Digital Remote Management for Care and Continuous Optimization Versus Usual Care in Patients With Coronary Heart Disease (DigiCare-CHD)
NCT ID: NCT07332494
Last Updated: 2026-01-12
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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NOT_YET_RECRUITING
NA
792 participants
INTERVENTIONAL
2026-01-31
2027-07-31
Brief Summary
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Detailed Description
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The DigiCare-CHD trial serves as a prospective, multicenter, open-label randomized controlled trial designed to enroll 792 patients who have successfully undergone PCI for acute or chronic coronary syndromes. Participants will be randomized 1:1 to either the Digital Remote Management group or the Usual Care group, with a follow-up period of 12 months.
Patients in the intervention arm will utilize a digital remote management platform. This system integrates home monitoring to track BP, lipid profiles, and physical activity. Key features include AI-driven alerts for abnormal values, automated decision support for medication titration (verified by physicians), and targeted health education. The primary endpoint is the rate of dual goal attainment for BP and LDL-C at 12 months. DigiCare-CHD aims to establish a proactive, closed-loop management strategy to effectively reduce residual cardiovascular risk and improve long-term prognosis in the post-PCI population."
Conditions
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Study Design
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RANDOMIZED
PARALLEL
TREATMENT
SINGLE
Study Groups
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Usual care Group
Patients receive standard post-PCI management, including guideline-directed medical therapy (GDMT) and routine outpatient follow-up visits at 1, 3, 6, 9, and 12 months.
No interventions assigned to this group
Digital Remote Management Group
1-year intervention:
1. BP Management: Protocol-driven self-monitoring frequencies. The system triggers alerts for BP \>130/80 mmHg and generates automated suggestions for medication titration, subject to physician approval.
2. Lipid Management: Automated reminders for laboratory testing. Optical Character Recognition (OCR) technology extracts data from lab reports. If LDL-C ≥1.4 mmol/L, the system proposes regimen intensification for physician review.
3. Exercise Management:Target of ≥6000 steps/day. Data is synchronized via wearables or smartphones. Inactivity triggers automated behavioral feedback.
4. Medication Management: Daily app-based reminders and digital "check-ins." Non-adherence triggers automated alerts followed by human intervention if persistent.
5. Symptom Monitoring: Patient-reported outcomes (e.g., chest pain/dyspnea) via the App, with automated triage for risk stratification.
6. Health Education: Push delivery of targeted secondary prevention educational materials.
Digital Remote Management Group
1-year intervention
1. BP Management: Protocol-driven self-monitoring frequencies. The system triggers alerts for BP \>130/80 mmHg and generates automated suggestions for medication titration, subject to physician approval.
2. Lipid Management: Automated reminders for laboratory testing. Optical Character Recognition (OCR) technology extracts data from lab reports. If LDL-C ≥1.4 mmol/L, the system proposes regimen intensification for physician review.
3. Exercise Management:Target of ≥6000 steps/day. Data is synchronized via wearables or smartphones. Inactivity triggers automated behavioral feedback.
4. Medication Management: Daily app-based reminders and digital "check-ins." Non-adherence triggers automated alerts followed by human intervention if persistent.
5. Symptom Monitoring: Patient-reported outcomes (e.g., chest pain/dyspnea) via the App, with automated triage for risk stratification.
6. Health Education: Push delivery of targeted secondary prevention educational materials.
Interventions
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Digital Remote Management Group
1-year intervention
1. BP Management: Protocol-driven self-monitoring frequencies. The system triggers alerts for BP \>130/80 mmHg and generates automated suggestions for medication titration, subject to physician approval.
2. Lipid Management: Automated reminders for laboratory testing. Optical Character Recognition (OCR) technology extracts data from lab reports. If LDL-C ≥1.4 mmol/L, the system proposes regimen intensification for physician review.
3. Exercise Management:Target of ≥6000 steps/day. Data is synchronized via wearables or smartphones. Inactivity triggers automated behavioral feedback.
4. Medication Management: Daily app-based reminders and digital "check-ins." Non-adherence triggers automated alerts followed by human intervention if persistent.
5. Symptom Monitoring: Patient-reported outcomes (e.g., chest pain/dyspnea) via the App, with automated triage for risk stratification.
6. Health Education: Push delivery of targeted secondary prevention educational materials.
Eligibility Criteria
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Inclusion Criteria
2. Diagnosis of Acute Coronary Syndrome (ACS) or Chronic Coronary Syndrome (CCS)
3. Status post-successful percutaneous coronary intervention (PCI).
4. Possession of a smartphone and ability to operate the application (independently or with caregiver assistance).
5. Provision of written informed consent.
Exclusion Criteria
2. Severe hepatic dysfunction (ALT/AST ≥3xULN or Total Bilirubin \>1.5 mg/dl)
3. Severe renal dysfunction (eGFR \< 30 ml/min/1.73m² or requiring dialysis)
4. Uncontrolled hypothyroidism (TSH \>1.5xULN or \>10 mIU/L, or unstable dosage within 6 weeks)
5. Life expectancy \< 1 year due to non-cardiovascular comorbidities
6. Severe sensory (hearing/vision) or cognitive impairment precluding device use
7. Conditions affecting adherence (e.g., substance use disorder, history of alcohol abuse)
18 Years
75 Years
ALL
No
Sponsors
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Beijing Anzhen Hospital
OTHER
Responsible Party
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Chang sheng Ma
Director of cardiology department
Locations
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13810720787
Beijing, , China
Beijing Tongren Hospital, Capital Medical University, Beijing, China
Beijing, , China
The First Affiliated Hospital of Dalian Medical University, Dalian, China
Dalian, , China
The First Hospital of Jilin University, Changchun, China
Jilin, , China
Countries
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Central Contacts
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Other Identifiers
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KS2025290
Identifier Type: -
Identifier Source: org_study_id
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