Association between hemoglobin A1c variability and subclinical coronary atherosclerosis in subjects with type 2 diabetes Hae Kyung Yang, Borami Kang, Seung-Hwan Lee, Kun-Ho Yoon, Byung-Hee Hwang, Kiyuk Chang, Kyungdo Han, Gunseog Kang, Jae Hyoung Cho PII: DOI: Reference:

S1056-8727(15)00165-8 doi: 10.1016/j.jdiacomp.2015.04.008 JDC 6437

To appear in:

Journal of Diabetes and Its Complications

Received date: Revised date: Accepted date:

22 January 2015 4 April 2015 14 April 2015

Please cite this article as: Yang, H.K., Kang, B., Lee, S.-H., Yoon, K.-H., Hwang, B.-H., Chang, K., Han, K., Kang, G. & Cho, J.H., Association between hemoglobin A1c variability and subclinical coronary atherosclerosis in subjects with type 2 diabetes, Journal of Diabetes and Its Complications (2015), doi: 10.1016/j.jdiacomp.2015.04.008

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ACCEPTED MANUSCRIPT Association between hemoglobin A1c variability and subclinical coronary atherosclerosis in subjects with type 2 diabetes

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Hae Kyung Yanga, Borami Kanga, Seung-Hwan Leea, Kun-Ho Yoona, Byung-Hee Hwangb,

Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St.

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Kiyuk Changb, Kyungdo Hanc, Gunseog Kangd, Jae Hyoung Choa, *

Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea. b

Division of Cardiology, Department of Internal Medicine, Seoul St. Mary’s Hospital,

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College of Medicine, The Catholic University of Korea, Seoul, Korea

Department of Medical Statistics, College of Medicine, The Catholic University of Korea,

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Seoul, Korea

Department of Statistics and Actuarial Science, Soongsil University

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Corresponding Author: Jae Hyoung Cho, MD, PhD.

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Division of Endocrinology and Metabolism, Department of Internal Medicine Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, # 222 Banpo-daero, Seocho-gu, Seoul 137-701, Korea Tel: 82-2-2258-6332, Fax: 82-2-595-2534, E-mail: [email protected]

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ACCEPTED MANUSCRIPT ABSTRACT Aims We examined the association between hemoglobin A1c (HbA1c) variability and

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subclinical coronary atherosclerosis in subjects with type 2 diabetes.

Methods We used the multidetector coronary computed tomography data collected from

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subjects with type 2 diabetes who did not have a history of cardiovascular disease or angina symptoms. HbA1c measurements preceding the date of cardiac imaging were retrospectively

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collected, and intraindividual SD (HbA1c-SD), CV and adjusted SD of HbA1c measurements were calculated. Subclinical coronary atherosclerosis was defined as calcium score > 400 without any cardiac symptoms.

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Results A total of 595 subjects were categorized according to the median value of each HbA1c variability indicators. The prevalence of subclinical coronary atherosclerosis was

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higher in higher HbA1c variability group compared with lower HbA1c variability group.

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Multivariable logistic regression analysis showed that higher HbA1c-SD and -CV were associated with the presence of subclinical coronary atherosclerosis, independent of mean

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HbA1c level in subjects with diabetes duration ≤ 10 years (OR [95% CI]; HbA1c-SD, 2.894 [1.105 – 7.584]; HbA1c-CV, 2.540 [1.022 – 6.316]). Conclusions Long-term stabilization of blood glucose level might be important in preventing subclinical coronary atherosclerosis in subjects with earlier period of type 2 diabetes. Keywords; Coronary artery disease; Hemoglobin A1c; Hemoglobin A1c variability; Multidetector computed tomography; type 2 diabetes mellitus

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ACCEPTED MANUSCRIPT 1. Introduction Glycemic variability comprises “glucose variability” and “hemoglobin A1c (HbA1c)

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variability”. Glucose variability relates to the within-day fluctuation of glucose levels, and may eventually reflect an increase in HbA1c level. Long-term glycemic variability, which is

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assessed by HbA1c fluctuation, reflects changes in glycemic control over longer periods of

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time [1].

