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Record W4412935789 · doi:10.1186/s12933-025-02890-7

Does diabetes status modify the association between the triglyceride-glucose index and major adverse cardiovascular events in patients with coronary heart disease? A systematic review and meta-analysis of longitudinal cohort studies

2025· review· en· W4412935789 on OpenAlexaboutno aff
Shicong Xu, Zhi‐Hui Zhang, Jing Li, Yiyan Ding, Yuanguo Chen, Yunxia Zhou, Siqi Hu

Bibliographic record

VenueCardiovascular Diabetology · 2025
Typereview
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineDiabetes mellitusAngiologyMeta-analysisDiseaseCohort studyCardiologyEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: The triglyceride-glucose (TyG) index, a surrogate marker for insulin resistance, has been shown to be closely associated with cardiovascular risk. However, it remains unclear whether diabetes status affects the association between the TyG index and the risk of major adverse cardiovascular events (MACEs) in patients with coronary heart disease (CHD). The aim of this study is to systematically evaluate the relationship between the TyG index and MACEs among CHD patients with different diabetes statuses. METHODS: We systematically searched PubMed, the Cochrane Library, Web of Science, and Embase from inception to March 13, 2025, for cohort studies examining the association between TyG and MACEs in patients with CHD with different diabetes statuses. The outcomes included all-cause mortality, nonfatal myocardial infarction, nonfatal stroke, and revascularization. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were extracted for the TyG index as both categorical and continuous variables. Study quality was assessed using the Newcastle-Ottawa Scale (NOS). All the statistical analyses were performed using Stata (version 17.0) and R (version 4.4.1). Depending on heterogeneity, either a fixed-effect or random-effects model was used to pool the data. Subgroup analysis and meta-regression are used to explore the sources of heterogeneity. This study was registered in PROSPERO (CRD: 420251018545). RESULTS: A total of 36 longitudinal cohort studies comprising 173,851 participants (119,232 with diabetes and 54,619 without diabetes) were included, with 9159 MACEs reported during the follow-up period. In diabetic patients, a higher TyG index significantly increased the risk of MACEs (categorical HR = 1.98, 95% CI 1.61-2.43; continuous HR = 1.57, 95% CI 1.38-1.78), all-cause mortality (HR = 1.74, 95% CI 1.45-2.08), nonfatal myocardial infarction (HR = 2.05, 95% CI 1.52-2.77), nonfatal stroke (HR = 1.73, 95% CI 1.12-2.66), and revascularization (HR = 2.52, 95% CI 1.26-5.04). In nondiabetic patients, a higher TyG index also significantly increased the risk of MACEs (categorical HR = 1.65, 95% CI 1.33-2.05; continuous HR = 1.74, 95% CI 1.46-2.06), all-cause mortality (HR = 1.50, 95% CI 1.18-1.90), nonfatal myocardial infarction (HR = 2.46, 95% CI 1.11-5.47), and revascularization (HR = 2.09, 95% CI 1.57-2.76). However, no association was observed between the TyG index and nonfatal stroke (HR = 1.66, 95% CI 0.88-3.12) in nondiabetic patients. CONCLUSION: Higher TyG index values appear to be associated with an increased risk of adverse cardiovascular events, all-cause mortality, nonfatal myocardial infarction, and revascularization in both diabetic and nondiabetic patients with CHD. However, no significant association was found between the TyG index and the risk of nonfatal stroke in nondiabetic patients. These findings suggest that the TyG index may offer potential prognostic value in CHD, but further high-quality prospective studies are warranted to confirm these associations and clarify their clinical implications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMeta-epidemiology (broad)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.237
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0290.016
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.280
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2025
Admission routes1
Has abstractyes

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