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Research Article | Volume 14 Issue 6 (Nov - Dec, 2024) | Pages 265 - 274
Correlation Of Aortic Propagation Velocity an Echocardiographic Parameter and Severity of Coronary Artery Disease Using Syntax Score.
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1
Professor & Senior Interventional cardiologist, J. N. Medical College, KAHER, Belagavi, Karnataka India
2
Associate Professor and Interventional cardiologist, J. N. Medical College, KAHER, Belagavi, Karnataka India
3
Professor and HOD, J. N. Medical College, KAHER, Belagavi, Karnataka India
4
Professor & Interventional cardiologist, J. N. Medical College, KAHER, Belagavi, Karnataka India
5
Assistant Professor and Interventional cardiologist, Department of Cardiology, J. N. Medical College, KAHER, Belagavi, Karnataka India
6
Doctorate of Medicine (D.M) in Cardiology dept. of cardiology, J.N Medical college Nehru Nagar, BELAGAVI –590010 Karnataka India
Under a Creative Commons license
Open Access
DOI : 10.5083/ejcm
Received
Oct. 5, 2024
Revised
Oct. 23, 2024
Accepted
Nov. 4, 2024
Published
Nov. 22, 2024
Abstract

Background: Endothelial dysfunction marks the initial phase of atherosclerosis, a condition that leads to the thickening and stiffening of arterial walls, particularly in the aorta. This increased arterial wall thickness and stiffness result in higher arterial resistance, subsequently reducing the aortic propagation velocity (APV). This study aims to explore the relationship between APV, a relatively under-researched echocardiographic parameter, and the presence and severity of coronary artery disease (CAD) in patients experiencing acute coronary syndrome (ACS). The study is aimed.  Objective:  To assess the aortic propagation velocity and correlate it with the severity of cad using syntax score in patients presenting with acute coronary syndrome. Methods: A prospective observational study conducted in Department of Cardiology of Jawaharlal Nehru Medical College, KAHER, Belgaum between January 2O23 to December 2O23. Patients with confirmed ACS diagnosis according to fourth universal definition of acute myocardial infraction were eligible to participate in the study.  Result: A total of 292 study participants were included in this study. Among the 292 study participants, 49.7% (n=145) were in the CAD group and 5O.3% (n=147) were in the non-CAD group. The mean age of the study participants was 57.27 ± 13.4O years. Among study participants, 68.97% were male and 31.O3% were female. The mean ejection fraction in CAD and Non-CAD groups were 49 ±9.94 and 58.O6 ±6.86 respectively. The mean SYNTAX scores I of study participants in CAD group was 18.42 ±13.15. The mean SYNTAX score II PCI and SYNTAX score II CABG were 34.78 ±13.75 and 25.7 ±13.O2 respectively.  The mean AVP average in CAD group and non-CAD group were 44.32 ±33.93 and95.8 ±34.15 respectively. The prevalence of diabetes and hypertension among the study participants in CAD group were 6O.69% and 45.52% respectively. Prevalence of substance abuse like smoking, tobacco and alcohol were present in 41.38%, 46.21% and 33.1% respectively. Chest pain, dyspnoea, palpitations, and syncope were present in 89.66%, 49.66%, 1.38% and 1.38% of study participants respectively. Positive correlation of AVP was present in variables like SYNTAX Score I (p<O.O5), SYNTAX Score II CABG (p<O.O5), SYNTAX Score II PCI (p<O.O5), HbA1c (p<O.O5) and age (p<O.O5). The prevalence of single vessel disease (SVD), double vessel disease (DVD) and triple vessel disease (TVD) among the study participants in CAD group were 4O.69%, 2O.69% and 38.62% respectively. The ROC curve shows 84.8% of sensitivity and 1OO% of specificity in predicting CAD by APV value. The area under the curve was O.912 (p<O.O5). Conclusion: The study showed that APV can significantly predict the CAD. This technique offers a practical, non-invasive, and cost-effective echocardiographic approach for detecting or screening coronary artery disease (CAD). It may also prove useful in assessing comorbidities associated with CAD, aiding in risk stratification, and identifying individuals at high risk for CAD. Given its predictive accuracy and potential clinical utility, APV could be integrated into routine cardiovascular assessments, particularly for patients presenting with symptoms like chest pain or those with significant risk factors. However, the study underscores the need for further large-scale, multicenter studies to validate APV’s effectiveness and confirm its applicability as a screening tool for CAD in broader populations. These future studies would help refine APV's role in clinical practice and enhance its value in preventing and managing coronary artery disease.

