Association between the triglyceride-glucose index and carotid plaque incidence: a longitudinal study

Zhang, Yichi; Wu, Zhuchao; Li, Xiaona; Wei, Jingkai; Zhang, Qun; Wang, Jianming

doi:10.1186/s12933-022-01683-6

Cited by 17 publications

(16 citation statements)

References 47 publications

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“…Previous studies have found strongly correlation between TyG index, TyG-BMI index and TG/HDL-C ratio and mortality in different populations. In a recent large cross-sectional study, TyG-BMI was found to be associated with CVD mortality among participants from the National Health and Nutrition Examination Survey (NHANES), and ROC analysis showed that the TyG index had better predictive ability for CVD mortality than the TyG-BMI index [21]. Similarly, in a large prospective cohort study, Lopez-Jaramillo et al reveled the positive correlation between higher TyG index and cardiovascular mortality [22].…”

Section: Discussionmentioning

confidence: 95%

Association between different insulin resistance surrogates and all-cause mortality in peritoneal dialysis patients

Zhao,

Shang,

Tian

et al. 2024

Preprint

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Background: The insulin resistance (IR) is related with poor outcomes in peritoneal dialysis (PD) patients. This study aimed to explore the association between surrogate IR indexes and all-cause mortality in PD patients. Methods: 1736 PD patients were enrolled from March 2010 to December 2021 in multiple PD centers. Cox proportional hazards models and restricted cubic splines (RCS) regression were constructed to assess the relationship between TyG index, TyG-BMI index, TG/HDL-C ratio and all-cause mortality. All three IR indexes were integrated into same model to access the predictive stability. Furthermore, forest plot was draw to display the result of subgroup analysis in PD patients. Results: 378 mortality events were recorded during a median follow-up time of 2098 days. The RCS regression showed a linear association between the TyG index and TyG-BMI index and all-cause mortality (P for non-linearity 0.566, 0.716 respectively), while a non-linear association between TG/HDL-C ratio and all-cause mortality (P for non-linearity 0.022). Multivariable Cox proportional hazards analyses indicated higher levels of TyG index, TyG-BMI index and TG/HDL-C ratio were independent risk factors for all-cause mortality in PD patients (HR 1.587, 95%CI 1.264-1.993; HR 1.449, 95%CI 1.085-1.934; HR 1.424, 95%CI 1.104-1.838, respectively). By integrating three IR indexes into the same model, the TyG index showed the highest predictive stability among them. Forest plot of TyG index showed there were no significant interactions in the subgroups. Conclusion: The TyG index, TyG-BMI index, and TG/HDL-C ratio were significantly associated with all-cause mortality in PD patients, and the TyG index may be the most stable surrogate marker for IR in PD patients among them, and IR was associated with all-cause mortality in PD patients.

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Section: Discussionmentioning

confidence: 95%

Association between different insulin resistance surrogates and all-cause mortality in peritoneal dialysis patients

Zhao,

Shang,

Tian

et al. 2024

Preprint

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“…Additionally, the final multivariate logistic regression equation excluded BG and TG as the confounding variables as they consist of the TyG Index. Whether the confounding variables were adjusted was determined by the following principle: Based on its association with the outcomes of interest, clinical significance, reports in the literature and changed the matched OR by at least 10%16 17 19(online supplemental table 1).…”

Section: Methodsmentioning

confidence: 99%

“…A study of urban workers in China reported that a higher TyG Index increased the risk of carotid plaque 16. Three studies have also reported a positive association between the TyG Index and carotid plaque based on prospective cohort designs in China 17–19. By contrast, another community-based observational research in a Chinese non-diabetic population observed the significantly positive relationship of TyG Index with carotid plaque instability, but did not find a statistically significant relationship between the TyG Index level and stable carotid plaque 20.…”

Section: Introductionmentioning

confidence: 98%

“…Furthermore, IR is involved in the pathological processes of atherogenesis and advanced plaque formation 15. However, the relationship between TyG Index and carotid plaque has only been considered in a few studies with inconsistent results, and the studies are limited to China 10 16–20. A study of urban workers in China reported that a higher TyG Index increased the risk of carotid plaque 16.…”

Section: Introductionmentioning

confidence: 99%

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Association between Triglyceride-Glucose Index and carotid plaque in Japanese population: a cross-sectional study

