Evidence map›Paper›PMID 42989338›Full record

ArticleLipids in health and disease2026

Lipid-metabolic risk stratification for carotid plaque in adults under 50 years undergoing health examinations: cross-sectional modeling and same-center longitudinal validation.

Hailong Qi, Xiaoyu Zhang, Kaixuan Zheng, Xueqin Wang, Mengduo Jiang, Huaqing Hu

Abstract read
In one paragraph

Article in Lipids in health 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

6 authors.

Hailong QiDepartment of General Practice, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
Xiaoyu ZhangHealth Management Center, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
Kaixuan ZhengDepartment of General Practice, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
Xueqin WangDepartment of Medical Engineering, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
Mengduo JiangDepartment of Medical Engineering, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China.
Huaqing HuDepartment of General Practice Teaching and Research Section, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, Anhui, China. huhuaqing@ahmu.edu.cn.

Funding

Anhui Provincial Health Research Project AHWJ2023A10009
6 · The paper itself

Abstract

backgroundCarotid plaque is an imaging marker of early subclinical atherosclerosis. Adults under 50 years of age undergoing health examinations often have low short-term absolute cardiovascular risk, yet adverse lipid-metabolic profiles may already be associated with early plaque formation. This study aimed to develop and evaluate a parsimonious lipid-metabolic risk stratification model for carotid plaque risk using routinely available health-examination variables.

methodsThis retrospective single-center study constructed two related cohorts from a health management center. The cross-sectional modeling cohort included 30,557 adults under 50 years of age examined between 2018 and 2023, of whom 1277 had prevalent carotid plaque, and was used for model development and internal validation. The same-center longitudinal validation cohort included 1679 baseline plaque-free participants with classifiable longitudinal plaque trajectories from repeated examinations between January 2020 and December 2024; 105 developed the primary incident carotid plaque outcome. Thirteen routine health-examination variables were considered. Variable selection and model development were performed only in the training set. The final multivariable logistic regression model included age, male sex, low-density lipoprotein cholesterol, systolic blood pressure, high-density lipoprotein cholesterol, and fasting glucose. Performance was assessed using AUROC and PR-AUC. Low-, intermediate-, and high-risk strata were defined using tertiles of predicted probability in the training set.

resultsIn the internal validation set, the final multivariable logistic regression model achieved an AUROC of 0.807 and a PR-AUC of 0.168, higher than those of the age- and sex-only model. In the same-center longitudinal validation cohort, the final model achieved an AUROC of 0.795 and a PR-AUC of 0.216 for the primary incident carotid plaque outcome. The observed outcome rates increased across low-, intermediate-, and high-risk strata: 0.75%, 3.41%, and 13.9%, respectively. The high-risk stratum included 82 of 105 primary incident carotid plaque outcomes. Sensitivity analysis using Firth penalized logistic regression showed directionally consistent associations.

conclusionsAmong adults under 50 years of age undergoing routine health examinations, a parsimonious lipid-metabolic model incorporating age, male sex, low-density lipoprotein cholesterol, systolic blood pressure, high-density lipoprotein cholesterol, and fasting glucose provided discrimination for prevalent carotid plaque status and stratified longitudinal incident plaque outcomes in a same-center repeated-examination cohort. This model provides an interpretable framework for early subclinical atherosclerosis risk communication and cardiometabolic risk management in health-examination settings.

Indexed as

Carotid Artery DiseasesLipidsPlaque, AtheroscleroticAdultCholesterol, HDLCholesterol, LDLCross-Sectional StudiesFemaleHumansLongitudinal StudiesMaleMiddle AgedRetrospective StudiesRisk AssessmentRisk FactorsCholesterol, HDLCholesterol, LDLLipidsCarotid plaqueHealth examinationLipid metabolismLogistic regressionRisk stratificationSubclinical atherosclerosis

Identifiers

PMID42989338
PMCPMC13737666

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.