Abstract
Introduction
Insulin resistance (IR) plays an important role in the occurrence and development of cardiovascular disease (CVD) in patients with chronic kidney disease (CKD). The triglyceride-glucose (TyG) index is a simple and effective tool to evaluate IR. This study aimed to evaluate the association of the TyG index with coronary artery disease (CAD) and the severity of coronary artery stenosis (CAS) in nondialysis patients with stages 3–5 CKD.
Methods
Nondialysis patients with stages 3–5 CKD who underwent the first coronary angiography at Zhongda Hospital affiliated with Southeast University from August 2015 to January 2017 were retrospectively analyzed. CAS was measured by coronary angiography, and the CAS score was calculated as the Gensini score. Logistic regression analysis was used to determine the related factors of CAD and severe CAS.
Results
A total of 943 patients were enrolled in this cross-sectional study and 720 (76.4%) of these patients were diagnosed with CAD. The TyG index in the CAD group (7.29 ± 0.63) was significantly higher than that in the non-CAD group (7.11 ± 0.61) (p < 0.001). Multivariate logistic regression analysis showed that a higher TyG index was an independent risk factor for CAD in CKD patients after adjusting for related confounding factors (OR = 2.865, 95% CI 1.681–4.885, p < 0.001). Patients in the CAD group were divided into three groups according to the Gensini integral quantile level. Multivariate logistic regression analysis showed that the TyG index was an independent related factor for severe CAS after adjusting for relevant confounding factors (p < 0.001).
Conclusions
The TyG index is associated with CAD and the severity of CAS in patients with nondialysis stages 3–5 CKD. A higher TyG index is an independent factor for CAD and severe CAS.
Introduction
Cardiovascular disease (CVD) is the most common complication in patients with chronic kidney disease (CKD) and the leading cause of death in patients with CKD. A previous study found that the mortality rate from cardiovascular events was 10–20 times higher in people with CKD than in people with normal renal function [Citation1]. Coronary artery disease (CAD) is one of the important pathophysiological manifestations of CVD in CKD patients [Citation2]. Coronary angiography is the gold standard for diagnosing CAD, which can directly observe the condition of coronary vessels and accurately reflect the location and severity of the lesion. If necessary, coronary intervention can be performed during the examination process [Citation3]; however, coronary angiography is an invasive test, and the use of contrast media may also exacerbate the progression of kidney disease [Citation4]. Therefore, finding simple and noninvasive indicators in the CKD population has important clinical significance for the early clinical diagnosis of CAD to delay the progression of CKD.
Insulin resistance (IR), the common pathophysiological basis of various CVDs, plays an important role in the pathogenesis of CVD in CKD and can predict the risk of cardiovascular death in CKD patients [Citation5,Citation6]. The hyperinsulinemic euglycemic clamp technique (HIET) is the gold standard for evaluating IR, but its extensive clinical application is limited due to the complicated and time-consuming operation [Citation7].
In recent years, a number of studies have proposed that the triglyceride-glucose (TyG) index is a reliable and convenient index for evaluating IR [Citation8–10]. Previous studies have found that the TyG index is closely related to traditional CVD risk factors such as hyperglycemia, hypertension, dyslipidemia, and obesity [Citation4]. Additionally, it is associated with the severity of coronary arteriosclerosis, coronary stenosis [Citation11], and coronary calcification [Citation12], all of which contribute to the formation and development of atherosclerosis and the occurrence of CAD. In a study of patients with mild to moderate renal impairment (estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2), the TyG index was associated with the occurrence of CAD and was significantly correlated with coronary artery lesion severity [Citation13]. However, it is still unclear whether the TyG index is clinically useful in indicating CAD in nondialysis CKD stages 3–5 patients to avoid the use of contrast media in such patients. Therefore, the aim of this study was to explore the correlation between the TyG index and CAD and the severity of coronary stenosis in nondialysis patients with CKD stages 3–5 to provide clinical evidence for the early diagnosis and treatment of CAD in patients with CKD.
