Evidence mapPaperPMID 40186173Full record

ArticleLipids in health and disease2025

Associations of the triglyceride-glucose index with short-term mortality in patients with cardiogenic shock: a cohort study.

Degang Mo, Peng Zhang, Mengmeng Wang, Jun Guan, Hongyan Dai

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Article in Lipids in health and disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Degang MoSchool of Medicine, Qingdao University, Qingdao, 266000, China.
Peng ZhangSchool of Medicine, Qingdao University, Qingdao, 266000, China.
Mengmeng WangSchool of Medicine, Qingdao University, Qingdao, 266000, China.
Jun GuanDepartment of Cardiology, Qingdao Municipal Hospital, No.5 Donghai Middle Road, Qingdao, 266071, China. guanjunqd@163.com.
Hongyan DaiDepartment of Cardiology, Qingdao Municipal Hospital, No.5 Donghai Middle Road, Qingdao, 266071, China. drdaihy@163.com.

Funding

Shandong Provincial Natural Science Foundation ZR2024MH214
6 · The paper itself

Abstract

backgroundCardiogenic shock (CS) is a severe cardiac disorder with a high mortality rate. The triglyceride-glucose (TyG) index, a biomarker of insulin resistance, is associated with cardiovascular disease-related mortality. This study aimed to investigate the association between the TyG index and mortality in patients with CS.

methodsThis retrospective cohort study analyzed 727 patients with CS from the Medical Information Mart for Intensive Care IV database. The TyG index was calculated as follows: ln[triglycerides (mg/dL) × fasting blood glucose (mg/dL)/2]. Outcomes included 28-day intensive care unit (ICU) mortality and 28-day in-hospital mortality. Kaplan-Meier survival curve models and Cox proportional hazards regression models were used to evaluate the prognostic significance of the TyG index. Receiver Operating Characteristic (ROC) curve analysis was used to determine the predictive efficacy of the TyG index for mortality. Subgroup analyses were conducted to determine the association between the TyG index and mortality across different groups.

resultsNon-survivors had a significantly higher TyG index (ICU: 9.30 vs. 9.13, p = 0.008; in-hospital: 9.29 vs. 9.13, p = 0.004). Adjusted Cox models showed that each 1-unit increase in the TyG index increased ICU mortality risk by 24% (hazard ratio [HR] = 1.24, 95% confidence interval [CI]:1.04-1.48; p = 0.015) and in-hospital mortality by 44% (HR = 1.44, 95% CI:1.11-1.88; p = 0.007). The Quartile 4 TyG index ICU mortality was increased by 77% (HR = 1.77, 95% CI:1.09-2.89) compared to that for Quartile 1 and in-hospital mortality was increased by 61% (HR = 1.61, 95% CI:1.08-2.38). The area under the ROC curve (AUROC) showed a modest standalone predictive ability of 0.56, but when combined with clinical variables, the AUROC improved to 0.80 (ICU) and 0.78 (in-hospital). Subgroup analyses identified stronger associations in patients ≥ 60 years, females, non-septic, and those with acute myocardial infarction or heart failure.

conclusionsThe TyG index is significantly associated with short-term mortality in patients with CS and may serve as a useful biomarker for risk stratification.

trial registrationNot applicable.

Indexed as

Blood GlucoseShock, CardiogenicTriglyceridesAgedBiomarkersFemaleHospital MortalityHumansIntensive Care UnitsKaplan-Meier EstimateMaleMiddle AgedPrognosisProportional Hazards ModelsRetrospective StudiesROC CurveBiomarkersBlood GlucoseTriglyceridesCardiogenic ShockShort-term MortalityTriglyceride-Glucose Index

Identifiers

PMID40186173
PMCPMC11969958

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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.