RecruitingNot ApplicableNCT06783049

Secondary Prevention of Ischemic Stroke and Transient Ischemic Attack With an Intelligent Management System

Secondary Prevention of Ischemic Stroke and Transient Ischemic Attack With an Intelligent System

Sponsor

Beijing Tiantan Hospital

Enrollment

4,490 participants

Start Date

Mar 3, 2025

Study Type

INTERVENTIONAL

Conditions

Ischemic Stroke Transient Ischemic Attack (TIA)

Summary

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.

Eligibility

Min Age: 18 Years

Inclusion Criteria6

Age ≥ 18 years.
Patients diagnosed with acute ischemic stroke or transient ischemic attack.
Time from onset to enrollment ≤ 14 days.
Presence of at least one modifiable risk factor (hypertension, diabetes).
Ability to independently use a smartphone to complete system tasks upon discharge, or with the assistance of family members.
Signed informed consent by the patient or their family members.

Exclusion Criteria3

Patients already enrolled in other stroke-related healthcare quality improvement projects or clinical trials.
Patients or family members who refuse to sign the informed consent form.
Pregnant or breastfeeding women.

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Interventions

BEHAVIORALCerebrovascular Disease Secondary Prevention Smart Management System

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.