European Journal of Cardiovascular Medicine

Coronary artery disease (CAD), which is the leading cause of cardiovascular mortality globally, accounts for more than 7 million deaths and 129 million disability adjusted life years (DALY), every year in the developing countries. CAD is an important cause of mortality and DALYs (1). Ischemic heart disease is the leading cause of death in India (2). More than half a billion people were affected due to CAD and cardiovascular deaths account for 20.5 million deaths globally in 2021. Around 4 in every 5 cardiovascular deaths occur in low and middle-income countries. About 80% of the premature heart attacks and strokes are preventable (3).

Combination of multiple factors including socio-economic status, metabolic factors, behavioral factors, and environmental risk factors can lead to development of cardiovascular diseases (CVDs). They can include uncontrolled blood pressure, poor diet, high cholesterol, uncontrolled diabetes, air pollution, increased BMI, smoking, use of tobacco & alcohol, physical inactivity, stress and kidney diseases. There are various measures taken to reduce the incidence of CVDs globally, however, the rate of decline is considered as insufficient (3). Risk stratification in acute coronary syndromes aims to identify the individuals with high risk of recurrent ischemic events who might benefit prognostically from further investigation and treatment (4). The global registry of acute coronary events (GRACE) and the can rapid risk stratification of unstable angina patients suppress adverse outcomes with early implementation of the American college of Cardiology/ American Heart Association guidelines (CRUSADE) scores are among the most frequently used risk assessment tools (5)

Current American and European clinical guidelines suggest the use of a GRACE risk score as a predictor of major adverse events in these patients. GRACE risk score was developed for patients presenting with ACS as a clinical risk prediction tool for estimating the cumulative 6‐ month risk of death and death or myocardial infarction to facilitate triage and management of patients with ACS (6, 7).

The GRACE Risk Score involves 8 variables from history, exam, EKG and laboratory testing. This includes age, heart rate / pulse, development (or history) of heart failure, systolic blood pressure, Killip class, initial serum creatinine concentration, elevated initial cardiac enzymes, cardiac arrest on admission, and ST segment deviation (8). The Synergy Between Percutaneous Coronary Intervention (SYNTAX) score, a comprehensive angiographic grading tool that takes into account anatomic risk factors, is the best-known scoring system to assess the extent of CAD (9). Based on the complexity of CAD, this score is capable of objectively guiding decision-making between coronary artery bypass grafting (CABG) surgery and percutaneous coronary intervention (PCI) (10). The SYNTAX score relies on invasive coronary angiography (CA) findings to calculate the coronary anatomic complexity. Consequently, noninvasively estimating the complexity of CAD prior to CA could change the prognostic plan, the timing, and the intensity of intervention, and possibly integrate a multidisciplinary approach by both interventional cardiologists and cardiac surgeons in patients with severe CAD. To date, several studies have investigated the correlation between risk-stratification scoring systems and the severity of CAD (11).

Source of Data

This study was conducted in the Cardiology Department of Jawaharlal Nehru Medical College, KAHER, Belagavi, from January 2023 to June 2024.

Study Design

A prospective observational study design was employed.

Sample Size and Sampling Method

A total of 249 patients were included in the study. Participants were selected using a simple random sampling method.

Inclusion Criteria

The study included:

• Patients aged >18 years admitted to the Cardiology Department with acute coronary syndrome (ACS).
• ACS cases diagnosed based on the fourth universal definition of acute myocardial infarction.

Exclusion Criteria

The study excluded patients with:

• A history of prior ischemic heart disease (IHD).
• Previous coronary revascularization procedures, including coronary stenting or coronary artery bypass grafting (CABG).
• Significant valvular heart disease.
• Myocarditis.
• Patients unwilling to undergo coronary angiography.

Study Protocol

• Patients meeting the inclusion and exclusion criteria and consenting to participate were enrolled in the study.
• Informed consent was obtained from all participants.
• A detailed medical history was recorded using a pre-designed proforma.
• GRACE Risk Score was calculated using www.mdcalc.com and www.qxmd.com
• The SYNTAX score was calculated for each participant as per the definitions provided on www.syntaxscore.org.