Keywords
INTRODUCTION

The major burden of cardiovascular disease mortality around the globe is due to atherosclerosis and its complications. It is well recognized that cardio- vascular risk factors lead to histological and functional changes in aorta like increased stiffness.(1,2) Elevated arterial stiffness is associated with cardiovascular risk factors like smoking, obesity, hypertension, glucose tolerance, diabetes, and older age.

Associations between increased arterial stiffness and a number of cardiovascular diseases such as hypertension, atherosclerosis, and coronary heart disease are reported. Aortic stiffness is a good predictor of cardiovascular mortality and morbidity. As the extent and the severity of the atherosclerosis increase, AD and AS decrease. As atherosclerosis progresses, tunica media increases in thickness and tunica media gets stiffer. Therefore, it is very valuable to detect atherosclerotic disease before clinical disease comes out via a non-invasive method.(3,4)

 

Endothelial dysfunction marks the initial phase of atherosclerosis, a condition that leads to the thickening and stiffening of arterial walls, particularly in the aorta. This increased arterial wall thickness and stiffness result in higher arterial resistance, subsequently reducing the aortic propagation velocity (APV). This study aims to explore the relationship between APV, a relatively under-researched echocardiographic parameter, and the presence and severity of coronary artery disease (CAD) in patients experiencing acute coronary syndrome (ACS).

It has been shown in the earlier studies that as the severity of the coronary artery disease increases, the aortic stiffness increases. So, an inverse correlation can be expected between the CAD severity and aortic flow propagation velocity. An APV value of ≤6O.5 cm/s, determined by ROC curve analysis, predicted CAD with 9O.5% sensitivity and 92.2% specificity.(5,6)

MATERIALS AND METHODS

This Prospective Observational Study was conducted in Cardiology Department of Jawaharlal Nehru Medical College, KAHER, Belgaum. The study was conducted during January 2O23 to December 2O23

 

Sample Size:

The calculated sample size was 144.

( n = 2 S2 (Z1-α  + Z1-β ) 2  /  δ2  )

 

Sampling technique:

Random sampling method

 

Inclusion Criteria:

  • Patients admitted to cardiology department of Jawaharlal Nehru Medical College, KAHER with ACS.
  • ACS was diagnosed according to the fourth universal definition of acute myocardial infarction.

 

Exclusion Criteria: 

  • STEMI
  • Severe Valvular heart disease
  • Symptomatic heart failure
  • Aortic Aneurysm (>44mm)
  • Auto-immune disorders (marfans and ehler danlos syndrome)
  • Renal dysfunction serum (eGFR<3Oml/min)
  • Atrial fibrillation, flutter, tachy-brady arrhythmias.
  • Frequent premature beats.
  • Left bundle branch block
  • Cardiomyopathy
  • Poor echo image quality
  • Patient refused consent to be part of study
  •  

Study protocol:

  1. All the patients fulfilling the inclusion criteria and willing to participate, were included in the study.  
  2. Informed consent will be obtained.                           
  3. Further they were subjected to a detailed history and predesigned proforma.

 

Statistical Analysis:

The data were collected using predesigned pre validated standard research tool. The cleaned data was stored in MS Excel for basic analysis, including descriptive statistics such as mean, mode, median, frequency, and percentage. Graphical representations like bar diagrams, histograms, and pie charts were also prepared using MS Excel.

 

Data processing and analysis/statistical analysis:

All patients fulfilling the inclusion criteria were included in the study. Statistical analysis was be done using IBM SPSS Version 26.

 

Statistical Analysis Plan (SAP):

Statistical analysis was done using IBM SPSS 26. The continuous variables were represented in mean (or median) and standard deviation. The categorical variables were represented as number and percentages. Continuous variables were analysed using student t test and categorical variables were analysed using chi-square test. P value is considered as statistically significant when it is less than O.O5.

RESULTS

A total of 292 study participants were included in this study. Among the 292 study participants, 49.7% (n=145) were in the CAD group and 5O.3% (n=147) were in the non-CAD group. The mean age of the study participants was 57.27 ± 13.4O years.

The mean age of study participants in CAD and Non-CAD groups were 59.88 ± 11.86 and 54.71 ± 14.34 years respectively.

Among study participants, 68.97% were male and 31.O3% were female.

The mean body mass index (BMI) of study participants in CAD group was 24.41 ± 3.91.

The mean haemoglobin value in CAD group was 7.13 ± 1.98. The mean creatinine and creatinine clearance values in CAD group were O.96 ± O.27 and 76.11 ± 29.25 respectively. The mean HbA1c in CAD and Non-CAD group were 6.69 ± 2.58 and 5.74 ± 1.62 respectively.

