OBJECTIVE—Cardiovascular events are high in patients with type 2 diabetes, whereas their risk stratification is more difficult. The higher risk may be related to differences in coronary plaque burden and composition. The purpose of this study was to evaluate whether differences in the extent and composition of coronary plaques in patients with and without diabetes can be observed using multislice computed tomography (MSCT).

RESEARCH DESIGN AND METHODS—MSCT was performed in 215 patients (86 [40%] with type 2 diabetes). The number of diseased coronary segments was determined per patient; each diseased segment was classified as showing obstructive (≥50% luminal narrowing) disease or not. In addition, plaque type (noncalcified, mixed, and calcified) was determined. Plaque characteristics were compared in patients with and without diabetes. Regression analysis was performed to assess the correlation between plaque characteristics and diabetes.

RESULTS—Patients with diabetes showed significantly more diseased coronary segments than nondiabetic patients (4.9 ± 3.5 vs. 3.9 ± 3.2, P = 0.03) with more nonobstructive (3.7 ± 3.0 vs. 2.7 ± 2.4, P = 0.008) plaques. Relatively more noncalcified (28 vs. 19%) and calcified (49 vs. 43%) and less mixed (23 vs. 38%) plaques were observed in patients with diabetes (P < 0.0001). Diabetes correlated with the number of diseased segments and nonobstructive, noncalcified, and calcified plaques.

CONCLUSIONS—Differences in coronary plaque characteristics on MSCT were observed between patients with and without diabetes. Diabetes was associated with higher coronary plaque burden. More noncalcified and calcified plaques and less mixed plaques were observed in diabetic patients. Thus, MSCT may be used to identify differences in coronary plaque burden, which may be useful for risk stratification.

At present, 200 million people worldwide have diabetes, whereas its prevalence is expected to continue increasing exponentially (1). A close relationship between type 2 diabetes and the development of coronary artery disease (CAD) exists (2), and cardiovascular disease is the main cause of death in this patient population (3).

Noninvasive testing, including myocardial perfusion scintigraphy and dobutamine stress echocardiography, has been used to detect CAD in diabetic patients (4,5), and a clear association between abnormal test results and worse outcome has been demonstrated, similar to that in the general population (6). Nonetheless, after normal findings, elevated event rates are still observed in diabetic patients compared with nondiabetic individuals (6,7), indicating a need for further refinement of prognostication in this population. The higher event rates in patients with diabetes compared with those in patients without diabetes could be related to differences in coronary plaque burden and composition. Therefore, direct visualization of coronary plaque burden could be a useful tool for risk stratification. Indeed, using invasive techniques, a considerably higher extent of CAD and plaque burden have been demonstrated in the presence of diabetes (8,9).

To date, atherosclerosis has been noninvasively assessed in patients with type 2 diabetes using coronary calcium scoring, which reveals extensive atherosclerosis (10,11). Still, coronary calcium scoring may seriously underestimate coronary plaque burden as noncalcified lesions are not recognized (12). More recently, contrast-enhanced multislice computed tomography (MSCT) coronary angiography has become available, which allows, in contrast to calcium scoring, detection of both calcified and noncalcified coronary lesions (1316). As a result, the technique potentially allows a more precise noninvasive evaluation of coronary atherosclerosis, which in turn could be valuable for improving risk stratification. Accordingly, the purpose of the present study was to evaluate whether differences in the extent and composition of coronary plaques in patients with diabetes compared with those in patients without diabetes can be observed with MSCT.

The study population consisted of 86 (40%) patients with known type 2 diabetes and 129 (60%) patients without diabetes who underwent examination with MSCT coronary angiography for recurrent chest pain complaints. Fifty-one (24%) patients were examined with a 16-slice MSCT scanner, whereas the majority (164 [76%]) underwent examination with 64-slice MSCT. Diabetes was diagnosed according to the American Diabetes Association criteria (17): 1) symptoms of diabetes and a casual plasma glucose level of ≥11.1 mmol/l or 2) a fasting plasma glucose level of ≥7.0 mmol/l. Only patients in sinus rhythm, without contraindications to MSCT, were included (18). All patients gave written informed consent to the study protocol, which was approved by the local ethics committee.

