Journal of Clinical Medicine Research, ISSN 1918-3003 print, 1918-3011 online, Open Access
Article copyright, the authors; Journal compilation copyright, J Clin Med Res and Elmer Press Inc
Journal website https://jocmr.elmerjournals.com

Original Article

Volume 18, Number 6, June 2026, pages 407-419


The Association Between Triglyceride-Glucose Index and Mortality Risk in Cardiovascular Disease Patients: A Meta-Analysis

Figures

↓  Figure 1. Flowchart. CVD: cardiovascular disease.
Figure 1.
↓  Figure 2. (a) All-cause mortality (high vs. low). (b) CVD mortality (high vs. low). HR: hazard ratio; CI: confidence interval.
Figure 2.
↓  Figure 3. (a) All-cause-dose-response. (b) CVD- dose-response. CVD: cardiovascular disease; TyG: triglyceride-glucose.
Figure 3.
↓  Figure 4. All cause-China. TyG: triglyceride-glucose.
Figure 4.

Tables

↓  Table 1. Characteristics With Regard to the Seventeen Included Studies
 
StudyCountryDesignPatientsAcute, %Cut-off for TyGN, M/FAge, yearsBMI, kg/m2T2DM, %Follow-up, years
aData are expressed as median (interquartile range). ACS: acute coronary syndrome; AHF: acute heart failure; AMI: acute myocardial infarction; BMI: body mass index; CHD: coronary heart disease; CHF: chronic heart failure; HF: heart failure; iHF: ischemic heart failure; M/F: male/female; NR: not reported; NSTE-ACS: non-ST-segment elevation acute coronary syndrome; PCS: prospective cohort study; RCS: retrospective cohort study; ROC: receiver operating characteristic; T2DM: type 2 diabetes mellitus; TyG: triglyceride-glucose index.
Guo et al, 2021 [19]ChinaRCSCHF0Tertiles546, 362/18465.18 (12.01)21.07 (1.83)1001, median
Hao et al, 2024 [13]ChinaPCSCHD74.6Quintile3,321, 2,404/91761.7 ± 11.725.6 ± 3.532.49.79, median
Hao et al, 2023 [14]ChinaRCSAMI100Tertiles1,144, 902/24262.1 ± 12.824.8 ± 3.318.91
Huang et al, 2022 [20]ChinaRCSAHF100Tertiles932, 579/35370 (61, 80)a24.2 (21.6, 27.1)a32.81.31
Jiao et al, 2022 [21]ChinaPCSACS100Tertiles662, 476/18681.87 ± 2.1424.57 ± 3.4034.9≤ 10
Mao et al, 2019 [8]ChinaRCSNSTE-ACS100Median438, 295/14362.5 (53.0, 68.0)a24 33 ± 3 1732.61
Ozcan et al, 2023 [22]TurkeyRCSHFNRTertiles773, 633/14063 (53, 72)aNR35.63.17
Shen et al, 2023 [23]ChinaPCSACS100Tertiles231, 156/7581.58 ± 1.9324.78 ± 3.421004.08
Sun et al, 2023 [24]ChinaRCSiHF0Quartiles2,055, 1,690/36560.3 ± 11.025.9 ± 3.238.53
Wang et al, 2020 [25]ChinaRCSACS100Tertiles2,531, 1,415/1,11666.3 ± 6.825.9 ± 2.71003
Xie et al, 2023 [26]ChinaRCSCHD59.2Tertiles1,061, 789/27261.8 ± 10.5NR52.71.83
Zhang et al, 2021 [9]ChinaRCSAMI100Tertiles1,932, 1,324/60865.4 ± 12.025.8 ± 3.51002.23
Zhang et al, 2022 [27]ChinaRCSACS100Median1,010, 735/27565.8 ± 10.125.6 ± 3.402.97
Zhao et al, 2020 [28]ChinaRCSNSTE-ACS100ROC798, 545/25360.9 ± 8.326.7 ± 3.21003
Zhao, et al, 2021 [10]ChinaRCSNSTE-ACS100Median1,510, 1,113/39759.7 ± 9.325.8 ± 3.104
Zhou et al, 2023 [11]ChinaRCSAHF100Tertiles823, 396/42773.0 ± 12.725.5 ± 4.7423.16
Zhou et al, 2023 [29]ChinaRCSCHF0Tertiles6,697, 4,579/2,11863.3 ± 14.225.2 (22.8, 27.8)a44.63.9