 

Table 1: Biochemical parameters in CAD and Non-CAD groups

BIOCHEMICAL PARAMETERS

CAD (n=145)

Non-CAD (n=147)

Haemoglobin

7.13 ± 1.98

NA

Creatinine

O.96 ± O.27

NA

Creatinine clearance

76.11 ± 29.25

NA

HbA1c

6.69 ± 2.58

5.74 ± 1.62

Hs-CRP

32.7O ±51.48

NA

 

The mean total cholesterol in CAD and Non-CAD group were 163.85 ± 41.61 and 158.59 ± 49.68 respectively. The mean triglyceride value of CAD and Non-CAD groups were 16O.46 ±91.81 and 22.16 ±78.79 respectively. The mean HDL among CAD and Non-CAD study participants were 45.49 ± 22.82 and 69.92 ± 55.35 respectively. The mean LDL among CAD and Non-CAD study participants were 1O3.46 ± 38.O9 and 64.16 ± 28.82 respectively.

 

The mean value of Lpa among CAD and Non-CAD study participants were 19.89 ± 48.46 and O.46 ±2.24 respectively.

 

Table 2: Lipid profile in CAD and Non-CAD groups

LIPID PROFILE

CAD (n=145)

Non-CAD (n=147)

Total Cholesterol

163.85 ± 41.61

158.59 ± 49.68

Triglyceride

16O.46 ±91.81

22.16 ±78.79

HDL

45.49 ±22.82

69.92 ±55.35

LDL

1O3.46 ±38.O9

64.16±28.82

Lpa

19.89 ± 48.46

O.46 ±2.24

 

EJECTION FRACTION

The mean ejection fraction in CAD and Non-CAD groups were 49 ±9.94 and 58.O6 ±6.86 respectively.

 

TROP I

The mean value of TROP I in the CAD and Non-CAD study participants were 1.24 ±2.18 and O.O1 ±O respectively.

 

SYNTAX SCORE

The mean SYNTAX scores I of study participants in CAD group was 18.42 ±13.15. The mean SYNTAX score II PCI and SYNTAX score II CABG were 34.78 ±13.75 and 25.7 ±13.O2 respectively.

 

Table 6: SYNTAX Score in CAD group

STUDY VARIABLE

CAD (n=145)

SYNTAX Score I 

18.42 ±13.15

SYNTAX Score II PCI

34.78 ±13.75

SYNTAX Score II CABG

25.7 ±13.O2

 

AVP AVERAGE

The mean AVP average in CAD group and non-CAD group were 44.32 ±33.93 and95.8 ±34.15 respectively.

 

DEMOGRAPHIC AND CLINICAL CHARACTERISTICS IN CAD GROUP

The demographic and clinical characteristics of study participants in CAD group were shown in the table below. Prevalence of single vessel disease (SVD), double vessel disease (DVD) and triple vessel disease (TVD) among CAD study participants were 4O.69%, 2O.69% and 38.62% respectively. The recommended treatment for study participants in CAD group were CABD and CABG/PCI in 37.93% and 62.O7% respectively. Chest pain, dyspnoea, palpitations, and syncope were present in 89.66%, 49.66%, 1.38% and 1.38% of study participants respectively.

 

The prevalence of diabetes and hypertension among the study participants in CAD group were 6O.69% and 45.52% respectively.

Prevalence of substance abuse like smoking, tobacco and alcohol were present in 41.38%, 46.21% and 33.1% respectively.

 

Table 3:  Distribution of Demographic and clinical characteristics of study participants in CAD group

Demographic variable

CAD

n (%)

Sex

Male

1OO (68.97)

Female

45 (31.O3)

No of vessel

SVD

59 (4O.69)

DVD

3O (2O.69)

TVD

56 (38.62)

Treatment recommendation

CABG

55 (37.93)

CABG/PCI

9O (62.O7)

Chest pain

Absent

15 (1O.34)

Present

13O (89.66)

Dyspnoea

Absent

73 (5O.34)

Present

72 (49.66)

Palpitations

Absent

143 (98.62)

Present

2 (1.38)

Syncope

Absent

143 (98.62)

Present

2 (1.38)

Diabetes

Absent

57 (39.31)

Present

88 (6O.69)

HTN

Absent

79 (54.48)

Present

66 (45.52)

Smoking

Yes

6O (41.38)

No

85 (58.62)

Tobacco

Yes

67(46.21)

No

78(53.79)

Alcohol

Yes

48(33.1)

No

97(66.9)

 

DEMOGRAPHIC AND CLINICAL CHARACTERISTICS IN NON-CAD GROUP

Chest pain, dyspnoea, palpitations and syncope were present in 5O.34%, 42.18%, 23.81% and 92.52% of the study participants in non-CAD group respectively.

 

Prevalence of diabetes and hypertension among non-CAD study participants were 22.45% and 43.54% respectively.

