Evidence mapPaperPMID 39756980Full record

ReviewJournal of atherosclerosis and thrombosis2025

New Approaches to Lipoproteins for the Prevention of Cardiovascular Events.

Masashi Fujino, Giuseppe Di Giovanni, Stephen J Nicholls

Abstract readReview
In one paragraph

Review in Journal of atherosclerosis and thrombosis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Masashi FujinoVictorian Heart Institute, Monash University.
Giuseppe Di GiovanniVictorian Heart Institute, Monash University.
Stephen J NichollsVictorian Heart Institute, Monash University.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Atherosclerotic cardiovascular disease (ASCVD) is a leading global cause of mortality, and recent research has underscored the critical role of lipoproteins in modulating cardiovascular (CV) risk. Elevated low-density lipoprotein cholesterol (LDL-C) levels have been linked to increased CV events, and while numerous trials have confirmed the efficacy of lipid-lowering therapies (LLT), significant gaps remain between recommended LDL-C targets and real-world clinical practice. This review addresses care gaps in LLT, emphasizing the necessity for innovative approaches that extend beyond LDL-C management. It explores combination therapy approaches such as statins combined with ezetimibe or PCSK9 inhibitors, which have shown promise in enhancing LDL-C reduction and improving outcomes in high-risk patients. Additionally, this review discusses new approaches in lipid modification strategies, including bempedoic acid, inclisiran, and drugs that lower Lp(a), highlighting their potential for CV risk reduction. Furthermore, it emphasizes the potential of polygenic risk scores to guide LLT and lifestyle changes despite challenges in implementation and genetic testing ethics. This article discusses the current guidelines and proposes innovative approaches for optimizing lipoprotein management, ultimately contributing to improved patient outcomes in ASCVD prevention.

Indexed as

Cardiovascular DiseasesHypolipidemic AgentsLipoproteinsCholesterol, LDLHumansHydroxymethylglutaryl-CoA Reductase InhibitorsCholesterol, LDLHydroxymethylglutaryl-CoA Reductase InhibitorsHypolipidemic AgentsLipoproteinsAtherosclerotic cardiovascular diseaseCombination therapyLipid-lowering therapyPersonalized medicinePolygenic risk score

Identifiers

PMID39756980
PMCPMC11883213

What Socratic holds

Texttitle and abstract
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.