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In the United States, the proportion ofelderly people increased by 22% in2040, arteriosclerosis became a hugeeconomic burden for the health. (1)

In Hue, Huynh Van Minh's at Hue Central Hospital,LEAD accounted for 79% of general vasculardiseases..(3)

In Vietnam, according to VietNam nationalheart institude, the percentage of LEAD in2003 was 1.7% to 2007 was 3.4%.(2)

(1),(3) Huỳnh Văn Minh, Nguyễn Anh Vũ (2014), "Bệnh viêm tắc động mạch chi dưới", Giáo trình sau đại học Tim mạch học. NXB Đại học Huế, tr.381-390.(2) Đinh Thị Thu Hương (2011), "Khuyến cáo 2010 của Hội Tim mạch học Quốc gia Việt Nam về chẩn đoán và điều trị bệnh động mạch chi dưới",Tạp chí Tim mạch học Việt Nam. 58, tr. 74-85.

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LEAD is often caused by arteriosclerosis, the risk factorsof LEAD are such as: elderly people , smoking, diabetes,hypertension, dyslipidemia, increased homocysteine,increased CRP,

The vascular age has been much researched for initialevaluation of the risk of arteriosclerosis. Vascular age isassociated with cardiovascular risk factors such ashypertension, diabetes, coronary artery disease ...

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“Study the associated among vascular age, ankle–brachial index, brachial-ankle

pulse wave velocity and lower extremity angiography in the patient with lower

extremity arterial disease” with object:

Study the vascular age, ankle–brachial index, brachial-

ankle pulse wave velocity and result of lower extremity

angiography.

The correlation and the association of vascular age, ankle–

brachial index, brachial-ankle pulse wave velocity with

traditional rick factors and with result of lower extremity

angiography.

Object 1

Object 2

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Selection criteria

- Patients with clinical symptoms and ABI ≤0,9 agree to participate in the study.

Exclusion criteria :

- Patients don’t agree to participate in the study.

- Patients have severe heart failure, CKD, malignant disease, blood disease.

- Patients have anemia, hyperthyroidism, COPD, pregnant.

- Patients have acute or chronic diseases that affect test results bloods lipid,

blood pressure prognosis of death.

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Study design : Cross sectional study

Study location: Department of Cardiology and Department of Injury – Chest, Hospital Hue University of Medicine and Pharmacy.

Statistical analysis: SPSS 20.0

Duration: from January 2018 to February 2019

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Study means:

Digital Subtraction Angiography Ankle Brachial Index and Pulse Wave Velocity

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Forty five patients hospitalized at Hospital Hue University ofMedicine and Pharmacy.

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Age groups n %

<60 age 4 8,9

60-79 age 18 40,0

≥ 80 age 23 51,1

Total 45 100,0

ҧ𝑥 ± 𝑆𝐷 77,89 ± 10,93

Table 3.1. Distribution by age groups

Rate of patients over 60 years: 91,1%

Nguyễn Thị Ngân (2017): 68,54±11,71

Ngô Đắc Hồng Ân (2017): 69±13

Lê Hoàng Bảo (2014): 70,7±12,3

Criqui (2012): 38-59 5,6%

60-69 15,9%

70-82 33,8%

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Sex n %

Male 24 53,3

Female 21 46,7

Total 45 100

Table 3.2. Distribution by gender

Chart 3.1. Distribution of male and female by age

groups

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5

10

15

20

25

30

Nhỏ hơn 60 60-80 Lớn hơn 80

8.9

22.2 22.2

0

17.8

28.9

Nam

Nữ

Rate M:F = 1,14:1

K. Kroger (2010): male (62,1%)

E. Selvin (2004): male (68,7%)

Ng. L. Rân (2017): male (61,4%)

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Chart 3.2. Distribution of risk factors

0 10 20 30 40 50 60 70

Tăng huyết áp

Rối loạn lipid

Hút thuốc lá

Tăng đường huyết

Thừa cân béo phì

Lối sống tĩnh tại, ít vận động

68.9

11.1

51.1

33.3

8.9

44.4

Phạm T Ngọc Liên (2017)

78,6% rối loạn lipid

71,4% hypertension

38,6% smoking

Nguyễn T Ngân (2017)

