Increased arterial stiffness in childhood onset diabetes: a cardiovascular magnetic resonance study

Increased arterial stiffness in childhood onset diabetes: a cardiovascular magnetic resonance study Abstract Aims Arterial stiffness is a strong predictor of cardiovascular events. We aimed to assess the impact of type 1 diabetes (T1D) on arterial stiffness and cardiac function in young adults. Methods and results Aortic pulse wave velocity (PWV), distensibility, left ventricular (LV) function and LV mass were measured by cardiovascular magnetic resonance imaging (CMR) in 47 T1D patients and 33 healthy controls. All were participants in the Atherosclerosis and Childhood Diabetes study, with baseline values registered 5 years previously. The patients had a mean age of 20.8 years and a median duration of diabetes of 10.0 years. PWV was significantly higher in the diabetes group compared with controls, mean 4.10 (SD = 4.58) vs. 3.90 (SD = 4.04) m/s, P = 0.045. In the diabetes group, insulin pump users at baseline had lower PWV than multiple injection users, mean 3.94 (SD = 0.38) vs. 4.23 (SD = 0.48) m/s, P = 0.028. Also in the diabetes group, multiple regression analysis identified C-reactive protein (CRP), female gender and insulin pump use as independent baseline risk factors for PWV 5 years later. There was no difference in cardiac function or LV mass between the diabetes and control groups. Conclusion In this prospective study, we found increased PWV assessed by CMR in young adults with T1D compared with controls. Also, CRP, female gender and insulin pump use emerged as independent baseline risk factors for PWV 5 years later. arterial stiffness, type 1 diabetes, cardiovascular magnetic resonance imaging, pulse wave velocity, C-reactive protein Introduction Patients with type 1 diabetes (T1D) suffer from increased morbidity and mortality from cardiovascular disease (CVD).1 There is insufficient knowledge about the early phases of atherosclerosis, which makes decisions on whether or not to prescribe life-long preventive medication to children and young adults challenging, particularly in patients with existing risk factors like T1D.2 This is partly due to the lack of clinically useful techniques to precisely measure subclinical atherosclerosis. Arterial stiffness is a strong predictor of cardiovascular events and all-cause mortality.3 It is involved in the pathogenesis of atherosclerosis, primarily by being a determinant of systolic hypertension.4 Several measures of arterial stiffness have been employed, but pulse wave velocity (PWV) has been considered the gold standard.5 Its predictive accuracy has been demonstrated in a number of studies.6,7 To date, ultrasound and tonometry have been the most widely used methods for assessing PWV by measuring the travel time of a pulse wave on two levels (usually carotid-femoral) and estimate the travel distance by tape measure. (PWV = distance/time in m/s.) The estimate of the distance, however, can be inaccurate due to differences between patients in body surface contours and the curvature of the aorta. This inaccuracy can influence the outcome considerably.8 Aortic PWV can also be assessed by cardiovascular magnetic resonance (CMR), which enables precise measurement of the distance and time of travel for the pulse wave through the entire aorta.9,10 CMR has shown good agreement with invasive pressure measurements and a high level of reproducibility.11 In adults, PWV was increased in T1D patients compared with healthy control subjects.12 In the Dallas heart study, aortic arch PWV was associated with non-cardiac vascular events, but not, however, with cardiovascular death or non-fatal cardiac events.13 In childhood onset T1D, a recent study showed a trend toward reduced distensibility in the thoracic aorta, but no difference in PWV compared with healthy control subjects.14 There is a lack of comprehensive longitudinal CMR-studies on arterial stiffness in childhood onset T1D. CMR is currently considered the gold standard for the measurement of right and left ventricular volumes, mass and function, boasting high accuracy and reproducibility.15 Reference values have been published for all these parameters.16 With modern steady-state free precession cine sequences combined with parallel processing techniques, most cine stacks can be acquired in just one breath-hold. Our aim was to assess the impact of T1D on early atherosclerosis by measuring aortic stiffness and both systolic and diastolic cardiac function by CMR, as well as analyse their longitudinal relationship with cardiovascular risk factors, long-term glycaemic control and mode of treatment. Methods Study population The study ‘Atherosclerosis and Childhood diabetes’ (ACD) is a longitudinal, prospective population-based study with follow-up of the participants every fifth year.17 The present study was conducted from 2011 to 2013 as a part of the 5-year follow-up of the ACD study, and participants above 18 years of age were invited. All the diabetes patients who were included used intensified insulin injection treatment (≥4 daily insulin injections) or insulin pumps. None of them had overt retinopathy or nephropathy. To isolate the effect of T1D in early atherosclerosis the participants who smoked, were pregnant, had current infectious disease, were hypertensive, had chronic diseases other than diabetes or were on long-term medication (except insulin and contraceptives) were excluded. A total of 47 diabetes patients and 33 controls were included in the study. They all gave their written informed consent. The protocol was approved by the Norwegian Regional Committee for Research Ethics, and the study was conducted according to the Declaration of Helsinki. The examinations were performed after an overnight fasting period as a part of the 5-year follow-up in the ACD study. Baseline clinical examination and laboratory analyses were available for all diabetes patients and 17 of the controls, and have been described previously.17 From the Norwegian Childhood Diabetes Registry, we were able to obtain annual HbA1c values from 2000 to 2012, all measured at the same DCCT-standardized laboratory using high performance liquid chromatography (Variant; Bio-Rad, Richmond, CA, USA), CV <3%. On average, each patient had 8 HbA1c measurements (range 3–12). From these values, we calculated mean HbA1c at baseline and at follow-up. We also multiplied mean HbA1c by the diabetes duration in years to estimate the glycaemic burden at each time point. Markers of inflammation were assessed as previously reported.18 Other routine laboratory analyses were performed by conventional methods. CMR acquisition and analysis CMR was performed using a 1.5 T Achieva MRI scanner (Philips Healthcare, Best, The Netherlands) under standardized patient conditions, which included a minimum of 10 min supine rest in a quiet room with stable room temperature. No meals, caffeine or smoking was allowed for at least 3 h beforehand. Images were analysed quantitatively using dedicated software (cvi42; Circle Cardiovascular Imaging, Calgary, Canada). Examples are shown in Figure 1. Figure 1 View largeDownload slide Aortic pulse wave velocity and left ventricular function. The figure shows where the phase contrast velocity maps were obtained; across the mitral valve, thin black circle (A), and at two levels of the aorta, thick black lines (B). A standardized approach was used to measure the path length following the mid-line course of the aorta, black broken line. Figure 1 View largeDownload slide Aortic pulse wave velocity and left ventricular function. The figure shows where the phase contrast velocity maps were obtained; across the mitral valve, thin black circle (A), and at two levels of the aorta, thick black lines (B). A standardized approach was used to measure the path length following the mid-line course of the aorta, black broken line. Aortic PWV A retrospectively electrocardiogram (ECG)-gated gradient-echo pulse sequence with velocity encoding was applied to measure through-plane flow at two pre-defined positions in the ascending and abdominal aorta. Both positions were aligned to represent a true perpendicular imaging plane on the aorta. Imaging parameters included the following: echo-time = 7.4 ms (ascending), 6.5 ms (abdominal), repetition time = 12 ms (ascending), 10 ms (abdominal), flip-angle = 20 degrees, slice thickness = 10 mm, field of view = 280 mm, matrix size = 256 × 163 (ascending), 232 × 160 (abdominal), Venc = 190 cm/s (ascending), 160 cm/s (abdominal), scan percentage = 80%. The temporal resolution was approximately 25 ms depending on the heart rate. Aortic PWV was calculated as Δx/Δt (expressed in m/s), where Δx is the aortic path length between the two imaging levels and Δt is the time delay between the arrival of the foot of the pulse wave at these levels. A standardized approach was used to provide consistent data to measure the path length between the middle of both levels (indicated by the curved line following the mid-line course of the aorta in Figure 1). A pre-saturation slab was placed at both levels to identify both imaging planes accurately. The upslopes and the timing of the flow curves were also performed in a standardized way. The intersection of the tangent line to the upstroke, based on the three time points with the greatest acceleration gradients, and the baseline was considered as the arrival time of the pulse wave.9–10 A single observer (K.H.S.), blinded to the clinical status of the subjects, analysed the flow measurements. Aortic PWV was calculated twice within 4–8 weeks to examine intra-observer variability, Aortic distensibility Distensibility of the aorta derived from flow measurements at the mid-ascending aorta was calculated using the following formula: D = (Amax − Amin)/(Amin × pulse pressure)19 where D = distensibility (mmHg−1), Amax = maximal aortic area (mm2), Amin = minimal aortic area (mm2), pulse pressure = systolic blood pressure (BP) – diastolic BP (mmHg). The BP was recorded using a semi-automated sphygmomanometer (Champion, Riester, Ventura, CA, USA) in conjunction with the CMR examination. Mean arterial pressure (MAP) was calculated as [systolic BP + (2 × diastolic BP)]/3. The aortic area was calculated in a semi-automatic way, based on automatic contour detection by density profiles of the maximal and minimal areas and manual correction when neighbouring vessels had areas of tangent contours. Aortic contours were drawn twice within 4–8 weeks to assess intra-observer variability in distensibility. LV function The entire heart was imaged in the short-axis orientation using ECG-gated breath-hold multishot echo-planar imaging as described previously.20 Imaging parameters included the following: echo time = 1.6 ms, repetition time = 3.2 ms, temporal resolution = 35–40 ms per cardiac phase, depending on the heart rate, flip angle = 60 degrees, slice thickness = 8 mm, field of view = 350 mm, matrix size = 172 × 184. Cardiac volumes, ejection fraction and left ventricular mass were also assessed. Furthermore, an ECG-gated gradient-echo sequence with velocity encoding was performed to measure blood flow across the mitral valve for the determination of LV diastolic function. Imaging parameters included the following: echo time = 6.8 ms, repetition time = 10 ms, flip angle = 20 degrees, slice thickness = 10 mm, field of view = 340 mm, matrix size = 220 × 175, Venc = 150 cm/s, scan percentage = 83%. In each cardiac phase, the area of the mitral valve was manually traced, and the corresponding flow vs. time curve was derived automatically. Flow velocities in early diastole (E) and at atrial contraction (A) were assessed and the early peak filling rate, which is the maximal flow rate of E, the atrial peak filling rate, which is the maximal flow rate of A, and the ratio of E and A peak filling rates (E/A) were used for analysis. Furthermore, the peak acceleration and peak deceleration gradients of E were calculated. Statistical analysis Demographic and clinical data are presented as either proportions, means with their standard deviations (SD) or medians with the 25th and 75th percentile. Differences in continuous variables between groups were tested with the Student t-test, alternatively the Mann–Whitney U test for non-normally distributed data. For categorical data, a χ2 test was used. Correlation analyses between continuous variables were performed for diabetes patients and controls separately using Pearson's correlation coefficient (r) for normally distributed data, or otherwise Spearman’s rho ( ρ). To avoid false negative results, type II errors, methods to correct for multiple testing have not been applied. Linear regression analysis was performed to study the association between current conventional risk factors as exposure variables with PWV and EA Peak ratio as outcome variables. To identify possible confounders, we studied all variables that could influence the outcome. Only variables with significant relationships with both the exposure and the outcome variables were considered as possible confounders and included in the analysis. Adjustment for multiple confounding factors was conducted by linear regression analysis with a manual backward elimination procedure. A significance level of 5% was applied. To identify possible independent baseline risk factors for outcomes 5 years later, univariable regression analysis was employed. A significance level of 20% was deemed necessary for a variable to be included in the regression model. Subsequently, a manual backward stepwise elimination procedure was performed. A significance level of 5% was used for the final model. All statistical analyses were performed using IBM SPSS Statistics for Macintosh, version 19.0 (Armonk, NY, USA: IBM Corp.). Results The clinical and metabolic characteristics of the patients at baseline and follow-up are shown in Table 1. Table 1 Clinical and metabolic characteristics at baseline and 5-year follow-up Baseline 5-year follow-up Diabetes Controls P-value Diabetes Controls P-value n 47 17 47 33 Diabetes duration (years)a 5.3 (3.2, 9.5) 10.0 (7.9, 14.1) Insulin pump users n (%) 20 (42.6) 23 (48.9) Age (years) 15.9 (1.8) 15.4 (2.0) 0.291 20.8 (1.8) 21.1 (1.9) 0.419 Girls, n (%) 23 (48.9) 9 (52.9) 0.777 23 (48.9) 18 (54.5) 0.656 Height (cm) 170.3 (8.9) 170.3 (7.8) 0.995 174.3 (8.5) 175.0 (9.2) 0.756 Weight (kg) 66.1 (15.2) 59.0 (12.2) 0.066 78.4 (15.5) 72.4 (14.8) 0.082 BMI (kg/m2)a 21.6 (19.3, 25.2) 19.0 (17.9, 23.7) 0.025 23.8 (22.6, 28.0) 22.9 (20.5, 25.9) 0.055 Waist circumference (cm) 76.5 (9.8) 69.5 (6.4) 0.011 83.8 (10.5) 77.9 (10.0) 0.013 Systolic blood pressure (mmHg) 104.8 (11.1) 104.6 (10.8) 0.944 115.6 (11.5) 114.4 (8.8) 0.620 Diastolic blood pressure (mmHg) 62.1 (9.5) 60.5 (6.2) 0.455 69.8 (9.0) 69.9 (7.3) 0.947 Pulse pressure (mmHg) 42.8 (7.7) 44.1 (9.3) 0.571 45.8 (9.1) 44.5 (8.8) 0.538 HbA1c (%) [mmol/mol, SD] 8.2 (1.0) [66, 10.9] 5.3 (0.3) [34, 3.3] <0.001 8.7 (1.3) [72, 14.2] 5.2 (0.3) [33, 3.3] <0.001 Mean HbA1c (%) [mmol/mol, SD] 7.9 (1.1) [63, 12.0] 8.3 (1.0) [67, 10.9] Glycaemic burden (% x years) 51.8 (34.8) 93.6 (36.0) Total cholesterol (mmol/L) 4.5 (0.7) 4.0 (0.7) 0.009 4.8 (1.0) 4.5 (0.9) 0.101 HDL (mmol/L) 1.7 (0.5) 1.6 (0.4) 0.285 1.6 (0.4) 1.6 (0.5) 0.940 LDL (mmol/L) 2.5 (0.6) 2.1 (0.6) 0.035 2.8 (0.8) 2.5 (0.7) 0.112 Triglycerides (mmol/L)a 0.7 (0.6, 0.9) 0.6 (0.4, 0.7) 0.206 1.0 (0.7, 1.5) 1.0 (0.7, 1.5) 0.784 Total cholesterol/HDL cholesterol 2.8 (0.6) 2.7 (0.7) 0.575 3.3 (1.1) 3.1 (1.0) 0.495 ApoB/ApoA-I 0.52 (0.12) 0.65 (0.52) 0.339 0.61 (0.16) 0.55 (0.19) 0.147 Urine albumin/creatinine (mg/mmol)a 0.50 (0.30, 1.28) 0.77 (0.35, 1.64) 0.669 0.57 (0.24, 1.19) 0.28 (0.13, 0.96) 0.300 Baseline 5-year follow-up Diabetes Controls P-value Diabetes Controls P-value n 47 17 47 33 Diabetes duration (years)a 5.3 (3.2, 9.5) 10.0 (7.9, 14.1) Insulin pump users n (%) 20 (42.6) 23 (48.9) Age (years) 15.9 (1.8) 15.4 (2.0) 0.291 20.8 (1.8) 21.1 (1.9) 0.419 Girls, n (%) 23 (48.9) 9 (52.9) 0.777 23 (48.9) 18 (54.5) 0.656 Height (cm) 170.3 (8.9) 170.3 (7.8) 0.995 174.3 (8.5) 175.0 (9.2) 0.756 Weight (kg) 66.1 (15.2) 59.0 (12.2) 0.066 78.4 (15.5) 72.4 (14.8) 0.082 BMI (kg/m2)a 21.6 (19.3, 25.2) 19.0 (17.9, 23.7) 0.025 23.8 (22.6, 28.0) 22.9 (20.5, 25.9) 0.055 Waist circumference (cm) 76.5 (9.8) 69.5 (6.4) 0.011 83.8 (10.5) 77.9 (10.0) 0.013 Systolic blood pressure (mmHg) 104.8 (11.1) 104.6 (10.8) 0.944 115.6 (11.5) 114.4 (8.8) 0.620 Diastolic blood pressure (mmHg) 62.1 (9.5) 60.5 (6.2) 0.455 69.8 (9.0) 69.9 (7.3) 0.947 Pulse pressure (mmHg) 42.8 (7.7) 44.1 (9.3) 0.571 45.8 (9.1) 44.5 (8.8) 0.538 HbA1c (%) [mmol/mol, SD] 8.2 (1.0) [66, 10.9] 5.3 (0.3) [34, 3.3] <0.001 8.7 (1.3) [72, 14.2] 5.2 (0.3) [33, 3.3] <0.001 Mean HbA1c (%) [mmol/mol, SD] 7.9 (1.1) [63, 12.0] 8.3 (1.0) [67, 10.9] Glycaemic burden (% x years) 51.8 (34.8) 93.6 (36.0) Total cholesterol (mmol/L) 4.5 (0.7) 4.0 (0.7) 0.009 4.8 (1.0) 4.5 (0.9) 0.101 HDL (mmol/L) 1.7 (0.5) 1.6 (0.4) 0.285 1.6 (0.4) 1.6 (0.5) 0.940 LDL (mmol/L) 2.5 (0.6) 2.1 (0.6) 0.035 2.8 (0.8) 2.5 (0.7) 0.112 Triglycerides (mmol/L)a 0.7 (0.6, 0.9) 0.6 (0.4, 0.7) 0.206 1.0 (0.7, 1.5) 1.0 (0.7, 1.5) 0.784 Total cholesterol/HDL cholesterol 2.8 (0.6) 2.7 (0.7) 0.575 3.3 (1.1) 3.1 (1.0) 0.495 ApoB/ApoA-I 0.52 (0.12) 0.65 (0.52) 0.339 0.61 (0.16) 0.55 (0.19) 0.147 Urine albumin/creatinine (mg/mmol)a 0.50 (0.30, 1.28) 0.77 (0.35, 1.64) 0.669 0.57 (0.24, 1.19) 0.28 (0.13, 0.96) 0.300 Significant differences in bold Mean values (SD). SD, standard deviation. a Median (25th and 75th percentiles). Table 1 Clinical and metabolic characteristics at baseline and 5-year follow-up Baseline 5-year follow-up Diabetes Controls P-value Diabetes Controls P-value n 47 17 47 33 Diabetes duration (years)a 5.3 (3.2, 9.5) 10.0 (7.9, 14.1) Insulin pump users n (%) 20 (42.6) 23 (48.9) Age (years) 15.9 (1.8) 15.4 (2.0) 0.291 20.8 (1.8) 21.1 (1.9) 0.419 Girls, n (%) 23 (48.9) 9 (52.9) 0.777 23 (48.9) 18 (54.5) 0.656 Height (cm) 170.3 (8.9) 170.3 (7.8) 0.995 174.3 (8.5) 175.0 (9.2) 0.756 Weight (kg) 66.1 (15.2) 59.0 (12.2) 0.066 78.4 (15.5) 72.4 (14.8) 0.082 BMI (kg/m2)a 21.6 (19.3, 25.2) 19.0 (17.9, 23.7) 0.025 23.8 (22.6, 28.0) 22.9 (20.5, 25.9) 0.055 Waist circumference (cm) 76.5 (9.8) 69.5 (6.4) 0.011 83.8 (10.5) 77.9 (10.0) 0.013 Systolic blood pressure (mmHg) 104.8 (11.1) 104.6 (10.8) 0.944 115.6 (11.5) 114.4 (8.8) 0.620 Diastolic blood pressure (mmHg) 62.1 (9.5) 60.5 (6.2) 0.455 69.8 (9.0) 69.9 (7.3) 0.947 Pulse pressure (mmHg) 42.8 (7.7) 44.1 (9.3) 0.571 45.8 (9.1) 44.5 (8.8) 0.538 HbA1c (%) [mmol/mol, SD] 8.2 (1.0) [66, 10.9] 5.3 (0.3) [34, 3.3] <0.001 8.7 (1.3) [72, 14.2] 5.2 (0.3) [33, 3.3] <0.001 Mean HbA1c (%) [mmol/mol, SD] 7.9 (1.1) [63, 12.0] 8.3 (1.0) [67, 10.9] Glycaemic burden (% x years) 51.8 (34.8) 93.6 (36.0) Total cholesterol (mmol/L) 4.5 (0.7) 4.0 (0.7) 0.009 4.8 (1.0) 4.5 (0.9) 0.101 HDL (mmol/L) 1.7 (0.5) 1.6 (0.4) 0.285 1.6 (0.4) 1.6 (0.5) 0.940 LDL (mmol/L) 2.5 (0.6) 2.1 (0.6) 0.035 2.8 (0.8) 2.5 (0.7) 0.112 Triglycerides (mmol/L)a 0.7 (0.6, 0.9) 0.6 (0.4, 0.7) 0.206 1.0 (0.7, 1.5) 1.0 (0.7, 1.5) 0.784 Total cholesterol/HDL cholesterol 2.8 (0.6) 2.7 (0.7) 0.575 3.3 (1.1) 3.1 (1.0) 0.495 ApoB/ApoA-I 0.52 (0.12) 0.65 (0.52) 0.339 0.61 (0.16) 0.55 (0.19) 0.147 Urine albumin/creatinine (mg/mmol)a 0.50 (0.30, 1.28) 0.77 (0.35, 1.64) 0.669 0.57 (0.24, 1.19) 0.28 (0.13, 0.96) 0.300 Baseline 5-year follow-up Diabetes Controls P-value Diabetes Controls P-value n 47 17 47 33 Diabetes duration (years)a 5.3 (3.2, 9.5) 10.0 (7.9, 14.1) Insulin pump users n (%) 20 (42.6) 23 (48.9) Age (years) 15.9 (1.8) 15.4 (2.0) 0.291 20.8 (1.8) 21.1 (1.9) 0.419 Girls, n (%) 23 (48.9) 9 (52.9) 0.777 23 (48.9) 18 (54.5) 0.656 Height (cm) 170.3 (8.9) 170.3 (7.8) 0.995 174.3 (8.5) 175.0 (9.2) 0.756 Weight (kg) 66.1 (15.2) 59.0 (12.2) 0.066 78.4 (15.5) 72.4 (14.8) 0.082 BMI (kg/m2)a 21.6 (19.3, 25.2) 19.0 (17.9, 23.7) 0.025 23.8 (22.6, 28.0) 22.9 (20.5, 25.9) 0.055 Waist