Open Access

Relation between low-density lipoprotein cholesterol/apolipoprotein B ratio and triglyceride-rich lipoproteins in patients with coronary artery disease and type 2 diabetes mellitus: a cross-sectional study

  • Shigemasa Tani1, 2, 3Email author,
  • Tsukasa Yagi2, 3,
  • Wataru Atsumi2, 3,
  • Kenji Kawauchi2, 3,
  • Rei Matsuo2, 3 and
  • Atsushi Hirayama3
Cardiovascular Diabetology201716:123

https://doi.org/10.1186/s12933-017-0606-7

Received: 3 July 2017

Accepted: 23 September 2017

Published: 2 October 2017

Abstract

Background

The low-density lipoprotein cholesterol/apolipoprotein B (LDL-C/apoB) ratio has conventionally been used as an index of the LDL-particle size. Smaller LDL-particle size is associated with triglyceride (TG) metabolism disorders, often leading to atherogenesis. We investigated the association between the LDL-C/apoB ratio and TG metabolism in coronary artery disease (CAD) patients with diabetes mellitus (DM).

Methods

In the cross-sectional study, the LDL-C/apoB ratio, which provides an estimate of the LDL-particle size, was calculated in 684 consecutive patients with one additional risk factor. The patients were classified into 4 groups based on the presence or absence of CAD and DM, as follows: CAD (−) DM (−) group, n = 416; CAD (−) DM (+) group, n = 118; CAD (+) DM (−) group, n = 90; CAD (+) DM (+) group, n = 60.

Results

A multi-logistic regression analysis after adjustments for coronary risk factors revealed that the CAD (+) DM (+) condition was an independent predictor of the smallest LDL-C/apoB ratio among the four groups. Furthermore, multivariate regression analyses identified elevated TG-rich lipoprotein (TRL)-related markers (TG, very-LDL fraction, remnant-like particle cholesterol, apolipoprotein C-II, and apolipoprotein C-III) as being independently predictive of a smaller LDL-particle size in both the overall subject population and a subset of patients with a serum LDL-C level < 100 mg/dL. In the 445 patients followed up for at least 6 months, multi-logistic regression analyses identified increased levels of TRL-related markers as being independently predictive of a decreased LDL-C/apoB ratio, which is indicative of smaller LDL-particle size.

Conclusions

The association between disorders of TG metabolism and LDL heterogeneity may account for the risk of CAD in patients with DM. Combined evaluation of TRL-related markers and the LDL-C/apoB ratio may be of increasing importance in the risk stratification of CAD patients with DM. Further studies are needed to investigate the useful clinical indices and outcomes of these patients.

Clinical Trial Registration UMIN (http://www.umin.ac.jp/) Study ID: UMIN000028029 retrospectively registered 1 July 2017

Keywords

Coronary artery disease Diabetes mellitus LDL-particle size Triglyceride-rich lipoproteins

Introduction

Progression of coronary atherosclerosis in patients with diabetes mellitus (DM) is characterized by increased frequency, extent, complexity, and rate of progress compared to that in non-DM patients [13].

In a meta-analysis that assessed the preventive effect of statins on cardiovascular (CV) events, the preventive effect on CV mortality was found to be no more than 20% even when the serum low-density lipoprotein cholesterol (LDL-C) level was controlled with a statin [4], and among the residual risks of statin therapy, insulin resistance, Impaired glucose tolerance, and lipid metabolism abnormalities [5], especially defective triglyceride (TG) metabolism, was found to cause a decrease in LDL-particle size, which has a powerful atherogenic effect [6].

Moreover, TG metabolites, i.e., chylomicrons, very low density lipoprotein (VLDL), and remnant-like particle cholesterol (RLP-C), which are TG-rich lipoproteins (TRLs), and, apolipoprotein (apo) C-II and apo C-III which are involved in the metabolic process, etc., have been demonstrated to be involved in the progression of atherosclerosis [6].

Density gradient ultracentrifugation, nondenaturing gradient gel electrophoresis, and nuclear magnetic resonance spectroscopy are the methods that are usually employed to measure LDL-particle diameter; however, these methods present problems in clinical settings due to their cost and complexity [7]. Each LDL-particle has one apolipoprotein (apo) B molecule, which is recognized by LDL receptors that clear LDL from the plasma. Thus, the apoB concentration represents the plasma number of LDL-particles. Thus, the LDL-C/apoB ratio reflects indirectly the LDL-particle size [7].

An LDL-C/apoB ratio of 1.2 has been suggested to correspond to an LDL diameter of 25.5 nm, which is the cut-off value for distinguishing LDL pattern A (large buoyant LDL) from LDL pattern B [small dense (sd)-LDL] [7, 8], indicating the presence of a large quantity of sd-LDL. In fact, the Québec Cardiovascular Study demonstrated that in patients with LDL-particle sizes of 25.5 nm or smaller, the CAD incidence increased significantly as the serum LDL-C level increased, while in patients having large LDL-particle sizes of 26.0 nm or greater, no significant difference in CAD events was observed according to the absolute serum LDL-C level [9].

We hypothesized that reduction of the LDL-C/apoB ratio is associated with disordered TG metabolism, particularly with increase of TRLs, and that the LDL-C/apoB ratio is lower in CAD patients with underlying DM than in CAD patients without DM, patients with DM alone and patients without CAD or DM.

The purpose of this study was to evaluate the LDL-C/apoB ratio as a marker of LDL-particle size in CAD patients with DM in a hospital-based cross-sectional study, and to clarify the relationships between the LDL-C/apoB ratio and TRL-related markers (TG, VLDL, RLP-C,apo C-II, and apo C-III), which are indicators of TG metabolism.

Methods

Study design and populations

This study was designed as a hospital-based cross-sectional study to investigate the relationship between the LDL-C/apoB ratio and TRL-related markers including TG, VLDL, RLP-C, apoC-II, and apo C-III, in CAD patients with type-2 diabetes. In addition, we examined the relationships among the changes in the LDL-C/apoB ratio and changes in the TRL-related markers in those cases that were still available for additional measurements 6 months later. This study is the sub-analysis of our previous study, which showed LDL-particle size and TG-metabolism disorder using cross-sectional method [10].

The study was conducted on a sample of 700 consecutive outpatients with the presence of one or more risk factors for CAD, who had undergone regular examinations for treatment of their various diseases at the Cardiovascular Center, Nihon University Surugadai Hospital between April 2009 and October 2009. This study was conducted in accordance with the ethical principles of the Declaration of Helsinki. The study protocol was approved by the Institutional Review Board at our institute and written informed consent was obtained from all the study participants.

