Effects of AI Assisted Follow-up Strategy on Secondary Prevention in CABG Patients
Last updated on July 2021Recruitment
- Recruitment Status
- Not yet recruiting
- Estimated Enrollment
- Same as current
Summary
- Conditions
- Artificial Intelligence
- Coronary Heart Disease
- Sleep Apnea
- Type
- Interventional
- Phase
- Not Applicable
- Design
- Allocation: RandomizedIntervention Model: Parallel AssignmentMasking: Quadruple (Participant, Care Provider, Investigator, Outcomes Assessor)Primary Purpose: Health Services Research
Participation Requirements
- Age
- Between 18 years and 70 years
- Gender
- Both males and females
Description
There are a large population of coronary heart disease patients in China, which needs more attention to optimize the secondary prevention and improve the prognosis. Secondary prevention has been showing the effects of improving symptoms, preventing disease progression, improving prognosis, and reduc...
There are a large population of coronary heart disease patients in China, which needs more attention to optimize the secondary prevention and improve the prognosis. Secondary prevention has been showing the effects of improving symptoms, preventing disease progression, improving prognosis, and reducing mortality in patients received coronary artery bypass grafting (CABG) surgery. In this study, we are trying to evaluate the effectiveness of artificial intelligence (AI) assisted follow-up strategy on secondary prevention for patients received CABG surgery. And we are trying to find out whether there is difference in secondary prevention of coronary heart disease between urban and rural patients.
Tracking Information
- NCT #
- NCT04636996
- Collaborators
- Not Provided
- Investigators
- Study Chair: Jia Shi, MD National Center for Cardiovascular Disease, China
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