circumference (cm) 76.5 (9.8) 69.5 (6.4) 0.011 83.8 (10.5) 77.9 (10.0) 0.013 Systolic blood pressure (mmHg) 104.8 (11.1) 104.6 (10.8) 0.944 115.6 (11.5) 114.4 (8.8) 0.620 Diastolic blood pressure (mmHg) 62.1 (9.5) 60.5 (6.2) 0.455 69.8 (9.0) 69.9 (7.3) 0.947 Pulse pressure (mmHg) 42.8 (7.7) 44.1 (9.3) 0.571 45.8 (9.1) 44.5 (8.8) 0.538 HbA1c (%) [mmol/mol, SD] 8.2 (1.0) [66, 10.9] 5.3 (0.3) [34, 3.3] <0.001 8.7 (1.3) [72, 14.2] 5.2 (0.3) [33, 3.3] <0.001 Mean HbA1c (%) [mmol/mol, SD] 7.9 (1.1) [63, 12.0] 8.3 (1.0) [67, 10.9] Glycaemic burden (% x years) 51.8 (34.8) 93.6 (36.0) Total cholesterol (mmol/L) 4.5 (0.7) 4.0 (0.7) 0.009 4.8 (1.0) 4.5 (0.9) 0.101 HDL (mmol/L) 1.7 (0.5) 1.6 (0.4) 0.285 1.6 (0.4) 1.6 (0.5) 0.940 LDL (mmol/L) 2.5 (0.6) 2.1 (0.6) 0.035 2.8 (0.8) 2.5 (0.7) 0.112 Triglycerides (mmol/L)a 0.7 (0.6, 0.9) 0.6 (0.4, 0.7) 0.206 1.0 (0.7, 1.5) 1.0 (0.7, 1.5) 0.784 Total cholesterol/HDL cholesterol 2.8 (0.6) 2.7 (0.7) 0.575 3.3 (1.1) 3.1 (1.0) 0.495 ApoB/ApoA-I 0.52 (0.12) 0.65 (0.52) 0.339 0.61 (0.16) 0.55 (0.19) 0.147 Urine albumin/creatinine (mg/mmol)a 0.50 (0.30, 1.28) 0.77 (0.35, 1.64) 0.669 0.57 (0.24, 1.19) 0.28 (0.13, 0.96) 0.300 Significant differences in bold Mean values (SD). SD, standard deviation. a Median (25th and 75th percentiles). The diabetes patients were slightly more overweight than the controls and had higher HbA1c and lipid values, particularly at baseline. Otherwise, the participants in both groups had similar characteristics. PWV was significantly increased in the diabetes group compared with controls, mean 4.10 (SD = 4.58) vs. 3.90 (SD = 4.04) m/s, P = 0.045. There was no difference in MAP between the groups, and MAP was not significantly correlated with PWV. We found no significant correlation with neither current nor baseline HbA1c, mean HbA1c or glycaemic burden at each time point. In addition there was no statistically significant gender difference in PWV in neither the diabetes nor the control group. Diabetes patients using insulin pumps at baseline had significantly lower PWV after 5 years, mean 3.94 (SD = 0.38) vs. 4.23 (SD = 0.48) m/s, P = 0.028. There was no statistically significant difference in PWV between patients using pumps or multiple injections at follow-up. PWV was significantly correlated with E acceleration peak in the diabetes group, r = 0.399, P = 0.007. There were no other significant correlations with the parameters for LV function in either patient group. In univariate regression models, systolic BP and body mass index were significantly associated with PWV in the diabetes group. When included in the same model, however, these two variables confounded each other. No other confounding variables were found. There were no significant associations in the control group. To determine the independent risk factors for PWV 5 years later in the diabetes group, any baseline variable associated with PWV (P < 0.2) were included in a linear regression analysis, in which gender, insulin pump use and C-reactive protein (CRP) remained significant (Table 2). The r2 for the model was 0.305. In the control group, no variables were identified as significant risk factors for PWV 5 years later. Insulin pump use did not correlate with HbA1c or mean HbA1c. It did, however, correlate inversely with glycaemic burden, both at baseline ( ρ = −0.305, P = 0.037) and at follow-up ( ρ = −0.295, P = 0.044). Table 2 Linear regression analysis. Baseline variables associated with PWV 5 years later in the diabetes group Baseline variable β SE P-value Female gender −31.6 13.1 0.021 Insulin pump use −25.4 12.6 0.051 CRP 7.6 2.6 0.006 Baseline variable β SE P-value Female gender −31.6 13.1 0.021 Insulin pump use −25.4 12.6 0.051 CRP 7.6 2.6 0.006 CRP, C-reactive protein. Table 2 Linear regression analysis. Baseline variables associated with PWV 5 years later in the diabetes group Baseline variable β SE P-value Female gender −31.6 13.1 0.021 Insulin pump use −25.4 12.6 0.051 CRP 7.6 2.6 0.006 Baseline variable β SE P-value Female gender −31.6 13.1 0.021 Insulin pump use −25.4 12.6 0.051 CRP 7.6 2.6 0.006 CRP, C-reactive protein. Intra-observer reproducibility for aortic PWV and distensibility was excellent. The average difference for PWV was −0.07 ± 0.23 (P > 0.05) and limits of agreement were −0.61 to 0.39. For distensibility, the average difference was 0.02 ± 0.8 (P > 0.05) and limits of agreement were −1.75 to 1.83. The calculations for PWV and distensibility were significantly correlated (PWV; r = 0.97, P < 0.001, distensibility; r = 0.96, P < 0.001). The variables assessed by CMR are shown in Table 3. Table 3 Variables assessed by CMR Variable Diabetes group Control group P-value Pulse wave velocity (m/s) 4.10 (4.58) 3.90 (4.04) 0.045 Distensibility (10−3 mmHg−1) 12.6 (5.7) 12.8 (4.2) 0.842 Mean arterial pressure (mmHg) 91.6 (11.2) 89.9 (9.2) 0.481 Ejection fraction (%) 62.9 (5.9) 61.6 (4.7) 0.269 Left ventricle mass (g) 119.7 (28.6) 119.7 (26.7) 0.997 E peak (mL/s) 489.1 (94.5) 509.6 (94.9) 0.343 E acceleration (L/s2) 6.9 (1.5) 6.8 (1.5) 0.742 E deceleration (L/s2) 4.7 (1.2) 4.9 (1.3) 0.519 A peak (mL/s) 183.4 (46.7) 175.9 (41.3) 0.450 EA peaka 2.7 (2.4, 3.2) 2.9 (2.5, 3.2) 0.267 Variable Diabetes group Control group P-value Pulse wave velocity (m/s) 4.10 (4.58) 3.90 (4.04) 0.045 Distensibility (10−3 mmHg−1) 12.6 (5.7) 12.8 (4.2) 0.842 Mean arterial pressure (mmHg) 91.6 (11.2) 89.9 (9.2) 0.481 Ejection fraction (%) 62.9 (5.9) 61.6 (4.7) 0.269 Left ventricle mass (g) 119.7 (28.6) 119.7 (26.7) 0.997 E peak (mL/s) 489.1 (94.5) 509.6 (94.9) 0.343 E acceleration (L/s2) 6.9 (1.5) 6.8 (1.5) 0.742 E deceleration (L/s2) 4.7 (1.2) 4.9 (1.3) 0.519 A peak (mL/s) 183.4 (46.7) 175.9 (41.3) 0.450 EA peaka 2.7 (2.4, 3.2) 2.9 (2.5, 3.2) 0.267 Mean values (SD). SD, standard deviation. a Median (25th and 75th percentiles). Table 3 Variables assessed by CMR Variable Diabetes group Control group P-value Pulse wave velocity (m/s) 4.10 (4.58) 3.90 (4.04) 0.045 Distensibility (10−3 mmHg−1) 12.6 (5.7) 12.8 (4.2) 0.842 Mean arterial pressure (mmHg) 91.6 (11.2) 89.9 (9.2) 0.481 Ejection fraction (%) 62.9 (5.9) 61.6 (4.7) 0.269 Left ventricle mass (g) 119.7 (28.6) 119.7 (26.7) 0.997 E peak (mL/s) 489.1 (94.5) 509.6 (94.9) 0.343 E acceleration (L/s2) 6.9 (1.5) 6.8 (1.5) 0.742 E deceleration (L/s2) 4.7 (1.2) 4.9 (1.3) 0.519 A peak (mL/s) 183.4 (46.7) 175.9 (41.3) 0.450 EA peaka 2.7 (2.4, 3.2) 2.9 (2.5, 3.2) 0.267 Variable Diabetes group Control group P-value Pulse wave velocity (m/s) 4.10 (4.58) 3.90 (4.04) 0.045 Distensibility (10−3 mmHg−1) 12.6 (5.7) 12.8 (4.2) 0.842 Mean arterial pressure (mmHg) 91.6 (11.2) 89.9 (9.2) 0.481 Ejection fraction (%) 62.9 (5.9) 61.6 (4.7) 0.269 Left ventricle mass (g) 119.7 (28.6) 119.7 (26.7) 0.997 E peak (mL/s) 489.1 (94.5) 509.6 (94.9) 0.343 E acceleration (L/s2) 6.9 (1.5) 6.8 (1.5) 0.742 E deceleration (L/s2) 4.7 (1.2) 4.9 (1.3) 0.519 A peak (mL/s) 183.4 (46.7) 175.9 (41.3) 0.450 EA peaka 2.7 (2.4, 3.2) 2.9 (2.5, 3.2) 0.267 Mean values (SD). SD, standard deviation. a Median (25th and 75th percentiles). Discussion We have applied a comprehensive CMR protocol to study young adults with childhood onset T1D. Our main finding was that arterial stiffness assessed by PWV was higher in these patients compared with healthy control subjects. Furthermore, in patients with T1D, high levels of inflammation, as measured by CRP, were significantly associated with increased arterial stiffness 5 years later, while female gender and insulin pump use seemed to have a protective effect. Our findings are in line with previous studies using other imaging and measuring techniques showing increased PWV in adults21 and children with T1D in the SEARCH for Diabetes in Youth study,22,23 but in contrast with a smaller study comparing young adults with 15 years of T1D duration with healthy control subjects.24 An important methodological advantage in the present study is that our CMR protocol provides precise and accurate measurements of arterial stiffness with high reproducibility. For non-invasive assessment of PWV, estimation of pulse wave travel distance is critical, and a source of inaccuracy in previously employed techniques.8 Despite the accuracy of CMR, the increase in PWV in T1D patients compared with healthy controls in our study remained small. In a comparable CMR study of slightly younger subjects, there was no significant difference in PWV.14 This difference provides insight into the timing of structural changes in the vasculature of patients with T1D. Prospective studies on PWV are scarce, but in the SEARCH CVD study, baseline metabolic syndrome, large waist and high-BP were associated with higher PWV over approximately 5 years.25 In the Caerphilly Prospective Study pulse pressure, CRP, glucose and waist circumference were found to be baseline predictors of PWV 20 years later.26 Interestingly, in the present study CRP was also found to be independently associated with PWV in the diabetes group, indicating a role for low-grade inflammation in the pathogenesis of arterial stiffness. A possible mechanism for this relationship is that low-grade inflammation impairs endothelial function, which in turn may result in increased arterial stiffness.27 A link between inflammation and endothelial function is supported by a study showing reduced forearm vasodilatation response hours after vaccination-induced inflammation.28 However, in a study that included adults with T1D, no association between endothelial dysfunction and arterial stiffness was found.29 Thus, further study is necessary. In the present study, insulin pump users at baseline had lower PWV at follow-up and in a regression model, baseline pump use was associated with reduced PWV 5 years later. Pump use was also correlated with glycaemic burden, but not with HbA1c or mean HbA1c. Thus, insulin pump use seems to have a protective effect on arterial stiffness, possibly independent of HbA1c. Previous studies have shown that insulin pump treatment diminishes blood glucose