MSCT data acquisition

All examinations were performed using a Toshiba Multislice Aquilion system (Toshiba Medical Systems, Tokyo, Japan). First, a prospective coronary calcium scan without contrast enhancement was performed, followed by 16- or 64-slice MSCT coronary angiography performed according to the protocols described elsewhere (19,20). If the heart rate was ≥65 beats/min, additional oral β-blockers (metoprolol, 50 or 100 mg, single dose, 1 h before the examination) were provided if tolerated.

MSCT data analysis

Coronary artery calcium score.

Coronary artery calcium was identified as a dense area in the coronary artery exceeding the threshold of 130 Hounsfield units. A total Agatston score was recorded for each patient.

Coronary plaque assessment.

MSCT angiograms were evaluated by two experienced observers who were unaware of the clinical history of the patients. Coronary arteries were divided into 17 segments according to the modified American Heart Association classification (21). The presence of coronary plaques was evaluated visually using axial images and curved multiplanar reconstructions. One coronary plaque was assigned per coronary segment. Plaques were classified as obstructive and nonobstructive using a 50% threshold of luminal narrowing. As shown in Fig. 1, three types of plaques were identified: 1) noncalcified plaques are plaques having a lower density compared with the contrast-enhanced vessel lumen, 2) calcified plaques are plaques with high density, and 3) mixed plaques are plaques with noncalcified and calcified elements within a single plaque. The presence of coronary plaques on MSCT, the presence of obstructive CAD in general and if located in the left main/left anterior descending (LAD) coronary artery, and the presence of obstructive CAD in one vessel (single-vessel disease) or two or three vessels (multivessel disease) were evaluated. For each patient, the number of diseased coronary segments (segments containing plaques or previously implanted stents) and the number of coronary segments with nonobstructive as well as obstructive plaques were determined. Also, the numbers of segments with, respectively, noncalcified, mixed, and calcified plaques were determined.

Statistical analysis

Categorical variables were expressed as numbers (percentages) and compared between groups with a χ2 test. Continuous variables were expressed as means ± SD and compared with the two-tailed t test for independent samples. When not normally distributed, continuous variables were expressed as medians (interquartile range) and compared using nonparametric Mann-Whitney tests.

To determine the relationship between plaque characteristics and the presence of diabetes, linear regression analysis was performed when the dependent variable was continuous, and logistic regression analysis was performed when the dependent variable was categorical. First, univariate analysis was performed, followed by multivariate analysis with correction for the following variables: age, sex, risk factors for CAD, clinical presentation (typical angina pectoris or atypical chest pain together with the presence of multiple CAD risk factors), and use of statins.

P < 0.05 was considered statistically significant. Statistical analyses were performed using SPSS software (version 12.0; SPSS, Chicago, IL) and SAS software (release 6.12; SAS Institute, Cary, NC).

Baseline characteristics of patients with diabetes and without diabetes are provided in Table 1. In total, 215 patients (136 [63%] men; age [mean ± SD] 58 ± 11 years) were included, of whom 86 (40%) were patients with known type 2 diabetes. Ninety-six (45%) patients used statins (41 [48%] patients with diabetes, 55 [43%] without diabetes, P = 0.47), 91 (42%) used aspirin, 78 (36%) used β-blockers, and 69 (32%) used ACE inhibitors. Patients with diabetes were significantly younger compared with patients without diabetes and had a higher mean BMI and lower prevalence of previous CAD.

MSCT plaque characteristics

Total patient population.

Coronary plaque characteristics on MSCT in the entire population and in patients presenting with or without diabetes are shown in Table 2 and Fig. 2. After exclusion of 64 (2%) segments of nondiagnostic quality (n = 11 small caliber, n = 45 with motion artifacts due to elevated heart rate, and n = 8 with increased signal-to-noise ratio), a total of 2,941 coronary segments were included in the analysis. CAD was completely absent on MSCT in 41 (19%) patients. In the remaining 174 (81%) patients, 917 (31%) segments with plaques (n = 871 [30%]) or previously implanted stents (n = 46 [1%]) were observed. Of segments containing plaques, 675 (77%) showed nonobstructive and 196 (23%) showed obstructive CAD. In general, noncalcified plaques were observed in 204 (23%) segments, mixed plaques in 271 (31%) segments, and calcified plaques in 396 (46%) segments.

Diabetic patients versus nondiabetic patients.