The criterion for patient registration in the cross sectional study was the presence of one or more risk factors for CAD. The diagnostic criteria for the coronary risk factors used in this study were as follows; hypertension: systolic pressure of ≥ 140 mmHg and/or a diastolic pressure of ≥ 90 mmHg, or taking antihypertensive medication; diabetes mellitus: fasting plasma glucose ≥ 126 mg/dL and HbA1c ≥ 6.5%, or current treatment with anti-diabetic agents; lipid disorder: serum LDL-C ≥ 140 mg/dL, serum TG ≥ 150 mg/dL, and/or serum high-density lipoprotein cholesterol (HDL-C) less than 40 mg/dL, or current treatment with lipid-modifying medication; Cigarette smoking was defined as current smoking or smoking cessation within 1 year prior to the start of the study; chronic kidney disease: Estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73 m2; obesity: body mass index ≥ 25 kg/m2. A diagnosis of hyperuricemia was made when the serum uric acid level was 7.0 mg/dL or above, or taking medications.

Angiographically, CAD was defined as a history of documented myocardial infarction, prior coronary revascularization intervention (coronary artery bypass graft surgery or percutaneous coronary intervention), or the presence of ≥ 50% stenosis in 1 or more of the coronary arteries identified during cardiac catheterization.

Patients were not enrolled if they met any of the following exclusion criteria: hepatic dysfunction (alanine aminotransferase and aspartate aminotransferase ≥ 2 times the upper limit of the normal values), known malignant disease, or diagnosis of acute coronary syndrome within 3 months prior to the study.

Measurement of laboratory parameters

Fasting blood samples were collected early in the morning after a 12-h fast. The serum total cholesterol (TC), HDL-C, and TG levels were measured by the standard methods. The serum LDL-C level was estimated by using the Friedewald formula [11]. The VLDL fraction was measured by performing polyacrylamide-gel electrophoresis using the LipoPhor system (Joko, Tokyo, Japan). The RLP-C level was measured by an immunoadsorption assay (SRL Inc., Tokyo, Japan). The serum apolipoproteins were determined by turbidimetric latex agglutination assays (SRL). The malondialdehyde-modified LDL (MDA-LDL) level was measured by an enzyme-linked immunosorbent assay (SRL). The high sensitivity C-reactive protein (hs-CRP) level was measured by a nephelometric assay (Behring Diagnostic Marburg, Germany). The eGFR was calculated by using the abbreviated MDRD (Modification of Diet in Renal Disease) study formula modified by a Japanese coefficient [12].

Statistical analysis

Data are expressed as the mean ± standard deviation (SD) for continuous variables and as percentages for discreet variables. Data that did not have a normal distribution were expressed as medians (interquartile range). The data for categorical variables were analyzed by the χ2 test. For the subset analysis of four groups according to the presence or absence of DM and CAD, we used analysis of variance (ANOVA) followed by Bonferroni’s correction for covariates if differences were found in the patient characteristics or laboratory profile markers. In this study, an LDL-C/apoB ratio of 1.2 was deemed to correspond to an LDL particle size of 25.5 nm (the cutoff sd-LDL particle size), consistent with previous reports [79], and an LDL-C/apoB ratio of < 1.2 served as a dependent variable for the multivariate logistic regression analysis described below. A detailed multi-logistic analysis of each group was performed in which the presence or absence of CAD and DM was evaluated in patients with an LDL-C/apoB ratio of less than 1.2. Accordingly, multi-logistic regression analyses were performed with no adjustments (model 1), after adjustment for age and gender (model 2), and after adjustment for traditional coronary risk factors and concomitant use of drugs with an action that increases LDL-particle size (e.g., statins, fibrates, and glitazones [13]) (model 3). These analyses were used to evaluate the association between LDL-C/apoB ratios of less than 1.2 and the prevalence of CAD or DM. Furthermore, univariate and multivariate regression analyses were performed to identify independent variables of LDL-C/apoB ratio. As the TRLs-related markers constituted mutually confounding factors, five multivariate regression models incorporating the respective variables were established to carry out the analyses. All variables correlated with LDL-C/apoB ratio at p < 0.05 in the univariate regression analysis were entered into the multivariate model. For the cases that were still available for additional measurements 6 months later, a multi-logistic regression analysis was performed to identify variables that were significantly associated with the changes in the LDL-C/apoB ratio. Increase/decrease of the LDL-C/apoB ratio from the baseline was entered as a dependent variable, and the age, gender, CAD risk factors, and the absolute changes of the TRL-related markers were entered as independent variables. We used SPSS Window ver 12.0 (Statistical Package for the Social Sciences, SPSS Ins., Chicago, IL) for all analyses.

Results

Subjects

We excluded 16 subjects from the study because of missing laboratory data. A final total of 684 subjects were included in the study. The participants consisted of 470 (59%) male and 214 (41%) female patients. The patients were classified into the four groups according to the presence or absence of CAD and/or DM. Comparison of the four groups according to the presence or absence of CAD and/or DM is shown in Tables 1, 2, and 3.
Table 1

Patient characteristics

Variables

All cases n = 684

CAD (+)

CAD (+)

p value among the 4 groups

DM (+) n = 60

DM (−) n = 90

p value between the 2 groups

DM (+) n = 118

DM (−) n = 416

p value between the 2 groups

Male/female, n (%)

470 (69)/214 (31)

54 (90)/6 (10)

79 (88)/11 (12)

0.674

83 (70)/35 (30)

254 (61)/162 (39)

0.732

< 0.0001

Age (years)

62 ± 14

65 ± 10.3

64 ± 11.3

0.529

68 ± 113

60 ± 16

< 0.0001

< 0.0001

BMI (kg/m2)

24.1 ± 3.9

24.6 ± 3.5

24.4 ± 3.8

0.810

24.7 ± 4.1

23.7 ± 4.0

0.001

0.050

BMI ≥ 30, n (%)

51 (7.5)

4 (6.7)

5 (5.6)

0.911

13 (11.3)

30 (7.2)

0.049

0.384

Hypertension, n (%)

479 (70)

51 (85)

66 (73)

0.078

85 (72)

279 (67)

0.302

0.027

Cigarette smoking, n (%)

103 (15)

8 (13)

9 (10)

0.544

18 (15)

67 (16)

