute Cooper University Hospital Camden NJ"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Taryn","family":"Hester","sequence":"additional","affiliation":[{"name":"Cooper Neurological Institute Cooper University Hospital Camden NJ"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hermann Christian","family":"Schumacher","sequence":"additional","affiliation":[{"name":"Cooper Neurological Institute Cooper University Hospital Camden NJ"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James","family":"Bonner","sequence":"additional","affiliation":[{"name":"Inspira Medical Center Mullica Hill NJ"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher J.","family":"Love","sequence":"additional","affiliation":[{"name":"Viz.ai San Francisco CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0287-3967","authenticated-orcid":false,"given":"James E.","family":"Siegler","sequence":"additional","affiliation":[{"name":"Cooper Neurological Institute Cooper University Hospital Camden NJ"},{"name":"Department of Neurology University of Chicago Chicago IL"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.0000000000003981"},{"key":"e_1_3_2_3_2","volume-title":"FDA Permits Marketing of Clinical Decision Support Software for Alerting Providers of a Potential Stroke in Patients","author":"Office of the Commissioner","year":"2020","unstructured":"Office of the Commissioner . FDA Permits Marketing of Clinical Decision Support Software for Alerting Providers of a Potential Stroke in Patients. U.S. Food and Drug Administration; 2020. [cited 2024 January, 15]. https:\/\/www.fda.gov\/news\u2010events\/press\u2010announcements\/fda\u2010permits\u2010marketing\u2010clinical\u2010decision\u2010support\u2010software\u2010alerting\u2010providers\u2010potential\u2010stroke"},{"key":"e_1_3_2_4_2","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1038\/nbt0418-290","article-title":"FDA approves stroke\u2010detecting AI software","volume":"36","year":"2018","unstructured":"FDA approves stroke\u2010detecting AI software. Nat Biotechnol. 2018;36:290.","journal-title":"Nat Biotechnol"},{"key":"e_1_3_2_5_2","doi-asserted-by":"crossref","first-page":"795","DOI":"10.1186\/s12913-017-2755-5","article-title":"The hub\u2010and\u2010spoke organization design revisited: a lifeline for rural hospitals","volume":"17","author":"Elrod JK","year":"2017","unstructured":"Elrod JK, Fortenberry JL Jr. The hub\u2010and\u2010spoke organization design revisited: a lifeline for rural hospitals. BMC Health Serv Res. 2017;17:795.","journal-title":"BMC Health Serv Res"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1001\/jamaneurol.2023.3206"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.39335.541782.AD"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1161\/SVIN.121.000102"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jstrokecerebrovasdis.2020.104953"},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jstrokecerebrovasdis.2022.106952"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","DOI":"10.1001\/jamaneurol.2022.4714"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2008.08.010"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1161\/STR.0000000000000158"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1136\/neurintsurg-2018-013923"},{"key":"e_1_3_2_15_2","doi-asserted-by":"crossref","DOI":"10.1002\/brb3.2808","article-title":"Automated detection of intracranial large vessel occlusions using Viz.ai software: experience in a large, integrated stroke network","volume":"13","author":"Karamchandani RR","year":"2023","unstructured":"Karamchandani RR, Helms AM, Satyanarayana S, Yang H, Clemente JD, Defilipp G, Strong D, Rhoten JB, Asimos AW. Automated detection of intracranial large vessel occlusions using Viz.ai software: experience in a large, integrated stroke network. Brain Behav. 2023;13:e2808.","journal-title":"Brain Behav"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A6923"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1161\/SVIN.121.000224"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMms2004740"}],"container-title":["Stroke: Vascular and Interventional Neurology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.ahajournals.org\/doi\/full\/10.1161\/SVIN.123.001306","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,10]],"date-time":"2024-07-10T11:00:39Z","timestamp":1720609239000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ahajournals.org\/doi\/10.1161\/SVIN.123.001306"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5]]},"references-count":17,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2024,5]]}},"alternative-id":["10.1161\/SVIN.123.001306"],"URL":"https:\/\/doi.org\/10.1161\/svin.123.001306","relation":{},"ISSN":["2694-5746"],"issn-type":[{"value":"2694-5746","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5]]},"assertion":[{"value":"2023-12-18","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-02-08","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-03-09","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e001306"}}