Investigations

The following investigations were performed:

1. Serum Creatinine: Analyzed using Roche/Hitachi cobas c systems with automatic calculation of analyte concentrations.
2. Troponin I: Measured using the Electrochemiluminescence Immunoassay (ECLIA) on cobas e Immunoassay analyzers.
3. 12-Lead ECG: Conducted with the Nihon Kohden Cardiofax M machine.
4. Echocardiography: Performed using the Philips CS 50 portable echocardiography machine.
5. Coronary Angiography: Executed using Philips Azurion 5 and Azurion 3 CT machines with Philips QCA analysis capability.

Data Collection Procedure

Data were collected using a pre-designed, pre-validated standard research tool. The collected data were cleaned and stored in Microsoft Excel for analysis.

Statistical Analysis

Descriptive statistics, including mean, median, frequency, and percentage, were performed. Graphical representations, such as bar diagrams, histograms, and pie charts, were generated. Statistical analyses were conducted using IBM SPSS Statistics version 27.

• For continuous and normally distributed data, parametric tests such as the t-test, z-test, and F-test were applied.
• For categorical and non-normally distributed data, non-parametric tests, including the chi-square test, Mann-Whitney U test, Kruskal-Wallis test, and Wilcoxon signed rank test, were utilized.
• A p-value of <0.05 was considered statistically significant.

Age and Gender

A total of 249 study participants were included in the study. Mean age of the study participants was 60.02 ± 10.99 years. Majority of the study participants were between the age group of 45-65 years (n=144, 57.8%).

Table 1: Distribution of age among study participants

GENDER

Majority of the study participants were male (n=171, 68.7%). Distribution of gender among  the study participants is shown in the Table2.

Table 2: Distribution of gender among study participants

Body Mass Index (BMI)

The mean body mass index of the study participants was 25.27 ± 3.22. Majority of the study participants had normal BMI (n=121, 48.6%). Distribution of BMI among the study participants is shown in Table 3 Table 3: Distribution of BMI among study participants

Comorbidities

Prevalence of hypertension and diabetes among the study participants were 61% and 54.6% respectively. Prevalence of chronic obstructive pulmonary disease (COPD) and chronic kidney disease (CKD) among the study participants were 11.2% and 2.4% respectively (Table 4).

Table 4: Prevalence of comorbidities among study participants

Personal habits

Smoking, alcohol and consumption of tobacco were reported in 16.9%, 21.7% and 24.5% of the study participants respectively (Table 5).

Table 5: Prevalence of personal habits among study participants

Vitals – Heart rate and blood pressure

The mean heart rate of the study participants was 86.47 ± 18.47. The mean systolic and diastolic blood pressure of the study participants were 131.44 ± 23.60 and 80.84 ± 12.52 respectively (Table 6).

Table 6: Mean values of vitals among study participants

Killip Class

Among the study participants, 77.1% were classified as Killip Class I, 16.1% were classified as Killip Class II and 4.4% were classified as Killip Class III and 2.4% were classified as Killip Class IV respectively

Table 7: Classification of Killip Class among study participants

Diagnosis

Anterior wall myocardial infarction (AWMI), inferior wall myocardial infarction (IWMI) and posterior wall myocardial infarction (PWMI) were diagnosed in 27.7%, 17.3% and 4% of the study participants respectively. Non-ST elevation myocardial infarction was diagnosed among 31.3% of the study participants. Unstable angina was diagnosed in 19.7% of the study participants.

Symptoms

Majority of the study participants had angina (n=228, 91.6%), followed by dyspnea (n=146, 57%), angina equivalents (n=12, 4.8%), syncope (n=6, 2.4%) and palpitations (n=2, 0.8%).

Coronary Angiogram

In coronary angiogram, majority of the study participants had triple vessel disease (TVD) (n=91, 36.6%). Among study participants, double vessel disease (DVD) and double vessel disease with left main disease were reported in 30.1% and 1.6% respectively. Single vessel disease (SVD) and single vessel disease with left main disease were found in 22.1% and 0.4% respectively. Triple vessel disease (TVD) with left main disease was reported in 9.2% of the study participants  

Graph 2: Report of coronary angiogram among study participants

Troponin I

Troponin I was positive in 64.7% (n=161) of the study participants and negative in 35.3% (n=88) of the study participants

SYNTAX I Score

Majority of the SYNTAX I score of the study participants were less than 23 (n=158, 63.5%). SYNTAX I Score between 23-32 group and more than 32 groups were 24.1% and 12.4% respectively.