0.939

0.554

Dyslipidemia, n (%)

458 (67)

60 (100)

71 (82)

0.0005

107 (91)

216 (52)

< 0.0001

< 0.0001

Hyperuricemia

130 (19)

13 (25)

20 (22)

0.589

21 (18)

71 (17)

0.670

0.423

eGFR (ml/min/1.73m2)

70.4 ± 18.5

68.8 ± 14.0

69.0 ± 16.0

0.278

72.6 ± 20.4

70.3 ± 19.1

0.307

0.467

CKD stage 3 ≥, n (%)

192 (28)

15 (25)

28 (31)

0.401

30 (25)

116 (28)

0.562

0.697

CAD, n (%)

150 (22)

     

Effort AP/OMI

46/104

17 (28)/43 (78)

29 (32)/62 (68)

0.613

BNP (pg/mL)

23.1 (11.1/46.3)

32.5 (15.2/53.2)

35.5 (13.7/71.0)2

0.407

28.9 (15.1/75.4)1

19.4 (9.8/38.6)

0.081

0.0162

Cerebral Infarction, n (%)

20 (2.9)

2 (3.3)

3 (3.3)

0.705

8 (6.8)

7(1.7)

0.003

0.036

Peripheral arterial disease, n (%)

10 (1.5)

2 (3.3)

2 (2.2)

0.696

5 (4.2)

1 (0.2)

0.0005

0.006

HbA1c (%)

5.94 ± 0.77

6.83 ± 1.123,4

5.70 ± 0.34

< 0.0001

6.68 ± 0.863,4

5.64 ± 0.42

< 0.0001

< 0.0001

Duration of diabetes (years)*

5.3 (3.3/9.8)

6.2 (4.3/7.5)–

  

Concomitant drugs (%)

 Antiplatelets

190 (27.8)

55 (92)

69 (77)

0.017

60 (25)

37 (8.9)

< 0.0001

< 0.0001

 ACE inhibitors

52 (7.6)

11 (18)

14 (16)

0.655

6 (5.1)

21 (5.0)

0.770

< 0.0001

 ARBs

271 (40)

22 (37)

30 (33)

0.674

54 (46)

165 (40)

0.129

0.312

 β Blockers

144 (21)

25 (42)

21 (23)

0.017

27 (23)

71 (17)

0.070

0.0002

 Calcium channel blockers

316 (46)

32 (53)

46 (51)

0.790

54 (46)

184 (44)

0.974

0.430

 Statins

318 (46)

53 (88)

66 (73)

0.026

59 (50)

140 (34)

0.002

< 0.0001

 Fibrates

13 (1.9)

10 (1.7)

1 (1.1)

0.771

7 (5.9)

4 (1.0)

0.002

0.006

 Sulfonylurea

48 (7.0)

24 (40)

23(19)

 Metformin

19 (2.8)

8 (10)

–12 (10)

 

 α-Glucosidase inhibitor

45 (6.6)

20 (33)

23 (19)

 Thiazolidine

21 (3.1)

11 (18)

8 (6.8)

 Insulin

4 (0.7)

1 (1.7)

3 (2.5)

ANOVA and post hoc tests with Bonferroni correction were performed to test between-group differences

BMI body mass index, eGFR estimated glomelular flow rate; CKD chronic kidney disease, CAD coronary artery disease, AP angina pectoris, OMI old myocardial infarction, Hb hemoglobin, ACE angiotensin-converting enzyme, ARB angiotensin receptor blocker

* Median interquartile range in parentheses

1p < 0.05, 2 p < 0.01, 3 p < 0.0001 vs. CAD (−) DM (−) group

4p < 0.0001 vs. CAD (+) DM (−) group

Table 2

Laboratory profile

Variables

All cases n = 684

CAD (+)

CAD (−)

p value among the 4 groups

DM (+) n = 60

DM (−) n = 90

p value between the 2 groups

DM (+) n = 118

DM (−) n = 416

p value between the 2 groups

Lipids

 TC (mg/dL)

195 ± 38

176 ± 364,7

179 ± 314,7

0.380

196 ± 36

201 ± 38

0.064

< 0.0001

 LDL-C (mg/dL)

109 ± 31

97 ± 274,5

97 ± 254,5

0.710

109 ± 29

114 ± 31

0.209

< 0.0001

 HDL-C (mg/dL)

58 ± 17

51 ± 114,9

56 ± 15

0.012

56 ± 18

59 ± 17

0.029

0.0004

 non-HDL-C (mg/dL)

138 ± 35

126 ± 343,6

123 ± 284,7

0.866

140 ± 36

142 ± 35

0.363

< 0.0001

TRLs-related markers

 TG (mg/dL)*

122 (88/186)

192 (106/210)1

125 (86/173)5

0.128

145 (109/221)3

115 (83/176)

< 0.0001

0.003

 VLDL fraction (%)

12.9 ± 6.6

14.7 ± 6.92

13.5 ± 6.91,5

0.341

15.3 ± 6.94

11.9 ± 6.2

< 0.0001

< 0.0001

 RLP-C (mg/dL)*

5.4 (4.0/8.0)

5.3 (3.5/8.7)

4.9 (3.5/7.1)

0.271

6.0 (4.4/9.4)

5.3 (4.0/7.7)

0.027

0.096

 apo B (mg/dL)

90 ± 22

85 ± 211

83 ± 173,6

0.640

92 ± 21

92 ± 22

0.943

0.0012

 apo C-II (mg/dL)

4.6 ± 2.1

5.2 ± 2.62,8

4.3 ± 1.96

0.044

5.1 ± 2.42

4.4 ± 1.9

0.005

0.0009

 apo C-III (mg/dL)

10.2 ± 3.8

10.6 ± 4.6

9.9 ± 3.7

0.303

10.8 ± 4.4

10.0 ± 3.0

0.094

0.108

LDL oxidation marker

 MDA-LDL (U/L)

110 ± 46

106 ± 40

93 ± 333,6

0.051

114 ± 45

114 ± 49

0.207

0.001

Lipid ratio

 TG/HDL-C*

2.32 (1.44/3.60)

2.74 (1.93/4.46)1

2.29 (1.66/3.44)5

0.032

2.80 (1.84/4.58)2

2.04 (1.28/3.34)

0.018

0.007

Inflammatory marker

 WBC count (mm−3)

6096 ± 1630

6354 ± 1374

6126 ± 1271

0.258

6391 ± 1745

5960 ± 1685

0.013

0.037

 hs-CRP (mg/L)*

0.50 (0.30/1.20)

