Abstract
Objectives. Studies have shown that fasting blood glucose (FBG) is closely associated with poor prognosis in patients with coronary heart disease (CHD) after percutaneous coronary intervention (PCI), but its association with in-stent restenosis (ISR) is still unclear. Therefore, this study was to explore the association between FBG with ISR in patients with CHD after PCI. Design. In this cohort study, we included 531 patients with CHD who underwent PCI. Logistic regression, receiver operating characteristic (ROC), subgroup analysis and restricted cubic spline (RCS) were used to assess the association between FBG with ISR. Results. A total of 124 (23.4%) patients had ISR. Patients with higher levels of FBG had higher incidence of ISR compared to those with lower levels of FBG (p = 0.002). In multivariable logistic regression analyses, higher levels of FBG remained strongly associated with higher risk of ISR (as a categorical variable, OR: 1.89, 95% CI: 1.21–2.94, p = 0.005; as a continuous variable, OR: 1.12, 95% CI: 1.03–1.23, p = 0.011). ROC analysis also showed that FBG might be associated with the occurrence of ISR (AUC = 0.577, 95% CI: 0.52–0.64, p = 0.013). Subgroup analyses showed the association of FBG with ISR was also stable in several subgroups (< 60 years or ≥ 60 years, male, with or without smoking, without diabetes and without hypertension). And RCS analysis showed that FBG was linearly and positively associated with the risk of ISR. Conclusions. Higher levels of FBG were closely associated with higher risk of ISR in patients with CHD after PCI.
Introduction
In-stent restenosis (ISR) is defined as the occurrence of stenosis in at least 50% of the lumen diameter of the vessel in or adjacent to the stent after percutaneous coronary intervention (PCI), mainly due to vascular endothelial cell injury and cell proliferation [Citation1,Citation2]. Although the incidence of ISR varies from study to study due to the heterogeneity of the study population or differences in the content of the studies. However, the incidence of ISR may have been as high as 55% in the pre-stenting century and as high as 41% in the era of bare-metal stents, and it is encouraging to note that with improved treatment and the advent of drug-eluting stents, the incidence of ISR has dropped to less than 18%[Citation3,Citation4]. Nonetheless, current evidence continues to suggest that ISR is associated with poor prognosis in patients with coronary heart disease (CHD), so early intervention of controllable risk factors for ISR is urgent [Citation4]. Although Giustino et al. noted in a systematic review that stent implantation, anatomic and surgical factors are inextricably associated with the development of ISR, other risk factors may still play a role [Citation4]. An earlier systematic review by Wilson et al. showed that diabetes is strongly associated with the development of ISR [Citation5]. To our knowledge, diabetes is also an independent risk factor for cardiovascular disease (CVD), chronic kidney disease, and adverse events [Citation6–8], but the fact is that early diabetes or poor glycemic control has already begun to have a harmful effect on these diseases [Citation9,Citation10].
As a major risk factor for diabetes, insulin resistance (IR) has been shown to be strongly associated with the development of ISR, while the association between fasting blood glucose (FBG) with ISR is still unclear [Citation11,Citation12]. Therefore, in this cohort study, we aimed to explore the association between FBG with ISR in patients with CHD after PCI.
Subjects, materials and methods
Study population
This was a secondary analysis of a large single-center cohort study with data from an open database (Dryad Digital Repository) and is anonymous, detailed information is available from the published literature and database web pages (www.Datadryad.org) [Citation13,Citation14]. In this cohort study, all participants were from patients with CHD who were hospitalized and underwent PCI at the First Affiliated Hospital of Zhengzhou University from July 2009 to August 2011. As shown in , after excluding patients without follow-up angiography and FBG data, a total of 531 patients were included in the analysis. The initial study protocol was approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University and was in accordance with the Declaration of Helsinki. As this study was a retrospective study, informed consent of patients was waived.
Figure 1. Flow chart of the study population.
