Evidence map›Paper›PMID 42783016›Full record

ArticleJournal of cardiovascular development and disease2026

Clinical-Metabolic Risk Phenotypes and Carotid Plaque Burden Among Community-Dwelling Individuals at High Cardiovascular Risk: An Exploratory Cross-Sectional Study.

Zechang Lv, Dazhi Wang, Yubin Chen, Ziheng Xiao, Rui Lu, Benrong Liu, Wenchao Ou

Abstract read
In one paragraph

Article in Journal of cardiovascular development and disease, 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

7 authors.

Zechang LvDepartment of Cardiology, Guangzhou Institute of Cardiovascular Disease, Guangdong Key Laboratory of Vascular Diseases, State Key Laboratory of Respiratory Disease, the Second Affiliated Hospital, Guangzhou Medical University, Guangzhou 510260, China.ORCID 0009-0002-7387-6364
Dazhi WangDepartment of Cardiology, Guangzhou Institute of Cardiovascular Disease, Guangdong Key Laboratory of Vascular Diseases, State Key Laboratory of Respiratory Disease, the Second Affiliated Hospital, Guangzhou Medical University, Guangzhou 510260, China.
Yubin ChenDepartment of Cardiology, Guangzhou Institute of Cardiovascular Disease, Guangdong Key Laboratory of Vascular Diseases, State Key Laboratory of Respiratory Disease, the Second Affiliated Hospital, Guangzhou Medical University, Guangzhou 510260, China.
Ziheng XiaoDepartment of Cardiology, Guangzhou Institute of Cardiovascular Disease, Guangdong Key Laboratory of Vascular Diseases, State Key Laboratory of Respiratory Disease, the Second Affiliated Hospital, Guangzhou Medical University, Guangzhou 510260, China.
Rui LuDepartment of Cardiology, Guangzhou Institute of Cardiovascular Disease, Guangdong Key Laboratory of Vascular Diseases, State Key Laboratory of Respiratory Disease, the Second Affiliated Hospital, Guangzhou Medical University, Guangzhou 510260, China.
Benrong LiuDepartment of Cardiology, Guangzhou Institute of Cardiovascular Disease, Guangdong Key Laboratory of Vascular Diseases, State Key Laboratory of Respiratory Disease, the Second Affiliated Hospital, Guangzhou Medical University, Guangzhou 510260, China.
Wenchao OuDepartment of Cardiology, Guangzhou Institute of Cardiovascular Disease, Guangdong Key Laboratory of Vascular Diseases, State Key Laboratory of Respiratory Disease, the Second Affiliated Hospital, Guangzhou Medical University, Guangzhou 510260, China.

Funding

Guangzhou Municipal Science and Technology Bureau 2023A03J0400
6 · The paper itself

Abstract

backgroundCommunity-dwelling individuals at high cardiovascular risk are clinically heterogeneous, but whether distinct clinical-metabolic phenotypes differ in carotid plaque burden remains unclear.

methodsFrom 4191 participants in a community-based screening project conducted in two communities in Guangzhou, 1015 individuals in the high-cardiovascular-risk stage with nonmissing high-plaque-burden status were included. All 1015 participants underwent exploratory clustering using 17 clinical, metabolic, lifestyle-related, and disease-history variables. High plaque burden was defined as bilateral carotid plaques, multiple plaques, or maximum plaque thickness at or above the 75th percentile among plaque-positive participants. Logistic regression examined associations between phenotypes and high plaque burden.

resultsAmong the 1015 participants included in the clustering analysis, 329 (32.4%) met the definition of high plaque burden. Four phenotypes were identified: relatively low metabolic burden, older age-ASCVD burden, smoking-low HDL-C, and blood pressure-loaded phenotypes. The corresponding prevalences of high plaque burden were 15.9%, 44.4%, 49.7%, and 33.2%. After adjustment for age and sex, all three non-reference phenotypes showed higher odds of high plaque burden. In sensitivity analysis excluding age and prior ASCVD from clustering, the blood pressure-loaded phenotype remained associated with high plaque burden.

conclusionsFour exploratory clinical-metabolic phenotypes showed different levels of carotid plaque burden among community-dwelling individuals at high cardiovascular risk. The blood pressure-loaded and smoking-low HDL-C phenotypes were associated with greater plaque burden and may provide an exploratory framework for describing heterogeneity within high-risk populations.

Indexed as

carotid plaque burdencarotid ultrasoundclinical-metabolic phenotypeclustering analysiscommunity-based studyhigh cardiovascular risksubclinical atherosclerosis

Identifiers

PMID42783016
PMCPMC13607766

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.