Data from the Diabetes Control and Complications Trials (DCCT) and Finnish Diabetic Nephropathy (FinnDiane) study have suggested that HbA1c variability is an independent risk factor for the development of diabetic retinopathy and nephropathy in subjects with type 1

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diabetes [2, 3]. The Oxford Regional Prospective Study has shown that HbA1c variability is an independent variable that adds to the effect of HbA1c on the risk for microalbuminuria in

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young patients with type 1 diabetes [4]. The association between HbA1c variability and

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cardiovascular disease was confirmed in several studies with type 1 diabetes. In the FinnDiane Study, HbA1c variability was predictive of incident cardiovascular events [3]. The

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Pittsburgh Epidemiology of Diabetes Complications Study reported that changes in HbA1c over time were more strongly associated with coronary artery disease than was the baseline HbA1c value in subjects with type 1 diabetes [5]. Recently, a large clinical cohort of Caucasian subjects with type 2 diabetes from the Renal Insufficiency and Cardiovascular Events (RIACE) study reported that HbA1c variability is an independent correlate of albuminuria and the albuminuric phenotypes of chronic kidney disease (CKD), but not of non-abuminuric CKD or diabetic retinopathy [6]. Two prospective cohort studies from Japan and Taiwan, the Tsukuba Kawai Diabetes Registry 2 [7] and the 3

ACCEPTED MANUSCRIPT Diabetes Management through an Integrated Delivery System project [8], have shown that

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HbA1c level is associated with microalbuminuria in patients with type 2 diabetes.

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However, studies on the impact of HbA1c variability on cardiovascular disease in subjects with type 2 diabetes are inconclusive [9-13]. Previous reports were based on detecting overt

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cardiovascular events, and the association between subclinical coronary atherosclerosis and

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HbA1c variability has not been studied.

Diabetes is known as a coronary heart disease equivalent, and images by computed tomography (CT) have shown extensive calcification of vascular beds in subjects with diabetes, reported as coronary artery calcium score [14]. Coronary artery calcium score

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(CACS) is a useful method to identify subclinical atherosclerosis [15], and reflect the longterm impact of elevated cardiovascular risk factors and independently predict future risk of

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cardiovascular morbidity and mortality [16, 17].

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The aim of this study was to explore the relationship between HbA1c variability and subclinical coronary atherosclerosis determined with multi-detector coronary CT (MDCT) in

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patients with type 2 diabetes. To best of our knowledge, the association between HbA1c variability and MDCT finding has not been studied in subjects with or without type 2 diabetes.

2. Material and Methods 2.1 Study design We used the MDCT data collected for the CRONOS-ADM Registry (Coronary CT 4

ACCEPTED MANUSCRIPT angiography evaluation for clinical outcomes in asymptomatic patients with type 2 diabetes mellitus, registered with ClinicalTrials.gov NCT02070926), an observational cohort study on

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the clinical outcomes in asymptomatic patients with type 2 diabetes. This study enrolled

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asymptomatic patients with type 2 diabetes who underwent 64-slice, dual source MDCT at two hospitals affiliated with the Catholic University of Korea between January 2006 and

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December 2010. Patients were eligible for this study if they were >18 years of age and did

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not have past history of coronary artery disease, or angina or angina-equivalent symptoms. Asymptomatic status was confirmed using the Rose questionnaire for angina [18]. Those with type 1 diabetes, with known or suspected coronary artery disease; with a history of prior myocardial infarction, coronary revascularization, or cardiac transplantation; receiving

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treatment with antianginal medication; with ventricular or supraventricular arrhythmias; or with contraindications for the use of iodinated contrast were excluded. All the HbA1c

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measurements performed preceding the date of MDCT imaging were retrospectively

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collected. Among 935 subjects enrolled at the registry, 595 subjects who had 4 HbA1c recordings were analyzed in this study. The duration of diabetes and baseline HbA1c level of

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subjects who had < 4 HbA1c recordings (n=340) was 9.63 ± 9.04 years and 8.69 ± 2.30 %, respectively.

2.2 Imaging protocol and image reconstruction All patients were in normal sinus rhythm and were able to hold their breath as required for MDCT. Patients with a heart rate >70 beats per minute (bpm) were administered intravenous esmolol at a dose of 3 mg at 5-minute intervals, up to a total dose of 15 mg. If the patient’s 5

ACCEPTED MANUSCRIPT heart rate did not decrease to 1.5 mm were included in the analysis. Coronary plaques were identified as structures >1 mm2 within or adjacent to the coronary artery lumen that could be distinguished 6

ACCEPTED MANUSCRIPT clearly from the vessel lumen and the surrounding pericardial tissue.

