Evidence map›Paper›PMID 42482640›Full record

ArticleYonsei medical journal2026

Coronary Artery Disease Prediction in Korean Patients with Familial Hypercholesterolemia: Analysis Involving Cholesterol Efflux Capacity.

Hyeonji Lee, Eui Seob Sheen, Seungmin Seok, Ji Eun Lee, Da Yeon Kyun, Soo-Jin Ann, Chan Joo Lee, Sang-Hak Lee

Abstract read
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Article in Yonsei medical journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

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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

8 authors.

Hyeonji Lee *Graduate School, Yonsei University, Seoul, Korea.ORCID https://orcid.org/0009-0004-7693-6419
Eui Seob Sheen *Department of Biostatistics and Computing, Yonsei University Graduate School, Seoul, Korea.ORCID https://orcid.org/0009-0004-4986-2477
Seungmin SeokGraduate School, Yonsei University, Seoul, Korea.ORCID https://orcid.org/0009-0007-7231-362X
Ji Eun LeeGraduate School, Yonsei University, Seoul, Korea.ORCID https://orcid.org/0009-0009-9868-3631
Da Yeon KyunGraduate School, Yonsei University, Seoul, Korea.ORCID https://orcid.org/0009-0001-6746-020X
Soo-Jin AnnIntegrative Research Center for Cerebrovascular and Cardiovascular Diseases, Yonsei University College of Medicine, Seoul, Korea. hoppum@yuhs.ac.ORCID https://orcid.org/0000-0002-1466-8787
Chan Joo LeeDivision of Cardiology, Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-8756-409X
Sang-Hak LeeDivision of Cardiology, Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea. shl1106@yuhs.ac.ORCID https://orcid.org/0000-0002-4535-3745

Funding

Korean Society of Lipid and AtherosclerosisNational Research Foundation of Korea 2022R1A2C1004946National Research Foundation of Korea RS-2025-16066728
6 · The paper itself

Abstract

purposePatients with familial hypercholesterolemia (FH) are at high risk of coronary artery disease (CAD), and its prediction is of great clinical importance. This study aimed to identify predictors of CAD and construct an effective risk prediction model for Korean patients with FH. MATERIALS AND

methodsClinical and laboratory data of 245 patients were collected from the Korean FH registry. CAD was defined as ≥50% coronary stenosis on invasive or computed tomographic angiography. The cholesterol efflux capacity (CEC) was measured using J774A1 cells and radiolabeled cholesterol. Predictors of CAD were identified by multivariable logistic regression analysis, and the best-performing prediction model was determined based on its statistical indices.

resultsThe participants' mean age was 49.1 years; 92 (37.6%) were male, and 41 (16.7%) had CAD. Age [odds ratio (OR) 1.05;

conclusionTraditional risk factors, including hypertension and HDL-C, were predictors of CAD in Korean patients with FH, whereas CEC was not. The resulting CAD prediction model demonstrated satisfactory performance in this population.

Indexed as

CholesterolCoronary Artery DiseaseHyperlipoproteinemia Type IIAdultCholesterol, HDLCholesterol, LDLFemaleHumansLogistic ModelsMaleMiddle AgedRepublic of KoreaRisk FactorsCholesterolCholesterol, HDLCholesterol, LDLatherosclerosisEast Asian peoplegenetic diseasesinbornPreventive medicine

Identifiers

PMID42482640
PMCPMC13303138

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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.