variability,30 and this may be important in the development of arterial stiffness. A 72-h study of young subjects with T1D, however, showed no association between glucose variability and arterial stiffness.31 Still, over longer periods of time, glucose variability may affect arterial stiffness, possibly through increased levels of cross-linking advanced glycation end products.32 We were unable to show an effect of any HbA1c measure on PWV, most likely due to an insufficient number of patients. Existing literature documents an increased risk of mortality from ischemic heart disease in T1D, particularly among young women.1 We did not find a gender difference in PWV, yet in multivariate analysis in the diabetes group, female gender was associated with lower PWV. Previous studies in youth with T1D have shown increased vascular stiffness in males,22 and adult males with T1D had higher PWV.21 The gender specific effects of arterial stiffness on cardiovascular mortality in T1D remain uncertain. In the current study, no significant differences in cardiac functions were observed between diabetes patients and controls. Although our study does not allow establishing a causal relation between PWV and LV diastolic function, it is known that LV diastolic function may become impaired by aortic stiffness through various mechanisms.33,34 Furthermore, previous studies have shown impaired LV function in heart failure with normal ejection fraction35 and the metabolic syndrome.36 In our study, the only significant correlation with PWV was the E wave acceleration peak. This is in line with previous studies in young T1D patients,37 but contradictory to other recent publications.38,39 Nevertheless, our findings indicate that arterial stiffness develops before LV dysfunction in the early stages of CVD. The Framingham study showed that when using 8.4 m/s as the PWV cut-off value, the probability of a first major cardiovascular event within the next 8 years was about 3%.7 However, reference values for the more accurate CMR measurements are scarce. Voges et al.40 have presented data for normal values of PWV using CMR in children and young adults, but the methodology is based on PWV measurements within short distances of the thoracic aorta. To our knowledge, this is the first longitudinal study on arterial stiffness in T1D using comprehensive CMR methodology in this age group. Strengths and limitations Inherent strengths of this study are the prospective design and the accuracy of CMR. Repeated measurements of HbA1c over several years greatly improve the assessment of glycaemic burden. The modest number of patients and particularly participants with longitudinal data in the control group may be considered limitations. However, the experience from previous CMR studies shows that our study size corresponds to a fair amount of patients. Only a few studies have explored the possible relationship between aortic stiffness and cardiac function using CMR as a non-invasive tool, and the observations are similar to previous less precise studies that required larger sample sizes,41,42 owing to the high reproducibility of CMR measurements. However, PWV measurements are subject to sampling error, such that the area of evaluation could be in a region of stiffness, resulting in elevated PWV, or the area of evaluation could be in an area of less stiffness, leading to a lower PWV. Also, PWV varies somewhat with BP, though these variations are less pronounced in young individuals with stable BP. Conclusions The present CMR study demonstrated increased PWV in young adults with T1D compared with healthy control subjects, indicating increased arterial stiffness after 10 years of diabetes duration. Longitudinal data from 5 years of follow-up also showed that early inflammation as measured by CRP emerged as a potential risk factor for increased PWV at this early stage. In addition, female gender and insulin pump use seemed to have a protective effect on arterial stiffness. Acknowledgements The authors would like to acknowledge Eva B. Lindseth for all her work in including patients and organizing data, as well as Grethe Hansen and radiographer Vigdis Rosseland for coordinating and managing the CMR examinations. The authors would also like to thank the Norwegian Extra Foundation for Health and Rehabilitation for providing funds essential for the establishment of this study. Conflict of interest: None declared. References 1 Laing SP , Swerdlow AJ , Slater SD , Burden AC , Morris A , Waugh NR et al. Mortality from heart disease in a cohort of 23,000 patients with insulin-treated diabetes . Diabetologia 2003 ; 46 : 760 – 5 . Google Scholar CrossRef Search ADS PubMed 2 McCrindle BW , Urbina EM , Dennison BA , Jacobson MS , Steinberger J , Rocchini AP et al. Drug therapy of high-risk lipid abnormalities in children and adolescents: a scientific statement from the American Heart Association Atherosclerosis, Hypertension, and Obesity in Youth Committee, Council of Cardiovascular Disease in the Young, with the Council on Cardiovascular Nursing . Circulation 2007 ; 115 : 1948 – 67 . Google Scholar CrossRef Search ADS PubMed 3 Vlachopoulos C , Aznaouridis K , Stefanadis C. 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Echo planar MRI of the heart on a standard system: validation of measurements of left ventricular function and mass . J Comput Assist Tomogr 1996 ; 20 : 942 – 9 . Google Scholar CrossRef Search ADS PubMed 21 Llaurado G , Ceperuelo-Mallafre V , Vilardell C , Simo R , Freixenet N , Vendrell J et al. Arterial stiffness is increased in patients with type 1 diabetes without cardiovascular disease: a potential role of low-grade inflammation . Diabetes Care 2012 ; 35 : 1083 – 9 . Google Scholar CrossRef Search ADS PubMed 22 Urbina EM , Wadwa RP , Davis C , Snively BM , Dolan LM , Daniels SR et al. Prevalence of increased arterial stiffness in children with type 1 diabetes mellitus differs by measurement site and sex: the SEARCH for Diabetes in Youth Study . J Pediatr 2010 ; 156 : 731 – 7 , 737.e1. Google Scholar CrossRef Search ADS PubMed 23 Shah AS , Wadwa RP , Dabelea D , Hamman RF , D’agostino R , Marcovina S et al. Arterial stiffness in adolescents and young adults with and without type 1 diabetes: the SEARCH CVD study . Pediatr Diabetes 2015 ; 16 : 367 – 74 . Google Scholar CrossRef Search ADS PubMed 24 Sweitzer NK , Shenoy M , Stein JH , Keles S , Palta M , LeCaire T et al. Increases in central aortic impedance precede alterations in arterial stiffness measures in type 1 diabetes . Diabetes Care 2007 ; 30 : 2886 – 91 . Google Scholar CrossRef Search ADS PubMed 25 Dabelea D , Talton JW , D’agostino R , Wadwa RP , Urbina EM , Dolan LM et al. Cardiovascular risk factors are associated with increased arterial stiffness in youth with type 1 diabetes: the SEARCH CVD study . Diabetes Care 2013 ; 36 : 3938 – 43 . Google Scholar CrossRef Search ADS PubMed 26 McEniery CM , Spratt M , Munnery M , Yarnell J , Lowe GD , Rumley A et al. An analysis of prospective risk factors for aortic stiffness in men: 20-year follow-up from the Caerphilly prospective study . Hypertension 2010 ; 56 : 36 – 43 . Google Scholar CrossRef Search ADS PubMed 27 Stehouwer CD , Henry RM , Ferreira I. Arterial stiffness in diabetes and the metabolic syndrome: a pathway to cardiovascular disease . Diabetologia 2008 ; 51 : 527 – 39 . Google Scholar CrossRef Search ADS PubMed 28 Hingorani AD , Cross J , Kharbanda RK , Mullen MJ , Bhagat K , Taylor M et al. Acute systemic inflammation impairs endothelium-dependent dilatation in humans . Circulation 2000 ; 102 : 994 – 9 . Google Scholar CrossRef Search ADS PubMed 29 Llaurado G , Ceperuelo-Mallafre V , Vilardell C , Simo R , Albert L , Berlanga E et al. Impaired endothelial function is not associated with arterial stiffness in adults with type 1 diabetes . Diabetes Metab 2013 ; 39 : 355 – 62 . Google Scholar CrossRef Search ADS PubMed 30 Bruttomesso D , Costa S , Baritussio A. Continuous subcutaneous insulin infusion (CSII) 30 years later: still the best option for insulin therapy . Diabetes Metab Res Rev 2009 ; 25 : 99 – 111 . 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Google Scholar CrossRef Search ADS PubMed 38 Eltayeb AA , Ahmad FA , Sayed DM , Osama AM. Subclinical vascular endothelial dysfunctions and myocardial changes with type 1 diabetes mellitus in children and adolescents . Pediatr Cardiol 2014 ; 35 : 965 – 974 . Google Scholar CrossRef Search ADS PubMed 39 Ciftel M , Ertug H , Parlak M , Akcurin G , Kardelen F. Investigation of endothelial dysfunction and arterial stiffness in children with type 1 diabetes mellitus and the association with diastolic dysfunction . Diab Vasc Dis Res 2014 ; 11 : 19 – 25 . Google Scholar CrossRef Search ADS PubMed 40 Voges I , Jerosch-Herold M , Hedderich J , Pardun E , Hart C , Gabbert DD et al. Normal values of aortic dimensions, distensibility, and pulse wave velocity in children and young adults: a cross-sectional study . J Cardiovasc Magn Reson 2012 ; 14 : 77. Google Scholar CrossRef Search ADS PubMed 41 Cruickshank K , Riste L , Anderson SG , Wright JS , Dunn G , Gosling RG. Aortic pulse-wave velocity and its relationship to mortality in diabetes and glucose intolerance: an integrated index of vascular function? Circulation 2002 ; 106 : 2085 – 90 . Google Scholar CrossRef Search ADS PubMed 42 Eren M , Gorgulu S , Uslu N , Celik S , Dagdeviren B , Tezel T. Relation between aortic stiffness and left ventricular diastolic function in patients with hypertension, diabetes, or both . Heart 2004 ; 90 : 37 – 43 . Google Scholar CrossRef Search ADS PubMed Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png European Heart Journal – Cardiovascular Imaging Oxford University Press

Increased arterial stiffness in childhood onset diabetes: a cardiovascular magnetic resonance study

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Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: journals.permissions@oup.com.
