Relation Between Carotid Intima–Media Thickness and Left Ventricular Mass in Type 1 Diabetes Mellitus (from the Epidemiology of Diabetes Interventions and Complications [EDIC] Study)

Relation Between Carotid Intima–Media Thickness and Left Ventricular Mass in Type 1 Diabetes Mellitus (from the Epidemiology of Diabetes Interventions and Complications [EDIC] Study) Harjit Chahal, MD, MPHa,b, Jye-Yu C. Backlund, MPHc, Patricia A. Cleary, MSc, John M. Lachin, ScDc, Joseph F. Polak, MD, MPHd, Joao A.C. Lima, MDa,b, David A. Bluemke, MD, PhDa,b,e,*, and the DCCT/EDIC Research Group Type 1 diabetes mellitus (DM) is associated with early atherosclerosis and increased cardiovascular mortality. The relation between carotid intima–media thickness (cIMT), a marker of subclinical atherosclerosis, and left ventricular (LV) mass, an independent predictor of cardiovascular morbidity, has not been previously studied in type 1 DM. The Epidemiology of Diabetes Interventions and Complications (EDIC) study is a multicenter observational study designed to follow up the Diabetes Control and Complications Trial (DCCT) cohort. LV mass was measured with cardiac magnetic resonance imaging at EDIC year 15 and common cIMT was assessed using B-mode ultrasound at EDIC year 12. Multivariable linear regression models were used to assess the relation between cIMT at year 12 and LV mass at year 15. In total 889 participants had cardiac magnetic resonance imaging and cIMT measurements available for these analyses. At EDIC year 15, mean age of the participants was 49 ⴞ 7 years, mean DM duration was 28 ⴞ 5 years, and 52% were men. Spearman correlation coefficient (r) between LV mass and cIMT was 0.33 (p <0.0001). After adjusting for basic covariates (machine, reader, age, and gender), a significant association between LV mass and cIMT (estimate 2.0 g/m2 per 0.1-mm cIMT increment, p <0.0001) was observed. This association was decreased by the addition of systolic blood pressure, in particular 1.15 g/m2 per 0.1-mm cIMT increment (p <0.0001), and to a lesser extent other cardiovascular disease risk factors. Furthermore, the relation observed between LV mass and cIMT was stronger in patients with shorter duration of DM. In conclusion, cIMT was an independent predictor of larger LV mass in a well-characterized population with type 1 DM. © 2012 Published by Elsevier Inc. (Am J Cardiol 2012;110: 1534 –1540)

Parallel relations have been demonstrated between carotid intima–media thickness (cIMT) and left ventricular (LV) mass in population studies and particularly well documented in hypertensive populations.1–3 In this report we examine the relation between cIMT and LV mass in a cohort of patients with type 1 diabetes mellitus (DM). We

further explore how traditional cardiovascular risk factors and diabetic factors affect the association between cIMT and LV mass. We hypothesized that delineation of these interrelations would provide a better understanding of the mechanism of end-organ remodeling in type 1 DM and offer increased prognostic information for risk stratification. Methods

Departments of aRadiology and bCardiology, Johns Hopkins School of Medicine, Baltimore, Maryland; cThe Biostatistics Center, George Washington University, Rockville, Maryland; dTufts Medical Center, Tufts University School of Medicine, Boston, Massachusetts; eNational Institutes of Health, Bethesda, Maryland. Manuscript received April 14, 2012; revised manuscript received and accepted July 9, 2012. Acknowledgement for The DCCT/EDIC has been supported by U01 Cooperative Agreement grants (1983–93) and contracts (1994-present) with the Division of Diabetes Endocrinology and Metabolic Diseases of the National Institute of Diabetes and Digestive and Kidney Disease, and through support by the National Eye Institute, the National Institute of Neurologic Disorders and Stroke, the Genetic Clinical Research Centers Program (1993–2007), and Clinical Translational Science Center Program (2006-present), Bethesda, Maryland. *Corresponding author: Tel: 301-402-1854; fax: 301-480-0055. E-mail address: [email protected] (D.A. Bluemke). 0002-9149/12/$ – see front matter © 2012 Published by Elsevier Inc. http://dx.doi.org/10.1016/j.amjcard.2012.07.014