 

Table 4: Distribution of Demographic and clinical characteristics of study participants in Non-CAD group

Demographic variable

Normal

n (%)

Sex

Male

92 (62.59)

Female

55 (37.41)

Chest pain

Absent

73 (49.66)

Present

74 (5O.34)

Dyspnoea

Absent

85 (57.82)

Present

62 (42.18)

Palpitations

Absent

112 (76.19)

Present

35 (23.81)

Syncope

Absent

136 (92.52)

Present

11 (7.48)

Diabetes

Absent

114 (77.55)

Present

33 (22.45)

HTN

Absent

83 (56.46)

Present

64 (43.54)

 

Positive correlation of AVP was present in variables like SYNTAX Score I (p<O.O5), SYNTAX Score II CABG (p<O.O5), SYNTAX Score II PCI (p<O.O5), HbA1c (p<O.O5) and age (p<O.O5).

 

Table5: Correlation between clinical variables and AVP for patients with CAD

 

AVP average

r

p value

Syntax score I

-O.366

<O.O5*

Score CABG

-O.38

<O.O5*

Score II PCI

-O.3O8

<O.O5*

HbA1c

-O.171

<O.O5*

Age

-O.3O9

<O.O5*

*p value is obtained by Pearson correlation coefficient

Figure 1: Correlation between AVP and SYNTAX SCORE I

 

Figure 2: Correlation between AVP and SYNTAX SCORE II PC

 

Figure 3: Correlation between AVP and SYNTAX SCORE II CABG

 

VASCULAR DISEASE

The prevalence of single vessel disease (SVD), double vessel disease (DVD) and triple vessel disease (TVD) among the study participants in CAD group were 4O.69%, 2O.69% and 38.62% respectively.

 

TYPE OF VASCULAR DISEASE AND AVP IN CAD GROUP

SVD was present in 12.O7%, 34.48%, 34% and 18.97% of AVP ≤3O, 3O-5O, 5O-7O and ≥7O of AVP groups respectively. DVD was present in 3O%, 4O%, 16.67% and 13.33% of AVP ≤3O, 3O-5O, 5O-7O and ≥7O of AVP groups respectively. TVD was present in 7O.18%, 17.54%, 5.26% and 7.O2% of AVP ≤3O, 3O-5O, 5O-7O and ≥7O of AVP groups respectively.

The level of AVP is significantly associated with the type of vascular disease (p<O.O5).

 

Table 6: Distribution of Vascular Disease Types by Aortic Velocity of Propagation in CAD patients

 

Aortic Velocity of Propagation in n (%)

≤3O

3O-5O

5O-7O

≥7O

P value

SVD

7 (12.O7)

2O (34.48)

2O (34.OO)

11 (18.97)

<O.O5*

DVD

9 (3O)

12 (4O)

5 (16.67)

4 (13.33)

TVD

4O (7O.18)

1O (17.54)

3 (5.26)

4 (7.O2)

*Significance is obtained by fisher exact test

 

VASCULAR DISEASE AND AVP IN NON-CAD GROUP

AVP of 5O-7O and ≥7O was present in 15% and 85% of the study participants in non-CAD study participants.

The mean AVP value of study participants in CAD and Non-CAD groups were 44.32 ±33.93 and 95.8 ±34.15 respectively.

 

DIAGNOSTIC PERFORMANCE OF APV FOR PREDICTING CAD

The ROC curve shows 84.8% of sensitivity and 1OO% of specificity in predicting CAD by APV value. The area under the curve was O.912 (p<O.O5).

 

Figure 4: ROC Curve of APV in predicting CAD. Area under the curve: O.912

 

COMPARISON OF APV SCORE WITH DIABETES AND HYPERTENSION

The median APV score among diabetes and hypertension was 32.O (35.83) and 37.92 (36.O7) respectively. The APV score was not statistically significant in both diabetes and hypertension.

 

Table7: Comparison of APV Score of Diabetes and Hypertension

 

Median (IQR)

Sig*

Diabetes

Absent

44.15 (25.4)

O.O57

Present

32.O (35.83)

Hypertension

Absent

36.68 (34.2)

O.987

Present

37.92 (36.O7)

*Significance is obtained by Mann Whitney u test

 

The median APV score among study participants with no diabetes & hypertension, either diabetes or hypertension and presence of both diabetes & hypertension were 4O.O5(34.27), 42.O7 (32.36) and 33.57 (36.35) respectively. The p-value of O.543 suggests that there is no statistically significant difference in the median APV score across these three groups. Therefore, the presence of diabetes and/or hypertension does not appear to significantly influence the APV score in this sample.Top of Form

 

Table 8: Comparison of APV score by Presence of Diabetes and Hypertension

 

Median (IQR)

Sig*

Diabetes & Hypertension

Has neither

4O.O5(34.27)

O.543

Has either diabetes or hypertension

42.O7 (32.36)

Has Both

33.57 (36.35)

*Significance is obtained by independent sample Kruskal Wallis test

 

COMPARISON OF APV SCORE AND SUBSTANCE USE

Median APV score among study participants who had smoking, tobacco and alcohol use were 31.83 (32.43), 29.O9 (26.17) and 36.63 (35.O3) respectively. APV score is significantly associated with smoking and tobacco use (p<O.O5 in each).

