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Ali Pay Intelligent Navigation Applet-aided Pre-hospital Triage for Non-emergency Medical Service Patients With Acute Ischemic Stroke

NCT06613074 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 20000

Last updated 2025-08-08

No results posted yet for this study

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.

Conditions

  • Acute Ischemic Stroke

Interventions

DEVICE

Ali 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 & Collaborators

  • Second Affiliated Hospital, School of Medicine, Zhejiang University

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-04-01
Primary Completion
2026-05-01
Completion
2026-05-01

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06613074 on ClinicalTrials.gov