Evidence map›Paper›PMID 39508748›Full record

ArticleBiomolecules & biomedicine2025

Association of baseline remnant cholesterol independent of LDL-cholesterol with newly diagnosed diabetes in the Chinese population.

Yulu Yang, Xuehan Li, Jianwu Huang, Jiacheng Wu, Yalei Wang, Hao Chen, Zhihua Qiu, Zihua Zhou

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomolecules & biomedicine, 2025. 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. 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

8 authors.

Yulu YangDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xuehan LiDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Jianwu HuangDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Jiacheng WuDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yalei WangDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Hao ChenDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zhihua QiuDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zihua ZhouDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Key Laboratory of Biological Targeted Therapy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Hubei Engineering Research Center for Immunological Diagnosis and Therapy of Cardiovascular Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Remnant cholesterol (RC) is highly regarded in the cardiovascular field; however, its relationship with new-onset diabetes remains unclear. This study aimed to investigate the relationship between RC and the risk of developing diabetes, as well as its interaction with low-density lipoprotein cholesterol (LDL-c). This was a secondary analysis of a retrospective cohort study based on a Chinese population. A multivariate Cox proportional hazards regression was initially employed to assess the relationship between RC and newly diagnosed diabetes. This was followed by a subgroup analysis to explore intergroup heterogeneity. A clinical prediction model was then developed. Finally, the study further analyzed the interactions between LDL-c and RC. After adjusting for confounding factors, RC was significantly associated with an increased risk of diabetes (HR = 1.46, 95% confidence interval [CI] 1.36-1.57). Furthermore, this relationship was nonlinear, with an inflection point of 0.48 identified through the piecewise model. Subgroup analysis indicated that the association was more pronounced in individuals under 60 years and those with a body mass index < 24 kg/m2 (P for interaction = 0.0004, <0.0001, respectively). RC proved to be a more effective predictor of diabetes compared to other lipid profiles, and the clinical prediction model was successfully constructed. Notably, individuals in the low LDL-c/high RC group were found to have a 1.41-fold (95% CI 1.281.55) greater risk compared to those in the low LDL-c/low RC group. Significant correlations were observed between baseline RC levels and the risk of new-onset diabetes. Elevated RC was a strong predictor of diabetes risk, irrespective of LDL-c levels.

Indexed as

CholesterolCholesterol, LDLDiabetes MellitusLipoproteinsTriglyceridesAdultAgedChinaEast Asian PeopleFemaleHumansMaleMiddle AgedRetrospective StudiesRisk FactorsCholesterolCholesterol, LDLLipoproteinsremnant-like particle cholesterolTriglycerides

Identifiers

PMID39508748
PMCPMC12042679

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.