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Effectiveness of Decision Support for Cardiovascular Risk Management in People With Cardiovascular Disease (2-DECIDE)

D

dr.Frank L.J. Visseren

Status

Enrolling

Conditions

Shared-decision Making
Atherosclerotic Cardiovascular Diseases

Treatments

Other: No Intervention: usual care
Other: 2-DECIDE intervention: decision support for cardiovascular risk management

Study type

Interventional

Funder types

Other

Identifiers

NCT06871514
24U-1636

Details and patient eligibility

About

This study aims to improve the way patients with cardiovascular diseases are informed about their treatment options. It explores methods to support shared decision-making between patients and doctors. In some cases, doctors will take extra time to discuss treatment options in detail. To assess the impact, some patients will be asked to complete questionnaires after their clinic visits.

Enrollment

1,200 estimated patients

Sex

All

Ages

40 to 80 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • Established ASCVD

    • At least 30 days since last CVD event and/or the diagnosis of ASCVD. If no CVD events have occurred, imaging confirming ASCVD must have been conducted at least 30 days prior.
    • Documented ASCVD (defined according to the 2021 European Society of Cardiology guideline), which includes ASCVD established clinically or demonstrated unequivocally by imaging:
  • Clinically documented ASCVD includes previous myocardial infarction, acute coronary syndrome, coronary revascularization (Percutaneous Coronary Intervention (PCI) or Coronary Artery Bypass Surgery (CABG)), and other arterial revascularization procedures, ischemic stroke or transient ischemic attack, and peripheral artery disease (from Fontaine stage II). Angina pectoris (stable) without imaging evidence of atherosclerosis does not qualify as ASCVD.

  • ASCVD unambiguously identified through imaging, includes significant stenosis (>50%) on coronary angiography, computed tomography angiography, or carotic ultrasound. It also includes aortic aneurysms measuring ≥3cm. Only Carotid Intima-Media Thickness measurements (cIMT), Coronary Artery Calcium scoring or abnormal ankle-brachial index scores without evidence of stenosis, do not qualify as ASCVD.

  • Age 40-80 years (to allow for individual risk predictions with the SMART2 model

  • Patient attending the Cardiology or Vascular Medicine outpatient clinic

  • Sufficient understanding of the Dutch language (due to the questionnaires being administered in Dutch).

  • Written informed consent must be provided. Although the proposed intervention is not subject to the WMO, informed consent is required for the collection and processing of data, including the distribution of questionnaires.

Exclusion criteria

  • Patients currently participating in other interventional medication studies, or studies that directly affect the therapy plan

  • Remaining life expectancy of less than 2 years as assessed by a consulting healthcare professional (these patients have no indication for cardiovascular risk management)

  • Patients for whom individual risk predictions with the SMART2 model are not feasible:

    • Systolic Blood Pressure (SBP) <90 mmHg or >200 mmHg
    • Total cholesterol <2.5mmol/L or >8 mmol/L
    • High-Density Lipoprotein (HDL) cholesterol <0.6mmol/L or >2.5 mmol/L
    • Low-Density Lipoprotein (LDL) <0.1 mmol/L or >7.4 mmol /L
    • Estimated Glomerular Filtration Rate (eGFR) <30ml/min/1.73m2 or dialysis
    • Active treatment for malignity, pregnancy, history of organ transplantation, or liver failure
  • Previous participation in 2-DECIDE

Trial design

Primary purpose

Treatment

Allocation

Randomized

Interventional model

Sequential Assignment

Masking

None (Open label)

1,200 participants in 2 patient groups

Usual care
Other group
Treatment:
Other: No Intervention: usual care
2-DECIDE intervention
Experimental group
Treatment:
Other: 2-DECIDE intervention: decision support for cardiovascular risk management

Trial contacts and locations

8

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Central trial contact

Elbrich Wempe, MD, PhD candidate; Steven Hageman, Assistant professor

Data sourced from clinicaltrials.gov

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