The study designs for the Diabetes Control and Complications Trial (DCCT) and the Epidemiology of Diabetes Interventions and Complications (EDIC) study have been described elsewhere.4,5 Briefly, 1,441 patients with type 1 DM 13 to 39 years old without cardiovascular disease, hypertension, or hypercholesterolemia at baseline were recruited and randomly assigned to intensive or conventional diabetes therapy. More than 90% of the surviving DCCT cohort (1,301 subjects) agreed to be followed up in the EDIC study, which was designed as a prospective observational follow-up study of the DCCT cohort (Figure 1). The study was approved by the institutional review boards of all participating centers and all participants gave written informed consent. www.ajconline.org

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Table 1 Clinical characteristics of participants with cardiac magnetic resonance imaging and carotid intima–media thickness measurements available (included in present study) versus overall study population Clinical Characteristics

Figure 1. Participant flow chart from DCCT/EDIC cohort included in present study.

One thousand one hundred twenty-two participants from the EDIC cohort consented and were eligible for cardiac magnetic resonance imaging (MRI) examination, which was done at EDIC year 15 (Figure 1). Details of the cardiac MRI protocol have been previously described.6 Briefly, participants were scanned with 1.5-T magnets in all but 1 center, which had a 3-T magnet. Cardiac cine images were acquired in 2-chamber, 4-chamber, and short-axis planes with breath holds using an electrocardiograph-triggered steady-state free-precession pulse sequence (repetition time ⬍3.8 ms, echo time minimized milliseconds, flip angle maximized, spatial resolution 2.5 ⫻ 2 ⫻ 8 mm, slice gap 2 mm, temporal resolution 30 to 50 ms). All cardiac MRI studies were evaluated and quantified at a single reading center by readers who were blinded to patients’ clinical information. LV mass, volumes, and functional parameters were determined from short-axis cine images covering the heart from base to apex throughout the cardiac cycle using QMASS 6 (Medis, Leiden, the Netherlands). The intraclass correlation coefficient and percent technical error of measurement for LV mass were 0.96 and 4.52% respectively. Measurement of cIMT has been described in detail.7 cIMT was measured 3 times during the EDIC study, at baseline and years 6 and 12. A single longitudinal lateral view of the distal right and left common carotid arteries was obtained. Studies were performed by certified technicians at clinical centers, recorded on videotapes, and read in a central unit (Tufts University, Boston, Massachusetts) by 2 single readers who were unaware of subjects’ diagnostic groups, treatment assignments, and time of studies. Mean of the maximum IMT of the common carotid artery was defined as the mean of the maximum value for the near and far walls on the right and left sides. Intraclass correlation coefficient for cIMT measurements was 0.71. Because there was only a single measure available for cardiac MRI, we

Women Primary Intensive DCCT baseline Age (years) Adult Diabetes duration (years) Smoker Body mass index (kg/ m2) Hemoglobin A1c Serum cholesterol Total (mg/dl) High-density lipoprotein (mg/dl) Low-density lipoprotein (mg/dl) Triglycerides (mg/dl) Blood pressure (mm Hg) Systolic Diastolic Renal function Serum creatinine† Log albumin excretion rate (mg/24 hours) Albumin excretion rate ⱖ30 mg/24 hours Estimated glomerular filtration rate (ml/ min/1.73 m2) Estimated glomerular filtration rate ⬍60 ml/min/1.73 m2 Weight gain (DCCT baseline to closeout)

Included (n ⫽ 889)

Excluded (n ⫽ 552)

p Value*

47.5% 49.0% 51.2%

46.7% 52.5% 46.4%

0.787 0.197 0.076

27 ⫾ 7 88.3% 5.8 ⫾ 4.2 16.1% 23.3 ⫾ 2.7

27 ⫾ 8 83.5% 5.4 ⫾ 4.1 22.3% 23.5 ⫾ 3.0

0.775 0.010 0.072 0.003 0.411

8.7% ⫾ 1.5

9.1% ⫾ 1.7

⬍0.0001

175 ⫾ 33 50 ⫾ 12

178 ⫾ 34 51 ⫾ 12

0.309 0.466

109 ⫾ 29

110 ⫾ 30

0.910

79 ⫾ 45

85 ⫾ 51

0.029

114 ⫾ 11 73 ⫾ 8

115 ⫾ 12 73 ⫾ 9

0.080 0.570

0.81 ⫾ 0.15 2.39 ⫾ 0.78

0.80 ⫾ 0.15 2.47 ⫾ 0.80

0.344 0.098

9.8%

12.7%

0.086

114 ⫾ 28

0.183

112 ⫾ 26

0%

6.9 ⫾ 7.8

0.4%

0.073

8.3 ⫾ 9.4

0.061

* Based on chi-square test for categorical variables and Wilcoxon ranksum test for continuous variables. † No one had serum creatinine ⱖ2 mg/dl at Diabetes Control and Complications Trial baseline.

