Acute Ischemic Stroke
Conditions
Keywords
reperfusion therapy, pre-hospital triage
Brief summary
According to the Bigdata Observatory platform for Stroke of China (BOSC), the proportion of patients with acute ischemic stroke (AIS) receiving intravenous thrombolysis or endovascular treatment in China is 5.64% and 1.45% respectively. One of the important reasons for the low treatment rate is the prolonged pre-hospital and in-hospital delay. Besides, for patients receiving reperfusion therapy, the prolonged pre-treatment delay is associated with unfavorable functional outcomes. Although tons of efforts have been made to improve the efficiency of emergency medical system in the transportation of patients with AIS, little attention has been paid to patients who arrived at hospitals on their owns, which occupying approximately 2/3 of emergency patients. This leaves a huge gap in the pre-hospital management of patietns with AIS. Therefore, the investigators plan to develop an intelligent navigation system for patients with AIS. For the convenience of public use, this system was carried on the applet of Ali Pay, which has over 1.1 billion users in China. This system comprises of three functional modules, namely stroke knowledge education, stroke recognition and hospital recommendation. The investigators aim to explore whether this intelligent navigatino system could shorten pre-hospital delay and improve functional outcomes of patients with AIS undergoing reperfusion therapy.
Detailed description
According to the Bigdata Observatory platform for Stroke of China (BOSC), the proportion of patients with acute ischemic stroke (AIS) receiving intravenous thrombolysis or endovascular treatment in China is 5.64% and 1.45% respectively. One of the important reasons for the low treatment rate is the prolonged pre-hospital and in-hospital delay. Besides, for patients receiving reperfusion therapy, the prolonged pre-treatment delay is associated with unfavorable functional outcomes. Although tons of efforts have been made to improve the efficiency of emergency medical system in the transportation of patients with AIS, little attention has been paid to patients who arrived at hospitals on their owns, which occupying approximately 2/3 of emergency patients. This leaves a huge gap in the pre-hospital management of patietns with AIS. Therefore, the investigators plan to develop an intelligent navigation system for patients with AIS. For the convenience of public use, this system was carried on the applet of Ali Pay, which has over 1.1 billion users in China. This system comprises of three functional modules, namely stroke knowledge education, stroke recognition and hospital recommendation.The investigators aim to explore whether this intelligent navigatino system could shorten pre-hospital delay and improve functional outcomes of patients with AIS undergoing reperfusion therapy.
Interventions
DEVICEAli Pay intelligent navigation applet
The intelligent navigation applet comprises of three function modules: 1. Stroke knowledge public education: information regarding prevention and emergency treatment of stroke would be push to users' mobile phones regularly; 2. Stroke recognition: questionaires, voice interaction, and facial recognition are employed to identify patients with AIS and large vessel occlusion; 3. Hospital recommendation: this module combines real-time traffic and average in-hopital delay of each stroke center nearby, recommending the stroke center in which patients are mostly likely to receive reperfusion therapy
Sponsors
Second Affiliated Hospital, School of Medicine, Zhejiang University
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
SINGLE (Outcomes Assessor)
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Patients diagnosed as acute ischemic stroke undergoing reperfusion therapy within 24 hours of onset
Exclusion criteria
* Patients transported to hospitals via emergency medical service * Patients with in-hospital stroke
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Modified rankin scale (mRS) scores of 0-2 at 90 days after reperfusion therapy | 90 days |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Modified rankin scale (mRS) scores of 0-1 at 90 days after reperfusion therapy | 90 days | — |
| Modified rankin scale (mRS) scores of 0-3 at 90 days after reperfusion therapy | 90 days | — |
| Ordinal analysis of modified rankin scale (mRS) scores at 90 days after reperfusion therapy | 90 days | — |
| Time interval between onset to treatment | 1 day | — |
| Proportion of patients receiving reperfusion beyond time window | 1 day | Intravenous thrombolysis: treatment initiated within 4.5 - 9 hours after onset Mechanical thrombectomy: treatment initiated within 6 - 24 hours after onset |
| Proportion of patients receiving mechanical thrombectomy | 1 day | — |
| Time interval between onset to hospital | 1 day | — |
Countries
China
Contacts
Primary ContactMin Lou, PhD, MD
Outcome results
None listed