Evidence map›Paper›PMID 41739334›Full record

ReviewCurrent atherosclerosis reports2026

New Methods for Calculating LDL-Cholesterol and Related Biomarkers of Atherosclerotic Cardiovascular Disease Risk.

Anna Wolska, Yeganeh Mansourian, Rafael Zubirán, Maureen Sampson, Alan T Remaley

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Current atherosclerosis reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Anna WolskaLipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Bldg. 10/Rm. 8N220, Bethesda, MD, 20892, USA. anna.wolska@nih.gov.ORCID http://orcid.org/0000-0001-9479-0741
Yeganeh MansourianLipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Bldg. 10/Rm. 8N220, Bethesda, MD, 20892, USA.
Rafael ZubiránLipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Bldg. 10/Rm. 8N220, Bethesda, MD, 20892, USA.
Maureen SampsonDepartment of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD, USA.
Alan T RemaleyLipoprotein Metabolism Laboratory, Translational Vascular Medicine Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Bldg. 10/Rm. 8N220, Bethesda, MD, 20892, USA.

Funding

Research was supported by grant (23CVD02) from the Leducq Foundation and the Leducq Foundation for Cardiovascular Research. 23CVD02
6 · The paper itself

Abstract

purpose of reviewThis review describes the recently developed equations for calculating Low-density lipoprotein cholesterol (LDL-C), and equations for estimating small dense LDL-cholesterol (sdLDL-C), and LDL-triglycerides (LDL-TG) for atherosclerotic cardiovascular disease (ASCVD) risk assessment. RECENT

findingsThe new Modified Sampson-NIH equation provides a more accurate estimation of LDL-C across a wide range of TG levels compared to the traditional and still commonly used Friedewald equation. Furthermore, it is more accurate compared to other equations at the low LDL-C cutpoints used for high-risk and very high-risk ASCVD patients and is valuable for deciding the need for additional lipid-lowering therapy. New equations for calculating sdLDL-C and LDL-TG use the same lipid parameters as for calculating LDL-C but offer additional insights into atherogenic lipoprotein burden. High plasma TG and very low LDL-C concentrations necessitate more accurate LDL-C calculations, which can be readily adopted without additional cost to improve ASCVD risk management.

Indexed as

AtherosclerosisCardiovascular DiseasesCholesterol, LDLTriglyceridesBiomarkersHeart Disease Risk FactorsHumansRisk AssessmentRisk FactorsBiomarkersCholesterol, LDLTriglyceridesBiomarkersCardiovascular diseaseEquationsLDL-cholesterolRisk factorsSmall dense LDL

Identifiers

PMID41739334
PMCPMC12935843

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Registered trials

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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.