As can be derived from Table 2, the average number of diseased segments was higher in patients with diabetes (4.9 ± 3.5) compared with nondiabetic patients (3.9 ± 3.2) (P = 0.03). In particular, nonobstructive coronary plaques were more frequently observed on MSCT in the former population (Fig. 2A). In addition, CAD tended to be more severe in diabetic patients as both left main/LAD coronary artery disease and multivessel disease were more frequently diagnosed, although the difference did not reach statistical significance.

For plaque types, however, significant differences were observed between diabetic and nondiabetic patients as patients with diabetes presented with significantly more segments containing noncalcified plaques (1.3 ± 2.0 vs. 0.7 ± 1.2, P = 0.005) as well as calcified plaques (2.3 ± .8 vs. 1.5 ± 2.1, P = 0.02). Accordingly, the relative distribution of plaque types, as illustrated in Fig. 2B, also differed because plaques in patients with diabetes were more frequently either noncalcified (114 of 406 [28%] vs. 90 of 465 [19%]) or calcified (198 of 406 [49%] vs. 198 of 465 [43%]). In contrast, plaques in patients with diabetes were less frequently mixed (94 of 406 [23%] vs. 177 of 465 [38%]) (P < 0.0001).

Correlation of MSCT plaque characteristics and diabetes

The results of uni- and multivariate analyses of the correlation between MSCT plaque characteristics and the presence of diabetes are depicted in Table 3. After correction for baseline characteristics, the correlation of the number of diseased coronary segments as well as the number of segments with nonobstructive plaques and the presence of diabetes remained statistically significant. For plaque type, both the number of coronary segments with noncalcified and calcified plaques remained significantly correlated with diabetes.

In the present study, differences in coronary plaque characteristics between patients with and without diabetes were observed using MSCT coronary angiography. A significant, positive correlation between the presence of diabetes and coronary plaque extent was demonstrated. In particular, diabetes was associated with an increased number of nonobstructive plaques, indicating more diffuse CAD compared with that in patients without diabetes. Also, differences in the distribution of coronary plaque types were observed, with diabetic patients showing more noncalcified and calcified plaques and less mixed plaques.

Plaque burden

In the present study, a larger plaque burden was observed in patients with diabetes. Similar observations have been reported in previous invasive as well as postmortem studies (22,23). Nicholls et al. (23) recently reported observations in 654 subjects (including 128 with diabetes) using intravascular ultrasound; the authors demonstrated that diabetes was a strong, independent predictor of percent plaque volume and total atheroma volume, indicating that diabetes appears to be associated with a substantial increase in (diffuse) plaque burden.

In addition, diabetes was associated with more nonobstructive plaques in the current study. This has also been observed in studies using invasive coronary angiography (8,9). The increased total plaque burden may be related to the increased event rate, as observed in diabetic patients. Moreover, it has been suggested that plaque rupture may occur often in nonobstructive lesions, referred to as vulnerable plaques (2427). Many of these nonobstructive lesions will not be associated with stress-inducible ischemia, resulting in normal results on functional imaging tests, such as nuclear imaging or stress echocardiography (28,29). Whether the larger total plaque burden and the increased prevalence of nonobstructive lesions in diabetic patients translates into a higher event rate remains to be determined in future studies.

Plaque composition

Another important finding of the present study is the difference in distribution of different coronary plaque types between patients with and without diabetes. Relatively more noncalcified and calcified plaques were observed in patients with diabetes. At the same time, the proportion of mixed plaques (possibly regarded as an intermediate phase of coronary plaque development) was significantly lower in patients with diabetes. Accordingly, these observations could suggest a more rapid development of atherosclerosis in the presence of diabetes, with faster progression from noncalcified lesions to completely calcified lesions. A faster progression of atherosclerosis in patients with diabetes had been suggested previously on the basis of event rates in patients undergoing nuclear perfusion imaging (6,30). In the general population, a normal perfusion scan is associated with a low (<1%) hard event rate, which is sustained over long-term follow-up. In patients with diabetes, the hard event rate is equally low in the first 2 years in patients with a normal perfusion scan, but an increased event rate (despite the initial normal myocardial perfusion scan) is observed after 2 years of follow-up. This observation has been considered to be related to a faster progression of CAD in diabetic patients.