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The severity and extent of coronary artery disease was measured by several coronary CT

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angiography scores, including the CACS, segment involvement score (SIS), and segment stenosis score (SSS). The CACS was assessed with dedicated software (Siemens Calcium

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Score; Siemens). Coronary artery calcium was identified as a dense area in the coronary artery that exceeded the threshold of 130 HU. Subjects with CACS > 400 and without cardiac

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symptom were considered as having subclinical coronary atherosclerosis in this study. The SIS was calculated as the total number of coronary artery segments exhibiting plaque, irrespective of the degree of luminal stenosis within each segment (minimum = 0; maximum = 16). The SSS was used as a measure of overall coronary artery plaque extent. Each

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coronary segment was graded as having absent to severe plaque (scores from 0 to 3), based

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on the extent of obstruction of the coronary luminal diameter. The extent scores of each of the 16 segments were summed to yield a total score that ranged from 0 to 48. The plaque

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characteristics were described as calcified plaque (>130 HU), soft plaque (7%. The discrepancy between previous reports might be explained by differences in the study design (prospective study vs cross-sectional study) and different degree of HbA1c variability, baseline HbA1c level or ethnicity. Regarding the association between glycemic variability and the presence of subclinical atherosclerosis, one study

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demonstrated that mean amplitude of glycemic excursion calculated from continuous glucose monitoring was associated with subclinical atherosclerosis measured by carotid intima-media

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thickness in 216 Chinese subjects with type 2 diabetes [20]. Another study reported positive

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association between glucose variability and coronary artery calcium score in men with type 1 diabetes [21]. However, none of the previous studies reported the association between HbA1c

imaging.

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variability and the presence of subclinical atherosclerosis measured by coronary MDCT

Coronary MDCT is considered an excellent noninvasive tool for measuring the coronary artery calcification burden in subjects at high risk of cardiovascular disease. Moreover, the ability of coronary MDCT to characterize the composition of lesions according to the attenuation of plaque enables the identification of calcified, noncalcified, or mixed plaque lesions [22]. Several studies have shown that acute coronary syndrome and sudden cardiac death originate from nonstenotic, lipid-rich necrotic plaques rather than from more advanced, 13

ACCEPTED MANUSCRIPT stable, calcified lesions [23, 24]. In our analysis, HbA1c-CV and adj-HbA1c-SD were closely related to the presence of soft or mixed plaque but not to the presence of calcified plaque.

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Factors that determine the composition of coronary artery plaques are not fully understood.

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Previous studies have shown that increased LDL-cholesterol level [25] and visceral adipose tissue [26], and decreased HDL-cholesterol level [27] were associated with more noncalcified

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and less calcified plaque on coronary CT. Others have reported that apolipoprotein B and

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small HDL particles are associated with a larger plaque burden and more noncalcified plaque, whereas larger HDL and pre-2-HDL particles are associated with lower plaque burden and less non-calcified plaque [28]. In subjects with diabetes, coronary artery plaque composition and volume were associated with glycemic control status [29]. However, the exact

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mechanisms underlying these relationships are unclear.

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Several mechanisms may be involved in the association between short-term glycemic variability and outcomes. Glycemic excursions measured by continuous glucose

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measurement correlated with oxidative stress in subjects with type 2 diabetes [30], a well-

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known pathogenic factor in diabetes complications [31]. Glycemic fluctuation has been shown to cause an increase in inflammatory cytokines, and monocyte and macrophage adhesion to endothelial cells in animals and humans [32-34]. Additionally, the exposure to intermittent high glucose level leads to apoptosis of pancreatic -cells [35]. It remains unclear whether long-term glycemic variability has similar pathophysiological consequences on the micro- or macrovascular complications of diabetes. Several studies have suggested that a higher HbA1c variability may reflect overall glycemic control status [36], use of glucocorticoids or anti-psychotics [37], complex underlying disorders, poor quality of life, low socioeconomic status [38], or the lack of physiological and/or psychological support 14

ACCEPTED MANUSCRIPT systems [39].

