Endovascular treatment (EVT) is the standard treatment for acute ischemic stroke (AIS) caused by large vessel occlusion (LVO) according to current guidelines. However, while a rapidly-growing number of stroke centers become capable of performing EVT, the general quality of EVT remains unsatisfied, resulting in a considerable proportion of patients who could not reach functional independence. Our pre-established artificial intelligence (AI)-aided clinical feedback system could dynamically record and report key timepoints of EVT in-hospital process. Combined with multi-aspect intervention via remote/on-site surveillance and education, this may be a potential solution for quality improvement of EVT. Therefore, the aim of the study is to evaluate whether an AI-aided clinical feedback system coupled with multi-aspect intervention could improve the quality of EVT. Twenty hospitals with annual EVT cases > 30 will be 1:1 randomized into intervention group and control group. The intervention group will receive AI-based clinical feedback system coupled with multi-aspect intervention, including remote/on-site surveillance and education regarding in-hospital workflow and surgical procedures of EVT. The control group only deploys AI-aided clinical feedback system. The primary outcome is the ratio of good functional outcome (mRS > 2) at 3 month.
A clustered randomized control trial to evaluate whether multi-aspect intervention based on an AI-aided clinical feedback system could improve the quality of EVT and functional outcome of patients.