European Journal of Cardiovascular Medicine

Coronary artery disease (CAD) remains the leading cause of death worldwide, accounting for nearly one in three global deaths annually【1】. Despite significant advances in pharmacological therapies and interventional cardiology, the burden of CAD continues to rise, particularly in low- and middle-income countries such as India【1】. Compared to Western populations, CAD in South Asia tends to present at a younger age, with more severe disease and worse outcomes, leading to considerable loss of productive life years【1】. Therefore, identifying novel and cost-effective markers that improve early diagnosis, risk stratification, and prognostication is an urgent priority.

Traditionally, CAD risk assessment has relied on established factors such as hypertension, diabetes mellitus, smoking, obesity, and dyslipidemia. While these predictors are valuable, they do not fully account for interindividual variability in the development or progression of CAD【1】. A growing body of evidence suggests that visceral adiposity, especially fat depots in close proximity to the heart and coronary vessels, may play a unique role in atherogenesis【3】.

Epicardial Adipose Tissue: Anatomical and Physiological Significance

Epicardial adipose tissue (EAT) is a specialized visceral fat depot located between the myocardium and the visceral pericardium【3】. Unlike paracardial or mediastinal fat, EAT shares microcirculation with the coronary arteries, enabling direct paracrine and vasocrine interactions【3】. This unique anatomic relationship allows EAT to influence coronary vascular tone, endothelial function, and myocardial metabolism.

EAT is metabolically active, secreting both pro-inflammatory and anti-inflammatory adipokines. On the one hand, adiponectin and adrenomedullin exert protective, anti-atherogenic effects【3】. On the other hand, EAT is a rich source of pro-inflammatory cytokines such as tumor necrosis factor-α (TNF-α), interleukin (IL)-6, and monocyte chemoattractant protein-1 (MCP-1), which promote endothelial dysfunction, smooth muscle proliferation, and plaque instability【5】. The balance between these opposing adipokine profiles determines the impact of EAT on cardiovascular health【16】.

Histological studies have confirmed that EAT is more than a passive fat depot; it contains infiltrating macrophages and lymphocytes, highlighting its role as an immunologically active organ【5】,【13】. The close anatomic contiguity and lack of fascial separation between EAT and the coronary arteries suggest that local inflammatory mediators diffuse directly into the vascular wall, accelerating atherosclerotic processes【5】,【11】.

Epicardial Fat Thickness and Cardiometabolic Risk

Echocardiographic epicardial fat thickness (EFT) is a simple, reproducible, and non-invasive measure of EAT. Unlike other imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI), echocardiography is cost-effective, radiation-free, and widely available, making it particularly suitable for resource-limited settings【4】.

Several studies have demonstrated that EFT reflects visceral adiposity more accurately than general anthropometric measures such as body mass index (BMI) or waist circumference【3】,【6】. Moreover, EFT correlates strongly with cardiometabolic risk factors including metabolic syndrome, insulin resistance, and type 2 diabetes mellitus【15】. Mahabadi et al. in the Framingham Heart Study reported that pericardial fat was independently associated with cardiovascular disease burden, even after adjusting for BMI and waist circumference【6】.

Similarly, Eroglu et al. showed that EFT measured by echocardiography was significantly higher in patients with angiographically proven CAD than in controls, and it increased with disease severity【14】. Other investigators have highlighted the association between EFT and subclinical atherosclerosis, coronary calcification, and carotid intima-media thickness【12】,【17】.

Association Between EFT and Coronary Artery Disease

The mechanistic link between EFT and CAD lies in its dual role as both an energy source and an inflammatory mediator. During ischemic stress, EAT releases free fatty acids to support myocardial metabolism【3】. However, chronic expansion of EAT creates a pro-inflammatory environment that contributes to atherogenesis【11】. Mazurek et al. provided seminal evidence that human EAT is a source of inflammatory mediators such as TNF-α and IL-6, which were found in higher concentrations in patients with CAD than in controls【5】.

Observational studies have demonstrated strong associations between EFT and angiographic CAD. Ahn et al. reported that increased EFT measured by echocardiography was an independent predictor of angiographically significant CAD【7】. Eroglu et al. corroborated these findings, showing that EFT ≥ 7.6 mm was associated with higher Gensini scores, suggesting a dose–response relationship between EFT and disease severity【14】. Similarly, Hirata et al. found enhanced inflammation in EAT biopsies of patients with CAD, supporting a pathological role for this tissue【13】.