used the cIMT measure from EDIC year 12 because this was obtained closest to the time of the cardiac MRI study. During the DCCT participants underwent an annual medical history and physical examination, electrocardiography, and laboratory testing for fasting lipid levels, serum creatinine values, and other risk factors for cardiovascular disease.4 Glycated hemoglobin (hemoglobin A1c) values were measured quarterly.8 During the EDIC follow-up study the same methods used in the DCCT were continued, but hemoglobin A1c was measured annually, and fasting lipid levels and renal function indexes were measured in alternate years. Hypertension was defined as blood pressure ⱖ140/90 mm Hg or use of antihypertensive medications.5 Hyperlipidemia was defined as low-density lipoprotein (LDL) levels ⱖ130 mg/dl or use of lipid-lowering medication. Macroalbuminuria was defined by urinary excretion of

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Table 2 Clinical characteristics of participants immediately before or at time of cardiac magnetic resonance scan by gender Variable White Attained age (years) Attained duration of diabetes mellitus (years) Current cigarette smoker Body mass index (kg/m2) Body mass index ⱖ25 kg/m2 Body mass index ⱖ30 kg/m2 Natural waist-to-hip ratio Mean systolic blood pressure (mm Hg) Mean diastolic blood pressure (mm Hg) Hypertension† Antihypertensive medication Hemoglobin A1c Before cardiac magnetic resonance imaging Mean hemoglobin A1c Mean high-density lipoprotein cholesterol (mg/dl) Mean low-density lipoprotein cholesterol (mg/dl) Mean total cholesterol (mg/dl) Mean triglyceride (mg/dl) Hypercholesterolemia‡ Lipid-lowering medication Albumin excretion rate ⱖ30 mg/24 hours or end-stage renal disease (sustained) Albumin excretion rate ⱖ300 mg/24 hours or end-stage renal disease (ever) Estimated glomerular filtration rate ⬍60 ml/min/1.73 m2 Left ventricular mass/body surface area (g/m2) Common intima–media thickness year 12 (mm) Any angiotensin-converting enzyme inhibitor or angiotensin receptor blocker Any ␤ blocker

Women (n ⫽ 422)

Men (n ⫽ 467)

p Value*

96.7% 49 ⫾ 7 27.8 ⫾ 4.9 10.7% 27.9 ⫾ 5.3 67.1% 30.3% 0.80 ⫾ 0.07 115 ⫾ 8 72 ⫾ 5 45.0% 36.3%

96.6% 50 ⫾ 6 27.4 ⫾ 4.8 12.0% 28.2 ⫾ 4.1 75.8% 31.1% 0.91 ⫾ 0.07 120 ⫾ 7 76 ⫾ 5 52.9% 44.5%

0.857 0.005 0.207 0.533 0.043 0.004 0.817 ⬍0.0001 ⬍0.0001 ⬍0.0001 0.019 0.012

8.0 ⫾ 1.3 8.0 ⫾ 1.0 60 ⫾ 12 110 ⫾ 20 186 ⫾ 23 78 ⫾ 35 54.3% 47.6% 23.7%

7.8 ⫾ 1.2 7.9 ⫾ 1.0 50 ⫾ 11 111 ⫾ 21 178 ⫾ 24 89 ⫾ 45 72.4% 67.5% 28.3%

0.063 0.282 ⬍0.0001 0.523 ⬍0.0001 0.0006 ⬍0.0001 ⬍0.0001 0.121

6.6%

11.4%

0.015

7.8 64.0 ⫾ 10.3 0.65 ⫾ 0.10 49.1%

4.9 76.5 ⫾ 12.2 0.71 ⫾ 0.16 58.7%

0.075 ⬍0.0001 ⬍0.0001 0.004

8.1%

7.9%

0.941

Values are presented as mean ⫾ SD or percentage. * Based on chi-square test for categorical variables and Wilcoxon rank-sum test for continuous variables. † Blood pressure ⱖ140/90 mm Hg or use of antihypertensive medications. ‡ Low-density lipoprotein levels ⱖ130 mg/dl or use of lipid-lowering medication.

