Artificial intelligence-based decision support software to improve the efficacy of acute stroke pathway in the NHS: an observational study
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View abstract on PubMed
Summary
This summary is machine-generated.The e-Stroke AI tool significantly reduced door-in-door-out times for endovascular thrombectomy (EVT) referrals. This artificial intelligence support may improve patient outcomes, indicating faster stroke treatment.
Area Of Science
- Neurology
- Medical Imaging
- Health Informatics
Background
- Early identification of large vessel occlusion (LVO) is critical for endovascular thrombectomy (EVT) in acute stroke.
- The drip-and-ship model necessitates rapid referral from acute stroke centers (ASCs) to comprehensive stroke centers (CSCs).
- Artificial intelligence (AI) decision support tools are emerging to expedite LVO detection.
Purpose Of The Study
- To evaluate the impact of implementing e-Stroke AI decision support software.
- To assess changes in process metrics and patient outcomes within the hyperacute stroke pathway.
- To determine the effectiveness of AI in an United Kingdom ASC setting.
Main Methods
- Retrospective cohort study comparing pre- and post-AI implementation periods (January 2019 - March 2021).
- Analysis of time windows including door-in-door-out (DIDO) and door-to-referral times.
- Modified Rankin Score (mRS) used for assessing patient disability at 3 months.
Main Results
- Significant reduction in mean DIDO time (141 to 79 min, p<0.001) and door-to-referral time (71 to 44 min, p=0.01) post-AI implementation.
- Increased proportion of patients achieving mRS 0-2 at 3 months (16% vs. 48%, p=0.04).
- Indication of improved functional outcomes, though requiring cautious interpretation due to sample size.
Conclusions
- e-Stroke AI significantly decreased DIDO time, suggesting faster image interpretation and EVT referral.
- The AI tool shows potential for improving patient functional independence post-EVT.
- Larger prospective studies are needed to confirm generalizability and widespread effectiveness.
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