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In our study, strong association was confirmed between HbA1c variability and the presence

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of subclinical coronary atherosclerosis among subjects with diabetes duration < 10 years, but not in those with longer duration of diabetes. Our finding is in agreement with the hypothesis

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of “metabolic memory” or “legacy effect”, the idea that early glycemic environment is remembered in the target organ and that early metabolic control has beneficial effects in

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preventing vascular complications of diabetes [40]. As reviewed by Chilelli et al. [41], although hyperglycemia has a key, early role in the development of diabetes complications, oxidative and glycoxidative stress mainly perpetuates tissue damage and the progression of complications in the longer term. They also demonstrated that macrovascular damage could

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be related to a later phase of diabetes and hyperglycemia itself plays a minor role with respect

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to other pathophysiological mechanisms (i.e. chronic interaction between oxidative stress and and glycation at tissue or vessel level). Although detailed underlying mechanism is unclear

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until know, our finding might suggest the importance of long-term stabilization of blood

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glucose level especially in those with earlier period of diabetes to prevent the development of subclinical coronary atherosclerosis. There is no gold standard definition on HbA1c variability cutoff, and we have categorized the HbA1c variability indices into 2 groups according to the median values of each index. Various previous reports regarding the association between HbA1c variability and micro- or macrovascular complications of diabetes, also categorized HbA1c variability measurements into 2 to 4 groups [3, 6, 8, 9]. The HbA1c-MEAN of our study population was 7.47 %, which shows an overall good glycemic control status of the enrolled subjects. While the HbA1cMEAN, HbA1c-SD and adj-HbA1c-SD of our patients were similar to that from the RIACE 15

ACCEPTED MANUSCRIPT study [6, 9] (7.57, 0.40 and 0.46 % respectively), the values were lower compared to the data from the Oxford Regional Prospective Study [4] (9.50, 1.05 and 0.91 %, respectively) or the

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Diabetes Management through an Integrated Delivery System project [8] (7.90, 1.12 and

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1.03 % respectively). Since HbA1c-SD and adj-HbA1c-SD can be affected by the HbA1cMEAN, we used HbA1c-CV to adjust for HbA1c-MEAN value and demonstrated that the

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association between HbA1c variability and subclinical coronary atherosclerosis was still

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intact. We tried to perform subgroup analysis according to HbA1c-MEAN of 8.0%, but due to small number of patients in each group, further analysis was not available. This study is limited in that further survey on overt cardiac event and mortality was not performed. Second, all patients were Korean, and it is uncertain whether our findings can be

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generalized to other ethnic groups. Third, our study was a retrospective study and HbA1c

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values were a part of a routine clinical follow-up plan. There were various intervals between HbA1c measurements for each patient and the number of measurements of HbA1c during

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observation period also differed. In order to minimize this limitation, we used SD of serially-

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measured HbA1c levels adjusted by the number of measurements (adj-HbA1c-SD) and HbA1c-CV to account for the mean HbA1c level. While HbA1c-CV was a significant predictor for subclinical coronary atherosclerosis in subjects with shorter duration of diabetes, this association was not confirmed with adj-HbA1c-SD. Since there is no gold standard for HbA1c variability index, we could only suggest a possibility that HbA1c variability (measured as HbA1c-SD or HbA1c-CV) might be an independent predictor for subclinical coronary atherosclerosis in subjects with diabetes duration ≤ 10 yrs. Other variables such as fasting or postprandial glucose level, inflammatory parameters, frequencies and degree of hypoglycemia and intrapersonal variation in body weight, blood pressure or lipid profiles 16

ACCEPTED MANUSCRIPT were not fully evaluated. Finally, our study was a cross-sectional study and the beneficial role of minimizing HbA1c variability by medication adjustment, education, encouragements or

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increasing compliance cannot be evaluated. Further prospective investigations are required to

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confirm the role of stabilizing HbA1c variability. The strengths of this study include the use of noninvasive MDCT to detect subclinical atherosclerosis, exclusion of previously known

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cardiovascular events and the adjustment for possible confounding factors.

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In conclusion, HbA1c-SD and HbA1c-CV were associated with subclinical coronary atherosclerosis in subjects with diabetes duration ≤ 10 yrs. Therefore, long-term stabilization of blood glucose level might be important in preventing subclinical coronary atherosclerosis in subjects with earlier period of type 2 diabetes. Further studies with a larger population in

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other ethnic groups are required to verify the present results.

