Visit-to-Visit Glycemic Variability is Associated with In-Stent Restenosis in Patients with Type 2 Diabetes after Percutaneous Coronary Intervention

Background: Patients with type 2 diabetes are under substantially higher risk of in-stent restenosis (ISR) after coronary stent implantation. We sought to investigate whether visit-to-visit glycemic variability is a potential predictor of ISR in diabetic patients after stent implantation. Methods: Type 2 diabetic patients underwent elective percutaneous coronary intervention were consecutively enrolled and 1-year follow-up coronary angiography was performed. The incidence of ISR and its relationship with visit-to-visit HbA 1c variability, expressed as coecient of variation (CV), standard deviation (SD) and variability independent of the mean (VIM), were studied. Multivariable Cox proportional hazards models were constructed to analyze the predictive value of glycemic variability for ISR.

risk of ISR than non-diabetic patients [6,7]. The prognosis of diabetic patients after DES implantation is also more dismal than that of non-diabetic patients, with increased rates of cardiac death, myocardial infarction, target lesion failure and target vessel revascularization [8].
Hyperglycemia is a critical contributory factor to the development of restenosis [9], partly attributed to endothelial dysfunction [10], excessive production of reactive oxygen species [11] and formation of advanced glycation end-production [12]. Pre-procedural optimal glycemic control was shown to be associated with lower rate of stent failure in comparison with suboptimal control patients [9]. A retrospective study analyzing glycemic control based on sequential HbA 1c measurements from preprocedural to 6-month follow-up also suggested that sustained glycemic control is associated with better clinical outcomes in diabetic patients after PCI [13].
On the other hand, emerging evidence suggests that glycemic variability confers an additional risk to diabetic complications, which is predicted by mean glucose levels alone and may, to some extent, underlie the pathogenesis of micro-and macro-vascular diabetic complications. A retrospective study analyzing data from Diabetes Control and Complications Trial (DCCT) demonstrated that HbA 1c variability adds to mean HbA 1c in predicting the development of retinopathy and nephropathy in type 1 diabetes [14]. A prospective study of cohort of type 2 diabetes from Renal Insu ciency and Cardiovascular Events (RIACE) revealed that HbA 1c variability affects chronic kidney disease more than average HbA 1c [15]. Recently, two independent groups showed that long-term glycemic variability, either estimated by serial measurements of fasting plasma glucose or by HbA 1c , was a strong predictor of allcause mortality [16]. However, the relationship between glycemic variability and ISR is still unclear. Therefore, in the present study, we sought to investigate whether visit-to-visit HbA 1c variability is a potential predictor of ISR in patients with type 2 diabetes after DES implantation.

Study population
A total of 920 consecutive patients with type 2 diabetes and coronary artery disease (CAD) were screened, who received follow-up coronary angiography ~ 12 months after DES-based PCI of de novo lesions in native coronary arteries between September 2014 and July 2018 from the database of Advanced Glycation Endproducts and Development of CAD Program (AGENDA) in Ruijin Hospital, Shanghai. ISR was de ned as recurrence of luminal diameter stenosis (DS) of > 50% within the stent or in the 5-mm proximal or distal segments adjacent to the stent at follow-up angiography.
For the purpose of this study and to avoid confounding serum data, patients who had acute coronary syndrome (n = 86) during initial angiography and PCI, familial hypercholesterolemia (n = 5), malignant tumor (n = 13), or renal failure requiring hemodialysis (n = 8) were excluded. Another 36 subjects with no hematological and biochemical indices at admission were further excluded. During follow-up, 5 patients died and 68 patients were lost to follow-up. For calculation of glycemic variability, subjects (n = 279) without at least three HbA 1c measurements during follow-up (≥ 3 months apart) were also excluded. The remaining 420 subjects constituted the study population (Fig. 1). The diagnosis of type 2 diabetes was made according to the criteria of American Diabetes Association. Hypertension was diagnosed according to seventh report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure (JNC 7). The estimated glomerular ltration rate (eGFR) was computed using the Chronic Kidney Disease Epidemiology Collaboration equation.
This study complies with the Declaration of Helsinki. The study protocol was approved by the local hospital ethics committee, and written informed consent was obtained from all participants.