0.55 (0.22/1.78)

0.40 (0.20/0.90)

0.290

0.80 (0.40/1.60)

0.50 (0.20/1.10)

< 0.0001

0.322

ANOVA and post hoc tests with Bonferroni correction were performed to test between-group differences

TC total cholesterol, LDL low-density lipoprotein, HDL high-density lipoprotein, TG triglyceride, VLDL very LDL, RLP remnant-like particle, apo apolipoprotein, MDA malondealdehyde-modified, WBC white blood count, hs-CRP high-sensitivity C-reactive protein

* Median interquartile range in parentheses

1p < 0.05, 2 p < 0.01, p < 0.001, p < 0.0001 vs. CAD (−) DM (−) group

5p < 0.05, p < 0.01, p < 0.001 vs. CAD (−) DM (+) group

8p < 0.05 vs. CAD (+) DM (−) group

Table 3

Lipid profile

Variables

CAD (+) n = 140

CAD (−) n = 534

p value between the 2 groups

DM (+) n = 190

DM (−) n = 494

p value between the 2 groups

non-HDL-C (mg/dL)

123 ± 31

142 ± 3 5

< 0.0001

139 ± 35

134 ± 35

0.105

TG (mg/dL)*

128 (92/186)

120 (87/187)

0.295

139 (107/218)

119 (89/176)

< 0.0001

VLDL (%)

14.0 ± 6.9

12.6 ± 6.5

0.025

14.8 ± 6.8

12.2 ± 6.3

< 0.0001

RLP-C (mg/dL)*

5.0 (3.5/7.4)

5.4 (4.1/8.0)

0.130

5.7 (4.2/8.9)

5.2 (3.9/7.4)

0.0026

apo C-II (mg/dL)

4.7 ± 2.2

4.6 ± 2.1

0.627

4.7 (3.5/6.1)

4.2 (3.1/5.3)

0.0004

apo C-III (mg/dL)

10.2 ± 4.0

10.2 ± 3.7

0.856

9.7 (8.0/12.3)

9.4 (7.8/11.4)

0.059

LDL-C/apoB ratio*

1.174 (1.073/1.231)

1.241 (1.138/1.333)

< 0.0001

1.173 ± 0.152

1.227 ± 0.152

< 0.0001

TG/HDL-C ratio*

2.497 (1.715/3.824)

2.555 (1.360/3.593)

0.063

3.558 ± 2.648

2.828 ± 2.717

0.002

TC total cholesterol, LDL low-density lipoprotein, HDL high-density lipoprotein, TG triglyceride, VLDL very LDL, RLP remnant-like particle, apo apolipoprotein, MDA malondealdehyde-modified, WBC white blood count, hs-CRP high-sensitivity C-reactive protein

* Median; interquartile range in parentheses

Table 3 shows the results of analysis from another viewpoint to provide a clearer understanding of the features of the lipid profiles for the four categories of patients shown in Table 2. The serum non-HDL-C level was significantly lower in the CAD (+) group than in the CAD (−) group, probably reflecting the statin treatment that is given to many patients of the CAD (+) group. The VLDL fraction was significantly higher in the CAD (+) group than in the CAD (−) group, probably reflecting a higher percentage of patients potentially having abnormal TG metabolism in the CAD (+) group, although the serum TG level did not differ significantly between the two groups. On the other hand, comparison between the DM (+) group and DM (−) group revealed a significantly greater number of patients with high levels of TRL-related markers in the DM (+) group than in the DM (−) group. Furthermore, the LDL-C/apoB ratio was significantly lower in the CAD (+) group than in the CAD (−) group, and TG/HDL-C ratio was higher in the CAD (+) group than in the CAD (−) group, although this difference was not statistically significant. Comparison of the DM (+) and DM (−) groups revealed a significantly lower LDL-C/apoB ratio and significantly higher TG/HDL-C ratio in the DM (+) group than in the DM (−) group.

Comparison of LDL-C/apoB ratio among the 4 groups

The LDL-C/apoB ratios of the entire group of patients ranged from 0.622 to 1.694 (mean ± SD: 1.223 ± 0.146, and the LDL-C/apoB ratio ranges according to group were: CAD (+) DM (+) group, 0.622–1.408 (1.153 ± 0.133); CAD (+) DM (−) group, 0.868–1.458 (1.171 ± 0.129); CAD (−) DM (+) group, 0.779–1.525 (1.203 ± 0.124); and CAD (−) DM (−) group, 0.692–1.694 (1.250 ± 0.150)). There were significant differences in the LDL-C/apoB ratios among the 4 groups (p < 0.0001) (Fig. 1).
Fig. 1

Comparison of LDL-C/apoB ratio among the 4 groups. DM diabetes mellitus, CAD coronary artery disease; error bar mean ± standard deviation; *p < 0.0001, vs. CAD (−) DM(−) group; **p < 0.001 vs. CAD (−) DM(−) group

Multi-logistic regression analysis to determine the relationship between the LDL-C/apoB ratio corresponding to sd-LDL and the presence or absence of CAD and DM

Multi-logistic regression analyses with no adjustments (model 1), after adjustments for age and gender (model 2), and after adjustments for coronary risk factors and concomitant use of drugs (model 3) were performed to evaluate the association between an LDL-C/apoB ratio of < 1.2 and the prevalence of CAD or DM. The analysis with adjustments for traditional coronary risk factors and concomitant drug use revealed that the CAD (+) DM (+) group was the only group exhibiting a significant and independent variable for a LDL-C/apoB ratio of less than 1.2, both in the overall cohort (Fig. 2), and in the subgroup of patients with serum LDL-C levels of less than 100 mg/dL (data not shown).
Fig. 2

Multi-logistic regression analysis to determine the relationship between LDL-C/apoB ratio corresponding to sd-LDL and the presence or absence of DM and CAD. DM diabetes mellitus, CAD coronary artery disease, OR odds ratio, CI confidence interval. CAD (−) DM (−) group, n = 416; CAD (−) DM (+) group, n = 118; CAD (+) DM (−) group, n = 90; DM (+) CAD (+) group, n = 60. For this logistic regression analysis, an LDL-C/apoB ratio of 1.2 was deemed to correspond to an LDL particle size of 25.5 nm (the cutoff sd-LDL particle size) [9, 13, 14], and an LDL-C/apoB ratio of < 1.2 served as a dependent variable. Model 1: Unadjusted. Model 2: Adjusted for age and sex. Model 3: Adjusted for age, sex, hypertension (yes/no), cigarette smoking (yes/no), body mass index, statins use (yes/no), fibratses use (yes/no), and glitazones use, (yes/no)

