Perceive and Calculated CV Risk
Study Details
Study Description
Brief Summary
Cardiovascular prevention guidelines use estimated 10-year atherosclerotic cardiovascular disease (ASCVD) risk to guide treatment decisions and engage patients in shared decision-making. Research has focused on refining the accuracy of these CV risk calculators for different populations, relatively little has been done to understand how patients perceive their own ASCVD risk. Accurate perception of a patient's risk by both the patient and the doctors is important because this is an important determinant of health-related behaviour. Patients often show optimistic bias when considering their own CV risk and consistently underestimate it.
We aim to determine patient perceived versus actual risk of ASCVD in a Chinese population. We aim to better understand the degree to which patients underestimate or overestimate their ASCVD risk and whether patients are better or worse at estimating their ASCVD risk relative to their peers of the same age and sex. Finally, we aim to evaluate patients willingness to follow guideline recommended CV prevention and specifically lipid-lowering therapy.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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Detailed Description
Cardiovascular prevention guidelines use estimated 10-year atherosclerotic cardiovascular disease (ASCVD) risk to guide treatment decisions and engage patients in shared decision-making. Research has focused on refining the accuracy of these CV risk calculators for different populations, relatively little has been done to understand how patients perceive their own ASCVD risk. Accurate perception of a patient's risk by both the patient and the doctors is important because this is an important determinant of health-related behaviour. Patients often show optimistic bias when considering their own CV risk and consistently underestimate it.
We aim to determine patient perceived versus actual risk of ASCVD in a Chinese population. We aim to better understand the degree to which patients underestimate or overestimate their ASCVD risk and whether patients are better or worse at estimating their ASCVD risk relative to their peers of the same age and sex. Finally, we aim to evaluate patients willingness to follow guideline recommended CV prevention and specifically lipid-lowering therapy.
Study Design
Outcome Measures
Primary Outcome Measures
- Evaluate correlation between patients' own estimates of their 10-year risk of heart disease or stroke with actual pooled-cohort-equation calculated risk estimates (using a validated CV risk calculation app). [12-months]
Secondary Outcome Measures
- Evaluate correlation between perceived and calculated 10-year CV risk in sub-groups based on age, sex, education level, known CV risks (e.g. smoking, diabetes, hyperlipidemia and hypertension [12-months]
- Evaluate patients' own estimates of 10-year CV risk relative to their peers using age- and sex-specific population risk percentiles. [12-months]
- Evaluate patients' willingness to follow recommendations for CV prevention based on their calculated 10-year CV risk profile (e.g. dietary, exercise, smoking and CV risk factor control) [12-months]
- Evaluate whether perceived or actual CVD risk is associated with current statin use or willingness to take statin. [12-months]
- Reasons for unwillingness to follow recommendations for CV preventions [12-months]
- Source of CV health information and advice [12-months]
Eligibility Criteria
Criteria
Inclusion Criteria:
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Aged 40 years and above
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Consent to complete questionnaire
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Lipid profile within 12 months
Exclusion Criteria:
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Known ASCVD defined as history of coronary heart disease (i.e. obstructive coronary disease, prior myocardial infarction, or prior coronary revascularization); cerebrovascular disease (i.e. stroke or transient ischemic attack); and peripheral arterial disease (i.e. obstructive peripheral disease, prior vascular amputation or prior revascularization)
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Other chronic illness with life-expectancy <12 months
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | The Chinese University of Hong Kong | Shatin | Hong Kong | 999077 |
Sponsors and Collaborators
- Chinese University of Hong Kong
- Gormin Tan gtan
Investigators
None specified.Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- 2022.573