Cardiovascular disease (CVD) is a leading cause of death, both in developing and developed nations1. As per WHO Health Risk Fact Sheet 2015 publication, at present cardiovascular disease are the number one cause of death globally and that more people die annually from cardiovascular disease than from any other cause2. It accounted for 17.5 million deaths worldwide in 2012 (31% of the total deaths), and this was expected to increase up to 24.2 million by 20303.

These risk factors included smoking, dyslipidemia, diabetes, hypertension, abdominal obesity, lack of daily consumption of fruits and vegetables, regular physical activity, regular alcohol consumption and psychosocial factors (e.g. depression, perceived stress and life events). This finding suggests that a large proportion of CVD can be prevented by aggressive risk factor modification in the individuals who are at risk of developing the disease. Accordingly, identifying individuals at the highest risk of developing CVD to target appropriate prevention and treatment strategies towards them has been the focus of research for over 40 years4.

Traditionally, cardiovascular(CV)risk is assessed by using one of the several risk algorithms that take into account the presence and severity of the various major CV risk factors. The commonly used risk assessment tools for this purpose include Framingham risk score (FRS)5,6. American College of Cardiology/American Heart Association (ACC/AHA) pooled cohort equations7, Systemic Coronary Risk Evaluation (SCORE)8, QRISK9–11, 3rd Joint British Societies’ (JBS3) risk calculator12, the World Health Organisation / International Society of Hypertension13 (WHO/ISH) CVD risk prediction.

Studies have confirmed that Epicardial adipose tissue (EAT) represent a true visceral fat and has been proposed as a cardio metabolic risk factor. Epicardial adipose tissue thickness (EATT) has been clinically correlated with metabolic syndrome, subclinical atherosclerosis and coronary artery disease 12,13,14,15,16.

Initial studies of Epicardial adipose tissue and ability to predict coronary artery disease have shown a wide variation in the mean Epicardial adipose tissue thickness. In a study evaluating epicardial adipose tissue thickness in hypertensive patients, a cut off of 3.1mm predicted metabolic syndrome with 100% sensitivity and 79% specificity17. In a small study evaluating Epicardial adipose thickness in patients with ACS undergoing CAG, it was observed that the mean epicardial adipose tissue thickness was 5.518.

A study by S-G Ahn et al showed that an epicardial adipose tissue thickness value of 3.0 mm was an independent risk factor for predicting coronary artery disease 19. However, a recent study which attempt- ed to established echocardiographic cut off point for the diagnosis of coronary artery disease had showed much higher value more than 10mm for predicting a coronary artery disease 20.

Therefore to establish a reliable range for Epicardial adipose tissue thickness to study the correlation between Epicardial adipose tissue thickness and severity of coronary artery disease is crucial.

This is a Prospective and analytical study was conducted in the Department of Cardiology of a tertiary level referral private institute in South India - Aster MIMS, Calicut, Kerala, India.

All consecutive patients scheduled for a coronary angiogram at the Department of Cardiology at our Institute.

INCLUSION CRITERIA

1. All patients undergoing coronary angiogram between 18-79 years who are referred for di- agnostic coronary angiogram.
2. Those patients did not have previously known coronary artery disease (CAD). 3. Those who did not have any other concomitant major cardiac illness.

EXCLUSION CRITERIA:

1. Patients who has previous history of coronary artery disease. 2. Age less than 18 years and more 80 years of age

All subjects scheduled for a coronary angiogram will undergo clinical evaluation, biochemical investigations and measurement of CIMT and epicardial fat thickness prior to coronary angiogram.

The clinical evaluation will include history regarding the presence or absence of CV risk factors, duration of CV risk factors, symptoms suggestive of CAD etc. Physical examination will height, weight & blood pressure (BP) measurement and the examination of CV system. BP will be measured in the right arm in supine position, using a standard sphygmomanometer. Biochemical investigations will include a fasting lipid profile and fasting & 2-h post-prandial blood glucose estimation.

Family history would be considered positive if a coronary event had occurred in a male first degree relative before the age of 55 years or a female first degree relative before the age of 65 years. Smoking or tobacco use in any form during the preceding month would also consider to be a CV risk factor.

CIMT assessment

CIMT measurement will be performed following the standard protocol.13 Distal common carotid artery (CCA) will be imaged on both sides with a 7.5 MHz frequency linear array transducer, attached to any standard vascular ultrasound machine. The artery will be imaged in a longitudinal plane to obtain opti- mal angle of incidence, defined as the plane in which the bifurcation of the carotid bulb into the internal and external carotid arteries can be visualised simultaneously with the bulb and distal CCA (also known as ‘tuning fork’ view).