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2047-2404
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Abstract

Abstract Aims Arterial stiffness is a strong predictor of cardiovascular events. We aimed to assess the impact of type 1 diabetes (T1D) on arterial stiffness and cardiac function in young adults. Methods and results Aortic pulse wave velocity (PWV), distensibility, left ventricular (LV) function and LV mass were measured by cardiovascular magnetic resonance imaging (CMR) in 47 T1D patients and 33 healthy controls. All were participants in the Atherosclerosis and Childhood Diabetes study, with baseline values registered 5 years previously. The patients had a mean age of 20.8 years and a median duration of diabetes of 10.0 years. PWV was significantly higher in the diabetes group compared with controls, mean 4.10 (SD = 4.58) vs. 3.90 (SD = 4.04) m/s, P = 0.045. In the diabetes group, insulin pump users at baseline had lower PWV than multiple injection users, mean 3.94 (SD = 0.38) vs. 4.23 (SD = 0.48) m/s, P = 0.028. Also in the diabetes group, multiple regression analysis identified C-reactive protein (CRP), female gender and insulin pump use as independent baseline risk factors for PWV 5 years later. There was no difference in cardiac function or LV mass between the diabetes and control groups. Conclusion In this prospective study, we found increased PWV assessed by CMR in young adults with T1D compared with controls. Also, CRP, female gender and insulin pump use emerged as independent baseline risk factors for PWV 5 years later. arterial stiffness, type 1 diabetes, cardiovascular magnetic resonance imaging, pulse wave velocity, C-reactive protein Introduction Patients with type 1 diabetes (T1D) suffer from increased morbidity and mortality from cardiovascular disease (CVD).1 There is insufficient knowledge about the early phases of atherosclerosis, which makes decisions on whether or not to prescribe life-long preventive medication to children and young adults challenging, particularly in patients with existing risk factors like T1D.2 This is partly due to the lack of clinically useful techniques to precisely measure subclinical atherosclerosis. Arterial stiffness is a strong predictor of cardiovascular events and all-cause mortality.3 It is involved in the pathogenesis of atherosclerosis, primarily by being a determinant of systolic hypertension.4 Several measures of arterial stiffness have been employed, but pulse wave velocity (PWV) has been considered the gold standard.5 Its predictive accuracy has been demonstrated in a number of studies.6,7 To date, ultrasound and tonometry have been the most widely used methods for assessing PWV by measuring the travel time of a pulse wave on two levels (usually carotid-femoral) and estimate the travel distance by tape measure. (PWV = distance/time in m/s.) The estimate of the distance, however, can be inaccurate due to differences between patients in body surface contours and the curvature of the aorta. This inaccuracy can influence the outcome considerably.8 Aortic PWV can also be assessed by cardiovascular magnetic resonance (CMR), which enables precise measurement of the distance and time of travel for the pulse wave through the entire aorta.9,10 CMR has shown good agreement with invasive pressure measurements and a high level of reproducibility.11 In adults, PWV was increased in T1D patients compared with healthy control subjects.12 In the Dallas heart study, aortic arch PWV was associated with non-cardiac vascular events, but not, however, with cardiovascular death or non-fatal cardiac events.13 In childhood onset T1D, a recent study showed a trend toward reduced distensibility in the thoracic aorta, but no difference in PWV compared with healthy control subjects.14 There is a lack of comprehensive longitudinal CMR-studies on arterial stiffness in childhood onset T1D. CMR is currently considered the gold standard for the measurement of right and left ventricular volumes, mass and function, boasting high accuracy and reproducibility.15 Reference values have been published for all these parameters.16 With modern steady-state free precession cine sequences combined with parallel processing techniques, most cine stacks can be acquired in just one breath-hold. Our aim was to assess the impact of T1D on early atherosclerosis by measuring aortic stiffness and both systolic and diastolic cardiac function by CMR, as well as analyse their longitudinal relationship with cardiovascular risk factors, long-term glycaemic control and mode of treatment. Methods Study population The study ‘Atherosclerosis and Childhood diabetes’ (ACD) is a longitudinal, prospective population-based study with follow-up of the participants every fifth year.17 The present study was conducted from 2011 to 2013 as a part of the 5-year follow-up of the ACD study, and participants above 18 years of age were invited. All the diabetes patients who were included used intensified insulin injection treatment (≥4 daily insulin injections) or insulin pumps. None of them had overt retinopathy or nephropathy. To isolate the effect of T1D in early atherosclerosis the participants who smoked, were pregnant, had current infectious disease, were hypertensive, had chronic diseases other than diabetes or were on long-term medication (except insulin and contraceptives) were excluded. A total of 47 diabetes patients and 33 controls were included in the study. They all gave their written informed consent. The protocol was approved by the Norwegian Regional Committee for Research Ethics, and the study was conducted according to the Declaration of Helsinki. The examinations were performed after an overnight fasting period as a part of the 5-year follow-up in the ACD study. Baseline clinical examination and laboratory analyses were available for all diabetes patients and 17 of the controls, and have been described previously.17 From the Norwegian Childhood Diabetes Registry, we were able to obtain annual HbA1c values from 2000 to 2012, all measured at the same DCCT-standardized laboratory using high performance liquid chromatography (Variant; Bio-Rad, Richmond, CA, USA), CV <3%. On average, each patient had 8 HbA1c measurements (range 3–12). From these values, we calculated mean HbA1c at baseline and at follow-up. We also multiplied mean HbA1c by the diabetes duration in years to estimate the glycaemic burden at each time point. Markers of inflammation were assessed as previously reported.18 Other routine laboratory analyses were performed by conventional methods. CMR acquisition and analysis CMR was performed using a 1.5 T Achieva MRI scanner (Philips Healthcare, Best, The Netherlands) under standardized patient conditions, which included a minimum of 10 min supine rest in a quiet room with stable room temperature. No meals, caffeine or smoking was allowed for at least 3 h beforehand. Images were analysed quantitatively using dedicated software (cvi42; Circle Cardiovascular Imaging, Calgary, Canada). Examples are shown in Figure 1. Figure 1 View largeDownload slide Aortic pulse wave velocity and left ventricular function. The figure shows where the phase contrast velocity maps were obtained; across the mitral valve, thin black circle (A), and at two levels of the aorta, thick black lines (B). A standardized approach was used to measure the path length following the mid-line course of the aorta, black broken line. Figure 1 View largeDownload slide Aortic pulse wave velocity and left ventricular function. The figure shows where the phase contrast velocity maps were obtained; across the mitral valve, thin black circle (A), and at two levels of the aorta, thick black lines (B). A standardized approach was used to measure the path length following the mid-line course of the aorta, black broken line. Aortic PWV A retrospectively electrocardiogram (ECG)-gated gradient-echo pulse sequence with velocity encoding was applied to measure through-plane flow at two pre-defined positions in the ascending and abdominal aorta. Both positions were aligned to represent a true perpendicular imaging plane on the aorta. Imaging parameters included the following: echo-time = 7.4 ms (ascending), 6.5 ms (abdominal), repetition time = 12 ms (ascending), 10 ms (abdominal), flip-angle = 20 degrees, slice thickness = 10 mm, field of view = 280 mm, matrix size = 256 × 163 (ascending), 232 × 160 (abdominal), Venc = 190 cm/s (ascending), 160 cm/s (abdominal), scan percentage = 80%. The temporal resolution was approximately 25 ms depending on the heart rate. Aortic PWV was calculated as Δx/Δt (expressed in m/s), where Δx is the aortic path length between the two imaging levels and Δt is the time delay between the arrival of the foot of the pulse wave at these levels. A standardized approach was used