2023

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ObjectivePrevious studies linking Triglyceride Glucose (TyG) Index to carotid plaque have yielded inconsistent results. Moreover, related studies on the population of Japan are rare. This study aims to provide further results.DesignA hospital-based cross-sectional study.SettingThe Shin Takeo Hospital.ParticipantsWe assessed 1904 Japanese participants (988 men and 916 women) whose mean age was 57±11.9 years, and those participants underwent health check-ups at Shinbuf Hospital at Shin Takeo Hospital from 1 April 2016 to 31 October 2017.MethodologyCarotid plaque, triglyceride and fasting glucose and other relevant indicators were collected. We used ultrasonography to evaluate carotid plaque. A multivariable logistic regression model and generalised additive model were used to evaluate the association between the TyG Index and carotid plaque. Subgroup and interaction analyses were validated for the consistency of these correlations.ResultsFollowing the adjustment of traditional carotid plaque risk factors, the non-linear relationship between the TyG Index and carotid plaque was investigated. Using a two-piecewise regression model, we calculated the inflection point to be 9.06. The OR and 95% CIs for the inflection points on the left and right sides were 1.70 (1.27 to 2.29) and 0.88 (0.52 to 1.47), respectively. According to the variables tested, the interactions between the TyG Index and all subgroup factors were analysed and significant interactions were not observed.ConclusionIn individuals who underwent a comprehensive check-up in Japan, the relationship between the TyG Index and carotid plaque is non-linear. When the TyG Index is less than 9.06, it is associated with carotid plaque.

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“…The ratio of triglycerides to high-density lipoprotein cholesterol (TG/HDL-C), triglyceride-glucose index (TyG index), TyGindex with body mass index (TyG-BMI), TyG index with waist circumference (TyG-WC), and metabolic score for insulin resistance (METS-IR), are the most common of these less complicated and practical markers [19,20]. Although prior studies have shown associations between these indices and CAD, there is no speci c threshold for utilizing these indices, and it remains uncertain which one of them better predicts CAD [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Which Surrogate Insulin Resistance Indices Best Predict Coronary artery disease? a machine learning approach

Mirjalili,

Soltani,

Meybodi

et al. 2024

Preprint

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Background Various surrogate markers of insulin resistance have been developed, capable of predicting coronary artery disease (CAD) without the need to detect serum insulin. For accurate prediction, they depend only on glucose and lipid profiles, as well as anthropometric features. However, there is still no agreement on the most suitable one for predicting CAD. Methods We followed a cohort of 2,000 individuals, ranging in age from 20 to 74, for a duration of 9.9 years. We utilized multivariate Cox proportional hazard models to investigate the association between TyG-index, TyG-BMI, TyG-WC, TG/HDL, plus METS-IR and the occurrence of CAD. The receiver operating curve (ROC) was employed to compare the predictive efficacy of these indices and their corresponding cutoff values for predicting CAD. We also used three distinct embedded feature selection methods: LASSO, Random Forest feature selection, and the Boruta algorithm, to evaluate and compare surrogate markers of insulin resistance in predicting CAD. In addition, we utilized the ceteris paribus profile on the Random Forest model to illustrate how the model's predictive performance is affected by variations in individual surrogate markers, while keeping all other factors consistent in a diagram. Results The TyG-index was the only surrogate marker of insulin resistance that demonstrated an association with CAD in fully adjusted model (HR: 2.54, CI: 1.34–4.81). The association was more prominent in females. Moreover, it demonstrated the highest area under the ROC curve (0.67 [0.63–0.7]) in comparison to other surrogate indices for insulin resistance. All feature selection approaches concur that the TyG-index is the most reliable surrogate insulin resistance marker for predicting CAD. Based on the Ceteris paribus profile of Random Forest the predictive ability of the TyG-index increased steadily after 9 with a positive slope, without any decline or leveling off. Conclusion Due to the simplicity of assessing the TyG-index with routine biochemical assays and given that the TyG-index was the most effective surrogate insulin resistance index for predicting CAD based on our results, it seems suitable for inclusion in future CAD prevention strategies.

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Association between the triglyceride-glucose index and carotid plaque incidence: a longitudinal study

Cited by 17 publications

References 47 publications

Association between different insulin resistance surrogates and all-cause mortality in peritoneal dialysis patients

Association between different insulin resistance surrogates and all-cause mortality in peritoneal dialysis patients

Association between Triglyceride-Glucose Index and carotid plaque in Japanese population: a cross-sectional study

Which Surrogate Insulin Resistance Indices Best Predict Coronary artery disease? a machine learning approach

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