Univariate and multivariate regression analyses of variables identified LDL-C/apoB ratio

All of the variables that correlated with the LDL-C/apoB ratios at p < 0.05 in the univariate regression analysis were entered into the 5 multivariate models. The results of the analyses of all of the multivariate regression models showed that serum TRLs-related markers were significant variables that were independent of LDL-C/apoB ratios. Next, similar analyses were performed in patients with serum LDL-C levels of < 100 mg/dL, patients with serum LDL-C levels of < 100 mg/dL, and patients taking/not taking lipid-modifying treatments. All the univariate and multivariate regression analyses showed that the high levels of TRL-related markers were independent determinants of a low LDL-C/apoB ratio (Table 4). Table 5 shows the correlations between LDL-C/apoB ratio and TRL-related markers among the 4 groups. LDL-C/apoB ratio and serum RLP-C level in the CAD (+) DM (−) group was the only correlation not showing statistical significant; on the other hand, statistically significantly negative correlations were noted between the LDL-C/apoB ratio and all TRL-related markers was noted.
Table 4

Univariate and multivariate regression analyses of variables identified LDL-C/apoB ratio

Variables

Univariate

Multivariate 1

Multivariate 2

Multivariate 3

Multivariate 4

Multivariate 5

r

p value

β

p value

β

p value

β

p value

β

p value

β

p value

All cases (n = 684)

 Age

−0.151

< 0.0001

−0.104

0.008

−0.125

0.001

−0.134

0.001

−0.144

0.0002

−0.141

0.0001

 Gender

−0.196

< 0.0001

−0.135

0.0003

−0.119

0.0005

−0.131

0.0007

−0.113

0.003

−0.079

0.027

 BMI

−0.134

0.001

0.020

0.622

0.002

0.960

0.011

0.797

0.018

0.646

0.048

0.201

 Cigarette smoking

−0.054

0.163

          

 Hypertension

−0.154

< 0.0001

−0.014

0.707

−0.009

0.814

−0.019

0.630

−0.024

0.527

−0.008

0.822

 Dyslipidemia

−0.244

< 0.0001

−0.047

0.311

−0.082

−0.068

−0.084

0.087

−0.052

0.266

−0.010

0.819

 Diabetes mellitus

−0.150

< 0.0001

0.009

0.856

0.027

0.582

<0.0001

0.994

0.004

0.932

−0.009

0.849

 HbA1c

−0.131

0.0008

0.01

0.836

0.025

0.612

0.025

0.630

0.032

0.522

0.029

0.542

 HDL-C

0.299

< 0.0001

0.155

0.007

0.045

0.295

0.181

< 0.0001

0.236

< 0.0001

0.344

< 0.0001

 Statins use

−0.220

< 0.0001

−0.131

0.003

−0.109

0.010

−0.138

0.003

−0.108

0.014

−0.147

0.0004

 Fibrates use

−0.122

0.002

−0.075

0.037

−0.059

0.088

−0.081

0.029

0.069

0.052

−0.063

0.061

 Glitazone use

−0.035

0.368

          

 TRLs-related markers

  TG*

0.446

0.0001

0.345

0.0001

  VLDL

0.502

0.0001

0.424

0.0001

  RLP-C*

0.304

0.001

0.240

0.0001

  apo C-II

0.353

0.0001

0.323

0.0001

  

  apo C-III

0.401

0.0001

0.045

0.0001

 Inflammatory markers

  WBC count

−0.130

0.0007

−0.036

0.339

−0.031

0.387

−0.053

0.170

−0.065

0.082

−0.035

0.318

  hs-CRP*

−0.110

0.005

0.002

0.956

−0.018

0.636

0.008

0.843

0.014

0.720

0.026

0.472

LDL-C < 100 mg.dL (n = 264)

 Age

−0.095

0.124

          

 Gender

0.183

0.003

−0.049

0.358

−0.052

0.318

−0.058

0.290

−0.040

0.437

−0.007

0.878

 BMI

−0.259

< 0.0001

−0.065

0.258

−0.076

0.174

−0.074

0.210

−0.044

0.426

−0.019

0.723

 Scigarette smoking

−0.045

0.477

          

 Hypertension

−0.207

0.0008

−0.033

0.562

−0.042

0.448

−0.035

0.555

−0.024

0.656

−0.025

0.625

 Dyslipidemia

−0.351

< 0.0001

−0.151

0.042

−0.189

0.009

−0.187

0.017

−0.162

0.023

−0.098

0.149

 Diabetes mellitus

−0.138

0.025

0.056

0.433

0.068

0.331

0.056

0.445

0.023

0.733

−0.006

0.926

 HbA1c

−0.154

0.013

−0.025

0.732

−0.037

0.598

−0.017

0.820

0.014

0.839

−0.001

0.987

 HDL-C

0.301

< 0.0001

0.055

0.347

−0.002

0.969

0.131

0.026

0.213

0.0001

0.313

< 0.0001

 Statins use

−0.193

0.002

0.005

0.937

−0.002

0.970

−0.038

0.583

0.007

0.917

−0.049

0.416

 Fibrates use

−0.269

< 0.0001

−0.167

0.002

−0.147

0.005

−0.196

0.0003

−0.156

0.002

−0.109

0.025

 Glitazone use

0.024

0.702

          

 TRLs-related markers

  TG*

0.601

0.0001

0.436

0.0001

  VLDL

0.606

0.0001

0.464

0.0001

  RLP-C*

0.502

0.0001

0.349

0.0001

  apo C-II

0.577

0.0001

0.453

0.0001

  apo C-III

0.591

0.0001

0.544

0.0001

 Inflammatory markers

  WBC count

−0.182

0.003

−0.078

0.144

−0.079

0.134

−0.106

0.056

−0.097

0.058

−0.075

0.123

  hs-CRP*

−0.083

0.184

          

Lipid-modifying treatment (n = 335)

 Age

−0.138

0.012

−0.176

0.001

−0.170

0.001

−0.186

0.001

−0.222

< 0.0001

−0.231

< 0.0001

 Gender

−0.201

0.0002

−0.176

0.002

−0.143

0.008

−0.162

0.006

−0.166

0.003

−0.131

0.014

 BMI

0.004

0.939

          