67,4% hypertension

Nguyễn L Rân (2016)

70,2% smoking

K. Kroger (2010)

84,2% hypertension

45,0% smoking

47,3% diabetes12

Risk factors Male (%) Female (%) p

Hypertension 54,8 45,2 p>0,05

Lipid disorders 40,0 60,0 p>0,05

Smoking 95,7 4,3 p<0,05

Diabetes 40,0 60,0 p>0,05

Overweight,

obesity33,3 66,7 p<0,05

Static lifestyle,

sedentary55,0 45,0 p>0,05

Table 3.3. Risk factors by gender

Phạm T Ngọc Liên (2017)

Smoking

Male 95,7%

Female 3,7%

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Chart 3.3. Distribution by clinical symptoms

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10

20

30

40

50

60

70

80

90

Rối loạn cảm giác chi dưới

Dáu hiệu đau đi lặc cách hồi

Mỏi chi Thay đổi màu sắc da

Loét

84.488.9

71.1

57.848.9

Nguyễn Lê Rân (2016)

49,1% claudication walking

89,5% sensory disorders

64,9% skin color changes

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Chart 3.4. Classification of Leriche Fontaine

I, 6.70IIa, 13.30

IIb, 8.90

III, 13.30

IV, 57.80

Nguyễn Lê Rân (2016)

31,6% stage II

57,9% stage III, IV

Nguyễn Thị Ngân (2017)

34,5% stage IV

Criqui (1996)

49% ABI<0,6

The rate of patients with late

stage disease is quite high.

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Waist Male (n=24) Female (n=21) p

Mean 84,38 ± 12,75 79,76 ± 12,58

p > 0,05Min 63 63

Max 105 108

Obesity: n/rate (%) 10 (22,2%) 8 (17,8%)

Total 18 (40,0%)

Waist mean: 82,22 ± 5,85cm , VBmin=63cm, VBmax=108cm

Table 3.4. Waist mean and rate obesity

Mingli He (2012) 85,70±9,70 cm

Nguyễn Thị Ngân (2017) 84,24±5,85 cm, difference between gender (p<0,05)

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GenderBMI group (kg/m2)

TotalGầy Bình thường Thừa cân Béo phì

Male 8 (17,8%) 12 (26,7%) 2 (4,4%) 2 (4,4%) 24

Female 10 (22,2%) 6 (13,3%) 3 (6,7%) 2 (4,4%) 21

Total 18 (40,0%) 18 (40,0%) 5 (11,1%) 4 (8,9%) n=45

p >0,05

BMI mean = 20,02±3,01 kg/m2

BMImin= 15,31 kg/m2 BMImax= 27,06 kg/m2

Table 3.5. Distribution by BMI

Mingli He (2012) BMI 25,6±3,6

Nguyễn Thị Ngân (2017) BMI 21,4±3,13, (p>0,05)