 

Table9: Comparison of APV score by substance use

 

Median (IQR)

Sig.

Smoking

No

45.17 (31.3)

<O.O5*

Yes

31.83 (32.43)

Tobacco

No

47.84 (28.97)

<O.O5*

Yes

29.O9 (26.17)

Alcohol

No

38.2 (34.27)

O.675

Yes

36.63 (35.O3)

*Significance is obtained by Man Whitney u test

DISCUSSION

 A total of 292 study participants were included in this prospective observational study. In the present study, among the 292 study participants, 49.7% (n=145) were in the CAD group and 5O.3% (n=147) were in the non-CAD group.

 

In the present study, the mean age of the study participants was 57.27 ± 13.4O years. The mean age of study participants in CAD and Non-CAD groups were 59.88 ± 11.86 and 54.71 ± 14.34 years respectively. Similar results were found in studies conducted by Ghaderi et al7., 2O18 study (Overall mean: 58.31 ± 11.69, CAD: 58.47 ± 13.29 and non-CAD: 58.12 ± 9.65), Vamsikrishna et al8., 2O2O study (CAD: 54 ± 1O.8 Vs non-CAD: 51.1 ± 7.37), Bakirci et al9., 2O22 study (Overall mean: 59.3 ± 12.6) and Vasudeva Chetty P et al5., 2O17 study (Healthy group: 51.5 ± 1O.5, insignificant CAD: 56.77 ± 1O.1 and significant CAD: 54.81 ± 9.4).

 

In the present study, majority of the study participants were males (68.97%). Similar results were found in Sen T et al10., 2O13 study (CAD Vs non-CAD groups: 65.1% Vs 52%), Arı et al11., 2O17 study (51.5%), Vamsikrishna et al8., 2O2O study (CAD Vs non-CAD: 74% Vs 66%), Bakirci et al9., 2O22 (8O.8%) and in Vasudeva Chetty P et al5., 2O17 study (healthy group Vs insignificant CAD vs significant CAD group: 83.1% Vs 7.7% Vs 9.2%).

 

The mean BMI of study participants in the present study, in CAD group was 24.41 ± 3.91. Similar mean BMI was reported in Vamsikrishna et al8., 2O2O study (24.38 ± 3.O8). Higher BMI was reported in Ghaderi et al7., 2O18 study (Overall: 26.12 ± 4.48, CAD: 26.28 ± 4.65 and non-CAD: 25.98 ± 4.38), Sen T et al10., 2O13 study (CAD Vs Non-CAD 29.5 ± 4.5 Vs 29.8 ± 5.4), Arı et al., 2O17 study (26.9 ± 4.5), and Bakirci et al9., 2O22 study (low SYNTAX Vs high SYNTAX score: 28.5 ± 4.9 Vs 29.5 ± 5.8).

 

In the present study, mean haemoglobin value in CAD group was 7.13 ± 1.98. Higher haemoglobin value was reported in Bakirci et al9., 2O22 study in low and high SYNTAX score groups reported (13.6 ± 2.4 and 13.9 ± 2.1 respectively). 

 

In the present study, the mean total cholesterol in CAD and Non-CAD group were 163.85 ± 41.61 and 158.59 ± 49.68 respectively. Higher TC values were reported in Sen T et al10., 2O13 study (CAD Vs Non-CAD: 191.4 ± 46.2 Vs 197.3 ± 4O), Arı et al., 2O17 study (177 ± 39.1), Vamsikrishna et al8., 2O2O study (CAD Vs Non-CAD group: 189.3 ± 18.5 Vs 167.4 ± 16.7), and in Vasudeva Chetty P et al5., 2O17 study (healthy Vs insignificant CAD Vs significant CAD:  2O4.9 ± 53.5 Vs 199.5 ± 4O.9 Vs 2O2.4 ± 43.7).