Data collection and definitions
In this study, we included demographic data, anthropometric data, comorbidity and medication data, blood markers data, coronary angiography data, and follow-up angiography data for statistical analysis, and the study variables included age, sex, smoking, diabetes, hypertension, stroke, previous myocardial infarction (MI), previous PCI, aspirin, clopidogrel, beta-blockers, angiotensin-converting enzyme inhibitor (ACEI), calcium channel blocker (CCB), statin, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), heart rate (HR), triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), creatinine, estimated glomerular filtration rate (eGFR), uric acid, FBG, left main disease, multi-vessel disease, number of treated vessels, number of stents, total stent length, stent type [sirolimus-eluting stent (SES) and paclitaxel-eluting stent (PES)], and ISR. In this study, according to the diagnosis of patients, all patients were divided into three categories: ST segment elevation myocardial infarction (STEMI), non-ST segment elevation myocardial infarction (NSTEMI) and chronic coronary syndrome (CCS). And fasting blood samples were collected for detection of blood markers before coronary angiography, and biochemical markers, including FBG, were obtained by professionals taking fasting blood samples from upper limb veins of patients, and these blood markers were detected by well-trained staff in standard biochemical laboratories using standardized laboratory techniques. And four lipid markers, FBG, uric acid, and creatinine were measured by collecting venous fasting serum samples from patients on the second day after admission, where LDL-C was measured by a direct method and eGFR was estimated by the MDRD formula, which is consistent with the Chinese population: eGFR (ml/min/1.73m2) = 175 x creatinine−1.234 x age−0.179 x 0.79 (if female), where creatinine is in mg/dL, and age is in years [Citation15]. Smoking was defined as a history of smoking in the past ten years. BMI is defined as weight (kg)/height (m2). And 2533 patients were followed up for a median of 29.8 months, among which 603 patients received coronary angiography again because of positive symptoms or signs or abnormal auxiliary examination, as well as the dynamic reexamination time recommended by the guidelines. ISR is defined as significant stenosis (≥ 50%) of the lumen diameter of the artery within or immediately adjacent to the stent area [Citation1].
Statistical analysis
The categorical variables were described by frequency (percentage), and Chi-square test or Fisher’s exact test was used to compare the differences of variables between groups. If the continuous variables conformed to the normal distribution, the mean ± standard deviation was described and the independent sample Student’s t test was used to compare the differences of variables between groups. When the continuous variables did not conform to the normal distribution, they were described by the median (quartile interval) and the Mann-Whitney U test was used to compare the differences of variables between groups. Then we used univariate logistic regression analysis to select covariates with p < 0.05 and clinically significant covariates to construct two multivariable logistic regression models. Model 1 adjusted for age and sex; model 2 adjusted for age, sex, stroke, previous PCI, clopidogrel, HR, HDL-C, creatinine, number of treated vessels and stent type. Then we used receiver operator characteristic (ROC) to evaluate the discriminatory ability of FBG on ISR. Subgroup analyses were used to explore the hierarchical association between FBG and ISR. Restricted cubic spline was used to analyze the potential nonlinear association of FBG with ISR. SPSS 26.0, MedCalc 19.6.1 and R 3.6.3 were used for statistical tests. A two-tailed P value < 0.05 was considered to be statistically significant.
Results
Baseline characteristics
As shown in , a total of 124 (23.4%) patients had ISR. We determined the optimal cutoff point for FBG to predict ISR by ROC analysis and then divided all patients into two groups: lower FBG group (FBG ≤ 5.37 mmol/L) and higher FBG group (FBG > 5.37 mmol/L). Patients with higher levels of FBG had higher rates of female, diabetes, multi-vessel disease and ISR, and higher levels of HR, TG, TC, but lower rates of smoking, beta-blockers utilization and statin utilization, lower levels of creatinine compared to those with lower levels of FBG (p < 0.05).
Table 1. Baseline characteristics of patients stratified by the optimal cutoff point of fasting blood glucose.
As shown in , the ISR group had higher proportion of previous PCI and SES/PES utilization, and higher levels of creatinine, FBG and number of treated vessels, but lower rates of clopidogrel and lower levels of HDL-C than those without ISR (p < 0.05).
Table 2. Baseline characteristics of patients stratified by the in-stent restenosis.