 Scigarette smoking

−0.036

0.510

          

 Hypertension

−0.144

0.009

−0.075

0.155

−0.077

0.129

−0.077

0.164

−0.075

0.161

−0.054

0.281

 Dyslipidemia

−0.120

0.029

−0.033

0.534

−0.042

0.406

−0.039

0.480

−0.028

0.604

−0.029

0.563

 Diabetes mellitus

−0.094

0.089

          

 HbA1c

−0.116

0.039

−0.065

0.218

−0.056

0.268

−0.056

0.309

−0.033

0.540

−0.044

0.381

 HDL-C

0.220

< 0.0001

0.027

0.635

−0.043

0.449

0.092

0.113

0.123

0.027

0.203

0.0002

 Statins use

0.019

0.731

          

 Fibrates use

−0.132

0.016

−0.088

0.945

−0.072

0.153

−0.108

0.051

−0.092

0.083

−0.066

0.187

 Glitazone use

0.014

0.800

          

 TRLs-related markers

  TG*

0.368

0.0001

0.299

0.0001

  VLDL

0.468

0.0001

0.424

0.0001

  RLP-C*

0.208

0.0002

0.133

0.019

  apo C-II

0.253

0.0001

0.249

0.0001

  apo C-III

0.384

0.0001

0.416

0.0001

 Inflammatory markers

  WBC count

−0.114

0.037

−0.038

0.495

−0.040

0.441

−0.075

0.192

−0.060

0.278

−0.006

0.916

  hs-CRP*

−0.060

0.276

          

No Lipid-modifying treatment (n = 349)

 Age

−0.105

0.051

          

 Gender

−0.203

0.0002

−0.073

0.163

−0.063

0.218

−0.072

0.178

−0.036

0.282

−0.008

0.867

 BMI

−0.213

< 0.0001

0.041

0.462

0.008

0.879

0.027

0.637

0.036

0.508

0.074

0.158

 Scigarette smoking

−0.087

0.119

          

 Hypertension

−0.084

0.121

          

 Dyslipidemia

−0.153

0.005

0.002

0.965

−0.039

0.475

−0.009

0.88

0.020

0.725

0.070

0.190

 Diabetes mellitus

−0.116

0.032

−0.03

0.575

0.006

0.916

−0.047

0.405

−0.040

0.451

−0.005

0.267

 HbA1c

−0.078

0.153

          

 HDL−C

0.354

< 0.0001

0.187

0.002

0.112

0.067

0.259

< 0.0001

0.349

< 0.0001

0.480

< 0.0001

 Glitazone use

−0.046

0.392

          

 TRLs-related markers

  TG*

0.490

0.0001

0.420

0.0001

  VLDL

0.518

0.0001

0.446

0.0001

  RLP-C*

0.408

0.0001

0.355

0.0001

  apo C-II

0.403

0.0001

0.417

0.0001

  apo C-III

0.410

0.0001

0.528

0.0001

 Inflammatory markers

  WBC count

−0.140

0.010

−0.012

0.822

0.002

0.968

−0.018

0.736

−0.037

0.471

−0.030

0.528

  hs-CRP*

−0.160

0.003

−0.035

0.511

0.006

0.916

−0.047

0.405

−0.037

0.471

−0.018

0.714

BMI body mass index, eGFR estimated glomelular flow rate; CKD chronic kidney disease, CAD coronary artery disease, AP angina pectoris, OMI old myocardial infarction, Hb hemoglobin, ACE angiotensin-converting enzyme, ARB angiotensin receptor blocker, TC total cholesterol, LDL low-density lipoprotein, HDL high-density lipoprotein, TG triglyceride, VLDL very LDL, RLP remnant-like particle, apo apolipoprotein, MDA malondealdehyde-modified, WBC white blood count, hs-CRP high-sensitivity C-reactive protein, r correlation coefficient, β standard partial regression coefficient, * log-transformed value was used; gender (0: female, 1: male); cigarette smoking (0: no, 1: yes); hypertension (0: no. 1: yes); diabetes mellitus (0: no, 1: yes); statins use (0: no. 1: yes); fibrates use (0: no. 1: yes); glitazones use (0: no. 1: yes)

Table 5

Correlations between the LDL-C/apo B ratio and TRLs-related markers among the 4 Groups

TRLs-related markers

CAD (+) DM (+) n = 60

CAD (+) DM (−) n = 90

CAD (−) DM (+) n = 118

CAD (−) DM (−) n = 416

r

p value

r

p value

r

p value

r

p value

TG

−0.351

0.007

−0.275

0.009

−0.62

< 0.0001

−0.49

< 0.0001

VLDL

−0.332

0.01

−0.314

0.003

−0.585

< 0.0001

−0.512

< 0.0001

RLP-C

−0.287

0.026

−0.175

0.107

−0.508

< 0.0001

−0.364

< 0.0001

apo C-II

−0.283

0.029

−0.281

0.008

−0.354

0.0001

−0.366

< 0.0001

apo C-III

−0.318

0.013

−0.356

0.001

−0.496

< 0.0001

−0.395

< 0.0001

TC total cholesterol, LDL low-density lipoprotein, HDL high-density lipoprotein, TG triglyceride, VLDL very LDL, RLP remnant-like particle, apo apolipoprotein, MDA malondealdehyde-modified, WBC white blood count, hs-CRP high-sensitivity C-reactive protein, r correlation coefficient

Multi-logistic regression analysis to identify the variables that were independently correlated with changes of the LDL-C/apoB ratio

In this cross-sectional study, we confirmed that increased levels of TRL-related markers were associated with a decrease of the LDL-C/apoB ratio. Therefore, we investigated, using the longitudinal method, the relationship between the absolute changes (∆) in the serum TG levels and the ∆ LDL-C/apoB ratio, in order to examine the causal relationship. During a follow up period of at least 6 months, multivariable logistic regression analysis conducted in the 445 patients who were followed up for at least 6 months after adjustments for age, gender and risk factors for CAD revealed that higher ∆ serum TG was an independent predictor of a decreased LDL-C/apoB ratio. Next, similar analyses were performed in patients with serum LDL-C levels of < 100 mg/dL, and patients taking/not taking lipid-modifying treatments. Statistical analyses revealed similar findings (Table 6). Similarly, all the multi-logistic regression analyses showed that higher ∆ values of other TRL-related markers were independent determinants of a decreased ∆ LDL-C/apoB ratio (data not shown).
Table 6

