Correlation of Glycemic Status with Angiographic Severity of Coronary Artery Disease in Acute Coronary Syndrome.

BACKGROUND

Cardiovascular disease (CVD) remains the leading cause of illness and death worldwide, placing a significant strain on healthcare systems. Its development is influenced by multiple factors, with major risk contributors including hypertension, dyslipidemia, diabetes mellitus (DM), and lifestyle-related behaviors. Among these, DM notably increases the risk of coronary artery disease (CAD), particularly acute coronary syndrome (ACS). Chronic hyperglycemia in DM accelerates atherosclerosis, thereby heightening the risk of vascular complications. Given the intricate relationship between diabetes and CVD, assessing the influence of glycemic status on CAD severity is essential. This study aims to evaluate the severity of CAD in diabetic, prediabetic, and nondiabetic patients presenting with ACS using the Gensini score, a validated angiographic tool for measuring disease severity.

AIM

To assess the severity of CAD in patients with ACS using the Gensini score, comparing disease severity among prediabetic, diabetic, and nondiabetic individuals.

MATERIALS AND METHODS

A 6-month hospital-based cross-sectional study was conducted at a tertiary care center from July to December 2023, involving 150 patients diagnosed with ACS who underwent coronary angiography (CAG). Data collection was carried out retrospectively (July to September 2023) from inpatient records and prospectively (October to December 2023) from patients meeting the inclusion criteria. Clinical parameters, including patient history, comorbid conditions, cardiac biomarkers, HbA1c levels, electrocardiography (ECG), echocardiography (ECHO), and angiographic findings, were analyzed. The severity of CAD was assessed using the Gensini score.

STATISTICAL ANALYSIS

Data were analyzed using Statistical Package for the Social Sciences (SPSS) version 22. Categorical variables were expressed as frequencies and percentages, with statistical significance determined using the Chi-square or Fisher's exact test. Continuous variables were represented as mean ± standard deviation (SD) and compared using analysis of variance (ANOVA). Pearson's correlation was employed to examine associations between variables. Multivariate regression analysis was conducted to identify predictors of CAD severity (based on the Gensini score), adjusting for potential confounders such as diabetes duration (HbA1c ≥6.5%), age, and other cardiovascular risk factors. A -value of <0.05 was considered statistically significant. Graphs were generated using Microsoft Excel and Word.

RESULTS

The study analyzed 150 patients with ACS who underwent CAG, comprising 114 diabetic, 20 prediabetic, and 16 nondiabetic individuals. A male predominance was observed, with 100 male participants. Diabetic patients exhibited the highest severity of CAD, with a mean Gensini score of 49.08 ± 39.67, followed by prediabetic patients with a mean score of 24.48 ± 41.42. Nondiabetic patients had the least severe CAD, with a mean Gensini score of 0.94 ± 2.56. Additionally, triple-vessel disease was more prevalent among diabetic individuals. A significant positive correlation was observed between diabetes duration and CAD severity, indicating that prolonged diabetes exposure is associated with more extensive coronary artery involvement.

CONCLUSION

This study confirms that diabetes significantly exacerbates the severity of CAD, with diabetic patients exhibiting more severe CAD than prediabetic and nondiabetic individuals. Additionally, the findings demonstrate a direct correlation between diabetes duration and increased CAD severity. The results emphasize the heightened risk of triple-vessel disease in diabetic patients, underscoring the necessity for targeted cardiovascular and diabetes management strategies to mitigate disease progression and improve patient outcomes.