Evidence map›Paper›PMID 41669968›Full record

ArticleJournal of the American Heart Association2026

Remnant Cholesterol and Atherosclerotic Cardiovascular Disease Risk in Populations With Different Low-Density Lipoprotein Cholesterol Elevations: A Prospective Cohort Study.

Hong Zheng, Guanlin Chen, Zhenyu Huo, Yulong Lan, Yuxian Wang, Peng Fu, Weiqiang Wu, Haixiang Zheng, Kuangyi Wu, Zegui Huang and 3 more

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

13 authors.

Hong ZhengDepartment of Cardiology Second Affiliated Hospital of Shantou University Medical College Shantou China.ORCID 0009-0002-8950-651X
Guanlin ChenDepartment of Cardiology Second Affiliated Hospital of Shantou University Medical College Shantou China.
Zhenyu HuoDepartment of Epidemiology and Biostatistics, School of Public Health North China University of Science and Technology Tangshan China.
Yulong LanDepartment of Cardiology Second Affiliated Hospital of Shantou University Medical College Shantou China.ORCID 0000-0002-6143-9709
Yuxian WangDepartment of Cardiology Second Affiliated Hospital of Shantou University Medical College Shantou China.ORCID 0009-0005-4534-7272
Peng FuDepartment of Cardiology Second Affiliated Hospital of Shantou University Medical College Shantou China.
Weiqiang WuDepartment of Cardiology Second Affiliated Hospital of Shantou University Medical College Shantou China.
Haixiang ZhengDepartment of Cardiology Second Affiliated Hospital of Shantou University Medical College Shantou China.ORCID 0009-0004-0062-9148
Kuangyi WuDepartment of Cardiology Second Affiliated Hospital of Shantou University Medical College Shantou China.ORCID 0009-0003-9482-216X
Zegui HuangDepartment of Cardiology Sun Yat-sen Memorial Hospital of Sun Yat-sen University Guangzhou China.ORCID 0000-0001-6091-5964
Dan Wu *Department of Cardiology Second Affiliated Hospital of Shantou University Medical College Shantou China.ORCID 0000-0002-9367-6557
Shouling Wu *Department of Cardiology Kailuan General Hospital Tangshan China.ORCID 0000-0001-7095-6022
Youren Chen *Department of Cardiology Second Affiliated Hospital of Shantou University Medical College Shantou China.ORCID 0000-0003-4401-3279

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLow-density lipoprotein cholesterol (LDL-C) and remnant cholesterol (RC) are risk factors for atherosclerotic cardiovascular disease (ASCVD). However, the extent to which differences in RC levels affect ASCVD risk in populations with varying degrees of LDL-C elevation remains unclear. This study aimed to investigate whether RC can provide additional risk stratification value across different sexes, ages, and elevated LDL-C statuses.

methodsThis study included 12 743 elevated LDL-C participants (LDL-C ≥3.4 mmol/L) and 50 073 age- and sex-matched non-elevated LDL-C controls from the Kailuan Study. Elevated LDL-C participants were categorized by RC levels into <0.5, 0.5 to <1.0, and ≥1.0 mmol/L subgroups. Kaplan-Meier curves and Cox proportional hazards models were used to assess the relationship between RC levels and ASCVD risk across different sexes, ages, and high LDL-C statuses.

resultsDuring a median follow-up of 12.8 years, 1686 elevated LDL-C participants (13.2%) and 5252 non-elevated LDL-C participants (10.5%) developed ASCVD. In the borderline-high LDL-C group (3.4 ≤ LDL-C < 4.1 mmol/L), those with the lowest RC levels showed no significant risk difference compared with controls (hazard ratio [HR], 1.03 [95% CI, 0.93-1.13]), and this pattern remained consistent across different sexes and ages. In contrast, in the high LDL-C group (LDL-C ≥4.1 mmol/L), even when RC was at the lowest level, ASCVD risk remained significantly higher than that of controls (HR, 1.20 [95% CI, 1.02-1.41]).

conclusionsIn the borderline-high LDL-C population, those with the lowest RC levels showed no significant risk difference compared with controls, and this pattern remained consistent across different sexes and age subgroups. In the high LDL-C population, even when RC was at the lowest level, ASCVD risk remained significantly higher than that of controls.

Indexed as

AtherosclerosisCholesterolCholesterol, LDLLipoproteinsTriglyceridesAdultAgedBiomarkersChinaFemaleHeart Disease Risk FactorsHumansMaleMiddle AgedProspective StudiesRisk AssessmentBiomarkersCholesterolCholesterol, LDLLipoproteinsTriglyceridesatherosclerotic cardiovascular diseaseKailuan Studylow‐density lipoprotein cholesterolremnant cholesterol

Identifiers

PMID41669968
PMCPMC13055447

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.