albumin ⱖ300 mg during a 24-hour period or end-stage renal disease. Clinical characteristics of DCCT/EDIC participants, measured immediately before or at time of cardiac MR scan, are reported as mean ⫾ SD or percentage as appropriate. Differences between participants and nonparticipants or men and women were compared using Wilcoxon rank-sum test for quantitative variables and chi-square test for categorical variables. Adjustment for body size was made by dividing LV mass by body surface area (LV mass index). Relation between cIMT and LV mass index was evaluated using the Spearman correlation coefficient. Multivariable linear regression models were used to study the association between LV mass and cIMT after adjusting for basic covariates: age, gender, MRI scan, primary versus secondary cohort, and cIMT reader and machine. Further models included cardiovascular risk factors: current smoking, mean systolic blood pressure over the DCCT/EDIC, mean LDL cholesterol, mean hemoglobin A1c, attained duration of DM, and history of macroalbuminuria. Covariate mean values were weighted means where values at each visit were weighted by the interval between values owing to differences in visit schedules during the DCCT and EDIC. The

most significant factor for the multivariate association among similar variables (e.g., systolic and diastolic blood pressures) was used. Strength of a covariate effect was measured by the semipartial type II R2, which is the change in model R2 when that covariate is dropped from the model, expressed as a percentage. The 2-way interaction between cIMT and each risk factor was assessed, and the interaction of cIMT and attained DM duration was significant in the final full model. cIMT and DM duration are continuous variables so the slope for regression of LV mass on cIMT over the range of attained duration is presented. All analyses were performed using SAS 9.2 (SAS Institute, Cary, North Carolina). A p value ⬍0.05 was considered statistically significant. Results Cardiac MRI and cIMT measurements were available in 889 participants (Figure 1). Comparison of included subjects to excluded subjects (Table 1) showed no significant differences in age, gender, DM duration, treatment assigned, renal function, body mass index, systolic and diastolic blood pressures, or total cholesterol levels. However,

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Table 3 Association of common carotid intima–media thickness with left ventricular mass/body surface area after minimal adjustment (basic model) and adjustment for other risk factors (fully adjusted model) LV Mass (g/m2)

Variable Basic Model* (R2 ⫽ 30%)

Age Men vs women Cohort† (secondary vs primary) Smoking Attained duration (per year) Mean systolic blood pressure‡ Mean low-density lipoprotein‡ Mean hemoglobin A1c‡ Albumin excretion rate ⱖ300 mg/24 hours/end-stage renal disease Common intima–media thickness (per 0.1 mm)

Fully Adjusted Model (R2 ⫽ 40%)

Semipartial R2 (%)

Estimate of Beta ⫾ SE

p Value

Semipartial R2 (%)

Estimate of Beta ⫾ SE

p Value

1.41 19.33 0.35

⫺0.25 ⫾ 0.06 11.84 ⫾ 0.77 ⫺1.56 ⫾ 0.75

⬍0.0001 ⬍0.0001 0.0365

1.14 13.34 0.001 1.10 0.36 2.86 0.74 0.000 08 2.82

⫺0.23 ⫾ 0.06 10.06 ⫾ 0.73 ⫺0.15 ⫾ 1.04 4.34 ⫾ 1.09 ⫺0.24 ⫾ 0.11 0.32 ⫾ 0.05 ⫺0.06 ⫾ 0.02 0.01 ⫾ 0.40 8.27 ⫾ 1.30

