The study was carried out over a period of 12 months between 1 January 2008 and 31 December 2008. We included 216 type 2 diabetic patients who consulted for complications screening at the Department of Endocrinology and Metabolism in our hospital on an annual basis. Type 2 diabetes was diagnosed according to 1999 World Health Organization (WHO) criteria . Eligibility was based on a stable therapeutic regimen with oral hypoglycemic agents and/or insulin for the previous 3 months. Exclusion criteria included recent acute complications such as diabetic ketoacidosis and hyperglycemic hyperosmolar state, severe and recurrent hypoglycemic events in the previous 3 months, a history of hepatic or renal impairment, or of other diseases that can influence glucose metabolism, including recent acute cerebral stroke, acute myocardial infarction, malnutrition, and cancers. In addition, claustrophobic patients, and patients with valvular prostheses, vascular clips, cardiac pacemakers, or other implanted devices sensitive to strong magnetic fields, were also excluded from the study. The original study received approval from the Ethics Committees of Shanghai Jiao Tong University Affiliated Sixth People’s Hospital in accordance with the principle of the Helsinki Declaration. Written informed consent was obtained from each participant.
Subcutaneous interstitial glucose was monitored continuously for 3 consecutive days using a retrospective CGM system (Medtronic Inc, Northridge, CA, USA). The sensor of the CGM system was inserted on day 0 and removed after 72 h; this generated a daily record of 288 continuous sensor values. A minimum of four capillary blood glucose readings per day, as measured by a SureStep blood glucose meter (LifeScan, Milpitas, CA, USA), were entered into the CGM system for calibration. The 24h mean blood glucose (MBG) level was calculated from the 288 consecutive sensor readings over a 24h period. The 24h MBG and intraday glycemic variability were based on the mean values taken on days 1 and 2. Intraday glycemic variability parameters include the standard deviation of blood glucose values (SDBG)  and the mean amplitude of glycemic excursions (MAGE) . MAGE was calculated by measuring the arithmetic mean of the differences between consecutive peaks and nadirs; measurement in the peak-to-nadir or nadir-to-peak direction was determined by the first qualifying excursion; only excursions of more than 1 SD of the mean glycemic values were considered because MAGE was designed to quantify only major swings of glycemia instead of minor ones. All patients wore blinded CGM system and received the same therapy as before admission. The CGM monitoring was performed in the hospital and the mean CGM period ± SD was 71 ± 3h. The reference values for CGM system in Chinese population have been reported elsewhere [12, 13].
Patients were instructed to adhere to a standard diet during the three-day period of CGM sensor monitoring. The diet was designed to ensure a total daily caloric intake of 25 kcal/kg/day, with 55% of calories coming from carbohydrates, 17% from proteins, and 28% from fats. Written instructions were provided to achieve the appropriate caloric content and to guide the consumption times, which included breakfast (20% of daily calories, 06:30–07:30), lunch (40%, 11:30–12:30), and dinner (40%, 18:00–19:00).
Cervical and intracranial magnetic resonance angiography (MRA) examination
All MRA examinations were performed using a 3.0 tesla MR system (Achieva, Philips Medical Systems). Intracranial MRA was performed using a 3D-TOF-MRA sequence with an 8-channel head coil or a 16-channel craniocervical joint coil. The 3D-TOF-MRA was obtained with repetition time/echo time (TR/TE) 30/3.2 msec, flip angle 20°, field of view (FOV) 250 × 220 mm, four slabs (180 slices), 1.2 mm slice thickness, matrix 1024 × 1024 and an acquisition time of 8 min 56 s. The acquired images were then transferred to a separate workstation (View Forum; Philips Medical Systems) to obtain both the maximum-intensity projection (MIP) and volume rendering (VR) images. Cervical MRA was performed using the high spatial resolution CEMRA sequence with a 16-channel craniocervical joint coil. Parameters were as follows: a 4.7/1.79 msec TR/TE; 27° flip angle; 320 × 320 mm FOV; 150 slices; 1.0 mm slice thickness, matrix 704 × 704 and an acquisition time of 1 min 27 s. A 1 ml bolus dose of gadolinium (0.5 mol/l, Magnevist; Bayer Health Care Pharmaceuticals) was administered intravenously at a flow rate of 2.5 ml/s by a power injector, followed by 21 ml of saline flush to measure the time taken for the gadolinium to reach the aortic arch. Subsequently, 19 ml of gadolinium was injected at the same rate. The average scanning delay time was 13 s (11–19 s).