Meta-analyses further support these observations. Alexopoulos et al. concluded that visceral adipose tissue, including EAT, is not only a marker of systemic adiposity but also an active promoter of coronary atherosclerosis【11】. These findings underscore the clinical value of measuring EFT in patients at risk for CAD.

Indian Evidence

In the Indian context, CAD is highly prevalent, with an estimated burden ranging between 5–20% in urban populations and 3.6–9.4% in rural populations【1】. Indian patients often present with CAD at a younger age and lower BMI, suggesting that traditional anthropometric markers may underestimate risk in this population.

Several Indian studies have begun to explore the role of EFT in CAD. Shetty et al. reported that EFT was significantly higher in Indian patients with CAD compared to controls, and it correlated with angiographic severity【8】. Similarly, Sharma et al. demonstrated that echocardiographic EFT could be used as a marker of CAD severity in Indian patients, highlighting its potential role in routine risk stratification【20】. Given the cost constraints and limited access to advanced imaging in many parts of India, echocardiographic EFT emerges as a practical and scalable tool.

Limitations of Current Evidence

Despite compelling data, several gaps remain. First, studies have reported heterogeneous cut-off values for EFT predictive of CAD, ranging from 3 mm to 10 mm【9】,【14】. This variation may reflect differences in populations, echocardiographic techniques, and disease definitions. Second, many prior studies were limited by small sample sizes and single-centre designs. Third, while EFT is associated with CAD, whether it provides incremental prognostic value beyond traditional risk scores remains under debate.

Moreover, echocardiographic measurement of EFT requires technical precision, as measurement sites (parasternal long-axis vs short-axis), timing within the cardiac cycle (end-systole vs end-diastole), and operator experience can all influence results【4】. Standardization of measurement protocols is essential before EFT can be widely adopted in clinical practice.

Rationale for the Present Study

Given the growing burden of CAD in India and the need for affordable, non-invasive diagnostic tools, echocardiographic EFT measurement holds promise as a practical marker of disease severity. Previous studies, though encouraging, have reported conflicting results and inconsistent cut-offs. Furthermore, limited Indian data exist that systematically evaluate the association between EFT and angiographic CAD using validated scoring systems such as the modified Gensini score【2】.

The present study was therefore designed to assess the relationship between echocardiographic EFT and angiographic CAD severity in patients undergoing coronary angiography for suspected CAD in a tertiary care hospital in South India. By evaluating EFT alongside traditional risk factors, this study aimed to clarify whether EFT could serve as a simple, reproducible, and cost-effective marker for identifying patients at greater risk of significant coronary stenosis.

Study Design

• This was designed as a single-centre, observational, cross-sectional study.
• The choice of design was intentional to establish association rather than causality, focusing on whether epicardial fat thickness (EFT) measured non-invasively by echocardiography correlates with the severity of coronary artery disease (CAD) as documented by coronary angiography (CAG).
• Being observational, no intervention was applied; all patients underwent standard diagnostic procedures as part of routine clinical care.

Study Setting

• Conducted in the Department of Cardiology, Government Medical College, Kozhikode, Kerala, India, a major tertiary care centre serving a large urban and semi-urban catchment area.
• The institution is well-equipped with facilities for echocardiography, electrocardiography, and catheterization laboratory services, ensuring uniform application of diagnostic modalities.
• The study was carried out under the supervision of the faculty of cardiology, ensuring adherence to institutional protocols and guidelines.

Study Period

• The research was carried out over 12 months.
• This duration was selected to ensure adequate sample accrual, accommodate seasonal variations in patient admissions, and maintain feasibility within the academic training schedule.
• Data collection, patient recruitment, and analyses were performed in real time, with monthly review meetings to ensure completeness of records.

Study Population

• The target population included patients undergoing diagnostic coronary angiography for suspected CAD.
• “Suspected CAD” was defined clinically based on:
• Symptoms such as typical or atypical angina, unexplained exertional dyspnea, or chest discomfort.
• Positive or equivocal non-invasive stress tests (e.g., treadmill test, nuclear scan, or echocardiographic stress imaging).
• Electrocardiographic evidence suggestive of ischemia or infarction.
• Patients were recruited consecutively to minimize selection bias.