Materials and methods
Study design and population
Nondialysis patients with CKD stages 3–5 who underwent coronary angiography at Zhongda Hospital Affiliated to Southeast University from August 2015 to January 2019 were selected. Inclusion criteria: (1) age ≥18 years; (2) nondialysis patients with CKD stages 3–5 (eGFR <60 mL/min/1.73 m2); and (3) coronary angiography received for the first time. Exclusion criteria: (1) acute infection, major surgery, trauma, history of bleeding, cerebrovascular disease, acute and chronic pancreatitis, obstructive jaundice, severe liver failure, acute renal insufficiency within the past 3 months; (2) malignant tumor, hematological diseases, thyroid diseases, and autoimmune diseases; (3) history of hemodialysis, peritoneal dialysis, or kidney transplantation; (4) history of percutaneous coronary intervention and coronary artery bypass grafting; history of old myocardial infarction; (5) valvular heart disease, cardiomyopathy, myocarditis, or severe heart failure; and (6) incomplete data.
Patient characteristics
Basic information about the patients, such as age, sex, height, weight, body mass index (BMI), and history of smoking, drinking, hypertension and diabetes, was collected. Blood samples were collected on the second day of hospitalization for examination of fasting blood glucose (FBG), precontrast creatinine (Scr), eGFR, serum uric acid (UA), serum calcium (Ca), serum phosphorus (P), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), albumin (Alb), hemoglobin (Hb), and other biochemical indicators. The TyG index was calculated as TyG index = Ln [TG (mg/dL)×FBG(mg/dL)/2][Citation14].
Coronary angiography and Gensini score
CAD is diagnosed when at least one of the left main, left anterior descending, left circumflex or right coronary arteries has lumen diameter stenosis of ≥50% [Citation15]. The severity of coronary stenosis was quantified using the Gensini score. Quantitative score for the degree of stenosis of each vessel: ≤25%, 1 point; 26–50%, 2 points; 51–75%, 4 points; 76–90%, 8 points’ 91–99%, 16 points; and 100% scored as 32 points. The scores of different segments of coronary artery are multiplied by the corresponding coefficients as the points of this stage. Left main trunk × 5.0; proximal left anterior descending branch *2.5, middle section *1.5, distal lesions *1.0; first diagonal branch *1.0, second diagonal branch *0.5; proximal left circumflex branch *2.5, middle and distal segment *1.0; posterior descending branch *1.0; posterior collateral branch *0.5; the proximal, middle, and distal segments of the right coronary artery *1.0, and the remaining small branches *0.5. The score of coronary lesions in each patient is the sum of the scores of each branch [Citation16]. The higher the Gensini score is, the more severe the CAD coronary stenosis.
Grouping method
(1) According to the angiography results, all research subjects were divided into two groups: a non-CAD group (n = 223) and a CAD group (n = 720). (2) According to the Gensini score tertiles, the CAD population was divided into three groups: a low score group (Gensini score ≤ 11, n = 316), a medium score group (12 ≤ Gensini score ≤ 52, n = 320) and a high score group (Gensini score ≥ 53, n = 307).
Statistical analysis
SPSS version 26.0 (SPSS Inc., Chicago, IL) was used for statistical analysis; the Kolmogorov–Smirnov (K-S) method was used to test the normality of measurement data, and measurement data of normal distribution were expressed as the mean ± standard deviation (x ± s). Between-group comparisons were made using independent samples T test or one-way ANOVA. Nonnormally distributed measurement data were measured by the median (1st quartile, 3rd quartile) [M (P25, P75)]. The Mann–Whitney U test was used for comparisons between groups. Count data were expressed as percentages (%), and the chi-square test was used for comparisons between groups. Multivariate logistic regression was used to analyze the correlation between the TyG index and CAD occurrence and severity of coronary stenosis; a receiver-operating characteristic (ROC) curve was drawn to evaluate the predictive value of the TyG index on CAD and coronary stenosis severity. p < 0.05 indicates that the difference is statistically significant.
Results
Patient characteristics
A total of 943 patients were included in this study, including 454 males (48.1%) and 489 females (51.9%), with an average age of 73.60 ± 8.63 years; 732 (77.6%) patients had hypertension, and 284 patients (30.1%) had diabetes. Upon evaluating the stage of CKD, 630 (66.8%) patients had CKD stage 3a, 248 (26.3%) had CKD stage 3b, 65 (6.89%) in CKD stages 4–5.
