Evidence map›Paper›PMID 40632051›Full record

ArticleJACC. Asia2025

Discordance of Small Dense LDL Cholesterol Beyond LDL Cholesterol or Non-HDL Cholesterol and Carotid Plaque.

Jinqi Wang, Xiaoyu Zhao, Yanchen Zhao, Rui Jin, Yunfei Li, Jiahe Wang, Yueruijing Liu, Zhiyuan Wu, Xiuhua Guo, Lixin Tao

Abstract read
In one paragraph

Article in JACC. Asia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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

10 authors.

Jinqi WangBeijing Key Laboratory of Environment and Aging, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China.
Xiaoyu ZhaoBeijing Key Laboratory of Environment and Aging, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China.
Yanchen ZhaoBeijing Key Laboratory of Environment and Aging, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China.
Rui JinBeijing Key Laboratory of Environment and Aging, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China.
Yunfei LiBeijing Key Laboratory of Environment and Aging, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China.
Jiahe WangBeijing Key Laboratory of Environment and Aging, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China.
Yueruijing LiuBeijing Key Laboratory of Environment and Aging, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China.
Zhiyuan WuHarvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Xiuhua GuoBeijing Key Laboratory of Environment and Aging, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China; National Institute for Data Science in Health and Medicine, Capital Medical University, Beijing, China; School of Medical and Health Sciences, Edith Cowan University, Perth, Australia. Electronic address: statguo@ccmu.edu.cn.
Lixin TaoBeijing Key Laboratory of Environment and Aging, Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China. Electronic address: taolixin@ccmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDifferent low-density lipoprotein (LDL) particles exhibit distinct proatherogenic properties.

objectivesThis study sought to evaluate associations of small dense low-density lipoprotein cholesterol (sdLDL-C), large buoyant low-density lipoprotein cholesterol (lbLDL-C), sdLDL-C/LDL-C ratio, and sdLDL-C/lbLDL-C ratio with carotid plaque (CP) risk in the general population, and to perform discordance analyses to determine which biomarker better reflects CP risk beyond low-density lipoprotein cholesterol (LDL-C) and non-high-density lipoprotein cholesterol (non-HDL-C).

methodsThis study enrolled 20,369 participants from Beijing Health Management Cohort. Discordant sdLDL-C, lbLDL-C, or ratio metrics (sdLDL-C/LDL-C and sdLDL-C/lbLDL-C) relative to LDL-C or non-HDL-C, and discordant ratio metrics relative to sdLDL-C, were defined by residual differences and median values. Logistic regression models were used to estimate ORs and 95% CIs.

resultsIn this study, higher levels of sdLDL-C (OR: 1.354; 95% CI: 1.299-1.410), sdLDL-C/LDL-C ratio (OR: 1.196; 95% CI: 1.148-1.247), and sdLDL-C/lbLDL-C ratio (OR: 1.153; 95% CI: 1.110-1.197) were more strongly associated with increased odds of CP than lbLDL-C (OR: 1.110; 95% CI: 1.070-1.151). Additionally, discordantly high sdLDL-C or low lbLDL-C relative to LDL-C or non-HDL-C were associated with increased odds of CP, whereas discordantly low sdLDL-C or high lbLDL-C were associated with reduced odds. Finally, discordantly high sdLDL-C/LDL-C and sdLDL-C/lbLDL-C ratios relative to LDL-C, non-HDL-C, or sdLDL-C were linked to increased odds of CP.

conclusionsThe sdLDL-C, sdLDL-C/LDL-C, and sdLDL-C/lbLDL-C, but not lbLDL-C, are superior to LDL-C and non-HDL-C in identifying individuals at increased risk of CP. The sdLDL-C/LDL-C and sdLDL-C/lbLDL-C ratios may capture additional risk information beyond sdLDL-C.

Indexed as

carotid plaquelarge buoyant low-density lipoprotein cholesterolresidual riskssdLDL-C/lbLDL-C ratiosdLDL-C/LDL-C ratiosmall dense low-density lipoprotein cholesterol

Identifiers

PMID40632051
PMCPMC12426842

What Socratic holds

Textmetadata
LicenceCC BY
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.