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73.3

20

6.7

< 5,2

5,2 – 6,2

≥ 6,2

42.2

48.9

8.9

< 1,0

1,0 – 1,6

˃1,6

40

24.4

20

8.96.7

< 2,6

2,6 – 3,4

3,4 – 4,2

4,2 – 5

≥ 5

64.417.8

17.8

< 1,7

1,7 – 2,3

≥ 5,7

Chart 3.5. Distribution by Cholesterol total Chart 3.6. Distribution by HDL-c

Chart 3.7. Distribution by LDL-c Chart 3.8. Distribution by Triglycerid18

Male Female Total p

Age 75,29 ± 12,17 80,86 ± 8,66 77,89 ± 10,93 p>0,05

Age vascular 79,21 ± 5,43 79,19 ± 4,76 79,20 ± 5,07 p>0,05

Table 3.6. Age vascular and Ageby gender

Phạm Thị Ngọc Liên Phan Thị Bích Phương

Age 64,36 ± 5,59 69,81 ± 11,01 62,08 ± 10,38

Age vascular 74,80 ± 9,14 72,15 ± 10,44 73,01 ± 8,59

Tuổi mạch cao hơn tuổi thực

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Location Right Left Total

baPWV (cm/s)2051,20 ± 845,08 2079,07 ± 752,13

2269,20 ± 853,27p < 0,05

Table 3.7. Means of baPWV

baPWV baPWV right baPWV left maxbaPWV

baPWV right - r=0,633; p<0,01 r=0,896; p<0,01

baPWV left r=0,633; p<0,01 - r=0,821; p<0,01

maxbaPWV r=0,896; p<0,01 r=0,821; p<0,01 -

Table 3.8. Correlate between baPWV right, left và maxbaPWV

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Gender Male Female

baPWV mean (cm/s) 2436,38 ± 732,48 2078,14 ± 955,44

p p > 0,05

Table 3.9. Means of baPWV by gender

Pulse Wave Velocity male higher than female

Chang Sheng Sheng (2014)

baPWV male 17,5 ± 3,8 m/s; female 18,1 ± 4,2 m/s

Phạm Thị Ngọc Liên (2017)

baPWV male 1900,93 ± 505,42 cm/s; female 2001,69 ±509,49 cm/s

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right Left mean

ABI mean0,72 ± 0,21 0,75±0,20

0,66±0,16p<0,05

Table 3.10. Means of index ABI

Index ABI ABI right ABI left minABI

ABI right - r=0,447; p>0,01 r=0,822; p<0,01

ABI left r=0,447; p>0,01 - r=0,726; p<0,01

minABI r=0,822; p<0,01 r=0,726; p<0,01 -

Table 3.11. Correlate between ABI left, right và min ABI

K. Kroger ABI means 0,72 ± 0,25

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ABI <0,4 0,4-0,69 0,70-0,90 0,91-1,3 Total

ABI right 3 (6,7%) 20 (44,4%) 12 (26,7%) 10 (22,2%) 45

ABI left 1 (2,2%) 15 (33,3%) 22 (48,9%) 7 (15,6%) 45

Table 3.12. Rate of classification of lower limb artery disease by ABI

ABI right (<0,9): 77,8%

ABI left(<0,9): 84,4%

Nguyễn Thị Ngân (2017) ABI<0,9: 26,3%

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AngiographyNarrow ≤50% Narrow >50% Complete block Total

n % n % n %

Common iliac atery 75 83,33 13 14,44 2 2,23 90

External iliac atery 76 84,44 11 12,22 3 3,34 90

Internal iliac atery 68 75,56 10 11,11 12 13,33 90

Common femoral

atery81 90,00 6 6,67 3 3,33 90

Shallow feoral atery 42 46,67 23 25,56 25 27,77 90

Deep femoral atery 84 93,33 4 4,44 2 2,23 90

Popliteal atery 75 84,27 7 7,87 7 7,86 89

Anterior tibial 23 25,84 11 12,36 55 61,80 89

Posterior tibial 19 21,35 14 15,73 56 62,92 89

Fibular 39 43,82 24 26,97 26 29,21 89

Table 3.13. Injury of lower limb arteries

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Rick fator Age vascular p

HypertesionYes 79,10±5,33

p>0,05No 79,43±4,64

Lipid disordersYes 77,60±7,60

p>0,05No 79,40±4,77

SmokingYes 79,87±4,46

p>0,05No 78,50±5,66

DiabetesYes 81,00±0,00

p<0,05No 78,30±6,04

Overweight, obesityYes 81,00±0,00

p>0,05No 79,02±5,28

Static lifestyle, sedentaryYes 79,50±4,66

p>0,05No 78,96±5,46

Table 3.14. The relation between artery age and traditional risk factors

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Rick factor minABI p

HypertesionYes 0,66±0,16

p>0,05No 0,63±0,16

Lipid disordersYes 0,76±0,08

p<0,05No 0,64±0,17

SmokingYes 0,66±0,17

p>0,05No 0,65±0,15

DiabetesYes 0,67±0,14

p>0,05No 0,65±0,17

Overweight, obesityYes 0,69±0,10

p>0,05No 0,65±0,17

Static lifestyle, sedentaryYes 0,61±0,17

p>0,05No 0,69±0,15

Table 3.15. The relation between minABI and traditional risk factors

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Rick factor baPWV p

HypertesionYes 2306,68±911,33

p>0,05No 2186,21±732,71

Lipid disordersYes 2470,60±444,06

p>0,05No 2244,03±891,81

SmokingYes 2451,17±753,23

p>0,05No 2078,95±925,69

DiabetesYes 2492,40±1035,09

p>0,05No 2157,60±740,79

Overweight, obesityYes 2219,50±59,56

p<0,05No 2274,05±894,61

Static lifestyle, sedentaryYes 2179,15±558,14

p<0,05No 2341,24±1037,30

Table 3.16. The relation between baWPV and traditional risk factors

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Risk factors Leriche - Fontain minABI maxbaPWV

