Evidence map›Paper›PMID 37254140›Full record

ArticleCardiovascular diabetology2023

Association between triglyceride-glucose index trajectories and carotid atherosclerosis progression.

Haixu Yu, Liyuan Tao, Yan-Guang Li, Lincheng Yang, Dan Liu, Yang Wang, Xiaoyan Hao, Honghai He, Ying Che, Peng Wang and 2 more

Open access · goldAbstract read
In one paragraph

Article in Cardiovascular diabetology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed, 1 pooled it
19.8field-weighted citation impact, top 1% of its field
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

57 citing papers in PubMed, 1 synthesis or guideline pooled it, 91 citations in OpenAlex.

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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

12 authors at 3 institutions in 2 countries.

Haixu YuNHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Key Laboratory of Molecular Cardiovascular Science, Beijing Key Laboratory of Cardiovascular Receptors Research, Department of Cardiology, Institute of Vascular Medicine, Ministry of Education, Peking University Third Hospital, 100191, Beijing, China.
Liyuan TaoResearch Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, 100191, China.
Yan-Guang LiNHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Key Laboratory of Molecular Cardiovascular Science, Beijing Key Laboratory of Cardiovascular Receptors Research, Department of Cardiology, Institute of Vascular Medicine, Ministry of Education, Peking University Third Hospital, 100191, Beijing, China.
Lincheng YangNHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Key Laboratory of Molecular Cardiovascular Science, Beijing Key Laboratory of Cardiovascular Receptors Research, Department of Cardiology, Institute of Vascular Medicine, Ministry of Education, Peking University Third Hospital, 100191, Beijing, China.
Dan LiuNHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Key Laboratory of Molecular Cardiovascular Science, Beijing Key Laboratory of Cardiovascular Receptors Research, Department of Cardiology, Institute of Vascular Medicine, Ministry of Education, Peking University Third Hospital, 100191, Beijing, China.
Yang WangPhysical Examination Center, Peking University Third Hospital, Beijing, 100191, China.
Xiaoyan HaoPhysical Examination Center, Peking University Third Hospital, Beijing, 100191, China.
Honghai HePhysical Examination Center, Peking University Third Hospital, Beijing, 100191, China.
Ying ChePhysical Examination Center, Peking University Third Hospital, Beijing, 100191, China.
Peng WangPhysical Examination Center, Peking University Third Hospital, Beijing, 100191, China.
Wei ZhaoNHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Key Laboratory of Molecular Cardiovascular Science, Beijing Key Laboratory of Cardiovascular Receptors Research, Department of Cardiology, Institute of Vascular Medicine, Ministry of Education, Peking University Third Hospital, 100191, Beijing, China. beate_vv@bjmu.edu.cn.
Wei GaoNHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Key Laboratory of Molecular Cardiovascular Science, Beijing Key Laboratory of Cardiovascular Receptors Research, Department of Cardiology, Institute of Vascular Medicine, Ministry of Education, Peking University Third Hospital, 100191, Beijing, China. weigao@bjmu.edu.cn.
Peking University · CNPeking University Third Hospital · CNMinistry of Education · RO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe triglyceride-glucose (TyG) index has been recognized as being an alternative cardiometabolic biomarker for insulin resistance associated with the development and prognosis of cardiovascular disease (CVD). However, the prospective relationship between baseline and long-term trajectories of the TyG index and carotid atherosclerosis (CAS) progression has yet to be investigated.

methodsThis longitudinal prospective cohort study included 10,380 adults with multiple general health checks at Peking University Third Hospital from January 2011 to December 2020. The TyG index was calculated as ln (fasting triglyceride [mg/dL] × fasting glucose [mg/dL]/2). The latent class trajectory modeling method was used to analyze the TyG index trajectories over the follow-up. Based on univariate and multivariate Cox proportional hazards analyses, hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated for the baseline and trajectory of the TyG index.

resultsDuring a median follow-up period of 757 days, 1813 participants developed CAS progression. Each 1-standard deviation (SD) increase in the TyG index was associated with a 7% higher risk of CAS progression after adjusting for traditional CVD risk factors (HR = 1.067, 95% CI 1.006-1.132). Similar results were observed when the TyG index was expressed as quartiles. According to different trajectory patterns, participants were categorized into low-stable, moderate-stable, and high-increasing groups. After multivariate adjustment, the moderate-stable group had a 1.139-fold (95% CI 1.021-1.272) risk of CAS progression. The high-increasing trajectory of the TyG index tended to be associated with CAS progression (HR = 1.206, 95% CI 0.961-1.513).

conclusionsParticipants with higher baseline and moderate-stable trajectory of the TyG index were associated with CAS progression. Long-term trajectories of the TyG index can help to identify individuals at a higher risk of CAS progression who deserve specific preventive and therapeutic approaches.

Indexed as

Cardiovascular DiseasesCarotid Artery DiseasesAdultBiomarkersBlood GlucoseGlucoseHumansProspective StudiesRisk AssessmentRisk FactorsTriglyceridesBiomarkersBlood GlucoseGlucoseTriglyceridesCarotid atherosclerosisInsulin resistanceLongitudinal studyProgressionTriglyceride-glucose index

Identifiers

PMID37254140
PMCPMC10230761
OpenAlexW4378783388

What OpenQuestion holds

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LicenceCC BY
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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.