Angiographic Analysis
Coronary angiography was performed using standard Judkins technique through radial or femoral approach. For each patient, multiple matched angiographic views were obtained after intracoronary administration of nitrate. Quantitative coronary analysis of all angiographic data before and after procedure and during follow-up was performed (TERRA, GE, USA) by two experienced interventional cardiologists, who were unaware of clinical information of the patients. Using the outer diameter of the contrast-lled catheter as the calibration, the minimal lumen diameter (MLD) and reference diameter (RD) in diastole before intervention was determined from multiple projections by interpolated method. Lesion length was measured as the distance (in millimeters) from the proximal to distal shoulder in the projection with the least amount of foreshortening. The lesion was stented using a normal-to-normal technique, usually including 5-mm-long, angiographically normal segments proximal and distal to the lesion. Net luminal loss was de ned as the difference between the MLD immediately after the procedure and that measured during follow-up. Net luminal gain was de ned as the difference between the MLD before the procedure and that measured during follow-up. A value of 0 mm was assigned for MLD in the case of total occlusion at baseline. For patients who underwent multi-lesion coronary angioplasty, the most severe restenotic lesion at follow-up was entered into the analysis.

Glycemic Variability Determinations
HbA 1c was measured in the baseline and during follow-up period for at least three times in 3-month intervals. Then the mean and variability of HbA 1c were calculated. Three measures of glycemic variability were employed for the analysis. Intraindividual variability of HbA 1c was primarily de ned as intraindividual coe cient of variation (CV) of HbA 1c across visits. The alternative variability of HbA 1c includes: 1) standard deviation (SD) and 2) the variability independent of the mean (VIM), which is calculated by the equation as previously reported [16]: VIM = 100 × SD/mean β , where β is the regression coe cient based on natural logarithm of SD on natural logarithm of mean of the study population. There is no signi cant correlation between VIM and mean HbA1c levels (Pearson's r = 0.070, P = 0.169).

Statistical analysis
Continuous variables were presented as median (interquartile range) or mean ± SD, and categorical data were summarized as frequencies (percentages). Normal distribution of continuous variables was evaluated by Shapiro-Wilk test. For normally distributed variables, differences in tertiles of glycemic variability and subgroup analysis were performed by one-way or two-way analysis of variance (ANOVA) followed by post hoc t-test with Bonferroni correction. For non-normally distributed continuous variables, differences were analyzed by Mann-Whitney U test or Kruskal-Wallis test. Differences in categorical variables were analyzed by χ 2 test. The association between measures of glycemic variability and the incidence of ISR was assessed by Cox regression from which hazard ratios (HR) and 95% con dence interval (CI) were calculated. The assumption of proportionality of the Cox model covariates was tested by plotting Schoenfeld residuals. Four models were constructed for each measure of glycemic variability and binary angiographic restenosis (DS ≥ 50%) was employed as the dependent variable. In model 1, sex and age were adjusted. In model 2, we further adjusted admission systolic and diastolic blood pressure, body mass index (BMI), non-high-density lipoprotein (HDL) cholesterol and eGFR. In model 3, additional adjustment was performed with the post-PCI RD of target vessel, total stented length and medication use including oral hypoglycemic agent and insulin. In model 4, we further adjusted for the mean level of HbA 1c during follow-up. Net reclassi cation improvements (NRI) and integrated discrimination improvements (IDI) were analyzed to assess the improvement in clinical utility of the prediction model by considering glycemic variability. All statistical analyses were performed using the R statistical package v.3.6.3 (R Project for Statistical Computing, Vienna, Austria). A 2-tailed < 0.05 was considered statistically signi cant.

Results
Baseline characteristics of the study population A total of 420 subjects with 688 lesions, with a mean follow-up period of 12.8 ± 1.3 months, were included in the analysis. The male-to-female ratio was 74:26 and the mean age was 64.5 ± 9.0 years. Among these subjects, 73.8% were with hypertension and 77.6% of the subjects were with multivessel disease. The mean HbA 1c during follow-up was 7.4 ± 1.2%, and CV, SD, VIM of HbA 1c during follow-up  (Table 1). There was no signi cant difference in age, sex, history of hypertension, admission blood pressure, smoking status and duration of diabetes between the three tertiles. At admission, subjects with the highest tertile of CV of HbA 1c had higher levels of HbA 1c , fasting and 2 h postprandial glucose, but lower 2 h postparandial insulin level than those with the lowest tertile. Fasting insulin level was similar between the three groups. Meanwhile, HDL cholesterol was lower, whereas serum creatine and highsensitivity C-reactive protein were higher in subjects with the highest tertile. Oral hypoglycemic agent (OHA) and insulin were more frequently used in subjects with higher CV of HbA 1c .