⬍0.0001 ⬍0.0001 0.8880 ⬍0.0001 0.0239 ⬍0.0001 0.0011 0.9737 ⬍0.0001

3.79

2.00 ⫾ 0.29

⬍0.0001

1.19 ⫾ 0.29

⬍0.0001

1.22

* Basic model was also adjusted for magnetic resonance imaging machine type and intima–media thickness reader. † Secondary cohort that had diabetes for 1 year to 15 years with mild to moderate nonproliferative retinopathy and urinary albumin excretion rate ⬍200 mg/dl at the Diabetes Control and Complications Trial baseline versus the primary cohort that had diabetes for 1 year to 5 years with no related complications. ‡ Weighted mean of covariate values during the Diabetes Control and Complications Trial and Epidemiology of Diabetes Interventions and Complications combined up to the time of cardiac magnetic resonance imaging when individual visit values were weighted by the interval between visits that differed during the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications. Table 4 Cardiovascular risk factors and association between common carotid intima–media thickness and left ventricular mass after minimal adjustment and adjustment for each risk factor separately Model

Model R2 (%)

Semipartial R2 (%)

Estimate of Beta ⫾ SE

p Value

30.9

1.08 3.31 0.54 3.52 5.14 1.11 0.43 3.69 0.66 3.00 5.64

4.31 ⫾ 1.17 1.88 ⫾ 0.29 ⫺0.30 ⫾ 0.12 1.94 ⫾ 0.29 0.42 ⫾ 0.05 1.15 ⫾ 0.30 ⫺0.04 ⫾ 0.02 1.97 ⫾ 0.29 1.13 ⫾ 0.39 1.81 ⫾ 0.29 10.90 ⫾ 1.24

0.0002 ⬍0.0001 0.0094 ⬍0.0001 ⬍0.0001 ⬍0.0001 0.0200 ⬍0.0001 0.0039 ⬍0.0001 ⬍0.0001

2.58

1.67 ⫾ 0.28

⬍0.0001

Basic model* ⫹ smoking Common intima⫺media thickness (per 0.1 mm) Basic model* ⫹ attained diabetes duration Common intima–media thickness (per 0.1 mm) Basic model* ⫹ mean systolic blood pressure Common intima–media thickness (per 0.1 mm) Basic model* ⫹ mean low-density lipoprotein Common intima–media thickness (per 0.1 mm) Basic model* ⫹ mean hemoglobin A1c Common intima–media thickness (per 0.1 mm) Basic model* ⫹ any albumin excretion rate ⱖ300 mg/24 hours or end-stage renal disease (ever) Common intima–media thickness (per 0.1 mm)

31.4 36.5 32.3 32.1 37.0

* Basic model adjusted for attained age, gender, study cohort, magnetic resonance imaging machine type, intima–media thickness reader, and machine type.

hemoglobin A1c levels, percentage of participants who were current smokers, and total triglyceride levels were significantly lower in subjects included in the present study versus values in those not included. Clinical characteristics of study participants at time of cardiac MRI stratified by gender are presented in Table 2. Most participants were white and 53% were men. Mean age was slightly older for men than women. Men had higher body mass index, higher systolic blood pressure, higher diastolic blood pressure, higher triglyceride levels, and lower high-density lipoprotein cholesterol than women and were more likely to be on antihypertensive and lipid-lowering medications than women. Men were also more likely to have albuminuria. Men and women

had similar attained duration of DM, weighted hemoglobin A1c levels, and LDL cholesterol levels. A smaller proportion of women than men were on angiotensinconverting enzyme inhibitors or angiotensin receptor blockers. LV mass indexed for body surface area and cIMT measurements were significantly higher in men than women and cIMT was significantly higher in men compared to women (Table 2). cIMT was significantly correlated with LV mass (r ⫽ 0.33, p ⬍0.0001) and LV mass indexed to body surface area (r ⫽ 0.28, p ⬍0.0001). In the basic adjusted model LV mass index was greater by 2 g/m2 for every 0.1-mm higher common cIMT (semipartial R2 ⫽ 3.8%, p ⬍0.0001; Table 3, basic model). In a model further adjusted for current

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Figure 2. Slope for regression of left ventricular mass indexed by body surface area per 0.1-mm change in carotid intima–media thickness (grams per square meter per 0.1 mm) (y axis) where the slope decreases as a function of increasing attained duration (years) of type 1 diabetes mellitus (x axis) (beta ⫽ ⫺0.12 ⫾ 0.05, p ⫽ 0.0071).