Systolic blood pressurer = 0,292

p > 0,05

r =-0,346

p <0,05

r = 0,288

p > 0,05

Diastolic blood pressurer = 0,151

p >0,05

r = 0,101

p >0,05

r = 0,514

p <0,05

Glucose bloodr = 0,183

p >0,05

r = 0,100

p >0,05

r = 0,423

p <0,05

Cholesterol totalr = 0,076

p > 0,05

r = 0,047

p > 0,05

r = 0,016

p > 0,05

LDL-Cr = 0,037

p > 0,05

r = 0,069

p > 0,05

r = 0,083

p > 0,05

Triglyceride r = 0,011

p > 0,05

r = 0,093

p > 0,05

r = 0,040

p > 0,05

HDL-Cr = 0,202

p > 0,05

r = 0,028

p > 0,05

r = 0,257

p > 0,05

BMIr = 0,117

p > 0,05

r = 0,281

p > 0,05

r = 0,318

p < 0,05

Table 3.17. The correlation between the risk factors and clinical severity

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y = -0.0033x + 1.1947

R² = 0.1581

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

70 90 110 130 150 170 190

min

AB

I

Systolic blood pressure (mmHg)

Linear regression graph between Systolic blood pressure with minABI

y = 31.597x - 215.33

R² = 0.1689

0

1000

2000

3000

4000

5000

6000

40 50 60 70 80 90 100 110 120

max

baP

WV

(cm

/s)

Diastolic blood pressure (mmHg)

Linear regression graph between Diastolic blood pressure with

maxbaPWV

Chart 3.5: Linear regression graph between

Systolic blood pressure with minABI

Chart 3.6: Linear regression graph between

Diastolic blood pressure with maxbaPWV

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y = 0.0023x + 3.5801

R² = 0.1362

0

5

10

15

20

25

30

0 1000 2000 3000 4000 5000 6000

Glu

cose

blo

od

(m

mo

l/L

)

maxbaPWV (cm/s)

Linear regression graph between glucose blood with maxbaPWV

y = 0,0009x + 18,265

R² = 0,0543

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18

20

22

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0 1000 2000 3000 4000 5000 6000

BM

I (k

g/m

2)

maxbaPWV (cm/s)

Linear regression graph between BMI with maxbaPWV

Chart 3.7: Linear regression graph between

glucose blood with maxbaPWV

Chart 3.8: Linear regression graph between

BMI with maxbaPWV

Relationship and correlation between arterial age, pulse wave

velocity, ABI index with traditional risk factors.

There was the contra variant association between ABI with systolic blood

pressure (r = 0,346; p < 0,05)

There was the association between baPWV with diastolic blood pressure (r =

0,514; p < 0,05), with fasting plama glucose (r = 0,423; p < 0,05), with BMI (r =

0,318; p < 0,05)

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Relationship and correlation between arterial age, pulse wave

velocity, ABI index with traditional risk factors.

- There is a correlation between ABI and systolic blood pressure (r=0,346;

p<0,05).

- There is a fairly close correlation between baPWV and diastolic blood

pressure (r=0,514; p<0,05).

- There is a average correlation between of baPWV and blood glucose

(r=0,423; p<0,05).

- There is a fairly close correlation between the baPWV and the body mass

index (r=0,318; p<0,05).

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1. It is recommended to combine arterial age method with measurement of

vascular velocity and ABI index to increase diagnostic capacity and predict

overall risk of prognostic contribution in patients with lower limb artery

disease.

2. Additional imaging techniques need to be used, in which digital imaging

angiography (DSA) gives high and necessary accuracy in patients with an

intravenous intervention prognosis. The use of ABI, baPWV and DSA

indicators will help increase the diagnostic value in difficult arterial segments

and increase the likelihood of detecting lower limb artery disease.

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