Angiographic Findings
There were no signi cant differences in the target vessels, stent counts, stented length, angiographic preand post-PCI RD, DS and MLD between the three groups ( Table 2). In the overall population, follow-up coronary angiography showed the prevalence of binary angiographic ISR, de ned as ≥ 50% DS, was 8.6%. The mean DS was 22.9 ± 16.8%, and the mean net luminal loss and net luminal gain was 0.42 ± 0.88 mm and 1.66 ± 0.83 mm, respectively. There was a signi cant increase in DS across tertiles of CV of HbA 1c ( Fig. 2A, P = 0.001). Compared with subjects with the lowest tertile, a higher percentage of DS was found in the highest tertile (26.63 ± 19.08 vs. 19.29 ± 14.47%, P < 0.001). Accordingly, net luminal gain (P < 0.001) was step-wisely decreased in subjects with higher glycemic variability as grouped by all the three measures (Fig. 2B). Although there was no difference in net luminal loss between tertiles of CV ( Fig. 2C; P = 0.124), it differed signi cantly between subjects with different tertiles of SD (P = 0.023) or VIM (P = 0.014) of HbA 1c (Supplementary gure I and II). In addition, comparison of glycemic variability between subjects with and without ISR also showed signi cantly higher glycemic variability in ISR patients as analyzed by all the three measures (Supplementary gure III).
The impact of glycemic variability on ISR was analyzed across subgroups of sex, age, dichotomized baseline BMI, eGFR and HbA 1c (Fig. 3). Since the rate of binary ISR was relatively low, DS at follow-up angiography was compared between subgroups. We found DS was increased across tertiles of CV of HbA 1c in male but not female subjects. A trend towards higher percentage of DS across the tertiles was more prominent in subjects with higher BMI and poorer renal function, and was similar between two age groups. Interestingly, compared with subjects with higher HbA 1c at the time of PCI (HbA 1c > 7%), those with lower HbA 1c (≤ 7%) appeared to have more severe restenosis when having higher CV of HbA 1c . There was no signi cant interaction term between tertiles of CV of HbA 1c and these grouping variables, with the solo exception of basal HbA 1c level (P = 0.010). Dividing subjects by tertiles of SD or VIM yielded similar ndings with a little variation (Supplementary gure IV and V).

Multivariate Analysis
Multivariate analysis was performed to analyze the association between the incidence of ISR and different measures of glycemic variability (

Discussion
The major ndings of the present study are that patients with type 2 diabetes and high post-procedure HbA 1c variability tend to have greater neointimal hyperplasia and increased rate of ISR in comparison with those with low HbA 1c variability. Evaluation of HbA 1c variability by different measures exhibits consistent ndings. Accounting for HbA 1c variability leads to better risk strati cation accuracy of ISR in patients with type 2 diabetes after stent implantation.

Impact Of Glycemic Level And Stability On Isr
Compelling evidence has demonstrated a substantially increased rate of ISR in diabetic patients after coronary intervention irrespective of the speci c treatment modalities including balloon angioplasty, baremetal stents (BMS) and DES [6,17,18]. However, very few studies analyzed the association of glucose level and stability with the rate of ISR. Corpus et al found that optimal glucose control (HbA 1c ≤ 7%) before catherization was associated with a ~ 2-fold decrease in rate of target vessel revascularization compared to those with suboptimal glucose control (HbA 1c > 7%) [9]. A single center prospective study showed that diabetic patients with poor glycemic control at time points both pre-and post-PCI had higher risk of major adverse cardiovascular events (MACE) than non-diabetic patients [13]. In contrast, a retrospective study showed that diabetic patients with good glycemic control (HbA 1c ≤ 6.9%) only at the time of PCI, but not at follow-up, was associated with signi cantly lower incidence of MACE compared to those with poor glycemic control (HbA 1c > 6.9%; 18.4% vs. 26.2%, P < 0.05) [19]. These studies unanimously suggest that glycemic control at the time of PCI is of importance to prevent subsequent restenosis and adverse cardiovascular outcomes, but with con icting ndings on the effect of postprocedural glycemic control. Actually, glycemic control in these studies was de ned according to the cutoff level of HbA 1c at certain time points without consideration of glycemic variability. A substantial proportion of patients in these studies received coronary intervention based on BMS, which does not necessarily respond in the same way as that of DES in the process of restenosis under hyperglycemic conditions.
In the present study, all the enrolled patients received DES-based PCI, which re ects the predominant treatment modality in current clinical practice. In accordance with previous reports, we found diabetic patients with poor glycemic control at the time of PCI (HbA 1c > 7%) had a 1.49-fold higher rate of ISR than those with good glycemic control (HbA 1c ≤ 7%). By grouping patients based on mean HbA 1c during follow-up instead, there was an even higher (2.54-fold) increased rate of ISR in subjects with good versus poor glycemic control. Importantly, we for the rst time reported that the rate of ISR and angiographic DS were increased across tertiles of HbA 1c variability parameters. There was also a trend towards greater net luminal loss and less net luminal gain in patients with higher variability of HbA 1c . Therefore, previous reports and our ndings suggest that both glycemic level and stability are important in the process of ISR after DES implantation in patients with type 2 diabetes. Interestingly, subgroup analysis showed that the impact of glycemic variability on DS was more prominent in subjects with good (HbA 1c ≤ 7%) as compared to those with poor glycemic control (HbA 1c > 7%) at the time of PCI, suggesting high glycemic variability is likely to be more in uential on ISR in individuals with seemingly controlled glycemic level.
Currently, there is no universally accepted "gold standard" to quantify glycemic variability. In this study, we assessed HbA 1c variability by three different measures. In addition to SD, CV and VIM were employed to adjust for mean HbA 1c during follow-up. VIM was calculated based on logarithmic curve tting to eliminate its correlation with mean HbA 1c , and CV is relatively simple and more feasible in clinical practice. Analysis of glycemic variability by all of these three measures yielded similar ndings. After adjusting for mean HbA 1c level during follow-up, different measures of HbA 1c variability remained signi cantly associated with the incidence of ISR. Inclusion of glycemic variability led to signi cantly increased risk prediction accuracy compared to the model that only includes conventional risk factors, lesion and procedure characteristics, and mean HbA 1c . These ndings support the notion that glycemic variability is independent of glycemic level in association with ISR. Actually, previous secondary analyses of data from DCCT [14] and Finnish Diabetic Nephropathy (FinnDiane) Study [20] revealed that HbA 1c variability is an independent predictor of incident microalbuminuria, progression of renal disease and also incident cardiovascular events in patients with type 1 diabetes. A study analyzing 58,832 patients with type 2 diabetes in a large primary care database in England showed that HbA 1c variability was strongly associated with overall mortality and emergency hospitalization and not explained by mean HbA 1c [21]. A single center prospective study found that elevated admission glycemic variability appears even more important than admission glucose in predicting 1-year MACE in patients with acute myocardial infarction [22]. Therefore, although it is hard to tease out the relative effect of glycemic variability after accounting for glycemic level in the process of ISR, glycemic variability appears to function independently in various diabetic complications including ISR.