to provide consistent data to measure the path length between the middle of both levels (indicated by the curved line following the mid-line course of the aorta in Figure 1). A pre-saturation slab was placed at both levels to identify both imaging planes accurately. The upslopes and the timing of the flow curves were also performed in a standardized way. The intersection of the tangent line to the upstroke, based on the three time points with the greatest acceleration gradients, and the baseline was considered as the arrival time of the pulse wave.9–10 A single observer (K.H.S.), blinded to the clinical status of the subjects, analysed the flow measurements. Aortic PWV was calculated twice within 4–8 weeks to examine intra-observer variability, Aortic distensibility Distensibility of the aorta derived from flow measurements at the mid-ascending aorta was calculated using the following formula: D = (Amax − Amin)/(Amin × pulse pressure)19 where D = distensibility (mmHg−1), Amax = maximal aortic area (mm2), Amin = minimal aortic area (mm2), pulse pressure = systolic blood pressure (BP) – diastolic BP (mmHg). The BP was recorded using a semi-automated sphygmomanometer (Champion, Riester, Ventura, CA, USA) in conjunction with the CMR examination. Mean arterial pressure (MAP) was calculated as [systolic BP + (2 × diastolic BP)]/3. The aortic area was calculated in a semi-automatic way, based on automatic contour detection by density profiles of the maximal and minimal areas and manual correction when neighbouring vessels had areas of tangent contours. Aortic contours were drawn twice within 4–8 weeks to assess intra-observer variability in distensibility. LV function The entire heart was imaged in the short-axis orientation using ECG-gated breath-hold multishot echo-planar imaging as described previously.20 Imaging parameters included the following: echo time = 1.6 ms, repetition time = 3.2 ms, temporal resolution = 35–40 ms per cardiac phase, depending on the heart rate, flip angle = 60 degrees, slice thickness = 8 mm, field of view = 350 mm, matrix size = 172 × 184. Cardiac volumes, ejection fraction and left ventricular mass were also assessed. Furthermore, an ECG-gated gradient-echo sequence with velocity encoding was performed to measure blood flow across the mitral valve for the determination of LV diastolic function. Imaging parameters included the following: echo time = 6.8 ms, repetition time = 10 ms, flip angle = 20 degrees, slice thickness = 10 mm, field of view = 340 mm, matrix size = 220 × 175, Venc = 150 cm/s, scan percentage = 83%. In each cardiac phase, the area of the mitral valve was manually traced, and the corresponding flow vs. time curve was derived automatically. Flow velocities in early diastole (E) and at atrial contraction (A) were assessed and the early peak filling rate, which is the maximal flow rate of E, the atrial peak filling rate, which is the maximal flow rate of A, and the ratio of E and A peak filling rates (E/A) were used for analysis. Furthermore, the peak acceleration and peak deceleration gradients of E were calculated. Statistical analysis Demographic and clinical data are presented as either proportions, means with their standard deviations (SD) or medians with the 25th and 75th percentile. Differences in continuous variables between groups were tested with the Student t-test, alternatively the Mann–Whitney U test for non-normally distributed data. For categorical data, a χ2 test was used. Correlation analyses between continuous variables were performed for diabetes patients and controls separately using Pearson's correlation coefficient (r) for normally distributed data, or otherwise Spearman’s rho ( ρ). To avoid false negative results, type II errors, methods to correct for multiple testing have not been applied. Linear regression analysis was performed to study the association between current conventional risk factors as exposure variables with PWV and EA Peak ratio as outcome variables. To identify possible confounders, we studied all variables that could influence the outcome. Only variables with significant relationships with both the exposure and the outcome variables were considered as possible confounders and included in the analysis. Adjustment for multiple confounding factors was conducted by linear regression analysis with a manual backward elimination procedure. A significance level of 5% was applied. To identify possible independent baseline risk factors for outcomes 5 years later, univariable regression analysis was employed. A significance level of 20% was deemed necessary for a variable to be included in the regression model. Subsequently, a manual backward stepwise elimination procedure was performed. A significance level of 5% was used for the final model. All statistical analyses were performed using IBM SPSS Statistics for Macintosh, version 19.0 (Armonk, NY, USA: IBM Corp.). Results The clinical and metabolic characteristics of the patients at baseline and follow-up are shown in Table 1. Table 1 Clinical and metabolic characteristics at baseline and 5-year follow-up Baseline 5-year follow-up Diabetes Controls P-value Diabetes Controls P-value n 47 17 47 33 Diabetes duration (years)a 5.3 (3.2, 9.5) 10.0 (7.9, 14.1) Insulin pump users n (%) 20 (42.6) 23 (48.9) Age (years) 15.9 (1.8) 15.4 (2.0) 0.291 20.8 (1.8) 21.1 (1.9) 0.419 Girls, n (%) 23 (48.9) 9 (52.9) 0.777 23 (48.9) 18 (54.5) 0.656 Height (cm) 170.3 (8.9) 170.3 (7.8) 0.995 174.3 (8.5) 175.0 (9.2) 0.756 Weight (kg) 66.1 (15.2) 59.0 (12.2) 0.066 78.4 (15.5) 72.4 (14.8) 0.082 BMI (kg/m2)a 21.6 (19.3, 25.2) 19.0 (17.9, 23.7) 0.025 23.8 (22.6, 28.0) 22.9 (20.5, 25.9) 0.055 Waist circumference (cm) 76.5 (9.8) 69.5 (6.4) 0.011 83.8 (10.5) 77.9 (10.0) 0.013 Systolic blood pressure (mmHg) 104.8 (11.1) 104.6 (10.8) 0.944 115.6 (11.5) 114.4 (8.8) 0.620 Diastolic blood pressure (mmHg) 62.1 (9.5) 60.5 (6.2) 0.455 69.8 (9.0) 69.9 (7.3) 0.947 Pulse pressure (mmHg) 42.8 (7.7) 44.1 (9.3) 0.571 45.8 (9.1) 44.5 (8.8) 0.538 HbA1c (%) [mmol/mol, SD] 8.2 (1.0) [66, 10.9] 5.3 (0.3) [34, 3.3] <0.001 8.7 (1.3) [72, 14.2] 5.2 (0.3) [33, 3.3] <0.001 Mean HbA1c (%) [mmol/mol, SD] 7.9 (1.1) [63, 12.0] 8.3 (1.0) [67, 10.9] Glycaemic burden (% x years) 51.8 (34.8) 93.6 (36.0) Total cholesterol (mmol/L) 4.5 (0.7) 4.0 (0.7) 0.009 4.8 (1.0) 4.5 (0.9) 0.101 HDL (mmol/L) 1.7 (0.5) 1.6 (0.4) 0.285 1.6 (0.4) 1.6 (0.5) 0.940 LDL (mmol/L) 2.5 (0.6) 2.1 (0.6) 0.035 2.8 (0.8) 2.5 (0.7) 0.112 Triglycerides (mmol/L)a 0.7 (0.6, 0.9) 0.6 (0.4, 0.7) 0.206 1.0 (0.7, 1.5) 1.0 (0.7, 1.5) 0.784 Total cholesterol/HDL cholesterol 2.8 (0.6) 2.7 (0.7) 0.575 3.3 (1.1) 3.1 (1.0) 0.495 ApoB/ApoA-I 0.52 (0.12) 0.65 (0.52) 0.339 0.61 (0.16) 0.55 (0.19) 0.147 Urine albumin/creatinine (mg/mmol)a 0.50 (0.30, 1.28) 0.77 (0.35, 1.64) 0.669 0.57 (0.24, 1.19) 0.28 (0.13, 0.96) 0.300 Baseline 5-year follow-up Diabetes Controls P-value Diabetes Controls P-value n 47 17 47 33 Diabetes duration (years)a 5.3 (3.2, 9.5) 10.0 (7.9, 14.1) Insulin pump users n (%) 20 (42.6) 23 (48.9) Age (years) 15.9 (1.8) 15.4 (2.0) 0.291 20.8 (1.8) 21.1 (1.9) 0.419 Girls, n (%) 23 (48.9) 9 (52.9) 0.777 23 (48.9) 18 (54.5) 0.656 Height (cm) 170.3 (8.9) 170.3 (7.8) 0.995 174.3 (8.5) 175.0 (9.2) 0.756 Weight (kg) 66.1 (15.2) 59.0 (12.2) 0.066 78.4 (15.5) 72.4 (14.8) 0.082 BMI (kg/m2)a 21.6 (19.3, 25.2) 19.0 (17.9, 23.7) 0.025 23.8 (22.6, 28.0) 22.9 (20.5, 25.9) 0.055 Waist circumference (cm) 76.5 (9.8) 69.5 (6.4) 0.011 83.8 (10.5) 77.9 (10.0) 0.013 Systolic blood pressure (mmHg) 104.8 (11.1) 104.6 (10.8) 0.944 115.6 (11.5) 114.4 (8.8) 0.620 Diastolic blood pressure (mmHg) 62.1 (9.5) 60.5 (6.2) 0.455 69.8 (9.0) 69.9 (7.3) 0.947 Pulse pressure (mmHg) 42.8 (7.7) 44.1 (9.3) 0.571 45.8 (9.1) 44.5 (8.8) 0.538 HbA1c (%) [mmol/mol, SD] 8.2 (1.0) [66, 10.9] 5.3 (0.3) [34, 3.3] <0.001 8.7 (1.3) [72, 14.2] 5.2 (0.3) [33, 3.3] <0.001 Mean HbA1c (%) [mmol/mol, SD] 7.9 (1.1) [63, 12.0] 8.3 (1.0) [67, 10.9] Glycaemic burden (% x years) 51.8 (34.8) 93.6 (36.0) Total cholesterol (mmol/L) 4.5 (0.7) 4.0 (0.7) 0.009 4.8 (1.0) 4.5 (0.9) 0.101 HDL (mmol/L) 1.7 (0.5) 1.6 (0.4) 0.285 1.6 (0.4) 1.6 (0.5) 0.940 LDL (mmol/L) 2.5 (0.6) 2.1 (0.6) 0.035 2.8 (0.8) 2.5 (0.7) 0.112 Triglycerides (mmol/L)a 0.7 (0.6, 0.9) 0.6 (0.4, 0.7) 0.206 1.0 (0.7, 1.5) 1.0 (0.7, 1.5) 0.784 Total cholesterol/HDL cholesterol 2.8 (0.6) 2.7 (0.7) 0.575 3.3 (1.1) 3.1 (1.0) 0.495 ApoB/ApoA-I 0.52 (0.12) 0.65 (0.52) 0.339 0.61 (0.16) 0.55 (0.19) 0.147 Urine albumin/creatinine (mg/mmol)a 0.50 (0.30, 1.28) 0.77 (0.35, 1.64) 0.669 0.57 (0.24, 1.19) 0.28 (0.13, 0.96) 0.300 Significant differences in bold Mean values (SD). SD, standard deviation. a Median (25th and 75th percentiles). Table 1 Clinical and metabolic characteristics at baseline and 5-year follow-up Baseline 5-year follow-up Diabetes Controls P-value