Clinical trial NCT06613074: Ali Pay Intelligent Navigation Applet-aided Pre-hospital Triage for Non-emergency Medical Service Patients with Acute Ischemic Stroke
Official title: Ali Pay Intelligent Navigation Applet-aided Pre-hospital Triage for Non-emergency Medical Service Patients with Acute Ischemic Stroke: a Step-wedge Cluster Randomized Controlled Trial
Study type: INTERVENTIONAL
Overall status: NOT_YET_RECRUITING
Phase: NA
Conditions: Acute Ischemic Stroke
Keywords: reperfusion therapy
pre-hospital triage
Lead sponsor: Second Affiliated Hospital, School of Medicine, Zhejiang University
Sponsor class: OTHER
First posted: 2024-09-25
Enrollment: 20000
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: HEALTH_SERVICES_RESEARCH

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.

Eligibility criteria: 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

Primary outcomes:
measure: Modified rankin scale (mRS) scores of 0-2 at 90 days after reperfusion therapy
timeFrame: 90 days
Secondary outcomes:
measure: Modified rankin scale (mRS) scores of 0-1 at 90 days after reperfusion therapy
timeFrame: 90 days
measure: Modified rankin scale (mRS) scores of 0-3 at 90 days after reperfusion therapy
timeFrame: 90 days
measure: Ordinal analysis of modified rankin scale (mRS) scores at 90 days after reperfusion therapy
timeFrame: 90 days
measure: Time interval between onset to treatment
timeFrame: 1 day
measure: Time interval between onset to hospital
timeFrame: 1 day
measure: Proportion of patients receiving reperfusion beyond time window
timeFrame: 1 day
measure: Proportion of patients receiving mechanical thrombectomy
timeFrame: 1 day
Other outcomes:
Locations:
Study officials:
References: