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Association of triglyceride-glucose index with the risk of incident aortic dissection and aneurysm: a large-scale prospective cohort study in UK Biobank

Cardiovascular Diabetology volume 23, Article number: 282 (2024) Cite this article

Abstract

Background

Triglyceride-glucose (TyG) index is an emerging surrogate indicator of insulin resistance, which has been demonstrated as a risk factor for various cardiovascular diseases including coronary syndrome, in-stent restenosis, and heart failure. However, association of TyG index with incident aortic dissection (AD) and aortic aneurysm (AA) remains to be investigated.

Methods

This study included 420,292 participants without baseline AD/AA from the large-scale prospective UK Biobank cohort. The primary outcome was incident AD/AA, comprising AD and AA. Multivariable-adjusted Cox proportional hazards regression models and restricted cubic spline (RCS) analyses were applied to assess the relationship between TyG index and the onset of AD/AA. In addition, the association between TyG index and incident AD/AA was examined within subgroups defined by age, gender, smoking status, drinking status, diabetes, hypertension, and BMI.

Results

Over a median follow-up period of 14.8 (14.1, 15.5) years, 3,481 AD/AA cases occurred. The incidence of AD/AA rose along with elevated TyG index. RCS curves showed a linear trend of TyG index with risk of incident AD/AA. TyG index was positively associated with risk of incident AD/AA after adjusting for age, gender, smoking status, drinking status, BMI, hypertension, LDL-c, and HbA1c, with adjusted HRs of 1.0 (reference), 1.20 (95% CI 1.08–1.35), 1.21 (95% CI 1.08–1.35), and 1.30 (95% CI 1.16–1.45) for TyG index quartiles 2, 3, and 4, respectively. Especially, participants in the highest TyG index quartile had highest risk of developing AA, with an adjusted HR of 1.35 (95% CI 1.20–1.52).

Conclusions

TyG index is independently associated with a higher risk of incident AD/AA, indicating the importance of using TyG index for risk assessment of AD/AA, especially for AA.

Introduction

Aortic dissection (AD) and aortic aneurysm (AA) are life-threatening cardiovascular conditions. AD involves the tearing and detachment of the intima and media layers of the aortic wall [1], often triggered by hypertension [2], Marfan syndrome [3], atherosclerosis [4], and other contributing factors. The incidence of AD is estimated to be 3 to 4 cases per 100,000 person-years [5], with a mortality rate that can reach as high as 50% without intervention. In contrast, AA refers to the localized or widespread dilation of the aortic wall [6], with abdominal and thoracic AA being the most prevalent forms [7]. These two conditions are strongly linked to aging, smoking, hypertension, hypercholesterolemia, and other factors [6]. The incidence of abdominal AA in men from 65 to 75 years of age is approximately 1.9% [8], while thoracic AA occurs at a rate of 5–10 per 100,000 person-years in the general population [9]. Aortic rupture is a serious complication progressed by AA, with a mortality rate exceeding 80% globally [7]. Therefore, thoroughly analyzing the influencing factors of AD and AA is of importance for clinicians to devise more targeted treatment plans and effective preventive measures.

The triglyceride-glucose (TyG) index is a new risk assessment tool for metabolic syndrome, first proposed by Simental-Mendía et al. in 2008 through a cross-sectional study involving 748 healthy participants [10]. TyG index, a composite indicator combining triglyceride (TG) and fasting blood glucose (FBG), is calculated as follows: TyG index = ln[TG (mg/dL) × FBG (mg/dL) ÷ 2] [11]. It provides a comprehensive, simple, cost-effective and repeatable alternative for assessing insulin resistance. Multiple studies have shown that TyG index is a significant marker for identifying those at risk of developing diabetes [12], obesity [13], stroke [14], and cardiovascular diseases, including coronary artery disease [15], in-stent restenosis [16], and heart failure [17]. By monitoring changes in TyG index, doctors can adjust patient lifestyles and treatment plans in time, thereby effectively preventing and controlling the occurrence of disease. However, it is unknown whether TyG index predisposes the general population to AD/AA. Therefore, we analyzed data from the large-scale prospective cohort in the UK Biobank to explore the association of TyG index with AD/AA onset.

Methods

Design and participants

The UK Biobank was designed as a large-scale prospective cohort study [18]. A total of 502,357 volunteers, from 37 to 73 years of age across the United Kingdom, had their health-related data from 2006 to 2010 collected by a touchscreen questionnaire that covered information ranging from demographics, socio-economics, and lifestyles, to health. The latest follow-up was conducted on the 30 November 2023. The North West Multi-Center Research Ethics Committee had approved the UK Biobank cohort study (No. 11/NW/03820), from which data can be accessed via http://www.ukbiobank.ac.uk/register-apply.

In the present study, among 502,357 participants who took part in the initial assessment visit from 2006 to 2010, those with AD/AA (n = 585) and connective tissue disease (n = 8,329) at baseline, as well as those with missing data on TG (n = 33,233) and FBG (n = 39,918) were excluded. A total of 420,292 eligible participants were included in the final analysis. A flowchart of the participants in this study is presented in Fig. 1.

Fig. 1
figure 1

Flowchart of the study participants

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Measures

TyG index was calculated as ln[TG (mg/dL) × FBG (mg/dL) ÷ 2] [11]. Socio-demographic information (age and gender), lifestyles (smoking status and drinking status), medical histories (doctor-diagnosed diabetes and hypertension), and use of medications (lipid-lowering drugs, anti-hypertension drugs, and insulin), were extracted from existing datasets of the UK Biobank. Additionally, anthropometric measurements (height and weight), systolic blood pressure (SBP), diastolic blood pressure (DBP), and laboratory assays [glycosylated hemoglobin (HbA1c), FBG, TG, total cholesterol (TC), high density lipoprotein cholesterol (HDL-c), and low density lipoprotein cholesterol (LDL-c)], were included in the data extraction. Body mass index (BMI), calculated as weight (kg) divided by height squared (m2)] [19], was categorized into underweight (BMI < 18.5 kg/m2), normal weight (18.5 kg/m2 ≤ BMI < 25.0 kg/m2), overweight (25.0 kg/m2 ≤ BMI < 30.0 kg/m2) and obesity (BMI ≥ 30.0 kg/m2). Smoking status was categorized as never smoker, previous smoker, and current smoker. Drinking status was divided into never drinking, previous drinking, and current drinking.

Outcomes

The primary endpoint of the present study was incident AD/AA (International Classification of Diseases, 10th revision [ICD-10] I71), a composite outcome of AD (ICD-10 I71.0) and AA (ICD-10 I71.1–I71.9). The secondary outcomes were AD and AA, which were further analyzed separately. Sources of reported AD/AA cases encompassed death registers, primary care records, hospital admission data, and self-reported diagnoses. The onset date for both conditions was designated as the date of first reported AD/AA. The follow-up period terminated either at the onset of AD/AA or upon censoring.

Statistical analysis

The missing values for potential covariates were less than 10%. Thus, categorial covariates, such as smoking status, drinking status, histories of diabetes and hypertension, lipid-lowering drugs, anti-hypertension drugs, and insulin were imputed by the mode. Continuous data, including HbA1c, BMI, SBP, DBP, TC, HDL-c, and LDL-c, were imputed by the mean.

Participants were stratified into four groups based on the quartiles of their baseline TyG index. The Kolmogorov-Smirnov test was used to check if the quantitative data displayed a normal distribution. Quantitative data following a skewed distribution (age, SBP, DBP, FBG, and TG) were presented as median and interquartile range [P25, P75], and the Kruskal-Wallis test was applied to compare their differences among the four groups. Quantitative data following a normal distribution (HbA1c, BMI, TC, HDL-c, LDL-c, and TyG index) were described by mean ± standard deviation, and one-way analyses of variance (ANOVAs) were used to compare their differences among four groups. Qualitative data (gender, smoking status, drinking status, diabetes, hypertension, BMI categories, lipid-lowering drugs, anti-hypertension drugs, and insulin) were expressed as numbers and percentage (%) and compared via a Pearson chi-square test.

The incidences (per 100,000 person-years) of AD/AA and its subtypes (AD and AA) were calculated. The cumulative incidences of AD/AA and its subtypes in different groups were compared via the log-rank test and presented by as a Kaplan–Meier plot. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) for AD/AA and its subtypes across TyG index quartiles were calculated using Cox proportional hazards regression models. Multivariable-adjusted models were presented as follows: Model 1 adjusted for age (continuous) and gender (categorical); Model 2 further adjusted for smoking status (categorial) and drinking status (categorial); and Model 3 additionally adjusted for BMI (continuous), hypertension (categorial), LDL-c (continuous), and HbA1c (continuous). Restricted cubic splines (RCS) were employed to explore the dose-response correlations of TyG index with AD/AA and its subtypes by adjusting for the covariates in Model 3.

Sensitivity analyses were conducted in this study to inspect the robustness and consistency of models. To avoid the effects of medications on the results, the use of lipid-lowering drugs, anti-hypertension drugs, and insulin were further adjusted (sensitivity analysis 1). During the follow-up period, participants who developed AD/AA within the first year were excluded (sensitivity analysis 2), and those who developed AD/AA within the first two year were further excluded (sensitivity analysis 3).

Subgroup analyses were conducted for age (< 60 vs. ≥60), gender (female vs. male), smoking status (never smoker vs. previous smoker vs. current smoker), drinking status (never drinking vs. previous drinking vs. current drinking), diabetes (yes vs. no), hypertension (yes vs. no), and BMI (underweight vs. normal weight vs. overweight vs. obesity). IBM SPSS Statistics (version 26.0) and R software (version 4.3.3) were used for data cleaning and statistical analysis. A two-tailed P-value of < 0.05 indicated statistical significance.

Results

Baseline characteristics of participants

Table 1 shows the baseline characteristics of participants in this study. The mean age of these participants was 58(50, 63) years. Participants in the higher TyG index quartiles were older than those in the lower TyG index quartiles (P < 0.001). Of the 420,292 participants, 194,931(46.4%) were male. The percentage of males in the higher TyG index quartiles was higher than that in the lower TyG index quartiles (P < 0.001). Participants in the higher TyG index quartiles had higher levels of HbA1c, BMI, SBP, DBP, FBG, TG, TC, and LDL-c, and were more likely to be previous and current smokers, never and previous drinkers, have histories of diabetes and hypertension, and use lipid-lowering drugs, anti-hypertension drugs, and insulin; In addition, they had lower levels of HDL-c and were less likely to be never smokers and current drinking, compared to those in the lower TyG index quartiles (P < 0.001).

Table 1 Baseline characteristics of participants
Full size table

Association of TyG with AD/AA

Kaplan–Meier curves of the cumulative incidences of AD/AA and its subtypes are shown in Fig. 2. During a median follow-up of 14.8 (14.1, 15.5) years, 3481 cases of AD/AA developed, including 239 AD and 3,329 AA, among the 420,292 participants. RCS showed a linear relationship of TyG index with AD/AA and its subtypes (Fig. 3).

Fig. 2
figure 2

Kaplan–Meier curves of cumulative incidence. TyG index quartile 1 was used as the reference group. A AD/AA, B AD, C AA

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Fig. 3
figure 3

Nonlinear relationship between TyG index and incident risk of outcomes. The relationship was evaluated by RCS after adjustment for age, gender, smoking status, drinking status, BMI, hypertension, LDL-c, and HbA1c (model 3). Solid lines in the figure represent the HRs, and the shaded regions represent the 95% CIs. A TyG index in AD/AA, B TyG index in AD, C TyG index in AA

Full size image

A graded growth in incidence of AD/AA was observed across TyG index quartiles (32.5 cases per 100,000 person-years in TyG index quartile 1, 52.8 cases per 100,000 person-years in TyG index quartile 2, 62.7 cases per 100,000 person-years in TyG index quartile 3, and 76.4 cases per 100,000 person-years in TyG index quartile 4). Compared with TyG index quartile 1, the HRs (95% CIs) of AD/AA in TyG index quartiles 2, 3, and 4 without adjustment were 1.62(1.45–1.81), 1.93(1.73–2.15), and 2.35(2.12–2.61), respectively (P for trend < 0.001) (Table 2).

Table 2 Baseline TyG index and incident risks of AD/AA
Full size table

After adjusting for age and gender, the TyG index-associated risk of AD/AA was greatly attenuated, with adjusted HRs (aHRs) (95% CIs) in TyG index quartiles 2, 3, and 4 of 1.25(1.12–1.39), 1.30(1.17–1.45), and 1.45(1.30–1.61), respectively (Model 1, P for trend < 0.001). This association was somewhat attenuated but still significant after additional adjustment for smoking status and drinking status (Model 2, P for trend < 0.001), and further adjustment for BMI, hypertension, LDL-c, and HbA1c (Model 3, P for trend < 0.001). Participants in the highest TyG index quartile had a higher incident risk of AD/AA, compared to the lowest quartile of TyG index [HR 1.30 (95% CI 1.16–1.45) vs. HR 1.20 (95% CI 1.08–1.35), P for trend < 0.001], after fully adjusting for potential covariates. Every unit increment in TyG index was associated with a 15% growth in the incident risk of AD/AA [HR 1.15 (95% CI 1.08–1.23), P < 0.001]. In particular, TyG index was independently associated with a higher risk of incident AA [HR 1.17 (95% CI 1.09–1.25)] but was not associated with risk of incident AD [HR 0.87 (95% CI 0.67–1.14)]. Similar and consistent results were obtained in sensitivity analyses (Table 2).

Subgroup analyses

Figure 4 shows the subgroup analyses of the association of TyG index with incident risk of AD/AA and its subtypes. TyG index, analyzed as a quantitative variable, was shown to increase the incident risk of AD/AA across different subgroups. A significant interaction between age and TyG index was observed (P for interaction < 0.001). The association between TyG index and risk of incident AD/AA was more pronounced in participants older than 60 years than in those younger than 60 years [HR 1.15 (95% CI 1.06–1.24) vs. HR 1.14 (95% CI 1.00–1.29)]. Gender also showed a significant interaction with TyG index (P for interaction < 0.001). The association between TyG index and risk of incident AD/AA was more obvious in females than in males [HR 1.29 (95% CI 1.11–1.51) vs. HR 1.11 (95% CI 1.03–1.20)].

Fig. 4
figure 4

Subgroup analyses of the association between TyG index and incident outcomes. The adjusted model 3 (age, gender, smoking status, drinking status, BMI, hypertension, LDL-c, HbA1c) was used in this analysis. A TyG index in AD/AA, B TyG index in AD, C TyG index in AA

Full size image

Additionally, smoking status (P for interaction = 0.026), drinking status (P for interaction = 0.039), diabetes (P for interaction < 0.001), hypertension (P for interaction < 0.001), and BMI (P for interaction = 0.016) also showed significant interactions with TyG index. The association between TyG index and risk of incident AD/AA was more prominent in current smokers, current drinkers, participants without diabetes and hypertension, and those with obesity, compared to other subgroups. For example, the HRs for never, previous, and current smokers were 0.98 (95% CI 0.87–1.11), 1.18 (95% CI 1.07–1.31), and 1.31 (95% CI 1.14–1.49), respectively. The HRs for previous and current drinking were 1.01 (95% CI 0.75–1.35) and 1.15 (95% CI 1.07–1.23), respectively. Similarly, the HR for participants without diabetes was 1.16 (95% CI 1.08–1.24), compared to 1.15 (95% CI 0.94–1.41) for those with diabetes. The HR for participants without hypertension was 1.18 (95% CI 1.06–1.32), compared to 1.13 (95% CI 1.04–1.22) for those with hypertension. The HR for obesity participants was 1.18 (95% CI 1.05–1.33), compared to 1.08 (95% CI 0.93–1.25) for normal weight participants, and 1.13 (95% CI 1.02–1.24) for overweight participants (Fig. 4).

Discussion

The present study based on 420,292 UK Biobank participants revealed that TyG index is independently associated with the risk of incident AD/AA, with a median follow-up time of 14.8 years. Specifically, TyG index-associated risk for incident AD/AA varied significantly across different TyG index strata and was particularly higher in the highest TyG index quartile, which is consistent with the result of sensitivity analyses. By excluding participants who developed AD/AA shortly after baseline (within the first year and within the first two years, respectively), sensitivity analyses validated the results and made the findings more robust. This method ensured that the findings were not unduly influenced by early endpoints that might reflect pre-existing conditions or other biases [17].

Subgroup analyses in this study found that TyG index could better predict risk of AD/AA in those older than 60 years, female, current smokers, current drinkers, those without diabetes and hypertension, and those with obesity. It indicated that participants in these subgroups are more likely influenced by TyG index, and they will benefit considerably from the monitoring of TyG index to help reduce the risk of AD/AA. In addition, subgroup analyses showed interactions of TyG index with age, gender, smoking status, drinking status, diabetes, hypertension, and BMI (P < 0.05), indicating that these factors together with TyG jointly affect the onset of AD/AA.

The hyperinsulinemic-euglycemic clamp is the gold standard for detecting insulin resistance, but it is difficult to be widely used in clinical practice owing to its complexity, time-consuming nature, and high cost. In 2008, Simental-Mendía et al. proposed the concept of TyG index, a simple and convenient index composed of two cardiovascular risk factors: TG and FBG [10]. This index has been widely applied to evaluate insulin resistance in many studies and has demonstrated good sensitivity and specificity [20].

Subsequently, TyG index has been proven in many previous studies to be independently associated with an increased risk of incident atherosclerotic cardiovascular diseases, such as myocardial infarction and stroke [21,22,23], and their adverse events [24, 25]. A retrospective cohort study involving 188 patients with abdominal AA following endovascular aneurysm repair showed that an elevated TyG index is associated with decreased the 5-year overall survival of patients [26]. Nevertheless, limited research focused on exploring the association of incident AD/AA with TyG index. The present study is the first to verify the positive association between TyG index and AD/AA based on a large prospective cohort study in the UK Biobank, indicating the essential role of insulin resistance in AD/AA.

The UK Prospective Diabetes Study (UKPDS) and the Diabetes Control and Complications Trial (DCCT), two studies exploring the effect of intensive blood-glucose control on complications in patients with diabetes conducted by the United Kingdom and the United Sates, respectively, pointed out that insulin resistance is the basis of various endocrine and metabolic disorder-related diseases [27, 28]. It has been regarded as a strong risk factor for atherosclerotic vascular diseases [29,30,31]. Insulin resistance can cause an imbalance in glucose metabolism, trigger oxidative stress and inflammatory responses, and promote the apoptosis of vascular endothelial cells and vascular smooth muscle cells, as well as damage vascular endothelial cells [32,33,34]. Moreover, insulin resistance can also alter lipid metabolism throughout the body and increase blood lipids, accelerating the formation and development of atherosclerotic plaques [35, 36]. In addition, extensive research has shown that atherosclerosis is a risk factor for AD/AA, which can progress into a penetrating atherosclerotic ulcer, triggering dissection [37]. Therefore, TyG index, being an alternative indicator for assessing insulin resistance, may correlate with an increased risk of AD/AA due to its correlation with metabolic disorders. Independent association of TyG index with incident risk of AA was observed in the study, but not with AD onset. This implies different underlying biological mechanisms between AA and AD. Disorders of insulin resistance and metabolism might be more relevant to the pathophysiology of AA than AD.

Diabetes has been recognized as a risk factor for atherosclerosis [38] and other cardiovascular diseases [39]. The present large-scale prospective cohort study involving 420,292 participants demonstrates that insulin resistance, evaluated by TyG index, increases the risk of incident AD/AA (especially for AA) even after adjusting for other covariates. These findings are inconsistent with previous studies [40,41,42]. Several studies have found that diabetes is negatively associated with the risk of AD/AA. For example, a two-step Mendelian randomization revealed that diabetes is a protective factor for AD [40]. Divyatha et al. reported that patients with diabetes have a decreased risk of AA [41]. A systematic review and meta-analysis involving 15,794 eligible participants also revealed the negative association of diabetes with AD [42]. However, most of these results were concluded from retrospective study or case-control study with relatively small sample size. Generally, prospective design is better suited for elucidating the underlying relationship between TyG index and AD/AA compared to case-control studies and retrospective design.

Strengths and limitations

This study represents the initial exploration of the association between TyG index and AD/AA, providing evidence-based support for the potential role of insulin resistance in AD/AA. A large sample size, a prospective research design, and a long follow-up time are the advantages of our study. The findings of the study were further strengthened and validated by sensitivity analyses and multiple subgroup analyses, increasing the robustness, consistency, and reliability of the results.

However, several limitations should be noted. Firstly, patients with AD are commonly divided into Stanford type A and Stanford type B according to the location of the tear. Incidence of Stanford type A is higher than Stanford type B [43], and it is a more serious and life-threatening illness due to its anatomic location in the ascending aorta and the aortic arch. However, detailed classification data on Stanford type A and Stanford type B is unavailable in the UK Biobank, and only 239 participants developed AD in this study, which limit our ability to conduct further analyses for Stanford type A and Stanford type B separately. Secondly, Summers et al. reported that dietary management for patients with diabetes and thoracic AA who underwent thoracic endovascular aneurysm repair have a higher risk of AA rupture [44]. However, data on dietary management for diabetes was unavailable in this study. It would be a potential confounder that remains to be further explored when evaluating the association of TyG index with AD/AA.

Conclusion

This study demonstrates that TyG index, a surrogate marker of insulin resistance, is independently associated with higher risk of incident AD/AA, indicating the importance of using TyG index for risk assessment of AD/AA, especially for AA. This study also underscores the important significance of metabolic health and insulin resistance in vascular diseases, indicating that management of metabolic parameters could be essential in preventing AA.

Data availability

This research has been conducted using the UK Biobank Resource under application number 84709. All bona fide researchers in academic, commercial, and charitable settings could be access to the data upon application once meets the approval criteria for compensation (http://www.ukbiobank.ac.uk/register-apply).

Abbreviations

AA:

Aortic aneurysm

AD:

Aortic dissection

ANOVA:

One-way analysis of variance

BMI:

Body mass index

CI:

Confidence interval

DBP:

Diastolic blood pressure

DCCT:

Diabetes control and complications trial

FBG:

Fasting blood glucose

HDL-c:

High density lipoprotein cholesterol

HR:

Hazard ratio

ICD-10:

International classification of diseases, 10th revision

LDL-c:

Low density lipoprotein cholesterol

RCS:

Restricted cubic spline

SBP:

Systolic blood pressure

TC:

Total cholesterol

TG:

Triglyceride

TyG:

Triglyceride-glucose

UKPDS:

UK prospective diabetes study

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Acknowledgements

Sincere appreciation goes to Dr. Stanley Li Lin, a native English speaker from America, because he has provided his professional editing for the English language of this manuscript. We also express our thanks to all the participants in this study and the team members of UK Biobank.

Funding

This work was supported by the Overseas Exchange and Cooperation program for graduate students at Shantou University Medical College, China (No. 002-18124704), Provincial Science and Technology Special Fund of Guangdong in 2021 (No. 20220616017-2), Funding for Guangdong Medical Leading Talent, the First Affiliated Hospital of Shantou University Medical College, China (No. 2019–2022), 2020 Li Ka Shing Foundation Cross-Disciplinary Research Grant, China (No. 2020LKSFG19B), and National Natural Science Foundation of China (No. 82270422).

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Authors and Affiliations

  1. Department of Cardiology, First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, China

    Cuihong Tian, Yequn Chen & Xuerui Tan

  2. Human Phenome Institute, Shantou University Medical College, Shantou, 515041, Guangdong, China

    Cuihong Tian, Yequn Chen & Xuerui Tan

  3. Guangdong Engineering Research Center of Human Phenome, Shantou, 515041, Guangdong, China

    Cuihong Tian, Yequn Chen & Xuerui Tan

  4. Glycome Research Institute, Shantou University Medical College, Shantou, 515041, Guangdong, China

    Cuihong Tian

  5. Clinical Medical Research Center, First Affiliated Hospital of Shantou University Medical College, No. 22 Xinling Road, Jinping District, Shantou, 515041, Guangdong, China

    Cuihong Tian & Xuerui Tan

  6. Molecular Cardiology Laboratory, First Affiliated Hospital of Shantou University Medical College, Shantou, 515041, Guangdong, China

    Cuihong Tian

  7. Department of Cardiology, Second Xiangya Hospital of Central South University, No.139 Renmin Middle Road, Furong District, Changsha, 410012, Hunan, China

    Binyi Xu & Zhaowei Zhu

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  1. Cuihong Tian
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  4. Xuerui Tan
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Contributions

Dr. Z.Z. and Prof. X.T., serving as the principal investigators, jointly contributed to the design of the study. Especially, Dr. Z.Z. provided the data and performed the statistical analysis for this study. Dr. C.T. was responsible for the conception, literature review and draft of this manuscript. Prof. Y.C and Dr. B.X. were responsible for the literature review and results interpretation. The final manuscript was approved by all authors.

Corresponding authors

Correspondence to Xuerui Tan or Zhaowei Zhu.

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Ethics approval and consent to participate

The consents were approved and electronically signed by all participants in the study. The ethical approval was obtained from the NHS North West Centre for Research Ethics Committee (No. 11/NW/03820).

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The authors declare no competing interests.

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Tian, C., Chen, Y., Xu, B. et al. Association of triglyceride-glucose index with the risk of incident aortic dissection and aneurysm: a large-scale prospective cohort study in UK Biobank. Cardiovasc Diabetol 23, 282 (2024). https://doi.org/10.1186/s12933-024-02385-x

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Keywords

Cardiovascular Diabetology

ISSN: 1475-2840