Sample Size

• A total of 151 patients were finally enrolled.
• The sample size was determined based on feasibility within the study period rather than a priori power calculation. However, the chosen sample size was comparable to previous Indian studies exploring epicardial fat thickness and CAD【8】,【20】.
• All patients fulfilling inclusion criteria during the study window were considered, ensuring representativeness of the clinical population.

Inclusion Criteria

Patients were eligible if they met the following:

1. Age ≥18 years.
2. Undergoing coronary angiography (CAG) for evaluation of suspected CAD.
3. Willingness to participate, documented by written informed consent.

Exclusion Criteria

To avoid confounders and ensure quality echocardiographic measurements, patients with the following were excluded:

• History of prior coronary revascularization (CABG or PCI), as this alters coronary anatomy and disease scoring.
• Poor echocardiographic window (e.g., due to obesity, lung disease, or chest wall deformity), limiting reliable EFT measurement.
• Chronic kidney disease (CKD), because uremic states are associated with systemic inflammation and altered fat distribution.
• Chronic liver disease (CLD), due to metabolic changes affecting visceral fat depots.
• Pericardial or pleural effusion, which interferes with accurate delineation of epicardial fat on echo.
• Significant chest wall deformities or previous thoracic surgery, which hinder standardized imaging.

Clinical Evaluation

Each patient underwent a structured evaluation including:

• History: Detailed history of chest pain, dyspnea, risk factors (diabetes, hypertension, dyslipidemia, smoking, family history of CAD).
• Anthropometry: Height, weight, body mass index (BMI), and waist circumference measured using standard protocols.
• Physical Examination: General assessment, blood pressure, heart rate, cardiovascular examination.
• Laboratory Investigations: Fasting lipid profile, fasting blood sugar, and other relevant baseline investigations.

Electrocardiography (ECG)

• Standard 12-lead ECG was performed for all patients.
• Findings such as ST-segment and T-wave changes, evidence of prior infarction, or rhythm disturbances were documented.
• ECG served as a baseline tool to compare with echocardiographic LV function and angiographic findings.

Echocardiographic Assessment

• Machine & Protocol: All echocardiograms were performed using a standard 2D echocardiography system with appropriate probes.
• EFT Measurement:
• View: Parasternal long-axis.
• Location: Right ventricular free wall.
• Timing: End-systole (when epicardial fat is most compressed and clearly delineated).
• Technique: Measured perpendicularly to the aortic annulus.
• Averaging: Three consecutive cardiac cycles measured and mean value taken.
• Left Ventricular (LV) Function:
• Assessed by Simpson’s biplane method.
• Classified as normal LV function or LV dysfunction (mild, moderate, severe).
• Blinding: The echocardiographer was blinded to coronary angiography results to prevent observer bias.

Coronary Angiography (CAG)

• Approach: Performed by experienced interventional cardiologists using femoral or radial approach with Judkins technique.
• Definition of CAD: ≥50% luminal stenosis in a major epicardial artery.
• Classification: Patients categorized into:
• Normal CAG
• Single-Vessel Disease (SVD)
• Double-Vessel Disease (DVD)
• Triple-Vessel Disease (TVD)
• Severity Assessment:
• Severity quantified using the Modified Gensini Score, which assigns weights based on degree of luminal narrowing and importance of the vessel segment.
• This scoring provided a numerical index to correlate with EFT.

Ethical Considerations

• The study protocol was approved by the Institutional Ethics Committee (IEC) of Government Medical College, Kozhikode.
• Written informed consent was obtained from all participants prior to enrolment.
• Confidentiality and anonymity of patient data were ensured in accordance with ethical principles of biomedical research (Declaration of Helsinki).

Statistical Analysis

• Data were entered into Microsoft Excel and analyzed using SPSS software.
• Continuous variables: Expressed as mean ± standard deviation (SD).
• Categorical variables: Expressed as frequencies and percentages.
• Comparisons:
• Student’s t-test for continuous variables.
• Chi-square test for categorical variables.
• Correlation: Pearson correlation coefficient used to assess association between EFT and Gensini score.

Significance: p < 0.05 considered statistically significant.

