Early experience utilizing artificial intelligence shows significant reduction in transfer times and length of stay in a hub and spoke model.
Interv Neuroradiol
; 26(5): 615-622, 2020 Oct.
Article
em En
| MEDLINE
| ID: mdl-32847449
ABSTRACT
BACKGROUND:
Recently approved artificial intelligence (AI) software utilizes AI powered large vessel occlusion (LVO) detection technology which automatically identifies suspected LVO through CT angiogram (CTA) imaging and alerts on-call stroke teams. We performed this analysis to determine if utilization of AI software and workflow platform can reduce the transfer time (time interval between CTA at a primary stroke center (PSC) to door-in at a comprehensive stroke center (CSC)).METHODS:
We compared the transfer time for all LVO transfer patients from a single spoke PSC to our CSC prior to and after incorporating AI Software (Viz.ai LVO). Using a prospectively collected stroke database at a CSC, demographics, mRS at discharge, mortality rate at discharge, length of stay (LOS) in hospital and neurological-ICU were examined.RESULTS:
There were a total of 43 patients during the study period (median age 72.0 ± 12.54 yrs., 51.16% women). Analysis of 28 patients from the pre-AI software (median age 73.5 ± 12.28 yrs., 46.4% women), and 15 patients from the post-AI software (median age 70.0 ± 13.29 yrs., 60.00% women). Following implementation of AI software, median CTA time at PSC to door-in at CSC was significantly reduced by an average of 22.5 min. (132.5 min versus 110 min; p = 0.0470).CONCLUSIONS:
The incorporation of AI software was associated with an improvement in transfer times for LVO patients as well as a reduction in the overall hospital LOS and LOS in the neurological-ICU. More extensive studies are warranted to expand on the ability of AI technology to improve transfer times and outcomes for LVO patients.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Inteligência Artificial
/
Angiografia Cerebral
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Acidente Vascular Cerebral
/
Tempo para o Tratamento
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Angiografia por Tomografia Computadorizada
/
Tempo de Internação
Tipo de estudo:
Observational_studies
/
Risk_factors_studies
Limite:
Aged
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Female
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Humans
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Male
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article