Evaluation of systemic inflammation markers in predicting cardiac risk in patients with acute chest pain

Abstract

Objectives: This study aimed to evaluate systemic inflammation markers in predicting cardiac risk in patients with acute chest pain (ACP), in this way identifying cases with acute coronary syndrome (ACS) in admission to the hospital. In addition, the relationship between these markers and the HEART score was investigated. Methods: By evaluating the laboratory/clinical data, patients with ACP (n=308) aged 18–70 were included in the study. As a result of clinical follow-up, patients were categorized into two groups: those diagnosed with ACS and those with non-ACS. Low-risk, moderate-risk, and high-risk patient groups were formed using the HEART score. From the routinely studied hemogram data, systemic immune inflammation index, systemic inflammation response index (SIRI), neutrophilto- lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio, and platelet-to-lymphocyte ratio (PLR) were calculated. Results: In determining the high-risk group, the highest area under the curve (AUC) was observed as 0.862 (95% confidence interval [CI]=0.818-0.898) at a cutoff value of 2.9 (69.3% sensitivity and 90.3% specificity) for NLR. For SIRI at a cutoff value of 2.0, the AUC value was found as 0.855 (95% CI=0.811 to 0.893), having 72.6% sensitivity and 85.2% specificity. The strongest association was between the HEART score and SIRI (r=0.612; p<0.001). Comparing patients without ACS and patients with ACS, there was no difference in lymphocyte counts, platelet counts, and PLR. In the ROC analysis for ACS, the SIRI performed that the highest AUC value was 0.858 (95% CI= 0.814 to 0.895), presenting 77.3% sensitivity and 79.5% specificity at a cutoff value of 1.19. Conclusion: When pre-pandemic data were evaluated, higher NLR or SIRI might help risk stratification for individuals with ACP, and it could be recommended for clinical benefit in the emergency department. SIRI, which includes the number of monocytes, may be helpful as a novel index in identifying individuals with ACS.