Study Population Characteristics

A total of 151 patients undergoing coronary angiography for suspected coronary artery disease (CAD) were enrolled. Of these, 113 (74.8%) were male and 38 (25.2%) were female, reflecting the typical male preponderance observed in CAD cohorts. The mean age was 53.4 years, ranging from 27 to 72 years, highlighting that the disease frequently affected middle-aged individuals within the productive age group.

Distribution by Coronary Angiography Findings

• Normal CAG: 53 patients (35.1%)
• CAD confirmed: 97 patients (64.9%)

This indicates that nearly two-thirds of individuals clinically suspected to have CAD did indeed harbor angiographically significant disease.

Clinical and Echocardiographic Characteristics

Left Ventricular Function

• In the normal CAG group, 96.2% (51 patients) had preserved LV function, while only 2 (3.8%) showed dysfunction.
• Conversely, in the CAD group, only 36.7% (36 patients) had preserved LV function, whereas 59 patients (60.2%) demonstrated LV dysfunction.
• The difference between groups was highly significant (p = 0.001), underscoring the strong association of CAD with LV impairment.

ECG Abnormalities

ST-T changes were more common in patients with CAD compared to those with normal angiograms, consistent with ischemic substrate, though not all abnormalities were statistically distinct between groups.

Distribution of Cardiovascular Risk Factors

Diabetes Mellitus

The prevalence of diabetes was comparable between normal and CAD groups, with no significant difference.

Hypertension

Similar patterns were observed for hypertension, present in both subsets, reflecting the high background prevalence in Indian populations.

Smoking

The proportion of smokers did not differ significantly between CAD and non-CAD subgroups.

Body Mass Index (BMI)

Mean BMI did not vary significantly, again indicating that traditional anthropometric indices were not robust discriminators in this cohort.

Dyslipidemia

While diabetes, hypertension, smoking, and BMI were not significantly different, dyslipidemia showed a strong association with CAD.

• Patients with dyslipidemia had higher mean epicardial fat thickness (7.89 mm) compared to those with normal lipid profiles (6.22 mm).

Coronary Angiographic Profile

Among the 97 CAD patients, vessel involvement was as follows:

• Single-Vessel Disease (SVD): 51 patients (33.8%)
• Double-Vessel Disease (DVD): 28 patients (18.5%)
• Triple-Vessel Disease (TVD): 18 patients (11.9%)

This gradation demonstrates that one-third of CAD cases had relatively localized disease, while approximately one-third had multivessel involvement (DVD or TVD).

Gensini Score

• Normal CAG: Mean score 0
• CAD patients: Mean score 5.8 ± 4.6

This quantitative index confirmed that angiographic burden was significantly higher in the CAD cohort.

Epicardial Fat Thickness (EFT) Findings

Normal vs CAD Groups

• Normal CAG group: Mean EFT 3.2 ± 1.4 mm
• CAD group: Mean EFT 7.1 ± 1.5 mm
• The difference was highly significant (p < 0.001).

Correlation with Disease Extent

EFT values increased progressively with the severity of vessel involvement:

• Normal CAG: 3.2 mm
• SVD: 6.56 mm
• DVD: 7.56 mm
• TVD: 7.82 mm

This stepwise gradient (p < 0.001) demonstrates a dose–response relationship, confirming that EFT mirrors angiographic severity.

Dyslipidemia Subgroup

As noted earlier, patients with dyslipidemia exhibited significantly greater EFT (7.89 mm) compared with those with normal lipid profiles (6.22 mm). This emphasizes the metabolic underpinning of EAT expansion.

Comparative Analysis Between Groups

When comparing normal CAG vs CAD populations:

• LV function: Significantly impaired in CAD group.
• Risk factors: No significant differences for diabetes, hypertension, smoking, or BMI; only dyslipidemia showed a significant correlation with CAD burden.
• Gensini score: Higher in CAD group, as expected.
• EFT: Markedly higher in CAD group, with progressive increase from SVD → DVD → TVD.

Key Observations

1. EFT is significantly higher in CAD patients compared to those with normal angiograms.
2. EFT demonstrates a graded relationship with vessel involvement (SVD < DVD < TVD).
3. Dyslipidemia is associated with higher EFT, while diabetes, hypertension, smoking, and BMI were not significantly different between groups.
4. LV dysfunction is strongly associated with CAD, reflecting disease severity.
5. Gensini score correlates positively with EFT, supporting its validity as an imaging biomarker.