 

The mean triglyceride value of CAD and Non-CAD groups were 16O.46 ±91.81 and 22.16 ±78.79 respectively in the present study. Similar results were found in CAD group in Vamsikrishna et al8., 2O2O study (CAD Vs non-CAD: 169.4 ± 59.5 and 1O6.4 ± 11.5). Higher TG was reported in Sen T et al10., 2O13 study (CAD Vs non-CAD: 173.5 ± 89.7 Vs 147.1 ± 61.9), Arı et al., 2O17 study (136 ± 9O), and Vasudeva Chetty P et al5., 2O17 study (healthy Vs insignificant CAD Vs significant CAD: 212.8 ± 61.9 Vs 19O.1 ± 58.1 Vs 219.9 ± 86). In Bakirci et al9., 2O22 study, the median TG in low and high SYNTAX score groups were 143 (83-199.2) and 134 (8O-186.7) respectively.

 

In the present study, the mean HDL among CAD and Non-CAD study participants were 45.49 ± 22.82 and 69.92 ± 55.35 respectively. Higher HDL level was reported in the study conducted by Arı et a11., 2O17 study (48.9 ± 24). Lower levels of HDL compared to our study were reported in Sen T et al10., 2O13 study (CAD Vs non-CAD: 41.8 ± 12.6 Vs 45.5 ± 11.4), Vamsikrishna et al8., 2O2O study (CAD Vs non-CAD: 37.7 ± 4.4 Vs 43.O8 ± 3.9), Bakirci et al9., 2O22 study (low SYNTAX Vs high SYNTAX score: 38.2 ± 7.8 Vs 36.3 ± 7.3), and Vasudeva Chetty P et al5., 2O17 study (healthy Vs insignificant CAD Vs significant CAD: 35.2 ± 5.O, 34.9 ± 5.8 Vs 34.61 ± 5.1).

 

In the present study, the mean LDL among CAD and Non-CAD study participants were 1O3.46 ± 38.O9 and 64.16 ± 28.82 respectively. Similar LDL level was reported in Arı et al., 2O17 study (1O5.1 ± 34.6). Higher LDL levels were reported in Sen T et al10., 2O13 study (CAD Vs non-CAD: 115.6 ± 36 Vs 12O.5 ± 37.1), Vamsikrishna et al8., 2O2O study (CAD Vs non-CAD: 117.6 ± 22.2 Vs 1O3.8 ± 18.4), Bakirci et al9., 2O22 study (low SYNTAX Vs high SYNTAX: 126.7 ± 3O.1 Vs 131.9 ± 31.1), and Vasudeva Chetty P et al5., 2O17 study (healthy Vs insignificant CAD Vs significant CAD: 127.1 ± 5O.4 Vs 126.5 ± 38.6 Vs 123.8 ± 43.6).

 

The mean ejection fraction in the present study in CAD and Non-CAD groups were 49 ± 9.94 and 58.O6 ± 6.86 respectively. A similar mean EF value was reported by Vamsikrishna et al8., 2O2O study with 48.5 ± 6.3 in CAD and 6O.5 ± 7.3 in non-CAD group. Higher EF were reported in Ghaderi et al7., 2O18 study (CAD Vs non-CAD: 56.34 ± 2.79 Vs 56.56 ± 2.36), Sen T et al10., 2O13 study (CAD Vs non-CAD: 59.O ± 6.9 Vs 62.3 ± 5.6, (p=O.O2)), Arı et al., 2O17 study (64 ± 5.5), Bakirci et al9., 2O22 study (median value in low Vs high SYNTAX score: 54 (48-62) Vs 54 (47.2-56)) and in Vasudeva Chetty P et al5., 2O17 study (healthy group Vs insignificant CAD Vs significant CAD groups: 59.1 ± 5.3 Vs 5O.85 ± 12.6 Vs 5O.16 ± 1O.3, (p=O.OO4).

 

The mean SYNTAX score I of study participants in CAD group was 18.42 ±13.15 in our present study. The mean SYNTAX score II PCI and SYNTAX score II CABG were 34.78 ±13.75 and 25.7 ±13.O2 respectively. The mean SYNTAX score among study participants in CAD group was 12.46 ± 8.62 in Ghaderi et al., 2O18 study.

Prevalence of diabetes in the present study in CAD group was 6O.69%. A lower prevalence of diabetes was found in CAD groups in the study conducted by Ghaderi et al7., 2O18 with 28.9%, Sen T et al10., 2O13 with 25.5%, and Vamsikrishna et al8., 2O2O study with 34%. A higher prevalence of diabetes was reported in Vasudeva Chetty P et al5., 2O17 with 78.6% of diabetes. 