Multi-logistic regression analysis to identify the variables that were independently correlated with changes of the LDL-C/apoB ratio

Variables

95% CI

OR

Upper

Lower

p value

All cases, n = 445

 TG

1.006

1.003

1.009

< 0.0001

 FBG

0.999

0.993

1.005

0.749

 HbA1c

2.112

0.843

5.259

0.108

 Age

0.988

0.971

1.006

0.186

 Gender

0.836

0.547

1.277

0.407

 BMI

0.982

0.929

1.037

0.503

 Cigarette smoking

0.968

0.535

1.751

0.914

 Hypertension

1.67

1.008

2.766

0.047

 Lipid-modufying treatment

0.972

0.651

1.451

0.889

LDL-C < 100 mg/dL, n = 188

 TG

1.007

1.002

1.011

0.004

 FBG

1.003

0.993

1.013

0.533

  HbA1c

0.932

0.276

3.144

0.91

 Age

0.991

0.962

1.021

0.563

 Gender

0.963

0.469

1.978

0.918

 BMI

0.877

0.897

1.066

0.604

 Cigarette smoking

1.446

0.569

3.671

0.438

 Hypertension

1.654

0.7

3.907

0.251

 Lipid-modufying treatment

1.335

0.67

2.659

0.412

Lipid-modifying treatment, n = 270

 TG

1.005

1.002

1.009

0.003

 FBG

0.998

0.991

1.005

0.56

 HbA1c

3.06

0.988

9.483

0.053

 Age

0.979

0.954

1.006

0.121

 Gender

0.825

0.479

1.423

0.489

 BMI

0.979

0.911

1.052

0.564

 Cigarette smoking

0.735

0.334

1.618

0.444

 Hypertension

1.45

0.751

2.799

0.269

No lipid-modifying treatment, n = 175

 TG

1.008

1.003

1.013

0.003

 FBG

1.002

0.991

1.013

0.73

 HbA1c

0.933

0.177

4.924

0.934

 Age

0.998

0.975

1.022

0.876

 Gender

0.817

0.403

1.022

0.876

 BMI

0.989

0.903

1.082

0.805

 Cigarette smoking

1.444

0.571

3.654

0.438

 Hypertension

2.351

1.033

5.343

0.042

BMI body mass index, eGFR estimated glomelular flow rate; CKD chronic kidney disease, CAD coronary artery disease, AP angina pectoris, OMI old myocardial infarction, Hb hemoglobin, ACE angiotensin-converting enzyme, ARB angiotensin receptor blocker, TC total cholesterol, LDL low-density lipoprotein, HDL high-density lipoprotein, TG triglyceride, VLDL very LDL, RLP remnant-like particle, apo apolipoprotein, MDA malondealdehyde-modified, WBC white blood count, hs-CRP high-sensitivity C-reactive protein, OR odds ratio, CI confidence interval, ∆ absolute change from baseline, gender (0: female, 1: male); cigarette smoking (0: no, 1: yes); hypertension (0: no. 1: yes); lipid-modifying treatment (0: no. 1: yes)

Discussion

In this study we showed that the LDL metabolism abnormality in CAD patients with DM is a pathological condition that strongly induces a decrease in LDL-particle size. A similar phenomenon occurs even in patients whose serum LDL-C levels are well controlled, and impaired TG metabolism plays a large role. Although this study evaluated the risk of CAD in DM by means of a cross-sectional and longitudinal design that focused on LDL-particle size and TG metabolism, the results may indicate the necessity of monitoring the qualitative changes in LDL-C, in addition to the quantitative changes, especially in CAD patients with DM.

Triglyceride is known as the most powerful determinant of the LDL-particle size [6]. LDL-particle size shows a significantly negative correlation with the fasting and postprandial serum TG levels, and is associated with postprandial hyperlipidemia often seen in patients with CAD and/or DM [14, 15]. Metabolism of TG-rich large VLDL is slower than that of ordinary VLDL. In cases where smaller LDL-particles are predominant, the formation of large VLDL increases, and accumulation of TRLs occurs under the influence of increased large VLDL formation and delayed catabolism of the large VLDL. Transfer of lipids takes place between the TRLs increased thus and HDL, leading to an increase of TG-rich LDL and formation of smaller LDL through degradation of TG via hepatic lipase activity [16]. As illustrated above, investigations have been reported concerning the association of increase in TRLs (as a result of abnormal TG metabolism) with reduction of the LDL-particle size. The results of the present study may be interpreted as indicating that promotion of LDL-particle size reduction by the above-mentioned abnormal TG metabolism is more marked in CAD patients with underlying DM.

In the multi-logistic regression analysis shown in Fig. 2, correction was made for an independent variable, i.e., the presence/absence of medication affecting the LDL-particle size. However, it is difficult to completely eliminate the influence of medication use on the LDL-particle size. Paradoxically, a tendency towards a lower LDL-particle size may not be avoidable in diabetic patients with CAD if the TG metabolism remains abnormal despite favorable blood glucose control (even in cases where favorable blood glucose control is accompanied by satisfactory serum LDL-C control with lipid metabolism-improving agents such as statins).

The Pioglitazone Effect on Regression of Intravascular Sonographic Coronary Obstruction Prospective Evaluation (PERISCOPE trial) [17], a randomized trial comparing glimepiride and pioglitazone that investigated the prevention of coronary plaque progression, reported not finding a significant difference in glycemic control between the two groups, but that the TG/HDL-C ratio, the ratio of a high TG level to a low HDL-C level that is a typical characteristic of lipid metabolism abnormality in DM [6], was significantly lower in the pioglitazone group, and that it contributed to preventing coronary plaque progression. Interestingly, it has also been reported that the TG/HDL-C ratio is a marker of abnormal TG metabolism and that the ratio is inversely correlated with LDL-particle size [18, 19]. This evidence appears to support our results. Thus, it is clear that glycemic and LDL-C control are important in preventing CV events in diabetic patients with CAD, and that improving abnormal TG metabolism may also be an important prevention strategy. It is necessary to regulate dysllipidemia in patients with DM. This can be done with lipid-lowering agents (e.g. statins, possibly in combination with a fibrate, niacin, omega-3 fatty acids, or ezetimibe) have proved effective in reducing atherogenic cholesterol particles including TRLs, inhibiting the progress of atherosclerosis [20].