Association of FBG with ISR
As shown in , univariate logistic regression analysis showed that previous PCI, clopidogrel, HDL-C, creatinine, FBG, number of treated vessels, and stent type were associated with the risk of ISR (p < 0.05), and higher levels of FBG were associated with higher risk of ISR (OR: 1.14, 95% CI: 1.05–1.24, p = 0.003).
Table 3. Univariate logistic regression analysis of in-stent restenosis.
As shown in , after adjusting for age and sex, higher levels of FBG were strongly associated with a higher risk of ISR, whether as a categorical or continuous variable (as a categorical variable, OR: 2.02, 95% CI: 1.34-3.06, p = 0.001; as a continuous variable, OR: 1.15, 95% CI: 1.05–1.25, p = 0.002). The association between FBG and ISR remained significant after adjusting for age, sex, stroke, previous PCI, clopidogrel, HR, HDL-C, creatinine, number of treated vessels and stent type (as a categorical variable, OR: 1.89, 95% CI: 1.21–2.94, p = 0.005; as a continuous variable, OR: 1.12, 95% CI: 1.03–1.23, p = 0.011).
Table 4. Association of FBG with ISR in multivariable logistic regression models.
In addition, as shown in , ROC analysis further showed that FBG might be associated with the occurrence of ISR (AUC = 0.577, 95% CI: 0.52–0.64, p = 0.013).
Figure 2. ROC curve evaluating predictive effect of FBG for ISR. ROC, receiver operator characteristic; FBG, fasting blood glucose; ISR, in-stent restenosis; AUC, area under the curve.
Subgroup analysis
As shown in , subgroup analyses showed that higher levels of FBG were closely associated with higher risk of ISR in several subgroups (< 60 years or ≥ 60 years, male, with or without smoking, without diabetes and without hypertension) (p < 0.05), and no interaction between FBG with each stratified variable was found (p for interaction > 0.05).
Table 5. Subgroups analyses for the association between FBG with ISR.
Restricted cubic spline analysis
As shown in , restricted cubic spline analysis showed that FBG was linearly and positively associated with the risk of ISR (Overall p < 0.05, p for nonlinearity = 0.587).
Figure 3. OR (95% CI) For the ISR according to FBG. The association was adjusted for variables included in the multivariable adjusted model 2 in . FBG: fasting blood glucose; ISR: in-stent restenosis; or: odds ratio; CI: confidence interval.
Discussion
In this cohort study, our study showed that higher levels of FBG was strongly associated with higher risk of ISR, and the association was also stable in several subgroups (< 60 years or ≥ 60 years, male, with or without smoking, without diabetes and without hypertension). And we also found FBG was linearly and positively associated with the risk of ISR.
The current evidence shows that the burden of CVD caused by diabetes is very large, and the incidence and mortality of CVD in patients with diabetes are significantly higher than those without diabetes [Citation6]. In addition to the currently recognized harmful effects of diabetes on microvessels, macrovessels, peripheral nerves and autonomic nerves, its harmful effects on ISR have also been paid more and more attention[Citation5, Citation16]. Although the pathogenesis of ISR remains unclear, current evidence confirms that diabetes is an independent risk factor for ISR [Citation5, Citation17]. For example, several studies have consistently shown that patients with diabetes have higher incidence of ISR [Citation18–20] However, adequate control of diabetes in patients with CHD after PCI does not seem to completely prevent the occurrence of ISR [Citation21]. Since up to 50% of patients with ISR have no obvious symptoms, metabolic abnormalities at the edge of the disease should also be included in the risk management of ISR [Citation22]. For instance, there are several evidence that excessive residual cholesterol, hypersensitive C-reactive protein and uric acid may also be involved in the occurrence and development of ISR [Citation23–25]. Then, blood glucose and IR are also inextricably associated with the risk of ISR. For instance, Zhu et al. used triglyceride-glucose index (TyG) as an alternative marker of IR in a large cohort study to evaluate its association with ISR and found an independent positive association of TyG with the risk of ISR [Citation26]. Furthermore, Wu et al. in a small sample study also found a positive association of TyG with the incidence of ISR in patients with acute coronary syndrome [Citation27]. In addition, Liu et al. used estimated glucose disposal rate (eGDR) as a surrogate marker of IR and reconfirmed the association of IR with ISR in patients with CHD after PCI [Citation28]. Besides, Corpus et al. found in a small sample cohort study of patients with CHD complicated with diabetes that poor blood glucose control was closely associated with