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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Ali Pay intelligent navigation applet group | Experimental | Patients in regions with Ali Pay intelligent navigation applet being released would be classified as experimental arm. In this arm, patients have access to this applet. The intelligent navigation applet comprises of three function modules:
| |
| Routine pre-hospital triage | No Intervention | Patients in regions without Ali Pay intelligent navigation applet being released would be classified as control arm. In this arm, patients do not have access to this applet. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Ali Pay intelligent navigation applet | Device | The intelligent navigation applet comprises of three function modules:
|
| Measure | Description | Time Frame |
|---|---|---|
| Modified rankin scale (mRS) scores of 0-2 at 90 days after reperfusion therapy | 90 days |
| Measure | Description | Time Frame |
|---|---|---|
| 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 | |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Min Lou, PhD, MD | Contact | 86057187783777 | lm99@zju.edu.cn |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Shaoxing People's Hospital | Recruiting | Shaoxing | Zhejing | 312000 | China |
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| Ordinal analysis of modified rankin scale (mRS) scores at 90 days after reperfusion therapy |
| 90 days |
| Time interval between onset to treatment | 1 day |
| Time interval between onset to hospital | 1 day |
| Proportion of patients receiving reperfusion beyond time window | Intravenous thrombolysis: treatment initiated within 4.5 - 9 hours after onset Mechanical thrombectomy: treatment initiated within 6 - 24 hours after onset | 1 day |
| Proportion of patients receiving mechanical thrombectomy | 1 day |
| ID | Term |
|---|---|
| D000083242 | Ischemic Stroke |
| ID | Term |
|---|---|
| D020521 | Stroke |
| D002561 | Cerebrovascular Disorders |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |
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