The baseline demographic characteristics of the study cohort (Table 1) revealed a mean age of 53.4 years, with the majority being males (74.8%). The age distribution was similar across normal CAG and CAD groups, indicating that age was not a major differentiator in this study population. This male preponderance is consistent with the well-recognized gender gap in CAD prevalence in South Asia【1】.

Cardiovascular risk factor distribution (Table 2) highlighted that diabetes, hypertension, smoking, and BMI were comparable between normal and CAD patients, showing no statistically significant differences. However, dyslipidemia was significantly more prevalent in CAD patients (45.4% vs. 22.6%, p = 0.01). This emphasizes that, in this cohort, abnormal lipid metabolism was the only conventional risk factor strongly associated with CAD burden. The importance of dyslipidemia was further underscored by its impact on EFT, as illustrated later.

Assessment of left ventricular (LV) function (Table 3) demonstrated a striking disparity. Among patients with normal CAG, 96.2% maintained preserved LV function, while only 36.7% of CAD patients showed preserved function. Conversely, 60.2% of CAD patients exhibited LV dysfunction, a difference that was highly significant (p < 0.001). This supports the close relationship between angiographic CAD burden and myocardial impairment. Figure 2 complements this observation through a stacked bar chart, clearly showing the dominance of LV dysfunction in CAD patients compared with the near-universal preservation of LV function in those with normal angiograms.

Epicardial fat thickness (EFT) emerged as the most important variable. Table 4 demonstrates that patients with normal CAG had a mean EFT of only 3.2 ± 1.4 mm, while patients with CAD had substantially thicker epicardial fat layers, with a progressive increase across single-vessel disease (6.56 mm), double-vessel disease (7.56 mm), and triple-vessel disease (7.82 mm). The differences were highly significant (p < 0.001). This dose–response gradient strongly supports the hypothesis that EFT is directly related to the extent of CAD. Figure 1 visually represents this trend, where the bar heights increase progressively across SVD, DVD, and TVD, with error bars indicating standard deviation. The pattern underscores the reproducibility and strength of the association.

Dyslipidemia and EFT were also strongly linked (Table 2, Table 4, Figure 3). Patients with dyslipidemia exhibited significantly greater mean EFT (7.89 mm) compared to patients with normal lipid profiles (6.22 mm). This finding highlights the metabolic underpinnings of epicardial adiposity, indicating that disordered lipid handling promotes expansion of this visceral fat depot. Figure 3 further illustrates this relationship, showing higher bar height for dyslipidemic patients compared with their normolipidemic counterparts.

Finally, Table 5 provides an integrated comparison of the most relevant variables between the two groups. CAD patients had significantly higher Gensini scores (5.8 ± 4.6 vs. 0, p < 0.05), higher EFT (7.1 ± 1.5 mm vs. 3.2 ± 1.4 mm, p < 0.001), and greater prevalence of LV dysfunction (60.2% vs. 3.8%, p < 0.001). Together, these findings consolidate the evidence that EFT is not only a surrogate of angiographic CAD presence but also of its severity and clinical consequences.

Table 1. Baseline Demographic Characteristics of the Study Population (n = 151)

SD: standard deviation; CAD: coronary artery disease; CAG: coronary angiography.

Table 2. Distribution of Cardiovascular Risk Factors

*BMI: body mass index. p < 0.05 significant.

Table 3. Left Ventricular Function in Normal vs CAD Groups

*LV: left ventricular; CAD: coronary artery disease. p < 0.05 significant.

Table 4. Epicardial Fat Thickness Across Coronary Disease Categories

*EFT: epicardial fat thickness; SVD: single-vessel disease; DVD: double-vessel disease; TVD: triple-vessel disease. p < 0.05 significant.

Table 5. Comparison of Key Variables Between Normal and CAD Patients

*CAD: coronary artery disease; EFT: epicardial fat thickness; LV: left ventricle. p < 0.05 significant.