smoking, presence of macroalbuminuria/end-stage renal disease, attained DM duration, mean systolic blood pressure, mean LDL cholesterol, and hemoglobin A1c, the association between LV mass and cIMT was attenuated but remained statistically significant (Table 3, fully adjusted model). Proportion of variability explained by covariates included in the basic model was 30% and that by the fully adjusted model was 40%. To assess the effect of individual risk factors on the relation between cIMT and LV mass index, we further developed a series of regression models over the basic model where each risk factor was added individually to the basic model (Table 4). We compared the R2 of the new model thus generated to the R2 of the basic model and the change if any for the beta coefficient between cIMT and LV mass index. The greatest changes in the model R2 and the semipartial R2 for cIMT were seen after adding mean systolic blood pressure or a history of endstage renal disease to the basic model, whereas other risk factors only minimally changed these R2 values. Although the 2 models including systolic blood pressure or end-stage renal disease were comparable in extent of variability explained for LV mass, the model obtained by adding systolic blood pressure decreased the beta estimate for cIMT by 42.5%, whereas end-stage renal disease decreased the beta estimate for cIMT by only 16.5%. We further assessed possible interactions between individual risk factors in the final model and cIMT in relation to LV mass. After correcting for multiple tests, the interaction of attained DM duration with cIMT on LV mass was significant. Interestingly, an inverse interaction was observed such that patients with shorter disease duration had a stronger association between cIMT and LV mass compared to those who had DM for a longer time (Figure 2). There were no significant interactions between other cardiovascular risk factors and effect of cIMT on LV mass.

Discussion In this study we found that in a population of wellcharacterized patients with type 1 DM, there was a strong association between ultrasound measurements of carotid wall thickness and MRI-determined LV mass. The association was most significantly attenuated (almost 50%) after addition of mean systolic blood pressure and changed minimally with addition of other risk factors, suggesting this relation is mediated predominantly through blood pressure– dependent mechanisms. Furthermore, patients with shorter duration of DM exhibited a more marked association between cIMT and LV mass. These findings suggest that parallel vascular and cardiac structural changes occur in patients with type 1 DM. LV mass and cIMT share common determinants such as age, gender, and body size and are affected by cardiovascular risk factors that occur with greater frequency in the type 1 DM population compared to age-matched nondiabetics. Although these subclinical target organ changes could be the result of common pathophysiologic pathways such as hemodynamic factors, neurohormonal influences, or atherosclerotic processes, it is not known whether the association between LV mass and cIMT is an interdependent bidirectional association or an actual cause– effect relation. Vascular remodeling is thought to be a composite of adaptive and atherosclerotic responses to altered hemodynamic load and accumulation of risk factors.9 Association between LV mass and cIMT could represent a compensatory adaptation to increased hemodynamic load in the 2 end organs and studies have shown that the relation is mediated mainly through hypertrophic responses.10 Findings from previous studies and the present study show that the relation between LV mass and cIMT persists even after adjusting for established risk factors, supporting an independent direct relation. The relation between cIMT and LV mass has been previously studied in a healthy population,11 a community-

