Keywords: Lipoprotein(a); adolescents; prevention; research proposal

Background:

Lipoprotein(a) [Lp(a)] is a genetically determined lipid particle associated with increased risk of atherosclerotic cardiovascular disease (CVD), including premature myocardial infarction and stroke. Lp(a) levels are stable throughout life and unaffected by lifestyle or standard lipid-lowering therapy. Despite its clinical relevance, Lp(a) is not routinely measured in annual check-ups, especially among adolescents without known CVD or family history, leading to missed opportunities for early prevention.

Research questions:

Could routine measurement of Lp(a) during young adults’ annual check-ups improve early identification of high cardiovascular risk and support more effective prevention in general practice?

Method:

This study will follow a pragmatic, three-phase design adapted for general practice settings:
A systematic literature review will summarize current evidence on Lp(a) as a risk factor, its clinical utility, and existing guidelines for testing in primary care.
A cross-sectional observational study will be conducted among adults aged 14–18 attending routine check-ups. The required sample size will be calculated based on expected Lp(a) prevalence in this age group to ensure statistical power. Data will include demographics, family history, lifestyle factors, and fasting blood samples for Lp(a) and standard lipid profiles. All procedures will be embedded in routine workflows to ensure feasibility.
A pilot follow-up study will involve participants with elevated Lp(a), who will receive GP-delivered lifestyle counseling. Feasibility outcomes will include recruitment rates, test acceptability, consultation duration, and patient-reported understanding. Quantitative data will be analyzed using SPSS; optional interviews may explore barriers and facilitators of implementation.

Results:

Conclusions:

Routine Lp(a) screening may improve early risk stratification and personalized prevention in general practice, particularly for patients not identified through traditional models.

Points for discussion:

How can Lp(a) testing be implemented in general practice without increasing system burden or patient anxiety?