the risk of target vessel revascularization [Citation10]. And Hage et al. also found that FBG was independently associated with ISR in another cohort study of patients with CHD complicated with diabetes[Citation29]. And Xue et al. also showed FBG > 6.1 mmol/L was associated with the risk of ISR [Citation30]. In addition, Zhao et al. also confirmed that FBG was an independent predictor of ISR in a cohort study including 398 patients with CHD [Citation31]. However, compared with the existing published literatures, our study not only confirmed the role of blood glucose control in ISR, but also confirmed that the association between FBG and ISR was different in several subgroups. Besides, to our surprise, we found that FBG was also closely related to ISR in CHD patients without diabetes. Furthermore, we not only found a significant positive association of FBG with the risk of ISR, but also found that the levels of FBG below 7.0 mmol/L could increase the risk of ISR, suggesting that FBG may have participated in the occurrence and development of ISR in the early stage of diabetes, so we should also monitor its impact on ISR and CVD when the FBG levels are at a normal high level.
Although we have made valuable discoveries, the pathological mechanisms involved in the development of ISR by FBG are still poorly understood. There may be several mechanisms involved in the pathogenic effect of FBG on ISR, such as endothelial cell injury, intimal proliferation, cell proliferation and cell migration caused by inflammation and oxidative stress and the increase of platelet aggregation [Citation2,Citation32–34].
Regardless of these valuable results, our study still had some limitations. First, because this was an observational study, the causal association between FBG and ISR could not be determined. Second, because this was a small sample study, the findings might not be representative. Third, due to the limitations of clinical studies, we might have uncontrollably missed some risk factors for ISR, so we need to further increase the sample size and enrich the study in future studies to try to determine the association between FBG and ISR. Fourth, because this study was a secondary analysis of a single-center cohort study with a large sample, and the study population and baseline characteristics were only derived from available data, we inevitably missed some baseline characteristics and follow-up parameters, such as the data of glycosylated hemoglobin, the time point of re-coronary angiography and the reason why patients did not review coronary angiography during follow-up. This was undoubtedly the biggest shortcoming of this study, and we will further improve this point in future studies. Finally, the current results were derived from data from 10 years ago, and the development of PCI methodology and drug therapy has made great progress, so the results might be limiting. However, in terms of the current research background, these findings still show that glycemic control is important in the prognostic management of CHD and suggest that we should incorporate FBG into the risk management of ISR.
Conclusions
In this real-world study based on hospitalized patients, our evidence showed a linear and positive association of FBG with ISR in patients with CHD after PCI, which not only reaffirms the potential association between fasting glucose control with ISR, but also adds additional evidence for the harmful effects of FBG on cardiovascular events.
Ethical approval and consent to participate
The original study protocol was approved by the Ethics Committee of the First affiliated Hospital of Zhengzhou University and complied with the Declaration of Helsinki. And informed consent was waived for all patients due to the nature of the retrospective study by the Ethics Committee of the First affiliated Hospital of Zhengzhou University.
Consent for publication
Not Applicable.
Authors’ contributions
Ge-cai Chen, Xu Huang, Zhong-bao Ruan, Li Zhu, Mei-xiang Wang and Yi Lu: Writing - review & editing. Ge-cai Chen: Data curation, Writing - original draft. Ge-cai Chen: Conceptualization, Methodology, Software. Cheng-chun Tang: Conceptualization, Funding acquisition, Project administration, Supervision. All authors read and approved the final manuscript.
Acknowledgments
We would like to thank all the patients, nurses, doctors and researchers who participated in the original study for their valuable contributions.
Disclosure statement
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Data availability statement
The datasets used/or analyzed during the current study are available from the corresponding author on reasonable request or the Dryad Digital Repository.
Additional information
Funding
References
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