Miscellaneous/Carotid and Ventricular Remodeling in Diabetes

dwelling older population,2 primary and secondary hypertension,12–14 patients with previous myocardial infarction,15 patients with type 2 DM,16 and patients with end-stage renal disease.17 In these studies the strength of association (r) between LV mass and cIMT measurements ranged from 0.20 to 0.62. A weaker relation was seen in patients with greater atherosclerotic burden (older population, patients with previous myocardial infarction) and a stronger relation was observed in hypertensive populations. The weaker relation observed in older patients and those with previous myocardial infarction could be due to the use of lipidlowering medications and angiotensin-converting enzyme inhibitors, which modify structural changes in arterial walls and cardiac structure. In the present study the long duration of DM (27 years) may have also resulted in weaker associations between LV mass and cIMT than in previous reports. Strength of the relation between LV mass and cIMT in the present study is within the range of previously published results. Although a direct comparison is not possible, our study findings are intermediate in this spectrum indicating that in a type 1 DM population, the relation between LV mass and cIMT may be mediated through a complex interplay of several different factors representing diabetic, atherosclerotic, and hemodynamic alterations in this population. We found that the slope of the relation between cIMT and LV mass was stronger for those with shorter duration of DM than in those with longer duration of DM. This could mean that the association is stronger early in the course of DM and shows a plateau effect with longer disease duration or that there is dissociation between these 2 parameters later in the course of DM. One possible explanation is the initiation over time of more aggressive risk factor decrease especially with drugs such as angiotensin-converting enzyme inhibitors and ␤ blockers, which have protective effects on ventricular remodeling. In the present study ⬎50% of participants were treated with angiotensin-converting enzyme inhibitors. Such drugs are being increasingly prescribed early in the course of the DM, possibly modifying the natural progression of the disease. This is further heightened by the fact that patients with type 1 DM currently have an exceptionally improved survival and life expectancy than that seen some decades ago. Moreover, our subjects were extensively monitored and treated for risk factors and complications such as nephropathy, neuropathy, and retinopathy, had strictly controlled hemoglobin A1c levels (all ⬍8), and relatively well-controlled other risk factors such as blood pressure and cholesterol levels (Table 2). Another possible mechanism of this observed relation with disease duration could be the opposite effects that DM duration has on cIMT and LV mass. In the DCCT/EDIC study DM duration has been shown to have an independent positive relation with cIMT7 and an inverse relation with LV mass (fully adjusted model in Table 4). Although no other risk factor had a significant interaction with the relation between cIMT and LV mass, it could also be true that the small variation in risk factors in the present study might limit the power to observe additional interactions between cIMT and these risk factors. This study is the first to describe the parallel relation between carotid wall thickness and LV mass in a large population of patients with type 1 DM taking into account

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the association of risk factors on these target organs. LV mass was determined using MRI, which is the gold standard for accurate estimation of cardiac parameters. Potential limitations of this study are that the study population might not be representative of the general DM population because this is a long-term observational study of a clinical trial where participants received close monitoring and follow-up. Carotid wall area, lumen diameter, and carotid plaque measurements were not available in the present study. Furthermore, we did not take into account patterns of LV hypertrophy (eccentric vs concentric). Moreover, this is a cross-sectional study because cardiac MRI was available at only 1 time point; hence, it is not possible to draw causal inferences. Cardiovascular disease is the leading cause of premature mortality in type 1 DM over and above that estimated from traditional cardiovascular disease risk factors. Accurate risk estimation and subsequent modifications with therapy are important goals for improved clinical outcomes in such patients. This study shows that even with well-controlled risk factors, subclinical alterations in cIMT and LV mass, which are independent predictors of cardiovascular disease events, occur in parallel to each other. Although there is a significant relation between these measurements, the association is not absolute, warranting the clinical evaluation of each component for better risk profiling. Further studies in type 1 DM populations using carotid and cardiac imaging markers for risk reclassification should be evaluated. Acknowledgments: The authors acknowledge the data processing and technical assistance of Wanyu Hsu, BS at the Biostatistics Center, George Washington University. Appendix A complete list of the members of the DCCT/EDIC Research Group is provided in the supplementary appendix published in the New England Journal of Medicine 2011; 365:2366 –2376. Participating radiologists and technologists are listed in the online-only data supplement in Circulation 2011;124:1737–1746. Industry contributors have had no role in the DCCT/EDIC study but have provided free or discounted supplies or equipment to support participants’ adherence to the study: Abbott Diabetes Care (Alameda, California), Animas (Westchester, Pennsylvania), Bayer Diabetes Care (North America Headquarters, Tarrytown, New York) Becton Dickinson (Franklin Lakes, New Jersey), CanAm (Atlanta, Georgia), Eli Lilly (Indianapolis, Indiana), Lifescan (Milpitas, California), Medtronic Diabetes Minneapolis, Michigan), Omron (Shelton, Connecticut), OmniPod® Insulin Management System (Bedford, Massachusetts), Roche Diabetes Care (Indianapolis, Indiana), and Sanofi-Aventis (Bridgewater, New Jersey). 1. Cuspidi C, Giudici V, Meani S, Negri F, Sala C, Zanchetti A, Mancia G. Extracardiac organ damage in essential hypertensives with left ventricular concentric remodelling. J Hum Hypertens 2010;24:380 – 386. 2. Kronmal RA, Smith VE, O’Leary DH, Polak JF, Gardin JM, Manolio TA. Carotid artery measures are strongly associated with left ventric-

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3.

4. 5.

6.

7.

8. 9. 10.