The increased prevalence of both noncalcified and calcified plaques also may have implications for calcium scoring. In a recent study by Raggi et al. (31), 10,377 asymptomatic individuals (including 903 patients with diabetes) were followed for a period of 5 ± 3.5 years after coronary calcium scoring with electron- beam computed tomography. Higher mortality was observed in diabetic patients compared with nondiabetic patients despite similar coronary calcium scores, a finding that was observed for every level of coronary calcification. The authors hypothesized that the difference in prognosis in diabetic and nondiabetic patients despite similar calcium load could be attributed to the presence of extensive diffuse noncalcified atherosclerosis, which could not be detected by calcium scoring. In line with these suggestions, the current study indeed demonstrated the presence of diffuse atherosclerosis with a significantly higher amount of noncalcified coronary plaques in the diabetic patients. Accordingly, calcium scores may underestimate total coronary plaque burden to a higher extent in patients with diabetes, and, thus, MSCT coronary angiography may have substantial incremental value over coronary calcium scoring, although this concept needs further study.

Limitations

This study is a comparative study, describing coronary atherosclerosis in patients with and without diabetes. Examinations were performed at a single time point and were not repeated over time. Also, MSCT angiograms were evaluated visually as no reliable quantitative algorithms are currently available. Two scanner generations (16- and 64-slice MSCT) were used during the study, which could have affected the accuracy of detection of different plaque types. Follow-up data are not yet available, and these data are needed to determine whether the observations on MSCT may provide prognostic information and may potentially be used to identify diabetic patients at increased risk. Finally, patients in the present study were referred for noninvasive cardiac evaluation of chest pain with known or suspected CAD. Accordingly, the findings may not be applicable to asymptomatic diabetic patients.

In addition, several limitations of MSCT in general should be mentioned. MSCT is still associated with an elevated radiation dose, and administration of contrast media is also required. Finally, the presence of ischemia cannot be determined on MSCT, and abnormal MSCT findings should ideally be combined with functional data.

In summary, differences in coronary plaque characteristics on MSCT were observed between patients with diabetes and without diabetes. Diabetes may be associated with a higher coronary plaque burden as determined on MSCT. Also, more noncalcified and calcified plaques in combination with less mixed plaques were observed in patients with diabetes, possibly reflecting faster progression of CAD in the presence of diabetes. MSCT may be used to identify differences in coronary plaque burden, which may eventually be useful for risk stratification of patients with diabetes.

Figure 1—

An example of diffuse atherosclerosis demonstrated on MSCT coronary angiography in a patient with type 2 diabetes. A: Three-dimensional volume–rendered reconstruction depicts severe narrowing of the proximal and mid–left anterior descending (LAD) coronary artery and occluded left circumflex coronary artery (LCx). B: The findings were confirmed by conventional coronary angiography. C and D: Curved multiplanar reconstruction and the corresponding transversal sections of the LAD show multiple obstructive mixed plaques in the whole course of the artery. E: A nonobstructive plaque followed by vessel occlusion was demonstrated in the LCx coronary artery. F: Diffuse nonobstructive calcified plaque and an obstructive noncalcified plaque were seen in the right coronary artery (RCA), which was confirmed by conventional coronary angiography (G).

Figure 1—

An example of diffuse atherosclerosis demonstrated on MSCT coronary angiography in a patient with type 2 diabetes. A: Three-dimensional volume–rendered reconstruction depicts severe narrowing of the proximal and mid–left anterior descending (LAD) coronary artery and occluded left circumflex coronary artery (LCx). B: The findings were confirmed by conventional coronary angiography. C and D: Curved multiplanar reconstruction and the corresponding transversal sections of the LAD show multiple obstructive mixed plaques in the whole course of the artery. E: A nonobstructive plaque followed by vessel occlusion was demonstrated in the LCx coronary artery. F: Diffuse nonobstructive calcified plaque and an obstructive noncalcified plaque were seen in the right coronary artery (RCA), which was confirmed by conventional coronary angiography (G).

Figure 2—

A: Clustered columns demonstrating the distribution of diseased coronary segments, segments with nonobstructive and obstructive plaques in diabetic and nondiabetic patients. ▪, diabetes present; □, no diabetes. B: Bar graph demonstrating the relative distribution of coronary segments with different plaque types in patients with diabetes and without diabetes (P < 0.0001). □, calcified plaques; ▒, mixed plaques; ▪, noncalcified plaques.