The intracranial portion of the internal carotid artery (I-ICA), the anterior, middle, and posterior cerebral arteries (ACA, MCA and PCA), the intracranial vertebral artery (I-VA), and the basilar artery (BA) were evaluated by intracranial MRA. The common carotid artery (CCA), the extracranial portion of the internal carotid artery (E-ICA), the extracranial vertebral artery (E-VA), the external carotid artery (ECA), and the subclavian artery (SUB) were evaluated by cervical MRA. All MRA findings were reviewed by two investigators who were blind to patient clinical data. The severity of arterial stenosis was rated into five grades depending on the narrowing of the arteries: without any reduction of arterial diameter; <10% reduction of arterial diameter; 10–50% reduction; 51–99% reduction; and complete occlusion . If stenosis severity for a given artery was different between the right and left sides, the side with more severe stenosis was used for grade assignment and analysis. When two or more stenoses were detected in different arteries, the most severe arterial stenosis grade was used for patient classification.
Common carotid arteries were assessed using a high resolution B-mode ultrasound (Sequoia 512, Siemens, Germany) equipped with a 10 MHz probe, as previously described . A single sonographer blind to patient clinical characteristics measured bilateral carotid arteries. Both common carotid arteries were scanned from proximal to distal in relation to the bifurcation. IMT was measured at the far wall of both common carotid arteries, approximately 1 cm proximal to the carotid bulb. The carotid IMT value was calculated as the mean of the maximal IMT of each carotid artery.
Anthropometric and biochemical measurements
Each patient had a physical examination including measurements of height, weight, and blood pressure in an air-conditioned, quiet room. We calculated body mass index (BMI) as weight (kg) divided by squared height (m). The blood pressure was measured indirectly using a mercury sphygmomanometer. Sitting blood pressure was measured after 5-min rest with a blood pressure cuff appropriately sized to arm circumference and placed on the subject’s non-dominant arm. The average of three measurements at two minute intervals was used for the analysis. Smoking status was based on an interview. Subjects were classified as nonsmokers or current smokers.
On a separate day from 3-day CGM measurement, venous blood sample was drawn on 6 AM after a 10 hour overnight fasting to test the biochemical measurements. Hepatic biomarkers, including alanine aminotransferase (ALT), aspartate aminotransferase (AST); renal function biomarkers including blood urea nitrogen (BUN), plasma creatinine, and uric acid; triglycerides (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), and low density lipoprotein cholesterol (LDL-C), were determined by standard enzymatic methods using a biochemical analyzer (Hitachi 7600–020, Tokyo, Japan). Fasting plasma glucose levels were assayed by the glucose oxidase method. Hemoglobin A1c (HbA1c) was measured by high-performance liquid chromatography with a Variant II Hemoglobin A1c analyzer (Bio-Rad Laboratories, Hercules, CA, USA).
Statistical analyses were performed using SPSS software version 17.0 (SPSS Inc., Chicago, IL, USA). Normally distributed data are presented as mean ± SD, whereas skewed variables are presented as median (interquartile range: 25th to 75th percentile). Clinical characteristics that followed a normal distribution were compared among groups using one-way analysis of variance with post-hoc LSD test, while those with non-normal distribution were compared using the Kruskal–Wallis test followed by Mann–Whitney U test with Bonferroni correction. In addition, a chi-squared test was used to determine the differences between groups in categorical variables. Variables that did not follow a normal distribution were log-transformed. Logistic regression analysis was performed to identify independent factors for cervical and/or intracranial plaque formation. The results of the regression were expressed as odds ratios (OR) with 95% confidence intervals (CI). In patients with negative finding on MRA, Spearman correlation coefficients were employed for correlation analysis between carotid IMT and variables. Multiple regression models were used to explore the influence of different variables on carotid IMT and to adjust for covariates. We calculated the number of patients required for the study to reject the null hypothesis 90% of the time (i.e., with a 1-tailed type II error rate of 0.1) when r was 0.40 or higher with a 2-tailed type I error at the 0.05 level of significance. Because this calculation led to a sample size of at least 61, the number 63 of patients who had negative finding on MRA was sufficient. A P value of <0.05 (two-tailed) was considered to indicate statistical significance.