Table No.6 Comparison of study variables with SYNTAX I Score

Graph 3: Boxplot of SYNTAX I Score among GRACE Risk score categories

Graph 4: Correlation of GRACE Risk score and SYNTAX I Score among study participants

Table 7: Comparison of coronary angiogram results and SYNTAX I Score

Sensitivity and Specificity

By ROC analysis, GRACE score predicted SYNTAX Score ≥32 with an area under ROC of 0.696 (p=0.001)

Comparison of SYNTAX SCORE II FOR PCI Vs GRACE RISK SCORE

SYNTAX II score for PCI and grace risk score were compared and Tabulated. A positive correlation was observed between GRACE score and SYNTAX score.

Table 8: Comparison of SYNTAX II Score for PCI and GRACE Risk score among study participants

Graph 5: Correlation of GRACE Risk score and SYNTAX II Score for PCI

SYNTAX SCORE II CABG Vs GRACE RISK SCORE

SYNTAX II score for CABG and grace risk score were compared and Tabulated. A positive correlation was observed between GRACE score and SYNTAX score (Table 18 and Graph 18).

Table 9: Comparison of GRACE Risk score and SYNTAX II Score for CABG among study participants

Graph 6: Correlation of GRACE Risk score and SYNTAX II Score for CABG

In our study, the study participants with Low, intermediate and high GRACE RISK scores were 57%, 28.5% and 14.5% respectively. Majority of the SYNTAX score of the study participants were less than 23 (n=158,  63.5%). Mean GRACE RISK score in SYNTAX <23, SYNTAX 23-32 and SYNTAX>32 groups were 100.15 ± 24.88, 114.41 ± 28.03 and 125.67 ± 28.84 respectively. In ROC analysis, GRACE score predicted SYNTAX Score more than 23 with an area under ROC of 0.696 (p=0.001).

SYNTAX score was significantly associated with age category, Killip class, LVEF, coronary angiogram results, GRACE Risk score, and tobacco use. SYNTAX Score had a positive correlation with GRACE RISK score in our study. The significance between age and SYNTAX score suggests that older individuals have higher risk of development of coronary artery disease. Higher Killip Class is associated with severity of coronary artery disease, indicating advanced   disease. Lower the LVEF value, the lower the cardiac output, which indicates the severe and complex coronary artery disease. Significance with coronary angiography results in our study suggests the presence of multi-vessel disease, which indicates the severity of angiographic findings and the disease. Significance of SYNTAX I and GRACE risk score suggests the high risk of outcome including the mortality, during or after the acute coronary syndrome. The association of tobacco use and higher SYNTAX score shows more risk of severe coronary artery disease.

The findings of this study align with previously established research highlighting the significance of risk stratification and clinical decision-making in acute coronary syndromes (ACS). The GRACE (Global Registry of Acute Coronary Events) and SYNTAX (Synergy Between PCI With Taxus and Cardiac Surgery) scores remain pivotal tools for guiding management and predicting outcomes in patients with ACS, particularly in those undergoing revascularization.

The inclusion of SYNTAX II in decision-making processes has further advanced the clinical application by incorporating patient-specific factors like age, comorbidities, and left ventricular function. SYNTAX II significantly improves the determination of appropriate revascularization strategies. This combined approach enables individualized management, ensuring that high-risk patients receive optimal care while minimizing procedural risks.

This discussion reinforces the value of multidimensional risk assessment in contemporary cardiology practice. Future research should explore integrating artificial intelligence and machine learning to enhance predictive accuracy and clinical utility of scoring systems in diverse populations.

In conclusion, this study demonstrates the valuable role of both the GRACE and SYNTAX scores in assessing risk in acute coronary syndrome (ACS) patients. The combined use of these scores offers a more comprehensive evaluation of patient prognosis, guiding clinical decisions on treatment strategies. While further research is needed to refine their application, these tools can help identify high-risk patients and improve outcomes through tailored interventions.