Figure 2—

A: Clustered columns demonstrating the distribution of diseased coronary segments, segments with nonobstructive and obstructive plaques in diabetic and nondiabetic patients. ▪, diabetes present; □, no diabetes. B: Bar graph demonstrating the relative distribution of coronary segments with different plaque types in patients with diabetes and without diabetes (P < 0.0001). □, calcified plaques; ▒, mixed plaques; ▪, noncalcified plaques.

Table 1—

Characteristics of patients with and without diabetes

All patientsPatients with diabetesPatients without diabetes
n 215 86 129 
Age (years)* 58 ± 11 56 ± 11 59 ± 12 
Male sex 136 (63) 56 (65) 80 (62) 
Hypercholesterolemia 114 (53) 53 (62) 61 (47) 
Arterial hypertension 107 (50) 48 (56) 59 (46) 
Smoking 80 (37) 33 (38) 47 (36) 
Family history of CAD 82 (38) 30 (35) 52 (40) 
BMI (kg/m2)* 27 ± 4 28 ± 5 26 ± 4 
Obesity 37 (17) 20 (24) 17 (14) 
Cardiac history    
Previous MI* 41 (19) 8 (9) 33 (26) 
Previous PCI* 42 (20) 9 (11) 33 (26) 
All patientsPatients with diabetesPatients without diabetes
n 215 86 129 
Age (years)* 58 ± 11 56 ± 11 59 ± 12 
Male sex 136 (63) 56 (65) 80 (62) 
Hypercholesterolemia 114 (53) 53 (62) 61 (47) 
Arterial hypertension 107 (50) 48 (56) 59 (46) 
Smoking 80 (37) 33 (38) 47 (36) 
Family history of CAD 82 (38) 30 (35) 52 (40) 
BMI (kg/m2)* 27 ± 4 28 ± 5 26 ± 4 
Obesity 37 (17) 20 (24) 17 (14) 
Cardiac history    
Previous MI* 41 (19) 8 (9) 33 (26) 
Previous PCI* 42 (20) 9 (11) 33 (26) 

Data are means ± SD or n (%).

*

P < 0.05 between patients with and without diabetes. MI, myocardial infarction; PCI, percutaneous coronary intervention.

Table 2—

MSCT plaque characteristics in the whole study population and comparison between patients with diabetes and without diabetes

All patientsPatients with diabetesPatients without diabetes
n 215 86 129 
Patients    
    Coronary plaques on MSCT 174 (81) 73 (85) 101 (78) 
    Obstructive CAD 80 (37) 34 (40) 46 (36) 
    Single-vessel disease 43 (20) 16 (19) 27 (21) 
    Multivessel disease 37 (17) 18 (21) 19 (15) 
    Obstructive CAD in left main/LAD coronary artery 61 (28) 29 (34) 32 (25) 
    Total Agatston calcium score 73 (0–387) 72 (0–372) 74 (0–391) 
Segments    
    No. of diseased segments* 4.3 ± 3.4 4.9 ± 3.5 3.9 ± 3.2 
    No. of segments with obstructive plaques 0.9 ± 1.7 1.0 ± 1.8 0.9 ± 1.6 
    No. of segments with nonobstructive plaques* 3.1 ± 2.7 3.7 ± 3.0 2.7 ± 2.4 
    No. of segments with noncalcified plaques* 1.0 ± 1.6 1.3 ± 2.0 0.7 ± 1.2 
    No of segments with mixed plaques 1.3 ± 1.8 1.1 ± 1.5 1.4 ± 2.0 
    No of segments with calcified plaques* 1.8 ± 2.4 2.3 ± 2.8 1.5 ± 2.1 
All patientsPatients with diabetesPatients without diabetes
n 215 86 129 
Patients    
    Coronary plaques on MSCT 174 (81) 73 (85) 101 (78) 
    Obstructive CAD 80 (37) 34 (40) 46 (36) 
    Single-vessel disease 43 (20) 16 (19) 27 (21) 
    Multivessel disease 37 (17) 18 (21) 19 (15) 
    Obstructive CAD in left main/LAD coronary artery 61 (28) 29 (34) 32 (25) 
    Total Agatston calcium score 73 (0–387) 72 (0–372) 74 (0–391) 
Segments    
    No. of diseased segments* 4.3 ± 3.4 4.9 ± 3.5 3.9 ± 3.2 
    No. of segments with obstructive plaques 0.9 ± 1.7 1.0 ± 1.8 0.9 ± 1.6 
    No. of segments with nonobstructive plaques* 3.1 ± 2.7 3.7 ± 3.0 2.7 ± 2.4 
    No. of segments with noncalcified plaques* 1.0 ± 1.6 1.3 ± 2.0 0.7 ± 1.2 
    No of segments with mixed plaques 1.3 ± 1.8 1.1 ± 1.5 1.4 ± 2.0 
    No of segments with calcified plaques* 1.8 ± 2.4 2.3 ± 2.8 1.5 ± 2.1 

