Evidence map›Paper›PMID 32926241›Full record

ReviewCurrent cardiology reports2020

Should We Use Genetic Scores in the Determination of Treatment Strategies to Control Dyslipidemias?

Katharina Lechner, Thorsten Kessler, Heribert Schunkert

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current cardiology reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 23% of its field
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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. 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 at 2 institutions in 1 country.

Katharina LechnerDepartment of Cardiology, German Heart Centre Munich, Technical University Munich, Lazarettstraße 36, 80636, Munich, Germany.
Thorsten KesslerDepartment of Cardiology, German Heart Centre Munich, Technical University Munich, Lazarettstraße 36, 80636, Munich, Germany.
Heribert SchunkertDepartment of Cardiology, German Heart Centre Munich, Technical University Munich, Lazarettstraße 36, 80636, Munich, Germany. schunkert@dhm.mhn.de.
Deutsches Herzzentrum München · DEGerman Centre for Cardiovascular Research · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewConventional risk stratification algorithms that rely on age, clustered phenotypic traits, and biomarkers under-recognize the sizeable subgroup of individuals at high polygenic risk for atherosclerotic cardiovascular disease (ASCVD). This review provides perspective on the promising role of genetic testing in cardiovascular prevention through the lens of lipid metabolism. RECENT

findingsRecent advances in cardiovascular genetics identified a number of common and rare variants affecting ASCVD risk. This genetic susceptibility can be assessed by polygenic risk scores (PRS) which quantify risk conferred by the cumulative impact of common variants. This results in a normally distributed spectrum of risk for coronary artery disease that is present at birth and amplifies the effects of modifiable risk factors including lipids. Polygenic risk is a significant determinant of ASCVD risk that is below the discrimination level of conventional guideline-based clinical frameworks. Genetic risk scores thus hold potential to refine phenotypic screening in cardiovascular prevention, identify subsets of the population that might derive particular benefit from early lifestyle and pharmaceutical interventions, and guide treatment eligibility. This might pave the way to personalized prevention aimed at reducing the unacceptable global burden of ASCVD.

Indexed as

AtherosclerosisCoronary Artery DiseaseDyslipidemiasBiomarkersHumansRisk AssessmentRisk FactorsBiomarkersCardiovascular preventionCoronary artery diseaseDyslipidemiasGenetic scoresGenome-wide association studyMyocardial infarctionRisk stratification

Identifiers

PMID32926241
OpenAlexW3086160776

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.