 

↓  Table 2. Quality Assessment of the Cohort Studies With Newcastle-Ottawa Quality Assessment Scale
 
StudyRepresentativeness of the exposed cohortSelection of the unexposed cohortAscertainment of exposureOutcome of interest not present at start of studyControl for important factor or additional factorOutcome assessmentFollow-up long enough for outcomes to occurAdequacy of follow-up of cohortsTotal quality scores
Quality assessment was performed using the Newcastle-Ottawa Quality Assessment Scale (NOS) for cohort studies. One star (☆) indicates that one star was awarded for meeting the quality criteria for the specific item. Two stars (☆☆) indicate two stars were awarded (typically for adequate control of both the primary and additional confounding factors). Em dash (—) indicates that the study did not meet the criterion for that item and received no star.
Guo et al, 2021 [19]5
Hao et al, 2024 [13]☆☆8
Hao et al, 2023 [14]☆☆8
Huang et al, 2022 [20]☆☆7
Jiao et al, 2022 [21]☆☆8
Mao et al, 2019 [8]☆☆7
Ozcan et al, 2023 [22]☆☆7
Shen et al, 2023 [23]☆☆8
Sun et al, 2023 [24]☆☆7
Wang et al, 2020 [25]☆☆7
Xie et al, 2023 [26]☆☆7
Zhang et al, 2021 [9]☆☆7
Zhang et al, 2022 [27]☆☆7
Zhao et al, 2020 [28]☆☆7
Zhao et al, 2021 [10]☆☆7
Zhou et al, 2023 [11]☆☆7
Zhou et al, 2023 [29]☆☆7

 

↓  Table 3. Subgroup Analysis
 
Effect sizeCoefficientStandard errortP>|t|a95% confidence interval
aThe two-tailed P value evaluating the statistical significance of each covariate. TyG: triglyceride-glucose; ACS: Acute coronary syndrome.
Country0.68619840.3815151.800.110−0.1935768 to 1.565974
With ACS0.03495450.08918320.390.705−0.1707022 to 0.2406113
Cut-off for TyG–0.01654320.1436475−0.120.911−0.3477949 to 0.3147084
With diabetes–0.46693220.3607914−1.290.232−1.298919 to 0.3650543
Follow-up–0.129240.1357905−0.950.369−0.4423735 to 0.1838936
Intercept0.29283920.52619560.560.593−0.9205701 to 1.506248

 

↓  Table 4. Outcomes of the Stratified Analysis
 
OutcomesNumber of studiesHR (95%CI)PAHeterogeneity test
PI2 (%)
PA: P for association; it represents the statistical significance P value for the pooled effect size (HR) to test whether the HR is significantly different from 1. CVD: cardiovascular disease; T2DM: type 2 diabetes mellitus; HR: hazard ratio; CI: confidence interval.
All-cause mortality141.43 (1.27, 1.62)< 0.0010.15028.5
Type of CVD
  Acute91.38 (1.13, 1.68)0.0010.21725.5
  Chronic21.62 (1.28, 2.05)< 0.0010.6990.0
With T2DM
  Yes51.50 (1.10, 2.05)0.0110.12045.4
  No41.76 (0.53, 5.86)0.358< 0.00190.9
CVD mortality71.62 (1.33, 1.97)< 0.0010.24922.7
Type of CVD
  Acute51.47 (1.09, 1.99)0.0120.32314.3
  Chronic22.21 (1.03, 4.73)0.0420.07368.9

 

↓  Table 5. Outcomes With Regard to the Sensitivity Analysis and the Test of Publication Bias
 
OutcomesNumber of studiesSensitivity analysisEgger’ s test
HR (95% CI)RobustP value
CVD: cardiovascular disease; HR: hazard ratio; CI: confidence interval.
All-cause mortality141.38 (1.23, 1.54) to 1.47 (1.29, 1.69)Yes0.619
CVD mortality81.55 (1.32, 1.82) to 1.70 (1.38, 2.10)Yes0.549