Comparison of baseline characteristics of patients in the CAD group and the non-CAD group
Among the patients, there were 720 patients (76.4%) in the CAD population and 223 (23.6%) in the non-CAD population. Compared with the non-CAD group, the proportion of smoking history, hypertension, diabetes, UA, HDL-C, eGFR, Alb, and TyG index were significantly increased in the CAD group (p < 0.05), while Ca and HDL-C was significantly decreased (p < 0.05), as shown in .
Table 1. Baseline features of the non-CAD and CAD groups.
Coronary stenosis in patients with CAD
According to the tertiles of the Gensini score, CAD patients were divided into three groups, namely, the low score group (Gensini score ≤ 11, n = 316), middle score group (Gensini score 12–52, n = 320) and high score group (Gensini score ≥ 53, n = 307). The comparison results of different indicators between groups are shown in . BMI, FBG, UA, Ca, HDL-C, Alb, eGFR, and difference in the TyG index were statistically significant (p < 0.05). Among them, with the increase in the Gensini score, the TyG index gradually increased (p < 0.05).
Table 2. Baseline data of the Gensini score group.
The relationship between the TyG index and the risk of CAD
With the occurrence of CAD as the dependent variable (non-CAD = 0, CAD = 1), univariate logistic regression was performed, and the results showed that age, gender, history of smoking, history of hypertension, history of diabetes, UA, FBG, eGFR, HDL-C, Alb, and TyG index were correlated with CAD (p < 0.05), as shown in . After adjusting for confounding factors, it was found that for every increase of 1 in the level of the TyG index, the risk of CAD increased by approximately 2.865 times, and a high TyG index was an independent correlative factor for the occurrence of CAD in CKD patients (OR = 2.865, 95% CI 1.681–4.885, p < 0.001), as shown in .
Table 3. One-way logistic regression analysis of CAD.
Table 4. Multivariate logistic regression analysis of CAD.
The relationship between the TyG index and severe coronary stenosis in patients with CAD
As the existence of severe coronary stenosis (Gensini score < 53 is 0, Gensini score ≥ 53 is 1) was the dependent variable to conduct univariate logistic regression analysis, the results suggested that history of drinking, history of hypertension, BMI, UA, Ca, FBG, TG, HDL-C, LDL-C, Fib, and TyG index were associated with severe coronary stenosis in patients with CAD (p < 0.05), as shown in . Factors with p ≤ 0.2 in univariate logistic regression were included in the multivariate logistic regression analysis. And the results showed that a high TyG index was an independent factor for the occurrence of severe coronary stenosis in CAD patients. TyG for every increase of 1 in the index level, the risk of CAD increased by 132% (OR = 2.32, 95% CI 1.485–3.627, p < 0.001), as shown in .
Table 5. One-way logistic regression analysis of severe coronary stenosis.
Table 6. Multivariate logistic regression analysis of severe coronary stenosis.
Discussion
In this study, we determined a significant correlation between the TyG index and the occurrence of CAD and severity of coronary stenosis in nondialysis patients with CKD stages 3–5. To the best of our knowledge, this is the first study to demonstrate a correlation between the TyG index and CAD in this population.
Studies have shown that the prevalence of CKD is increasing year by year. CAD is one of the main complications of CKD and one of the main causes of death in patients with advanced CKD. Therefore, it is of great significance for the early diagnosis and prevention of CAD in patients with CKD. IR can exist in the early stages of CKD and can even occur in the normal stage of eGFR. When renal insufficiency gradually progresses, IR also increases [Citation17]. IR plays an important role in the occurrence and development of CVD in CKD patients. IR can not only directly damage vascular endothelial cells but also indirectly lead to vascular endothelial injury and inflammation by causing hyperglycemia, hyperlipidemia, hypertension and abnormal fibrinolysis, causing vascular smooth muscle cell proliferation, atherosclerosis, and the formation of coronary artery stenosis (CAS) [Citation18]. In the general population, IR has been found to be one of the important factors in the formation of atherosclerosis[Citation19], and it can also induce plaque instability and promote the progression of arterial plaque, thereby increasing the incidence of cardiovascular events [Citation20]. Cho et al. [Citation21] found that in nondiabetic people with normal renal function, IR was independently associated with the occurrence of CAD; IR was also an independent predictor of CVD mortality in nondiabetic end-stage renal failure patients [Citation20]. The current gold standard for evaluating IR is the HIET, but its clinical application is limited due to its complicated and time-consuming operation [Citation14,Citation22]. Recent studies have also found that there is a significant correlation between TyG and the IR index. Therefore, the TyG index can be regarded as a reliable and simple index for the clinical evaluation of IR.
