The role of elevated lipoprotein(a) in aortic valve disease: a systematic review
Bibliographic record
Abstract
Background: Calcific aortic valve stenosis (CAVS) is the most prevalent valvular heart disease and a growing global health concern. Aortic sclerosis (ASc) and aortic stenosis (AS) represent a continuum of progressive disease characterized by leaflet thickening, inflammation, lipid deposition, and calcification. Lipoprotein(a) [Lp(a)], with its pro-atherogenic, pro-inflammatory, and pro-calcific properties, has emerged as a key contributor to this process. While its role in atherosclerotic cardiovascular disease is well established, the relationship between Lp(a) and CAVS has been demonstrated in several key studies; however, the available evidence remains limited in volume, and important gaps persist in understanding mechanisms, risk stratification, and therapeutic implications. Methods: A systematic literature search was conducted in PubMed, Cochrane Library, ScienceDirect, Medline, ResearchGate, Embase, and Google Scholar in accordance with PRISMA guidelines. Eligible studies included observational designs (cross-sectional, cohort, case-control) and randomized trials evaluating associations between Lp(a) levels, genetic variants, and CAVS. Study quality was assessed using the Newcastle-Ottawa Scale (NOS). Results: Eighteen studies met the inclusion criteria, comprising six case-control, six cohort, and six cross-sectional studies with a total of 153,192 participants. No randomized controlled trials were identified. Elevated Lp(a) levels were consistently associated with an increased risk of AS and aortic valve calcification (AVC), with a dose-dependent effect. The risk was highest at levels ≥50 mg/dl, though some evidence supported risk at ≥30 mg/dl. Genetic analyses identified rs10455872 as a significant risk allele, while rs3798220 showed inconsistent associations. Multi-ethnic cohorts highlighted racial variability: Afro-Caribbean individuals had higher baseline Lp(a) levels but lower AVC prevalence than Caucasians. Conclusion: Lp(a) is an independent risk factor for CAVS, influenced by both concentration and genetic variation. Early screening and emerging Lp(a)-lowering therapies, including antisense oligonucleotides, small interfering RNA, and PCSK9 inhibitors, may help mitigate disease progression. Further randomized trials are needed to determine whether Lp(a) reduction translates into cardiovascular and valvular benefit. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD42024533835, PROSPERO CRD42024533835.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".