Once this view is obtained, finer adjustments in the transducer position are done to ensure distal CCA is perfectly horizontal on the screen and ‘double lines’ of Intima and adventitia are clearly visualized in the far wall of the CCA (‘double-line’ sign). From this view, CIMT is measured as the distance between the lumen-Intima interface and the media-adventitia interface. Plaques, defined as 50% localized thickening of the Intima compared to the rest of the wall, are included in the measurement of CIMT if present within the distal 1 cm of CCA. The CCA will be imaged from two additional complimentary angles, approximately 45 degree anterior and posterior to the first image and the CIMT measurement is performed. The six values will be obtained (three for each side) were averaged and will be used for analysis.

ASSESSMENT OF EPICARDIAL ADIPOSE TISSUE:

It is a non-invasive, reliable, reproducible and safe method. Parasternal long axis view and short axis is used. It is seen as an echo free space anterior to the RV free wall and is measured during end diastole. Three measurements are usually taken. EAT assessment in Indian population there is only one study undertaken in Indian population by Ranjan Shetty et al., which found that the mean epicardial fat is 2.6 (range 0.3 to 7.0 mm). Like previous studies it also found that epicardial fat correlated with waist circumference and age.

STATISTICAL METHODS

The data will be managed on Microsoft excel spreadsheet (version 2007, Microsoft Corp, Seattle, Washington) and analysed using SPSS for Windows (release 25.0, SPSS Inc, Chicago, IL, USA). Standard descriptive analysis will be performed. The categorical variables will be expressed as actual numbers with percentages and the continuous variables as mean ± standard deviation (for normally distributed data) or as median with interquartile ranges (for CIMT and epicardial fat thickness, which were not normally distributed). The comparisons among different risk groups and disease groups will be performed using Chi- square test for categorical variables and one-way analysis of variance or Kruskale Wallis test, as appropriate, for continuous variables. C rho (r) was estimated to assess the relationship between various risk estimates and the measures of subclinical atherosclerosis. A p value <0.05 will be considered statistically significant

Mean age of the study subjects was found to be 58.55±9.55 years with majority (55.5%) in the 41-60 age group. The distribution of sex was studied here. Out of 1001 patients taken, 68.7 % of the samples were male and 31.3 % were female. Majority were males.

Median BP was found to be 120/80. 48.7% study subjects were hypertensive. Diabetes mellitus was found in 47.4% study subjects.

Median LVEF was 60%. RWMA was present in 32.1% study subjects. Median EAT was 0.30 cm while the median CIMT was 0.9 mm.

Median Hb was 13.40 g/dL. Median PLC was 2.42 lakhs. Median serum creatinine was 0.90 mg/dL. Median sodium level was 139 mmol/L while the median potassium was 4.20 mmol/L. Median total cho- lesterol was 198 mg/dL while that of LDL was 121 and HDL was 42. Median triglyceride value was 164 mg/dL.

Three vessel disease was found in 18.9% study subjects. 24.6% study subjects had two vessel disease. LMCA disease was found in 3.9% subjects. Two vessel disease was the most common finding (24.7%).

Median ASCVD was 10.65. Median FRS was 7.95 and medan JBS3 was 19.40.

JBS3 score, ASCVD score & FRS were significantly higher among CAD patients. EAT & CIT were also found to be statistically significant echo measures for CAD.

JBS3 score, ASCVD score & FRS were significantly higher among major CAD patients. EAT was also found to be statistically significant echo measure for major CAD.

Mean age of the study subjects was found to be 58.55±9.55 years with majority (55.5%) in the 41-60 age group. Sanchis-Gomar F et al described in his study CAD prevalence increases after 35 years of age in both men and women. The lifetime risk of developing CAD in men and women after 40 years of age is 49% and 32%, respectively.21

Age plays a vital role in the deterioration of cardiovascular functionality, resulting in an in- creased risk of cardiovascular disease (CVD) in older adults 22,23. The prevalence of CVD has also been shown to increase with age, in both men and women, including the prevalence of atherosclerosis, stroke and, myocardial infarction24. The American Heart Association (AHA) reports that the incidence of CVD in US men and women is ~40% from 40–59 years, ~75% from 60–79 years, and ~86% in those above the age of 80103.