Diabetes Controls P-value n 47 17 47 33 Diabetes duration (years)a 5.3 (3.2, 9.5) 10.0 (7.9, 14.1) Insulin pump users n (%) 20 (42.6) 23 (48.9) Age (years) 15.9 (1.8) 15.4 (2.0) 0.291 20.8 (1.8) 21.1 (1.9) 0.419 Girls, n (%) 23 (48.9) 9 (52.9) 0.777 23 (48.9) 18 (54.5) 0.656 Height (cm) 170.3 (8.9) 170.3 (7.8) 0.995 174.3 (8.5) 175.0 (9.2) 0.756 Weight (kg) 66.1 (15.2) 59.0 (12.2) 0.066 78.4 (15.5) 72.4 (14.8) 0.082 BMI (kg/m2)a 21.6 (19.3, 25.2) 19.0 (17.9, 23.7) 0.025 23.8 (22.6, 28.0) 22.9 (20.5, 25.9) 0.055 Waist circumference (cm) 76.5 (9.8) 69.5 (6.4) 0.011 83.8 (10.5) 77.9 (10.0) 0.013 Systolic blood pressure (mmHg) 104.8 (11.1) 104.6 (10.8) 0.944 115.6 (11.5) 114.4 (8.8) 0.620 Diastolic blood pressure (mmHg) 62.1 (9.5) 60.5 (6.2) 0.455 69.8 (9.0) 69.9 (7.3) 0.947 Pulse pressure (mmHg) 42.8 (7.7) 44.1 (9.3) 0.571 45.8 (9.1) 44.5 (8.8) 0.538 HbA1c (%) [mmol/mol, SD] 8.2 (1.0) [66, 10.9] 5.3 (0.3) [34, 3.3] <0.001 8.7 (1.3) [72, 14.2] 5.2 (0.3) [33, 3.3] <0.001 Mean HbA1c (%) [mmol/mol, SD] 7.9 (1.1) [63, 12.0] 8.3 (1.0) [67, 10.9] Glycaemic burden (% x years) 51.8 (34.8) 93.6 (36.0) Total cholesterol (mmol/L) 4.5 (0.7) 4.0 (0.7) 0.009 4.8 (1.0) 4.5 (0.9) 0.101 HDL (mmol/L) 1.7 (0.5) 1.6 (0.4) 0.285 1.6 (0.4) 1.6 (0.5) 0.940 LDL (mmol/L) 2.5 (0.6) 2.1 (0.6) 0.035 2.8 (0.8) 2.5 (0.7) 0.112 Triglycerides (mmol/L)a 0.7 (0.6, 0.9) 0.6 (0.4, 0.7) 0.206 1.0 (0.7, 1.5) 1.0 (0.7, 1.5) 0.784 Total cholesterol/HDL cholesterol 2.8 (0.6) 2.7 (0.7) 0.575 3.3 (1.1) 3.1 (1.0) 0.495 ApoB/ApoA-I 0.52 (0.12) 0.65 (0.52) 0.339 0.61 (0.16) 0.55 (0.19) 0.147 Urine albumin/creatinine (mg/mmol)a 0.50 (0.30, 1.28) 0.77 (0.35, 1.64) 0.669 0.57 (0.24, 1.19) 0.28 (0.13, 0.96) 0.300 Baseline 5-year follow-up Diabetes Controls P-value Diabetes Controls P-value n 47 17 47 33 Diabetes duration (years)a 5.3 (3.2, 9.5) 10.0 (7.9, 14.1) Insulin pump users n (%) 20 (42.6) 23 (48.9) Age (years) 15.9 (1.8) 15.4 (2.0) 0.291 20.8 (1.8) 21.1 (1.9) 0.419 Girls, n (%) 23 (48.9) 9 (52.9) 0.777 23 (48.9) 18 (54.5) 0.656 Height (cm) 170.3 (8.9) 170.3 (7.8) 0.995 174.3 (8.5) 175.0 (9.2) 0.756 Weight (kg) 66.1 (15.2) 59.0 (12.2) 0.066 78.4 (15.5) 72.4 (14.8) 0.082 BMI (kg/m2)a 21.6 (19.3, 25.2) 19.0 (17.9, 23.7) 0.025 23.8 (22.6, 28.0) 22.9 (20.5, 25.9) 0.055 Waist circumference (cm) 76.5 (9.8) 69.5 (6.4) 0.011 83.8 (10.5) 77.9 (10.0) 0.013 Systolic blood pressure (mmHg) 104.8 (11.1) 104.6 (10.8) 0.944 115.6 (11.5) 114.4 (8.8) 0.620 Diastolic blood pressure (mmHg) 62.1 (9.5) 60.5 (6.2) 0.455 69.8 (9.0) 69.9 (7.3) 0.947 Pulse pressure (mmHg) 42.8 (7.7) 44.1 (9.3) 0.571 45.8 (9.1) 44.5 (8.8) 0.538 HbA1c (%) [mmol/mol, SD] 8.2 (1.0) [66, 10.9] 5.3 (0.3) [34, 3.3] <0.001 8.7 (1.3) [72, 14.2] 5.2 (0.3) [33, 3.3] <0.001 Mean HbA1c (%) [mmol/mol, SD] 7.9 (1.1) [63, 12.0] 8.3 (1.0) [67, 10.9] Glycaemic burden (% x years) 51.8 (34.8) 93.6 (36.0) Total cholesterol (mmol/L) 4.5 (0.7) 4.0 (0.7) 0.009 4.8 (1.0) 4.5 (0.9) 0.101 HDL (mmol/L) 1.7 (0.5) 1.6 (0.4) 0.285 1.6 (0.4) 1.6 (0.5) 0.940 LDL (mmol/L) 2.5 (0.6) 2.1 (0.6) 0.035 2.8 (0.8) 2.5 (0.7) 0.112 Triglycerides (mmol/L)a 0.7 (0.6, 0.9) 0.6 (0.4, 0.7) 0.206 1.0 (0.7, 1.5) 1.0 (0.7, 1.5) 0.784 Total cholesterol/HDL cholesterol 2.8 (0.6) 2.7 (0.7) 0.575 3.3 (1.1) 3.1 (1.0) 0.495 ApoB/ApoA-I 0.52 (0.12) 0.65 (0.52) 0.339 0.61 (0.16) 0.55 (0.19) 0.147 Urine albumin/creatinine (mg/mmol)a 0.50 (0.30, 1.28) 0.77 (0.35, 1.64) 0.669 0.57 (0.24, 1.19) 0.28 (0.13, 0.96) 0.300 Significant differences in bold Mean values (SD). SD, standard deviation. a Median (25th and 75th percentiles). The diabetes patients were slightly more overweight than the controls and had higher HbA1c and lipid values, particularly at baseline. Otherwise, the participants in both groups had similar characteristics. PWV was significantly increased in the diabetes group compared with controls, mean 4.10 (SD = 4.58) vs. 3.90 (SD = 4.04) m/s, P = 0.045. There was no difference in MAP between the groups, and MAP was not significantly correlated with PWV. We found no significant correlation with neither current nor baseline HbA1c, mean HbA1c or glycaemic burden at each time point. In addition there was no statistically significant gender difference in PWV in neither the diabetes nor the control group. Diabetes patients using insulin pumps at baseline had significantly lower PWV after 5 years, mean 3.94 (SD = 0.38) vs. 4.23 (SD = 0.48) m/s, P = 0.028. There was no statistically significant difference in PWV between patients using pumps or multiple injections at follow-up. PWV was significantly correlated with E acceleration peak in the diabetes group, r = 0.399, P = 0.007. There were no other significant correlations with the parameters for LV function in either patient group. In univariate regression models, systolic BP and body mass index were significantly associated with PWV in the diabetes group. When included in the same model, however, these two variables confounded each other. No other confounding variables were found. There were no significant associations in the control group. To determine the independent risk factors for PWV 5 years later in the diabetes group, any baseline variable associated with PWV (P < 0.2) were included in a linear regression analysis, in which gender, insulin pump use and C-reactive protein (CRP) remained significant (Table 2). The r2 for the model was 0.305. In the control group, no variables were identified as significant risk factors for PWV 5 years later. Insulin pump use did not correlate with HbA1c or mean HbA1c. It did, however, correlate inversely with glycaemic burden, both at baseline ( ρ = −0.305, P = 0.037) and at follow-up ( ρ = −0.295, P = 0.044). Table 2 Linear regression analysis. Baseline variables associated with PWV 5 years later in the diabetes group Baseline variable β SE P-value Female gender −31.6 13.1 0.021 Insulin pump use −25.4 12.6 0.051 CRP 7.6 2.6 0.006 Baseline variable β SE P-value Female gender −31.6 13.1 0.021 Insulin pump use −25.4 12.6 0.051 CRP 7.6 2.6 0.006 CRP, C-reactive protein. Table 2 Linear regression analysis. Baseline variables associated with PWV 5 years later in the diabetes group Baseline variable β SE P-value Female gender −31.6 13.1 0.021 Insulin pump use −25.4 12.6 0.051 CRP 7.6 2.6 0.006 Baseline variable β SE P-value Female gender −31.6 13.1 0.021 Insulin pump use −25.4 12.6 0.051 CRP 7.6 2.6 0.006 CRP, C-reactive protein. Intra-observer reproducibility for aortic PWV and distensibility was excellent. The average difference for PWV was −0.07 ± 0.23 (P > 0.05) and limits of agreement were −0.61 to 0.39. For distensibility, the average difference was 0.02 ± 0.8 (P > 0.05) and limits of agreement were −1.75 to 1.83. The calculations for PWV and distensibility were significantly correlated (PWV; r = 0.97, P < 0.001, distensibility; r = 0.96, P < 0.001). The variables assessed by CMR are shown in Table 3. Table 3 Variables assessed by CMR Variable Diabetes group Control group P-value Pulse wave velocity (m/s) 4.10 (4.58) 3.90 (4.04) 0.045 Distensibility (10−3 mmHg−1) 12.6 (5.7) 12.8 (4.2) 0.842 Mean arterial pressure (mmHg) 91.6 (11.2) 89.9 (9.2) 0.481 Ejection fraction (%) 62.9 (5.9) 61.6 (4.7) 0.269 Left ventricle mass (g) 119.7 (28.6) 119.7 (26.7) 0.997 E peak (mL/s) 489.1 (94.5) 509.6 (94.9) 0.343 E acceleration (L/s2) 6.9 (1.5) 6.8 (1.5) 0.742 E deceleration (L/s2) 4.7 (1.2) 4.9 (1.3) 0.519 A peak (mL/s) 183.4 (46.7) 175.9 (41.3) 0.450 EA peaka 2.7 (2.4, 3.2) 2.9 (2.5, 3.2) 0.267 Variable Diabetes group Control group P-value Pulse wave velocity (m/s) 4.10 (4.58) 3.90 (4.04) 0.045 Distensibility (10−3 mmHg−1) 12.6 (5.7) 12.8 (4.2) 0.842 Mean arterial pressure (mmHg) 91.6 (11.2) 89.9 (9.2) 0.481 Ejection fraction (%) 62.9 (5.9) 61.6 (4.7) 0.269 Left ventricle mass (g) 119.7 (28.6) 119.7 (26.7) 0.997 E peak (mL/s) 489.1 (94.5) 509.6 (94.9) 0.343 E acceleration (L/s2) 6.9 (1.5) 6.8 (1.5) 0.742 E deceleration (L/s2) 4.7 (1.2) 4.9 (1.3) 0.519 A peak (mL/s) 183.4 (46.7) 175.9 (41.3) 0.450 EA peaka 2.7 (2.4, 3.2) 2.9 (2.5, 3.2) 0.267 Mean values (SD). SD, standard deviation. a Median (25th and 75th percentiles). Table 3 Variables assessed by CMR Variable Diabetes group Control group P-value Pulse wave velocity (m/s) 4.10 (4.58) 3.90 (4.04) 0.045 Distensibility (10−3 mmHg−1) 12.6 (5.7) 12.8 (4.2) 0.842 Mean arterial pressure (mmHg) 91.6 (11.2) 89.9 (9.2) 0.481 Ejection fraction (%) 62.9 (5.9) 61.6 (4.7) 0.269 Left ventricle mass (g) 119.7 (28.6) 119.7 (26.7) 0.997 E peak (mL/s) 489.1 (94.5) 509.6 (94.9) 0.343 E acceleration (L/s2) 6.9 (1.5) 6.8 (1.5) 0.742 E deceleration (L/s2) 4.7 (1.2) 4.9 (1.3) 0.519 A peak (mL/s) 183.4 (46.7) 175.9 (41.3) 0.450 EA peaka 2.7 (2.4, 3.2) 2.9 (2.5, 3.2) 0.267 Variable Diabetes group Control group P-value Pulse wave velocity (m/s) 4.10 (4.58) 3.90 (4.04) 0.045 Distensibility (10−3 mmHg−1) 12.6 (5.7) 12.8 (4.2) 0.842 