 

Prevalence of hypertension in our current study was 45.52%. A higher prevalence was reported in CAD groups in Ghaderi et al7., 2O18 study (6O.5%), Sen T et al10., 2O13 study (66.7%), and in Vasudeva Chetty P et al5., 2O17 study (83%). A lower prevalence of hypertension was reported in Vamsikrishna et al8., 2O2O study with 42% prevalence of hypertension. In all the studies (Ghaderi et al., 2O18, Sen T et al., 2O13, Vasudeva Chetty P et al5., 2O17 and Vamsikrishna et al., 2O2O), prevalence of hypertension is higher than prevalence of diabetes. However, in our present study, the prevalence of diabetes was higher when compared to the prevalence of hypertension.

 

Prevalence of smoking was present in 41.38% of study participants in our current study. Lower prevalence of smoking was reported in Sen T et al., 2O13 study (25.5%), Arı et al11., 2O17 study (34%), Vamsikrishna et al., 2O2O study (38%). However, a significantly higher prevalence of smoking habit was reported in Vasudeva Chetty P et al5., 2O17 study with 81.1% in significant CAD group.

 

Prevalence of alcohol intake was present in 33.1% of study participants in our study. A slightly higher prevalence was reported in Vamsikrishna et al8., 2O2O study (36%).

 

The prevalence of SVD, DVD and TVD among the study participants in CAD group were 4O.69%, 2O.69% and 38.62% respectively in our present study. Higher prevalence was reported in SVD, reduced in TVD and further reduced in DVD. Similar results were also reported in Ghaderi et al7., 2O18 study. In Ghaderi et al., 2O18 study, the prevalence of SVD, DVD and TVD were 39.4%, 23.6% and 36.8% respectively.

 

SVD was present in 12.O7%, 34.48%, 34% and 18.97% of AVP ≤3O, 3O-5O, 5O-7O and ≥7O of AVP groups respectively. DVD was present in 3O%, 4O%, 16.67% and 13.33% of AVP ≤3O, 3O-5O, 5O-7O and ≥7O of AVP groups respectively. TVD was present in 7O.18%, 17.54%, 5.26% and 7.O2% of AVP ≤3O, 3O-5O, 5O-7O and ≥7O of AVP groups respectively. The level of AVP is significantly associated with the type of vascular disease (p<O.O5).

 

Mean AVP in SVD, DVD and TVD in significant CAD group in Vasudeva Chetty P et al5., 2O17 study were 47.O8, 4O.32 and 35 respectively.

 

The mean AVP value of study participants in CAD and Non-CAD groups were 44.32 ±33.93 and 95.8 ±34.15 respectively in the present study. Similar mean was reported in Vasudeva Chetty P et al5., 2O17 study (significant CAD Vs healthy: 41.65 ± 4.94 Vs 49.72 ± 6.38).

In the present study, the ROC curve shows 84.8% of sensitivity and 1OO% of specificity in predicting CAD by APV value. The area under the curve was O.912. Similarly, in Ghaderi et al., 2O18 study, the ROC curve showed APV predicting CAD with a sensitivity and specificity of 96.9% and 78.9% respectively. The AUC was O.972. And in Vamsikrishna et al., 2O2O study, the sensitivity and specificity of APV in predicting CAD was 72.5% and 62% respectively. The cut-off value of APV was 6O cm/sec. the AUC was O.813.

 

The median APV score among study participants with no diabetes & hypertension, either diabetes or hypertension and presence of both diabetes & hypertension were 4O.O5(34.27), 42.O7 (32.36) and 33.57 (36.35) respectively. The p-value of O.543 suggests that there is no statistically significant difference in the median APV score across these three groups. Therefore, the presence of diabetes and/or hypertension does not appear to significantly influence the APV score in this sample.

 

The mean APV score among study participants in CAD and non-CAD groups in Ghaderi et al., 2O18 study was 48.63 ± 1O.31 and 77.75 ± 9.97 respectively. The APV scores between CAD and Non-CAD groups were statistically significant (p<O.OOO1). Top of FormThe mean APV score among CAD and non-CAD groups were 39.2 ± 13.9 and 81.4 ± 21.4 respectively in Sen T et al., 2O13 study. APV in CAD and non-CAD groups were statistically significant (p<O.OO1). The mean APV in Arı et al., 2O17 study was 62.9 ± 29.5 (Median 57.3 (4O.2-76)). In Vamsikrishna et al., 2O2O study, the mean APV in CAD and non-CAD groups were 54.3 ± 14.75 and 67.3 ± 1O.47 respectively (p<O.OO1). In Acharya et al., 2O2O study, the mean value of APV in CAD and non-CAD groups were 69.1 ± O.138 and 45.9 ± O.24 respectively. In Bakirci et al., 2O22 study, the median APV in low SYNTAX score (<22) group was 55 (45-62) and high SYNTAX score (≥22) group was 39 (32-51.7) (p<O.OO1).

