The purpose of this study is to develop a digital health-based intelligent management system for the secondary prevention of ischemic stroke and to evaluate its effectiveness through a multicenter randomized controlled trial, assessing its health economic value. Participants will receive usual care after discharge (control group) or be managed with a WeChat-based intelligent management system after discharge (intervention group). At one year, all patients will undergo face-to-face follow-up to assess clinical events, medication adherence, and the achievement of target risk factor levels.
Before discharge, patients receive standard education on the secondary prevention of ischemic stroke from their physician, covering topics such as secondary prevention medications, risk factor management, lifestyle modifications, and rehabilitation. Additionally, the "Intelligent Management System," a WeChat-based applet, is activated for each patient. The system records basic patient information and integrates with mobile IoT devices, such as blood pressure monitors and glucose meters, allowing for self-monitoring of risk factors post-discharge. Based on international guidelines, high-level evidence, and the expertise of stroke specialists, a comprehensive clinical decision-making tree is established. This serves as the foundation for an AI feedback system that provides intelligent feedback on risk factor control and predicts recurrence risk. The patient interface includes educational content on ischemic stroke, risk factor management, lifestyle adjustments, and follow-up schedules post-discharge. The system also features a physician interface, which enables attending doctors to offer online consultations, schedule face-to-face follow-up appointments, and manage patients long-term. Each patient is assigned to an "Online Stroke Care Team," which includes a "Health Management Officer" responsible for facilitating communication between the patient and the physician and providing basic health guidance. Additionally, an "Online Doctor" is available to answer stroke-related medical questions. The Health Management Officer monitors patients' health data and arranges online or in-person consultations for those with poor adherence or suboptimal target achievement. Patient management is guided by the theory of health empowerment, creating an integrated online and offline ischemic stroke management intervention model.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
OTHER
Masking
SINGLE
Enrollment
4,490
The continuous post-discharge intervention for patients was conducted using the Cerebrovascular Disease Secondary Prevention Smart Management System. This system, integrated with a WeChat-based applet, records patients' basic information and connects with mobile IoT devices such as blood pressure monitors and glucose meters. This allows patients to self-monitor their risk factors post-discharge. Based on international guidelines, high-level evidence, and the clinical expertise of cerebrovascular specialists, a comprehensive clinical decision-making tree was developed. This serves as the foundation for an AI feedback system that provides intelligent feedback on risk factor control and predicts the risk of recurrence.
Beijing Tsinghua Changgung Hospital
Beijing, Beijing Municipality, China
ACTIVE_NOT_RECRUITINGThe First Affiliated Hospital of Shihezi University
Shihezi, Xinjiang, China
ACTIVE_NOT_RECRUITINGBeijing Tiantan Hospital
Beijing, China
RECRUITINGVascular events and all-causes death
Vascular and all-cause mortality events were collected for one year post-enrollment through face-to-face follow-ups and patient self-reports. Vascular events included stroke recurrence, transient ischemic attacks, myocardial infarction, vascular interventions or surgeries, and systemic embolism. If a patient experienced both a vascular event and death, only one event was recorded. In cases of multiple vascular events, only the first event was documented.
Time frame: From enrollment to 1 year follow-up
Risk factor control rate
Risk factor control was defined as achieving glycated hemoglobin (HbA1c) ≤7% or blood pressure below the target set at discharge. If a patient had both hypertension and diabetes at enrollment, meeting the criteria for both conditions was considered two achieved targets. If the patient had only hypertension or diabetes at enrollment, meeting the target for the respective condition was considered one achieved target.
Time frame: From enrollment to 1 year follow-up
Readmission to hospital within 1 year
Time frame: From enrollment to 1 year follow-up
Stroke-related readmission
Time frame: From enrollment to 1 year follow-up
Direct medical costs
Time frame: From enrollment to 1 year follow-up
Rate of good adherence to secondary prevention medicine
Time frame: From enrollment to 1 year follow-up
Adverse drug reaction
Time frame: From enrollment to 1 year follow-up
Body mass index
Time frame: From enrollment to 1 year follow-up
Waist circumstance
Time frame: From enrollment to 1 year follow-up
Frequency of blood pressure monitoring
calculated as time/week
Time frame: From enrollment to 1 year follow-up
Frequency of blood glucose monitoring
calculated as time/week
Time frame: From enrollment to 1 year follow-up
Blood lipid levels
Included total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglyceridee
Time frame: From enrollment to 1 year follow-up
Rehabilitation
Time frame: From enrollment to 1 year follow-up
Smoking
Time frame: From enrollment to 1 year follow-up
Alcohol
Time frame: From enrollment to 1 year follow-up
Regular exercise
Time frame: From enrollment to 1 year follow-up
Overall physical activity level
Assessed by IPAQ-S, calculated as MET-min/week
Time frame: From enrollment to 1 year follow-up
Fatigue
Assessed by Fatigue Severity Scale (FSS). Fatigue was defined as total FSS score ≥36
Time frame: From enrollment to 1 year follow-up
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