1. Vedanthan, R., Seligman, B., & Fuster, V. "Global Perspective on Acute Coronary Syndrome." Circulation Research, vol. 114, no. 12, 2014, pp. 1959–1975. doi:10.1161/CIRCRESAHA.114.302782.
2. World Health Organization (WHO). "India Data | World Health Organization." who.int, 2023. Available from: https://data.who.int/countries/356.
3. World Heart Federation. "World Heart Report 2023: Full Report." World Heart Federation, 2023. Available from: https://world-heart-federation.org/resource/world-heart-report-2023/.
4. Timmis, A. "Coronary Disease: Acute Coronary Syndromes: Risk Stratification." Heart, vol. 83, no. 2, 2000, pp. 241–246. doi:10.1136/hrt.83.2.241.
5. Tscherny, K., Kienbacher, C., Fuhrmann, V., van Tulder, R., Schreiber, W., Herkner, H., et al. "Risk Stratification in Acute Coronary Syndrome: Evaluation of the GRACE and CRUSADE Scores in the Setting of a Tertiary Care Centre." International Journal of Clinical Practice, vol. 74, no. 2, 2020, doi:10.1111/ijcp.13406. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7027537/.
6. Ibanez, B., James, S., Agewall, S., Antunes, M. J., Bucciarelli-Ducci, C., Bueno, H., et al. "2017 ESC Guidelines for the Management of Acute Myocardial Infarction in Patients Presenting with ST-Segment Elevation." European Heart Journal, vol. 39, no. 2, 2017, pp. 119–177. doi:10.1093/eurheartj/ehx393.
7. O’Gara, P. T., Kushner, F. G., Ascheim, D. D., Casey, D. E., Chung, M. K., de Lemos, J. A., et al. "2013 ACCF/AHA Guideline for the Management of ST-Elevation Myocardial Infarction: a Report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines." Circulation, vol. 127, no. 4, 2013, pp. e362-425. doi:10.1161/CIR.0b013e3182742cf6. Available from: https://www.ncbi.nlm.nih.gov/pubmed/23247304
8. Yao, Y., Shao, C., Li, X., Wang, Z., Zuo, C., Yan, Y., et al. "A Novel Biomarker Scoring System Alone or in Combination with the GRACE Score for the Prognostic Assessment in Non-ST-Elevation Myocardial Infarction." Clinical Epidemiology, vol. 14, 2022, pp. 911–923. doi:10.2147/CLEP.S365487. Available from: https://www.dovepress.com/a-novel-biomarker-scoring-system-alone-or-in-combination-with-the-grac-peer-reviewed-fulltext-article-CLEP.
9. Sianos, G., Morel, M. A., Kappetein, A. P., Morice, M. C., Colombo, A., Dawkins, K. D., et al. "The SYNTAX Score: an Angiographic Tool Grading the Complexity of Coronary Artery Disease." EuroIntervention, 2005. Available from: https://eurointervention.pcronline.com/article/the-syntax-score-an-angiographic-tool-grading-the-complexity-of-coronary-artery-disease.
10. Serruys, P. W., Morice, M. C., Kappetein, A. P., Colombo, A., Holmes, D. R., Mack, M. J., et al. "Percutaneous Coronary Intervention versus Coronary-Artery Bypass Grafting for Severe Coronary Artery Disease." New England Journal of Medicine, vol. 360, no. 10, 2009, pp. 961–972. doi:10.1056/NEJMoa0804626.
11. Isilak, Z., Kardesoglu, E., Aparci, M., Uz, O., Yalcin, M., Yiginer, O., et al. "Comparison of Clinical Risk Assessment Systems in Predicting Three-Vessel Coronary Artery Disease and Angiographic Culprit Lesion in Patients with Non-ST Segment Elevated Myocardial Infarction/Unstable Angina Pectoris." Kardiologia Polska, vol. 70, no. 3, 2012, pp. 242–250. doi:10.5603/KP.2012.0034. Available from: https://pubmed.ncbi.nlm.nih.gov/22430403/.