Possible Mechanisms
It is unclear the speci c mechanism by which glycemic variability affects the development of restenosis in diabetic patients. Based on previous clinical and basic science studies, potential mechanisms include: First, glycemic uctuation was shown to stimulation production of reactive oxygen species and proin ammatory cytokines, which are essential players in the pathogenesis of restenosis [23]. Second, glycemic variability is strongly correlated with postprandial β-cell dysfunction in type 2 diabetic patients using OHA. Consistently, we found postprandial insulin level was lower and insulin resistance was higher in patients with the highest tertile of CV than those with the lowest tertile [24]. Given that insulin resistance is an established contributory factor in restenosis, the impact of glycemic variability on ISR may also be secondary to insulin resistance.

Study Limitation
Our ndings should be interpreted in the context of following limitations. First, this study is a retrospective analysis based on prospectively collected data, and all the enrolled patients were from a single center. Second, uctuations in fasting plasma glucose (FPG) and HbA 1c appear to function differentially in the process of diabetic complications [14,25]. Variability of FPG was not analyzed in this study, which may have different features or function in different phases as compared to that of HbA 1c .
Third, this study was not designed to analyze the predictive value of glycemic variability for hard endpoint in diabetic patients underwent PCI. Although we found ISR rate was signi cantly elevated in patients with high variability of HbA 1c , whether these patients suffer higher risk of cardiovascular mortality remains inconclusive.

Conclusions
In conclusion, our ndings suggest that greater visit-to-visit HbA 1c variability is associated with higher incidence of ISR in patients with type 2 diabetes after stent implantation. Variability of HbA1c adds to mean level for risk prediction of ISR.

Declarations
Ethics approval and consent to participate The study was approved by the Hospital Ethics Committee, and written informed consent was obtained from all patients.

Consent for publication
Not applicable Availability of data and material The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests
The authors declare that they have no competing interests.  Flow chart of recruitment procedure. T2DM, type 2 diabetes mellitus; CAD, coronary artery disease; PCI, percutaneous coronary intervention; HbA1c, glycated hemoglobin A1c.

Figure 2
Cumulative frequency of restenosis according to tertiles of CV of HbA1c. Cumulative frequency curves for diameter stenosis (A), net luminal gain (B) and net luminal loss (C) at follow-up angiography in subjects with different tertiles of CV of HbA1c. CV, coe cient of variation; HbA1c, glycated hemoglobin A1c.

Figure 3
The impact of glycemic variability on ISR across subgroups. The impact of glycemic variability on ISR was analyzed in the overall population (A) and across subgroups of sex (B), age (C), dichotomized baseline BMI (D), dichotomized baseline eGFR (E) and dichotomized baseline HbA1c (F). ISR, in-stent restenosis; BMI, body mass index; eGFR, estimated glomerular ltration rate; HbA1c, glycated hemoglobin A1c.

Supplementary Files
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