The distribution of sex was studied here. Out of 1001 patients taken, 68.7 % of the samples were male and 31.3 % were female. Majority were males. Sanchis-Gomar F et al described in his study CAD prevalence increases after 35 years of age in both men and women. The lifetime risk of developing CAD in men and women after 40 years of age is 49% and 32%, respectively. 25

In the AHA 2019 Heart Disease and Stroke Statistical Update, the incidence of CVD was reported to be 77.2% in males and 78.2% in females, from ages 60–79 years. Furthermore, the incidence of CVD was reported to be 89.3% in males, and 91.8% in females, in adults above 80 years of age26. With respect to coronary artery disease (CAD), the strongest risk factors are male gender and age

Median BP was found to be 120/80. 48.7% study subjects were hypertensive. Diabetes mellitus was found in 47.4% study subjects. Dyslipidemia was present in 45.5% study subjects. 11.1% had family history of CAD. 14.5% study subjects were on statin therapy. 1.9% had a past history of stroke. 14% study subjects had the habit of smoking. Kennel et al in 1996 in his article reported that in the Framingham cohort, a systolic of 20mmHg and diastolic of 10 mmHg increase was observed from age 30 years to 65 years, and hypertension is most common risk factor associated with cardiovascular events. 27 Hyperlipidemia is considered the second most common risk factor for ischemic heart disease, According to the World Health Organization, raised cholesterol caused an estimated 2.6 million deaths. A recent cross-sectional study utilizing the coronary calcium score indicated a 55%, 41%, and 20% higher prevalence of hypercholesterolemia, combined hyperlipidemia, and low HDL-c, respectively.28

Diabetes mellitus: A 2017 meta-analysis indicated that diabetic patients with an A1C > 7.0 had an 85% higher likelihood (hazard ratio 1.85, 95% CI 1.14-2.55) of cardiovascular mortality, compared to those with an A1C < 7.0%. It also revealed that non-diabetic patients with an A1C > 6.0% had a 50% higher likelihood (hazard ratio, 1.50, 95% CI 1.01-2.21) of cardiovascular mortality compared to those with an A1C of < 5.0%. Researchers also reported a significant study heterogeneity. 29

Family history is also a significant risk factor. Patients with a family history of premature cardiac dis- ease younger than 50 years of age have an increased CAD mortality risk. A 2015 meta-analysis revealed that smoking resulted in a 51% increased risk (21 studies, RR 1.51, 95% CI 1.41.1-62) of coronary heart disease in diabetic patients.30

Two vessel disease was the most common finding (24.7%). Three vessel disease was found in 18.9% study subjects. 24.6% study subjects had two vessel disease. LMCA disease was found in 3.9% subjects. Zimmermann et al. 31 demonstrated that both in young men and women, normal coronaries, minimal lesions, SVD and DVD were more common than their older counterparts. 32 Mohammed et al also observed that SVD was more common in young population and TVD was common in older people. 33 Mahajan et al in his study revealed Isolated LMCA Ostial stenosis is a rare condition. Its incidence has been reported to be between 0.05%–0.88% in various studies. It is more commonly reported in women, usually before menopause. 34

Median Hb was 13.40 g/dL. Median PLC was 2.42 lakhs. Median serum creatinine was 0.90 mg/dL. Median sodium level was 139 mmol/L while the median potassium was 4.20 mmol/L. Median total cholesterol was 198 mg/dL while that of LDL was 121 and HDL was 42. Median triglyceride value was 164 mg/dL. Naveen Greg et al. 35in his article demonstrated the average age of the whole population was 57.3 ± 9.5 years. Males were predominant. Only 3.6% of the study population had young MI patients. Most were non-obese subjects. The prevalence of hypertension, smoking, diabetes mellitus (DM) was almost simi- lar, each constituting about 30% of the study population. Average LDL was lower than expected i.e. 86.7 ± 32.2 mg/dl. A low HDL and high triglyceride were highly prevalent. Only 2.5% had a family his- tory of premature CVD. 36

Mean of risk scores and significance in the study was JBS3 Score 22.94±12.17, ASCVD Risk Score 15.16±11.69, Framingham Risk Score 10.65±7.48, EAT  0.33±0.12, CIT 0.24±0.30.  JBS3 score, AS-CVD score & FRS were significantly higher among CAD patients. EAT & CIT were also found to be statistically significant echo measures for CAD.JBS3 score, ASCVD score & FRS were significantly higher among major CAD patients. EAT was also found to be statistically significant echo measure for major CAD.

Our study concludes overall sensitivity of Clinical Risk scores in isolation for detection of significant CAD is low and their negative predictive value for ruling out significant CAD is low. The positive predictive value for predicting CAD is high for all the clinical risk scores. The Imaging parameters in isolation EAT and CIT have a better Sensitivity and Negative predictive value to predict significant CAD. Addition of Imaging parameters to clinical risk scores either EAT or CIT or both significantly increas- es sensitivity of all 3 Clinical Risk scores. Overall JBS 3 clinical risk score fares better in isolation to predict significant CAD in our population. Combining EAT and CIT estimation increases the accuracy in CAD prediction, and in combination, FRS fares better compared to other risk scores. Estimation of CV risk may appear as a time-consuming process but is a worthwhile exercise.

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