Cardiovascular diseases remain the leading cause of mortality globally, with acute coronary syndrome (ACS) comprising a significant share of that burden (1). ACS includes a clinical spectrum ranging from unstable angina (UA) to non–ST-elevation myocardial infarction (NSTEMI) and ST-elevation myocardial infarction (STEMI). Among these, unstable angina is characterized by new-onset, rest, or worsening angina in the absence of detectable myocardial necrosis, typically indicated by normal cardiac troponin levels (2).

Despite the absence of biomarker evidence of infarction, patients with UA are at a high risk of progression to myocardial infarction (MI) or sudden cardiac death. This risk underscores the need for early, accurate-risk stratification to guide the urgency of intervention and intensity of therapy. However, current tools such as ECG, troponin levels, and risk scoring systems like GRACE and TIMI may not fully capture the dynamic risk profile of UA patients, especially in the early stages of presentation (3).

Inflammation has emerged as a critical factor in the pathophysiology of atherosclerosis and its acute complications. It contributes to plaque formation, destabilization, and eventual rupture, leading to thrombus formation and myocardial ischemia. Inflammatory mediators and immune cell activation are directly involved in the progression from stable atherosclerotic lesions to the unstable plaques that underlie ACS events (4). Therefore, systemic inflammation is not only a consequence but also a predictor of adverse cardiovascular outcomes, including MI (5).

Given the central role of inflammation, there is growing interest in identifying inflammatory biomarkers that are both clinically informative and easily obtainable. High-sensitivity C-reactive protein (hs-CRP) and interleukin-6 (IL-6) have shown prognostic value but are often costly or not routinely available (6). This highlights the need for accessible, inexpensive, and reliable markers of systemic inflammation that can aid in risk stratification in real-world settings.

The Systemic Inflammatory Response Index (SIRI) has emerged as a promising candidate. It is calculated using the formula (7):SIRI=Neutrophils×MonocytesLymphocytesThis composite index integrates pro-inflammatory cells (neutrophils and monocytes) with anti-inflammatory and regulatory lymphocytes, offering a broader picture of immune balance (8). Elevated SIRI reflects an intensified inflammatory state and has been associated with poor outcomes in various malignancies, infections, and increasingly, cardiovascular conditions.

However, the specific utility of SIRI in predicting myocardial infarction in patients presenting with unstable angina is still underexplored (9). Identifying such a relationship could have significant clinical value by improving early triage and tailoring treatment intensity for high-risk UA patients.

This study aims to evaluate the predictive role of SIRI in identifying patients with unstable angina who are at increased risk of myocardial infarction, potentially contributing to more effective, data-driven risk stratification in acute care settings.

In our study, patients with higher Systemic Inflammatory Response Index (SIRI) values (≥0.744) demonstrated a significantly more adverse clinical and angiographic profile compared to those with lower SIRI levels. These patients were older and had a higher prevalence of comorbidities such as hypertension and diabetes mellitus both of which are well-known contributors to systemic inflammation and accelerated atherosclerosis. This pattern is consistent with findings from Xei et al., who reported similar demographic and metabolic trends among ACS patients in the highest SIRI tertile, suggesting that SIRI reflects not only acute inflammatory burden but also underlying chronic cardiovascular risk exposure (10).

Laboratory results showed that patients in the high SIRI group had significantly elevated hs-cTnI levels (though all values remained below the 99th percentile URL), despite being classified as unstable angina at presentation. This supports the hypothesis that a higher SIRI may signal subclinical myocardial damage or increased vulnerability to plaque rupture. Liuize et al. similarly found that elevated SIRI was associated with troponin elevation and adverse short-term outcomes even in patients initially considered low-risk based on traditional markers (11).

From an angiographic standpoint, a significantly higher SYNTAX score and increased prevalence of multivessel coronary artery disease were observed in the high SIRI group. These findings suggest a direct correlation between systemic inflammation and coronary lesion complexity. De Azevedo and He et al. reported comparable outcomes in a large-scale ACS cohort, where high SIRI levels were independently associated with both angiographic severity and the need for more complex revascularization strategies (12, 13).

