Evidence map›Paper›PMID 39474338›Full record

ArticleHealth science reports2024

Vital Predictive and Prognostic Roles of Triglyceride-Glucose Index in Women With Acute Myocardial Infarction: A Retrospective Cohort Study.

Xiao-Xia Qiu, Yong-Li Chen, Xin-Kang Wang, Re-Hua Wang

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In one paragraph

Article in Health science reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 2 pooled it
–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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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

3 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

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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.

Xiao-Xia QiuDepartment of Cardiology Shengli Clinical Medical College of Fujian Medical University Fuzhou China.
Yong-Li ChenSouth Branch of Cardiology Department Fujian Provincial Hospital Fuzhou China.ORCID 0009-0006-4690-7531
Xin-Kang WangFuzhou University Affiliated Provincial Hospital Fuzhou China.
Re-Hua WangFuzhou University Affiliated Provincial Hospital Fuzhou China.ORCID 0000-0002-2988-1433

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: As a biomarker of insulin resistance (IR) in patients with acute myocardial infarction (AMI), the triglyceride-glucose index (TyG index) has received significant attention. However, most research on AMI has focused on male patients, as it is traditionally believed to primarily affect males. Therefore, this study was conducted on a female population with AMI to investigate the potential correlation between the TyG index and their outcomes. Methods: A total of 320 women who were admitted to Fujian Provincial Hospital for AMI between January 2017 and December 2019 were included in this study. The TyG index was calculated using the following formula: ln [fasting triglycerides (TG) (mg/dL) × fasting plasma glucose (FPG) (mg/dL)/2]. The primary endpoint of the study was the occurrence of major adverse cardiovascular and cerebrovascular events (MACCEs), which included all-cause mortality, myocardial infarction, repeat revascularization, rehospitalization for heart failure and stroke. The association between the TyG index and unfavorable outcomes in female patients was investigated using the Cox proportional hazards regression model. Results: It was ultimately estimated that 111 patients developed MACCEs. Females with high TyG indices had a higher prevalence of diabetes, elevated heart rates, and hemoglobin A1c, as well as a higher likelihood of undergoing thrombus aspiration and stent placement. The TyG index was found to be positively correlated with the prevalence of hypertension, diabetes, low-density lipoprotein cholesterol, hemoglobin A1c, and damaged vessels. However, this correlation was modest, yet statistically significant. Furthermore, after adjusting for conventional risk factors, the TyG index (HR: 4.292, 95% CI: 2.784-6.616, Conclusion: As an independent risk predictor, the TyG index has the potential to enhance clinical outcomes for women with AMI.

Indexed as

acute myocardial infarction (AMI)femaleinsulin resistance (IR)major adverse cardiac and cerebral events (MACCEs)triglyceride‐glucose index (TyG index)

Identifiers

PMID39474338
PMCPMC11513407

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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.