Evidence map›Paper›PMID 38313836›Full record

ArticleFrontiers in endocrinology2023

Association between triglyceride glucose index and adverse clinical outcomes in patients with acute myocardial infarction and LDL-C≤1.8 mmol/L who underwent percutaneous coronary intervention: a prospective cohort study.

Hong-Wei Zhao, Yong Wang, Cheng-Fu Wang, Qing-Kun Meng

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Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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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

4 authors.

Hong-Wei ZhaoDepartment of Cardiology, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Yong WangDepartment of Cardiology, Shenzhen Luohu Hospital Group Luohu People's Hospital (The Third Affiliated Hospital of Shenzhen University), Shenzhen, China.
Cheng-Fu WangDepartment of Cardiology, The People's Hospital of Liaoning Province, Shenyang, China.
Qing-Kun MengDepartment of Cardiology, The People's Hospital of Liaoning Province, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Recently, the triglyceride glucose (TyG) index has emerged as a reliable predictive indicator for adverse outcomes of cardiovascular disease. However, the roles of the TyG index in patients with acute myocardial infarction (AMI) and low-density lipoprotein cholesterol (LDL-C)≤1.8 mmol/L after percutaneous coronary intervention (PCI) remain unclear. Methods: A total of 599 patients diagnosed with AMI and LDL-C ≤ 1.8 mmol/L at the 1-month follow-up after PCI were consecutively enrolled between January 2017 and January 2020. The patients were subsequently divided into three groups based on tertiles of the TyG index. The parameters, including the TyG index, were compared to explore the risk factors associated with major adverse cardiovascular and cerebrovascular events (MACCEs) during the 1-year follow-up. Results: Sixty-nine patients (11.5%) with 90 MACCEs were recorded during the 1-year follow up, including 13 patients (8.6%) in the Tertile 1 group, 36 (12.0%) in the Tertile 2 group, and 20 (13.4%) in the Tertile 3 group. Patients with a higher TyG index had a significantly increased incidence of MACCEs compared to those with a lower TyG index (22.1% vs. 14.0% vs. 9.9%, p=0.010). Kaplan-Meier analysis demonstrated that patients with a higher TyG index had a significantly lower probability of survival without MACCEs. Furthermore, a binary logistic regression model indicated that the TyG index was the only independent predictor for MACCEs in these patients. Conclusion: A higher TyG index was associated with a higher incidence of MACCEs in patients with AMI and well-controlled LDL-C levels after PCI. This suggests that the TyG index can serve as a predictive indicator for adverse cardiovascular outcomes in these patients.

Indexed as

Cholesterol, LDLMyocardial InfarctionPercutaneous Coronary InterventionBiomarkersBlood GlucoseGlucoseHumansProspective StudiesTriglyceridesBiomarkersBlood GlucoseCholesterol, LDLGlucoseTriglyceridesacute myocardial infarctionlow density lipoproteinmajor adverse cardiac and cerebrovascular eventPCItriglyceride glucose index

Identifiers

PMID38313836
PMCPMC10835789

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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 OpenQuestion graph.