The American Journal of Cardiology (www.ajconline.org)

ular mass in older adults (a report from the Cardiovascular Health Study). Am J Cardiol 1996;77:628 – 633. Shigematsu Y, Hamada M, Ohtsuka T, Hashida H, Ikeda S, Kuwahara T, Hara Y, Kodama K, Hiwada K. Left ventricular geometry as an independent predictor for extracardiac target organ damage in essential hypertension. Am J Hypertens 1998;11:1171–1177. DCCT Research Group. The Diabetes Control and Complications Trial (DCCT). Design and methodologic considerations for the feasibility phase. Diabetes 1986;35:530 –545. Epidemiology of Diabetes Interventions and Complications (EDIC). Design, implementation, and preliminary results of a long-term follow-up of the Diabetes Control and Complications Trial cohort. Diabetes Care 1999;22:99 –111. Turkbey EB, Backlund JY, Genuth S, Jain A, Miao C, Cleary PA, Lachin JM, Nathan DM, van der Geest RJ, Soliman EZ, Liu CY, Lima JA, Bluemke DA; DCCT/EDIC Research Group. Myocardial structure, function, and scar in patients with type 1 diabetes mellitus. Circulation 2011;124:1737–1746. Epidemiology of Diabetes Interventions and Complications (EDIC) Research Group. Effect of intensive diabetes treatment on carotid artery wall thickness in the epidemiology of diabetes interventions and complications. Diabetes 1999;48:383–390. DCCT Research Group. Feasibility of centralized measurements of glycated hemoglobin in the Diabetes Control and Complications Trial: a multicenter study. Clin Chem 1987;33:2267–2271. Bots ML, Hofman A, Grobbee DE. Increased common carotid intima– media thickness. Adaptive response or a reflection of atherosclerosis? Findings from the Rotterdam Study. Stroke 1997;28:2442–2447. Meijs MF, Doevendans PA, Cramer MJ, Vonken EJ, Velthuis BK, van der Graaf Y, Visseren FL, Mali WP, Bots ML; SMART Study Group. Relation of common carotid intima–media thickness with left ventricular mass caused by shared risk factors for hypertrophy. J Am Soc Echocardiogr 2009;22:499 –504.

11. Muiesan ML, Salvetti M, Zulli R, Pasini GF, Bettoni G, Monteduro C, Rizzoni D, Castellano M, Agabiti-Rosei E. Structural association between the carotid artery and the left ventricle in a general population in Northern Italy: the Vobarno study. J Hypertens 1998;16: 1805–1812. 12. Cuspidi C, Mancia G, Ambrosioni E, Pessina A, Trimarco B, Zanchetti A; APROS Investigators. Left ventricular and carotid structure in untreated, uncomplicated essential hypertension: results from the Assessment Prognostic Risk Observational Survey (APROS). J Hum Hypertens 2004;18:891– 896. 13. Muiesan ML, Rizzoni D, Salvetti M, Porteri E, Monteduro C, Guelfi D, Castellano M, Garavelli G, Agabiti-Rosei E. Structural changes in small resistance arteries and left ventricular geometry in patients with primary and secondary hypertension. J Hypertens 2002;20:1439 – 1444. 14. Rizzoni D, Muiesan ML, Porteri E, Salvetti M, Castellano M, Bettoni G, Tiberio G, Giulini SM, Monteduro C, Garavelli G, Agabiti-Rosei E. Relations between cardiac and vascular structure in patients with primary and secondary hypertension. J Am Coll Cardiol 1998;32:985– 992. 15. Agewall S, Henareh L, Jogestrand T. Intima–media complex of both the brachial artery and the common carotid artery are associated with left ventricular hypertrophy in patients with previous myocardial infarction. J Hypertens 2005;23:119 –125. 16. Poppe KK, Whalley GA, Somaratne JB, Keelan S, Bagg W, Triggs CM, Doughty RN. Role of echocardiographic left ventricular mass and carotid intima–media thickness in the cardiovascular risk assessment of asymptomatic patients with type 2 diabetes mellitus. Intern Med J 2011;41:391–398. 17. London GM, Guerin AP, Marchais SJ, Pannier B, Safar ME, Day M, Metivier F. Cardiac and arterial interactions in end-stage renal disease. Kidney Int 1996;50:600 – 608.