The TyG index is related to the prevalence of CAD, the severity of coronary stenosis, and the prognosis. Cho et al. [Citation21] performed coronary CTA in 5764 non-CKD and nondiabetic patients and found that compared with the low TyG index population, the prevalence of CAD increased significantly in the high TyG index population. For special populations such as CKD, there are few studies on the correlation between the TyG index and CAD. In this study, we focused on the nondialysis patients with CKD stages 3–5. CAD was diagnosed by coronary angiography showing stenosis ≥50% of at least one major coronary lumen diameter. We found that compared with the Non-CAD group, the TyG index in the CAD group was significantly higher; the multivariate logistic regression analysis showed that for every increase of 1 in the TyG index level, the risk of CAD increased by approximately three times, and a high TyG index had an independent correlation with the occurrence of CAD. In this study, CAD patients were further grouped according to the tertiles of the Gensini score, and it was found that the Gensini score increased with the increase in the TyG index, indicating that the higher TyG index denoted severe coronary stenosis. The multivariate logistic regression analysis showed that for each increase of 1 in the level of the TyG index, the risk of severe coronary stenosis increased by 132%, suggesting that a high TyG index is an independent factor associated with severe coronary stenosis in patients with CAD. Two previous studies on patients with mild to moderate renal impairment (eGFR ≥ 60 mL/min/1.73 m2) also found that the prevalence of CAD and the number and severity of coronary stenosis increased significantly with increasing TyG index [Citation13,Citation22]. Previous studies have also pointed out that in people with normal renal function without traditional cardiovascular risk factors, the TyG index is an independent marker for predicting subclinical CAD [Citation23]. In addition, through ROC curve analysis in our study, it was found that the AUC of the TyG index for predicting CAD was less than 0.60, which was predictive to a certain extent, but further clinical studies with larger samples are needed to further verify this predictive value. For the first time, this study found that for nondialysis patients with CKD stages 3–5, there was a significant correlation between the TyG index and the occurrence of CAD.
This study has certain limitations. First, this study is a single-center, retrospective study, and it is difficult to infer the causal relationship between the TyG index and CAD, which requires further research for verification. Second, all patients were tested for a single TyG index without dynamic detection. Third, due to the inevitable confounding factors in clinical practice, the AUC of the TyG index is less than 0.6.
In conclusion, this study found that the TyG index was closely related to the severity of CAD and coronary stenosis in nondialysis patients with CKD stages 3–5, and a high TyG index was an independent factor for the occurrence of CAD and severe coronary stenosis. Strengthening the active intervention of IR in early CKD patients is beneficial to reduce cardiovascular complications in CKD patients. In the future, large-scale clinical trials are needed to conduct more in-depth research to provide more evidence for the early clinical diagnosis and treatment of CAD in CKD patients.
Author contributions
Dan Liu designed the study, performed the experiments, collected clinicopathological data, contributed to the statistical analysis, and wrote the article. Xiaoyang Guan, Ruoxin Chen and Shengchun Xu contributed to clinical data acquisition, analyzed the data, and participated in drafting the work. Ci Song and Shanhu Qiu participated in drafting the work. Hong Liu and Jingyuan Cao contributed to design of this study and revised the draft.
Statement of ethics
This study complied with the guidelines for human studies and includes evidence that the research was conducted ethically in accordance with the World Medical Association Declaration of Helsinki. In the manuscript, authors state that subjects have given their written informed consent and that the study protocol was approved by the institute’s committee on human research (2020ZDSYLL215-Y01).
Acknowledgments
The authors would like to thank AJE (https://www.aje.com) for the English language review.
Disclosure statement
The authors have no conflicts of interest to declare.
Additional information
Funding
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