In the present study, statistically significantly negative correlations were observed between the LDL-C/apoB ratio and most TRL-related markers in all the four groups. When this observation is considered with the results of multi-logistic regression analysis, we may say that the present study supported validity of our hypothesis that reduction of the LDL-particle size, which can be induced by abnormal TG metabolism, is more marked in CAD patients with underlying DM. If the above-mentioned results are considered with the finding of a higher TG/HDL-C ratio in the CAD patients with underlying DM than in the CAD patients without DM, we may say that the more advanced coronary atherosclerosis in CAD patients with underlying DM is the reason for the higher prevalence of more advanced cases or cases with complex lesions seen in this patient group.

As shown in Table 3, in the present study, we compared the estimated LDL-particle size (based on the TG/HDL-C ratio) in patients with/without CAD and DM. The results suggest that the TG/HDL-C ratio may also serve as a useful marker of the LDL-particle size. Thus, it seems necessary, in the future, to discuss which of LDL-C/apoB ratio and TG/HDL-C ratio should be selected as a marker of the LDL-particle size depending on the features of the study population or study design.

Interestingly, some investigations [21, 22] have reported that the LDL-C/apo B ratio is independently associated with the future development of cardiometabolic syndrome which involves characteristic lipid abnormalities such as hypertriglycemia and smaller LDL-particle size. Thus, the LDL-C/apo B ratio and TRLs may provide useful information when assessing atherosclerotic cardiovascular risks.

Furthermore, an additional study by a longitudinal method revealed that elevated levels of TRL-related markers were independently predictive of a decreased LDL-particle size. Due to its observational design, we were unable to establish a causal relationship in this study, but the results of the 2 studies with different (cross-sectional and longitudinal) designs taken together strongly suggest an association between increased levels of TRL-related markers and decrease of the LDL-particle size in patients with disordered TG metabolism; thus, the LDL-C/apoB ratio may serve as a useful predictor of the future development of CAD.

In the present study, we indirectly analyzed the association of the LDL-C/apoB ratio with the severity of coronary atherosclerosis in CAD patients with underlying DM. However, it is important to bear in mind that the progression of coronary atherosclerosis is powerfully stimulated by interactions among diabetes-associated factors (insulin resistance, abnormal glucose tolerance, etc.) and other factors such as abnormal lipid metabolism [5].

Study limitations and clinical implications

First, the relationships bewteen the LDL-C/apoB ratio and TRL-related markers were analyzed by dividing the patients according to the history (positive/negative) of intake of lipid-modifying drug treatment and good serum LDL-C control, because lipid modifying drugs have an effect of improving the LDL and TG metabolism. The possibility of the effects of lipid modifying drugs influencing the results of the present study cannot be excluded. It had also been reported that the influence on the LDL-particle size varies among the different types of statins [23]. Furthermore, the duration of treatment involving such drugs could not be ascertained in the present study. Second, in theory the LDL-C/apoB ratio is a marker of a patient’s mean LDL-particle diameter, but it does not indicate the exact LDL-particle diameter, which is measured using density gradient ultracentrifugation and nuclear magnetic resonance spectroscopy. Moreover, the significance of calculating the absolute LDL-C/apoB ratio cut-off value for CAD risk has not been determined. Third, no patients who were taking dipeptidyl peptidase (DPP)-4 inhibitors or sodium-glucose transporter (SGLT) 2 inhibitors were included among the subjects of this study. DPP-4 inhibitors and SGLT2 inhibitors have triglyceride lowing actions, and it would be very interesting to evaluate these actions comparatively [24, 25]. Fourth, because determination of the presence of CAD in this study population relied on the findings of coronary angiography, the existence of subjects in the study population of undetected cases of asymptomatic CAD which can be diagnosed primarily by an exercise stress test or non-invasive tests such as coronary artery computed tomography cannot be ruled out. Diabetic patients often have asymptomatic myocardial ischemia, and a particularly high prevalence of asymptomatic myocardial ischemia has been reported in diabetic patients with CAD and abnormal TG metabolism [26]. Finally, in the future, an interventional study to investigate the causal relationship is needed.

Conclusions

To further reduce the coronary risk in CAD patients with underlying DM, it may be of particular importance to pay attention not only to the quantitative changes of the serum LDL-C, but also to disorders of TG metabolism associated with LDL heterogeneity. Combined evaluation of TRL-related markers and the LDL-C/apoB ratio may be useful for assessing the risk status of CAD patients with underlying DM. Further studies are needed to investigate clinical outcomes of these patients.

Abbreviations

ANOVA: 

analysis of variance

apo: 

apolipoprotein

CAD: 

coronary artery disease

CV: 

cardiovascular

DM: 

diabetes mellitus

DPP: 

dipeptidyl peptidase

eGFR: 

estimated glomerular filtration rate

Hb: 

hemoglobin

HDL: 

high-density lipoprotein

hs-CRP: 

high-sensitivity C-reactive protein

LDL-C: 

low-density lipoprotein cholesterol

MDA: 

malondealdehyde-modified

MDRD: 

Modification of Diet in Renal Disease

PERISCOPE: 

Pioglitazone Effect on Regression of Intravascular Sonographic Coronary Obstruction Prospective Evaluation

RLP: 

remnant-like particle

SD: 

standard deviation

Sd: 

small-dense

SGLT: 

sodium-glucose transporter

TC: 

total cholesterol

TG: 

triglyceride

TRL: 

TG-rich lipoprotein

VLDL: 

very-low density lipoprotein

Declarations

Authors’ contributions

ST has designed this study in whole and drafted this manuscript. TY, WA, RM and KK have contributed to collect data. ST has contributed to statistical analyses in this study. AH have contributed to provide advice on interpretation of the results. ST revised this manuscript critically for important intellectual content and approved finally the manuscript submitted. All authors read and approved the final manuscript.

Acknowledgements

The authors would like to thank International Medical Information Center (http://www.imic.or.jp/services/translation.html) for the English language review. The authors would also like to thank Mr. Gary Cooper for his help in editing the English manuscript.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Consent for publication

If the manuscript is accepted, we approve it for publication in Cardiovascular Diabetology.

Ethical approval and consent to participate

This study was approved by the Institutional Ethics Committees of Nihon University Hospital. All participants were consentient to participate the study and signed the informed consent.

Funding

Not applicable.

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Authors’ Affiliations

(1)
Department of Health Planning Center, Nihon University Hospital
(2)
Department of Cardiology, Nihon University Hospital
(3)
Division of Cardiology, Department of Medicine, Nihon University School of Medicine

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