This study demonstrated that epicardial fat thickness (EFT) measured by transthoracic echocardiography (TTE) was significantly higher in patients with coronary artery disease (CAD) compared to those with normal coronary angiography (CAG). The mean EFT in the CAD group was 7.1 ± 1.5 mm versus 3.2 ± 1.4 mm in patients with normal coronaries (p < 0.001). Furthermore, EFT showed a stepwise increase across single-, double-, and triple-vessel disease (SVD, DVD, TVD), supporting a dose–response relationship between epicardial adiposity and the extent of angiographic disease. Dyslipidemia was the only traditional risk factor significantly associated with increased EFT, while diabetes, hypertension, smoking, and BMI did not show significant differences. Left ventricular (LV) dysfunction was also more prevalent in CAD patients, reinforcing the link between epicardial adipose tissue (EAT) expansion and adverse myocardial remodeling.

These findings strongly support the hypothesis that EFT, as measured non-invasively by echocardiography, is a practical and reproducible marker of CAD burden in Indian patients.

Epicardial Adipose Tissue: Biological and Pathophysiological Insights

Epicardial adipose tissue (EAT) is not an inert fat depot but a metabolically active tissue with both protective and pathological roles. Under physiological conditions, EAT provides mechanical cushioning to coronary arteries and serves as a source of free fatty acids for myocardial metabolism【3】. It also secretes anti-inflammatory adipokines such as adiponectin【3】. However, in the context of obesity, dyslipidemia, and insulin resistance, EAT undergoes phenotypic switching, secreting pro-inflammatory cytokines such as interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α), as well as chemokines that facilitate macrophage infiltration【5】.

Mazurek et al. demonstrated that EAT from patients with CAD contains significantly higher concentrations of pro-inflammatory mediators than subcutaneous adipose tissue, supporting its role as a local inflammatory reservoir adjacent to coronary vessels【5】. Similarly, Hirata et al. found enhanced inflammatory activity in EAT biopsies of CAD patients compared to controls【13】. These findings provide a mechanistic explanation for the strong correlation between EFT and CAD severity observed in the present study.

EFT and Coronary Artery Disease Severity

The progressive increase in EFT across normal, SVD, DVD, and TVD patients in this study mirrors findings from previous research. Ahn et al. reported that EFT measured by echocardiography was significantly higher in patients with angiographically proven CAD compared to controls【7】. Eroglu et al. confirmed that EFT thickness correlated not only with CAD presence but also with its severity, as determined by Gensini score【14】.

Our study adds to this body of evidence by demonstrating a clear dose–response relationship: mean EFT rose from 6.56 mm in SVD to 7.56 mm in DVD and 7.82 mm in TVD, compared to 3.2 mm in patients with normal coronaries. Such a graded relationship is critical, as it suggests that EFT is not just a binary marker of disease presence but a quantitative biomarker of CAD burden.

The Gensini score in our study also correlated positively with EFT. Patients with CAD had a mean Gensini score of 5.8 ± 4.6 compared to 0 in the normal CAG group. These findings echo the work of Mahabadi et al., who reported that pericardial fat volume correlated with the burden of coronary calcification and CAD progression in the Framingham Heart Study【6】.

EFT and Traditional Cardiovascular Risk Factors

Interestingly, in our cohort, diabetes mellitus, hypertension, smoking, and BMI were not significantly different between CAD and non-CAD groups, while dyslipidemia showed a strong association with EFT. This suggests that epicardial fat may act as a more sensitive marker of metabolic dysfunction than conventional anthropometric indices.

Sharma et al. in an Indian population similarly found that EFT correlated with CAD severity independent of BMI【20】. This is particularly relevant in South Asians, who often develop CAD at lower BMI values compared to Western populations【1】. The limited utility of BMI in reflecting visceral adiposity is well established, and EFT may serve as a more precise risk indicator in this demographic【8】,【11】.

The significant association between dyslipidemia and higher EFT (7.89 mm vs. 6.22 mm in normolipidemic patients) in our study supports earlier observations. Wang et al. reported that increased EAT volume was strongly associated with coronary atherosclerosis in type 2 diabetes patients, reinforcing the link between disordered lipid metabolism and EAT expansion【15】.

Echocardiographic Measurement: Strengths and Limitations

EFT can be measured using various imaging modalities, including CT and MRI, both of which provide high-resolution volumetric assessments【19】. However, these techniques are expensive, less accessible, and expose patients to radiation (in the case of CT). By contrast, echocardiography is low-cost, radiation-free, and widely available. Iacobellis et al. first described echocardiographic EFT measurement in 2003 and reported a good correlation with MRI-based measures【3】. Subsequent studies have validated its reproducibility【4】.