Mean arterial pressure (mmHg) 91.6 (11.2) 89.9 (9.2) 0.481 Ejection fraction (%) 62.9 (5.9) 61.6 (4.7) 0.269 Left ventricle mass (g) 119.7 (28.6) 119.7 (26.7) 0.997 E peak (mL/s) 489.1 (94.5) 509.6 (94.9) 0.343 E acceleration (L/s2) 6.9 (1.5) 6.8 (1.5) 0.742 E deceleration (L/s2) 4.7 (1.2) 4.9 (1.3) 0.519 A peak (mL/s) 183.4 (46.7) 175.9 (41.3) 0.450 EA peaka 2.7 (2.4, 3.2) 2.9 (2.5, 3.2) 0.267 Mean values (SD). SD, standard deviation. a Median (25th and 75th percentiles). Discussion We have applied a comprehensive CMR protocol to study young adults with childhood onset T1D. Our main finding was that arterial stiffness assessed by PWV was higher in these patients compared with healthy control subjects. Furthermore, in patients with T1D, high levels of inflammation, as measured by CRP, were significantly associated with increased arterial stiffness 5 years later, while female gender and insulin pump use seemed to have a protective effect. Our findings are in line with previous studies using other imaging and measuring techniques showing increased PWV in adults21 and children with T1D in the SEARCH for Diabetes in Youth study,22,23 but in contrast with a smaller study comparing young adults with 15 years of T1D duration with healthy control subjects.24 An important methodological advantage in the present study is that our CMR protocol provides precise and accurate measurements of arterial stiffness with high reproducibility. For non-invasive assessment of PWV, estimation of pulse wave travel distance is critical, and a source of inaccuracy in previously employed techniques.8 Despite the accuracy of CMR, the increase in PWV in T1D patients compared with healthy controls in our study remained small. In a comparable CMR study of slightly younger subjects, there was no significant difference in PWV.14 This difference provides insight into the timing of structural changes in the vasculature of patients with T1D. Prospective studies on PWV are scarce, but in the SEARCH CVD study, baseline metabolic syndrome, large waist and high-BP were associated with higher PWV over approximately 5 years.25 In the Caerphilly Prospective Study pulse pressure, CRP, glucose and waist circumference were found to be baseline predictors of PWV 20 years later.26 Interestingly, in the present study CRP was also found to be independently associated with PWV in the diabetes group, indicating a role for low-grade inflammation in the pathogenesis of arterial stiffness. A possible mechanism for this relationship is that low-grade inflammation impairs endothelial function, which in turn may result in increased arterial stiffness.27 A link between inflammation and endothelial function is supported by a study showing reduced forearm vasodilatation response hours after vaccination-induced inflammation.28 However, in a study that included adults with T1D, no association between endothelial dysfunction and arterial stiffness was found.29 Thus, further study is necessary. In the present study, insulin pump users at baseline had lower PWV at follow-up and in a regression model, baseline pump use was associated with reduced PWV 5 years later. Pump use was also correlated with glycaemic burden, but not with HbA1c or mean HbA1c. Thus, insulin pump use seems to have a protective effect on arterial stiffness, possibly independent of HbA1c. Previous studies have shown that insulin pump treatment diminishes blood glucose variability,30 and this may be important in the development of arterial stiffness. A 72-h study of young subjects with T1D, however, showed no association between glucose variability and arterial stiffness.31 Still, over longer periods of time, glucose variability may affect arterial stiffness, possibly through increased levels of cross-linking advanced glycation end products.32 We were unable to show an effect of any HbA1c measure on PWV, most likely due to an insufficient number of patients. Existing literature documents an increased risk of mortality from ischemic heart disease in T1D, particularly among young women.1 We did not find a gender difference in PWV, yet in multivariate analysis in the diabetes group, female gender was associated with lower PWV. Previous studies in youth with T1D have shown increased vascular stiffness in males,22 and adult males with T1D had higher PWV.21 The gender specific effects of arterial stiffness on cardiovascular mortality in T1D remain uncertain. In the current study, no significant differences in cardiac functions were observed between diabetes patients and controls. Although our study does not allow establishing a causal relation between PWV and LV diastolic function, it is known that LV diastolic function may become impaired by aortic stiffness through various mechanisms.33,34 Furthermore, previous studies have shown impaired LV function in heart failure with normal ejection fraction35 and the metabolic syndrome.36 In our study, the only significant correlation with PWV was the E wave acceleration peak. This is in line with previous studies in young T1D patients,37 but contradictory to other recent publications.38,39 Nevertheless, our findings indicate that arterial stiffness develops before LV dysfunction in the early stages of CVD. The Framingham study showed that when using 8.4 m/s as the PWV cut-off value, the probability of a first major cardiovascular event within the next 8 years was about 3%.7 However, reference values for the more accurate CMR measurements are scarce. Voges et al.40 have presented data for normal values of PWV using CMR in children and young adults, but the methodology is based on PWV measurements within short distances of the thoracic aorta. To our knowledge, this is the first longitudinal study on arterial stiffness in T1D using comprehensive CMR methodology in this age group. Strengths and limitations Inherent strengths of this study are the prospective design and the accuracy of CMR. Repeated measurements of HbA1c over several years greatly improve the assessment of glycaemic burden. The modest number of patients and particularly participants with longitudinal data in the control group may be considered limitations. However, the experience from previous CMR studies shows that our study size corresponds to a fair amount of patients. Only a few studies have explored the possible relationship between aortic stiffness and cardiac function using CMR as a non-invasive tool, and the observations are similar to previous less precise studies that required larger sample sizes,41,42 owing to the high reproducibility of CMR measurements. However, PWV measurements are subject to sampling error, such that the area of evaluation could be in a region of stiffness, resulting in elevated PWV, or the area of evaluation could be in an area of less stiffness, leading to a lower PWV. Also, PWV varies somewhat with BP, though these variations are less pronounced in young individuals with stable BP. Conclusions The present CMR study demonstrated increased PWV in young adults with T1D compared with healthy control subjects, indicating increased arterial stiffness after 10 years of diabetes duration. Longitudinal data from 5 years of follow-up also showed that early inflammation as measured by CRP emerged as a potential risk factor for increased PWV at this early stage. In addition, female gender and insulin pump use seemed to have a protective effect on arterial stiffness. Acknowledgements The authors would like to acknowledge Eva B. Lindseth for all her work in including patients and organizing data, as well as Grethe Hansen and radiographer Vigdis Rosseland for coordinating and managing the CMR examinations. The authors would also like to thank the Norwegian Extra Foundation for Health and Rehabilitation for providing funds essential for the establishment of this study. Conflict of interest: None declared. References 1 Laing SP , Swerdlow AJ , Slater SD , Burden AC , Morris A , Waugh NR et al. Mortality from heart disease in a cohort of 23,000 patients with insulin-treated diabetes . Diabetologia 2003 ; 46 : 760 – 5 . Google Scholar CrossRef Search ADS PubMed 2 McCrindle BW , Urbina EM , Dennison BA , Jacobson MS , Steinberger J , Rocchini AP et al. Drug therapy of high-risk lipid abnormalities in children and adolescents: a scientific statement from the American Heart Association Atherosclerosis, Hypertension, and Obesity in Youth Committee, Council of Cardiovascular Disease in the Young, with the Council on Cardiovascular Nursing . Circulation 2007 ; 115 : 1948 – 67 . Google Scholar CrossRef Search ADS PubMed 3 Vlachopoulos C , Aznaouridis K , Stefanadis C. 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European Heart Journal – Cardiovascular ImagingOxford University Press

Published: Jul 25, 2017

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