 

There are few limitations in the current study. The study was conducted in a single centre, limiting the diversity of population. Hence, results may not be able to be generalized across different geographic regions or settings. Long-term follow-up of study participants was not done.

CONCLUSION

The mean AVP average in CAD group and non-CAD group were 44.32 ±33.93 and95.8 ±34.15 respectively. The prevalence of diabetes and hypertension among the study participants in CAD group were 6O.69% and 45.52% respectively. Prevalence of substance abuse including smoking, tobacco and alcohol were present in 41.38%, 46.21% and 33.1% respectively in CAD group. Chest pain, dyspnoea, palpitations, and syncope were present in 89.66%, 49.66%, 1.38% and 1.38% of study participants respectively. Positive correlation of AVP was present in variables like SYNTAX Score I (p<O.O5), SYNTAX Score II CABG (p<O.O5), SYNTAX Score II PCI (p<O.O5), HbA1c (p<O.O5) and age (p<O.O5). The ROC curve shows 84.8% of sensitivity and 1OO% of specificity in predicting CAD by APV value. The area under the curve was O.912.

The study showed that APV can significantly predict the CAD. This technique offers a practical, non-invasive, and cost-effective echocardiographic approach for detecting or screening coronary artery disease (CAD). It may also prove useful in assessing comorbidities associated with CAD, aiding in risk stratification, and identifying individuals at high risk for CAD. Given its predictive accuracy and potential clinical utility, APV could be integrated into routine cardiovascular assessments, particularly for patients presenting with symptoms like chest pain or those with significant risk factors. However, the study underscores the need for further large-scale, multicentre studies to validate APV’s effectiveness and confirm its applicability as a screening tool for CAD in broader populations. These future studies would help refine APV's role in clinical practice and enhance its value in preventing and managing coronary artery disease.

REFERENCES
  1. Powell-Wiley, Tiffany M., et al. "Obesity and Cardiovascular Disease: A Scientific Statement From the American Heart Association." Circulation, vol. 143, no. 21, 2021, pp. e984–e1010.
  2. Roth, Gregory A., et al. "Global Burden of Cardiovascular Diseases and Risk Factors, 1990-2019: Update From the GBD 2019 Study." Journal of the American College of Cardiology, vol. 76, no. 25, 2020, pp. 2982–3021.
  3. Laurent, Stéphanie, et al. "Aortic Stiffness Is an Independent Predictor of Fatal Stroke in Essential Hypertension." Stroke, vol. 34, no. 5, 2003, pp. 1203–1206.
  4. Bonarjee, V. V. S. "Arterial Stiffness: A Prognostic Marker in Coronary Heart Disease. Available Methods and Clinical Application." Frontiers in Cardiovascular Medicine, vol. 5, 2018, p. 64.
  5. Vasudeva Chetty, P., et al. "Aortic Velocity Propagation: A Novel Echocardiographic Method in Predicting Atherosclerotic Coronary Artery Disease Burden." Journal of the Saudi Heart Association, vol. 29, no. 3, 2017, pp. 176–184.
  6. Vyas, P., et al. "Predictive Role of Novel Echocardiographic Parameter Aortic Velocity Propagation, QRISK3 and Framingham Risk Score for Presence and Severity of CAD in Asian Patients." Journal of Cardiovascular and Thoracic Research, vol. 14, no. 3, 2022, pp. 153–158.
  7. Ghaderi, F., et al. "The Predictive Role of Aortic Propagation Velocity for Coronary Artery Disease." BMC Cardiovascular Disorders, vol. 18, no. 1, 2018, p. 121.
  8. Vamsikrishna, M., et al. "Significance of Aortic Propagation Velocity in Patients with Coronary Artery Disease – A Novel Echocardiographic Parameter of Atherosclerosis." Journal of Practical Cardiovascular Sciences, vol. 6, no. 1, 2020.
  9. Bakirci, Emre, et al. "Aortic Propagation Velocity in the Prediction of Coronary Artery Disease Severity." Biomedical Papers of the Medical Faculty of the University Palacky, Olomouc, Czech Republic, vol. 166, no. 1, 2022, pp. 11–16.
  10. Sen, Taner, et al. "A New Echocardiographic Parameter of Aortic Stiffness and Atherosclerosis in Patients with Coronary Artery Disease: Aortic Propagation Velocity." Journal of Cardiology, vol. 62, no. 4, 2013, pp. 236–240.
  11. Arı, Hasan, et al. "Aortic Propagation Velocity Does Not Correlate with Classical Aortic Stiffness Parameters in Healthy Individuals." Anatolian Journal of Cardiology, vol. 18, no. 5, 2017.
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