In our study, EFT was measured in the parasternal long-axis view on the right ventricular free wall at end-systole, averaged over three cardiac cycles. This standardized protocol minimized interobserver variability. Nonetheless, echocardiographic measurement has limitations:

1. Operator dependence – requires technical expertise and consistent measurement sites【4】.
2. Two-dimensional limitation – echocardiography provides linear thickness rather than volumetric assessment【12】.
3. Variability in cut-offs – studies have reported thresholds ranging from 3 mm to 10 mm for predicting CAD【9】,【14】.

Despite these limitations, the practicality of echocardiography makes it the modality of choice in real-world clinical settings, especially in resource-limited environments such as India.

Comparison with Previous Studies

Our findings are consistent with multiple international and Indian studies:

• Ahn et al. (Korea): EFT significantly higher in CAD patients, independent of BMI【7】.
• Eroglu et al. (Turkey): EFT correlated with presence and severity of CAD, with thresholds around 7.6 mm【14】.
• Mahabadi et al. (Germany): Pericardial fat independently associated with coronary calcium progression【6】.
• Shetty et al. (India): Echocardiographic EFT correlated with angiographic CAD severity【8】.
• Sharma et al. (India): EFT as a practical marker of CAD severity in Indian patients【20】.

What distinguishes our study is its focus on an Indian tertiary care population, where CAD manifests at younger ages and with distinct risk profiles. By demonstrating that EFT correlates strongly with angiographic severity in this demographic, our findings underscore its value as a population-specific marker.

Clinical Implications

1. Risk Stratification
• EFT measurement can complement conventional risk scores (e.g., Framingham, ASCVD) by incorporating visceral adiposity assessment.
• Particularly useful in Indian patients, where BMI underestimates cardiometabolic risk.
2. Screening Tool
• As echocardiography is already widely used for LV function assessment, adding EFT measurement requires minimal additional effort.
• Routine EFT measurement could help identify high-risk individuals even before symptomatic CAD.
3. Target for Intervention
• Lifestyle modifications and pharmacotherapies (e.g., statins, GLP-1 agonists, SGLT2 inhibitors) have been shown to reduce visceral adiposity and may influence EAT volume【11】,【16】.
• Monitoring EFT could serve as a surrogate marker for therapeutic efficacy in cardiometabolic risk reduction.

Study Strengths

• Well-defined cohort: 151 consecutive patients undergoing CAG for suspected CAD.
• Blinded echocardiography: EFT measured without knowledge of angiographic results, minimizing observer bias.
• Robust endpoints: CAD severity quantified using modified Gensini score and vessel count.
• Clinical relevance: EFT measured with simple 2D echocardiography, a modality available even in district hospitals across India.

Limitations

• Cross-sectional design: Precludes causal inference; longitudinal studies are required to assess predictive value.
• Single-centre: Limits generalizability, though results align with international literature.
• No volumetric imaging: CT/MRI not used, so total EAT volume not assessed.
• Cut-off values not established: Our study confirms association but does not define a diagnostic threshold specific to Indian populations.

Future Directions

• Large, multicentric studies in diverse Indian populations to establish normative EFT ranges and diagnostic cut-offs.
• Longitudinal cohorts to evaluate EFT as a predictor of incident CAD events and long-term outcomes.
• Interventional studies testing whether reduction in EFT (via lifestyle, pharmacotherapy, or surgery) translates into improved cardiovascular outcomes.
• Integration into risk models: Combining EFT with conventional and novel biomarkers (e.g., hs-CRP, procalcitonin) may refine risk prediction.

This study confirms that echocardiographic epicardial fat thickness is significantly higher in patients with angiographically proven CAD and correlates positively with disease severity as quantified by vessel involvement and Gensini score. Among traditional risk factors, dyslipidemia showed the strongest association with increased EFT, underscoring the metabolic basis of epicardial adiposity.

EFT measurement is simple, inexpensive, and reproducible, making it a valuable adjunct in the early identification and risk stratification of CAD in resource-limited settings such as India. By incorporating EFT into routine echocardiography, clinicians can gain insights into both structural heart disease and underlying metabolic risk, bridging a critical gap in cardiovascular prevention and management.

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