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ACCEPTED MANUSCRIPT Acknowledgments

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The authors acknowledge the study field workers and nurses involved in CRONOS-ADM

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Registry.

Conflict of interest

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All authors declare that there is no conflict of interest associated with this manuscript.

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Contributions to authorship

H.K.Y. designed the study, researched and analyzed data and wrote manuscript. B.K.

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researched data and contributed to discussion. S.H.L. and K.H.Y. contributed to discussion and reviewed and edited the manuscript. B.H.H. and K.C. researched and analyzed data. K.H

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and G.K analyzed data and contributed to discussion. J.H.C. designed the study, contributed

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to discussion, edited the manuscript and made final approval of the version to be published.

Grant support: There is no funding resource.

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ACCEPTED MANUSCRIPT Figure legend

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Figure 1. Prevalence of subclinical coronary atherosclerosis in lower and higher

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HbA1c variability group.

The numbers in the bar represent the prevalence of subclinical coronary atherosclerosis in

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lower and higher HbA1c variability groups. *, P-value < 0.05

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ACCEPTED MANUSCRIPT Table 1. Baseline clinical characteristics.

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62.50% 24.02 ± 2.98 126.48 ± 15.69 72.55 ± 9.02 18.34 ± 9.41

57.20% 24.37 ± 3.19 124.81 ± 12.77 74.42 ± 9.2 12.26 ± 8.51

81.30% 72.70% 27.00% 973.43 ± 454 7.65 ± 1.29

58.20% 60.60% 28.90% 973.38 ± 434.95 7.42 ± 1.23

0.71 (0.61,0.81) 8.87 (7.82, 9.92) 0.65 (0.57, 0.74) 8.12 ± 2.62 85.32 ± 18.2 86.35 ± 19.83

0.65 (0.60, 0.69) 8.32 (7.80, 8.85) 0.60 (0.56, 0.61) 7.87 ± 2.49 80.40 ± 19.35 95.40 ± 24.53

4.01 ± 0.75 1.30 (1.18, 1.42) 1.23 ± 0.32 2.18 ± 0.66 47.70% 62.50% 33.40% 4.70% 70.30% 50.20%

4.25 ± 0.82 1.44 (1.35, 1.53) 1.27 ± 0.31 2.36 ± 0.70 42.00% 66.60% 22.90% 7.90% 62.10% 57.90%

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Males (%) Body mass index (kg/m2) Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Duration of diabetes (year) Diabetes duration over 10 yrs (%) Hypertension (%) Current or ex-smoker (%) Follow up period (day) HbA1c-MEAN (%) HbA1c-SD (%) HbA1c-CV Adj-HbA1c-SD (%) Fasting plasma glucose (mmol/L) Baseline serum creatinine (μmol/L) eGFR (MDRD) Total cholesterol (mmol/L) Triglyceride (mmol/L) HDL-cholesterol (mmol/L) LDL-cholesterol (mmol/L) Use of sulfonylurea Use of metformin Use of insulin Use of DPP4-inhibitor Use of statin (%) Use of aspirin (%)

595 64.88 ± 8.90 58.32% 24.29 ± 3.15 125.17 ± 13.46 74.02 ± 9.19 13.57 ± 9.05 54.04% 59.43% 28.45% 973 ± 439 7.47 ± 1.25 0.51 (0.49, 0.54) 6.98 (6.64, 7.33) 0.48 (0.45, 0.51) 7.93 ± 2.52 81.33 ± 19.45 93.4±23.85 4.20 ± 0.81 1.21 (1.16, 1.26) 1.26 ± 0.31 2.32 ± 0.70 43.19% 65.71% 25.38% 7.23% 63.87% 58.32%

ED

Number Age (year)

Subclinical coronary atherosclerosis Presence Absence 128 467 69.77 ± 7.42 63.54 ± 8.81

SC

Total

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Association between hemoglobin A1c variability and subclinical coronary atherosclerosis in subjects with type 2 diabetes.

We examined the association between hemoglobin A1c (HbA1c) variability and subclinical coronary atherosclerosis in subjects with type 2 diabetes...
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