RESUMEN
Introduction Acute coronary syndromes (ACS), encompassing non-ST elevation myocardial infarction (NSTEMI) and unstable angina (UA), present significant challenges in risk assessment and management, particularly in resource-constrained environments like India. The burden of cardiovascular diseases in such regions necessitates cost-effective and readily accessible tools for risk stratification. Previous research has emphasized the role of inflammatory markers in coronary artery disease (CAD), prompting investigations into simple and affordable biomarkers for risk assessment. Platelet lymphocyte ratio (PLR) and neutrophil lymphocyte ratio (NLR) have emerged as potential biomarkers for thrombotic activity in cardiac illnesses, offering simplicity, accessibility, and cost-effectiveness in risk assessment making them particularly valuable in resource-poor settings like India, where advanced diagnostic tools may be limited. Objective This study aims to evaluate the effectiveness of PLR and NLR as predictors of high-risk HEART (history, ECG, age, risk factors, and troponin) scores in patients with NSTEMI and UA. Methods A prospective cross-sectional study was conducted at the Saveetha Medical College and Hospitals in Chennai, India, from March 2021 to September 2022. The study included 288 adults diagnosed with NSTEMI or UA, aged 18 years and above. The inclusion criteria comprised patients with confirmed diagnoses of NSTEMI or UA based on clinical symptoms, electrocardiographic findings, and cardiac biomarker elevation. The exclusion criteria encompassed patients with active infections, acute traumatic injuries, end-stage renal disease, malignant neoplasms, and ST-elevation myocardial infarction (STEMI). In addition to the HEART score, PLR, and NLR were computed to assess the prognosis of patients admitted to the Saveetha Medical College and Hospitals. Results The statistical analysis revealed significant correlations between PLR, NLR, and HEART score risk categories. The Pearson's correlation coefficient indicated strong associations between PLR/NLR values and HEART score risk groups, suggesting their potential as predictive markers for adverse clinical outcomes. Additionally, analysis of variance (ANOVA) demonstrated significant differences in PLR/NLR values across different HEART score risk categories, further highlighting their relevance in risk stratification. The effect sizes for these correlations were moderate to large, indicating clinically meaningful associations between PLR/NLR and cardiovascular risk. Conclusion In cases of NSTEMI and UA, PLR and NLR show potential as simple and inexpensive indicators of high-risk patients. By leveraging these inexpensive biomarkers, healthcare providers can enhance risk assessment and prognostication in patients presenting with ACS, facilitating timely interventions and tailored management strategies.