Perceive and Calculated CV Risk

Official title

Patient-Perceived Versus Actual Risk of Cardiovascular Disease and Willingness to Follow Recommendations for Cardiovascular Prevention

Overview

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.

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.

Interventions

• Other Cardiovascular prevention guidelines
  Cardiovascular prevention guidelines use estimated 10-year atherosclerotic cardiovascular disease (ASCVD) risk to guide treatment decisions and engage patients in shared decision-making

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). [Time frame: 12-months]

Secondary outcome measures (6)

• 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 [Time frame: 12-months]
• Evaluate patients' own estimates of 10-year CV risk relative to their peers using age- and sex-specific population risk percentiles. [Time frame: 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) [Time frame: 12-months]
• Evaluate whether perceived or actual CVD risk is associated with current statin use or willingness to take statin. [Time frame: 12-months]
• Reasons for unwillingness to follow recommendations for CV preventions [Time frame: 12-months]
• Source of CV health information and advice [Time frame: 12-months]

Eligibility criteria

Inclusion criteria

• Aged 40 years and above
• Consent to complete questionnaire
• Lipid profile within 12 months

Exclusion criteria

• 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)
• Other chronic illness with life-expectancy <12 months

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Observational model

Case-only

Study locations

Hong Kong · 1 center

• The Chinese University of Hong Kong — Shatin

Publications

• Visseren FLJ, Mach F, Smulders YM, Carballo D, Koskinas KC, Back M, Benetos A, Biffi A, Boavida JM, Capodanno D, Cosyns B, Crawford C, Davos CH, Desormais I, Angelantonio ED, Franco OH, Halvorsen S, Richard Hobbs FD, Hollander M, Jankowska EA, Michal M, Sacco S, Sattar N, Tokgozoglu L, Tonstad S, Tsioufis KP, van Dis I, van Gelder IC, Wanner C, Williams B; ESC Scientific Document Group. 2021 ESC G PMID 35525570
• Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, Himmelfarb CD, Khera A, Lloyd-Jones D, McEvoy JW, Michos ED, Miedema MD, Munoz D, Smith SC Jr, Virani SS, Williams KA Sr, Yeboah J, Ziaeian B. 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on C PMID 30879339
• Lloyd-Jones DM, Braun LT, Ndumele CE, Smith SC Jr, Sperling LS, Virani SS, Blumenthal RS. Use of Risk Assessment Tools to Guide Decision-Making in the Primary Prevention of Atherosclerotic Cardiovascular Disease: A Special Report From the American Heart Association and American College of Cardiology. J Am Coll Cardiol. 2019 Jun 25;73(24):3153-3167. doi: 10.1016/j.jacc.2018.11.005. Epub 2018 Nov 10 PMID 30423392
• Webster R, Heeley E. Perceptions of risk: understanding cardiovascular disease. Risk Manag Healthc Policy. 2010;3:49-60. doi: 10.2147/RMHP.S8288. Epub 2010 Sep 6. PMID 22312218
• Thakkar J, Heeley EL, Chalmers J, Chow CK. Inaccurate risk perceptions contribute to treatment gaps in secondary prevention of cardiovascular disease. Intern Med J. 2016 Mar;46(3):339-46. doi: 10.1111/imj.12982. PMID 26662342

Identifiers

NCT: NCT05693857 · 2022.573

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