Data are means ± SD, median (interquartile range), or n (%).

*

P < 0.05 between patients with and without diabetes. LAD, left anterior descending.

Table 3—

Estimates of correlation of MSCT plaque characteristics with the presence of diabetes

MSCT characteristicsUnivariate
Multivariate
Parameter estimateP valueParameter estimateP value
Patients     
    Total Agatston calcium score 127.91 0.11 139 0.08 
    Coronary plaques on MSCT 1.56 (0.76–3.21) 0.23 1.35 (0.56–3.26) 0.50 
    Nonobstructive CAD 1.53 (0.70–3.32) 0.28 1.11 (0.42–2.94) 0.83 
    Obstructive CAD 1.59 (0.72–3.52) 0.25 2.09 (0.68–6.49) 0.20 
    Obstructive CAD in left main/LAD coronary artery 1.70 (0.77–3.74) 0.19 2.89 (0.90–9.31) 0.08 
    Single-vessel disease 1.11 (0.46–2.67) 0.82 1.35 (0.43–4.29) 0.61 
    Multivessel disease 1.77 (0.72–4.35) 0.21 4.78 (0.66–34.37) 0.12 
Segments     
    No. of diseased segments 1.01 0.03 1.51 0.0004 
    No. of segments with obstructive plaques 0.13 0.58 0.33 0.17 
    No. of segments with nonobstructive plaques 0.99 0.008 1.27 0.0005 
    No. of segments with noncalcified plaques 0.63 0.006 0.69 0.004 
    No of segments with mixed plaques −0.28 0.28 0.03 0.91 
    No of segments with calcified plaques* 0.77 0.02 0.88 0.008 
MSCT characteristicsUnivariate
Multivariate
Parameter estimateP valueParameter estimateP value
Patients     
    Total Agatston calcium score 127.91 0.11 139 0.08 
    Coronary plaques on MSCT 1.56 (0.76–3.21) 0.23 1.35 (0.56–3.26) 0.50 
    Nonobstructive CAD 1.53 (0.70–3.32) 0.28 1.11 (0.42–2.94) 0.83 
    Obstructive CAD 1.59 (0.72–3.52) 0.25 2.09 (0.68–6.49) 0.20 
    Obstructive CAD in left main/LAD coronary artery 1.70 (0.77–3.74) 0.19 2.89 (0.90–9.31) 0.08 
    Single-vessel disease 1.11 (0.46–2.67) 0.82 1.35 (0.43–4.29) 0.61 
    Multivessel disease 1.77 (0.72–4.35) 0.21 4.78 (0.66–34.37) 0.12 
Segments     
    No. of diseased segments 1.01 0.03 1.51 0.0004 
    No. of segments with obstructive plaques 0.13 0.58 0.33 0.17 
    No. of segments with nonobstructive plaques 0.99 0.008 1.27 0.0005 
    No. of segments with noncalcified plaques 0.63 0.006 0.69 0.004 
    No of segments with mixed plaques −0.28 0.28 0.03 0.91 
    No of segments with calcified plaques* 0.77 0.02 0.88 0.008 

Data are odds ratios(95% CI) or estimates of correlation. LAD, left anterior descending.

G.P. is supported financially by a training fellowship grant from the European Society of Cardiology, by a Huygens scholarship, and by Toshiba Medical Systems Europe. J.D.S. is supported financially by The Netherlands Heart Foundation (grant 2002B105). J.W.J. is an established investigator of the Netherlands Heart Foundation (grant 2001T032). J.J.B. has received research grants from GE Healthcare and BMS Medical Imaging.

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Published ahead of print at http://care.diabetesjournals.org on 26 January 2007. DOI: 10.2337/dc06-2104.

A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

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