The Influence of the Novel Computer-Aided Triage System Based on Artificial Intelligence on Endovascular Therapy in Patients with Large Vascular Occlusions: A Meta-Analysis.

Abstract

The integration of artificial intelligence (AI) with modern healthcare has become increasingly prominent. The purpose of this study is to explore the impact of the novel computer-aided triage system based on artificial intelligence (AI-CTS) on endovascular therapy (EVT) in patients with large vascular occlusions (LVO). This study marks the first comprehensive systematic review and meta-analysis on the subject. A comprehensive study was performed on PubMed, Medline, Embase, Cochrane Library, and Chinese databases from their establishment to September 2023, in accordance with PRISMA recommendations. RevMan 5.4 software was used for summative analysis. The outcomes included door-to-groin (DTG) time, time from CT scan initiation to EVT, time from CT scan to reperfusion, and 90-day modified Rankin Scale (mRS). A total of 7 studies involving 752 participants were included in the meta-analysis. The pooled results demonstrated that patients in the post-AI group had less time of DTG [SMD, 0.54; 95% CI, 0.40-0.69; P < 0.00001] and CT scan to EVT [SMD, 0.57; 95% CI, 0.42-0.73; P < 0.00001], as well as less time of CTA to recanalization [SMD, 0.63; 95% CI, 0.36-0.90; P < 0.00001]. There was no significant difference between the 2 groups in terms of the mRS at 90 days [OR, 0.66; 95% CI, 0.43-1.01; P = 0.06]. The combination of AI-CTS and EVT has improved the therapy process for LVO patients. However, the improvement in mRS at 90 days was not significant; further research is warranted.