Additionally, the proportion of patients presenting with Killip Class ≥ II was notably higher among those with elevated SIRI, indicating more severe hemodynamic compromise. This mirrors observations from Avranas et al., who found that inflammatory indices such as SIRI correlated strongly with heart failure severity and clinical instability in ACS settings (14). These findings together reinforce the clinical utility of SIRI as a simple, yet robust, marker that mirrors both systemic inflammation and disease severity in patients with unstable angina.

Further stratification of patients based on SIRI levels provided additional insights into its predictive utility. In our study, the mean SIRI was 1.042 ± 0.40, and both threshold-based grouping (≥0.744) and tertile analysis demonstrated a clear stepwise relationship between SIRI and cardiovascular risk. Patients in the highest tertile (≥1.20) exhibited a nearly threefold increase in myocardial infarction risk, as well as significantly more severe angiographic disease and hemodynamic compromise. This dose–response pattern highlights SIRI's potential to serve not only as a binary marker but as a dynamic risk stratifier across the clinical spectrum of unstable angina.

These findings are in line with those of patients with higher SIRI tertiles had significantly worse outcomes, including increased MACE rates and higher inflammatory burden, in a multicenter ACS cohort. Similarly, a study by Cid-Alvarez et al. involving patients with non-ST elevation ACS demonstrated that elevated SIRI values were strongly correlated with both higher SYNTAX scores and more advanced Killip classification, underscoring the index's utility in capturing anatomical and clinical disease severity (15).

Notably, the progressive increase in adverse cardiovascular indicators across tertiles in our study supports the use of SIRI as a risk continuum, rather than relying solely on dichotomous cutoffs. This trend has been reported in oncology and infectious disease settings as well, where increasing SIRI values predicted worsened prognosis and systemic decompensation. Applying this tiered approach to cardiovascular medicine could enable more nuanced risk triage in emergency and inpatient settings, particularly for unstable angina where early decisions regarding intervention strategy are critical.

The discriminative power of SIRI in predicting myocardial infarction was further confirmed through ROC analysis (AUC = 0.858). To evaluate its incremental value, we compared SIRI with established inflammatory indices including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII). SIRI demonstrated superior predictive performance compared to NLR (AUC 0.79), PLR (AUC 0.75), and SII (AUC 0.81) in our cohort, suggesting its potential advantage in risk stratification. This level of diagnostic accuracy—combined with a sensitivity of 90% and specificity of 94% at the optimal cutoff of 0.744 suggests that SIRI may serve as a highly effective early marker for identifying unstable angina patients at high risk for imminent infarction. These findings are consistent with those reported by Hassanzad et al., who demonstrated similarly high AUC values (0.83–0.86) for SIRI in predicting short-term MACE in patients with acute coronary syndrome (16).

The utility of SIRI as a predictive tool is further strengthened by its correlation with markers of clinical severity and myocardial injury. Patients with higher SIRI levels in our study had significantly elevated troponin I concentrations, higher SYNTAX scores, and a greater proportion of Killip Class ≥ II—metrics that reflect both the biological intensity of myocardial stress and the anatomical complexity of coronary artery disease. These associations reinforce the multifactorial relevance of SIRI as more than a static inflammation marker, but rather a proxy for total cardiovascular burden. Supporting this, a large retrospective study by Karadeniz and Zhang et al. found that SIRI outperformed traditional inflammatory indices like neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in predicting early infarction and clinical deterioration in ACS patients (17, 18).

Importantly, the performance metrics observed in our study compare favorably with several existing risk stratification tools. When added to models containing TIMI risk score components, SIRI significantly improved the AUC from 0.76 to 0.83 (p for comparison = 0.02), demonstrating meaningful incremental prognostic value beyond established clinical predictors. While tools like the HEART and TIMI scores offer useful frameworks, their reliance on subjective clinical judgment and delayed biomarker kinetics limits their predictive sharpness in early-stage unstable angina. The immediate availability of CBC parameters and the straightforward calculation of SIRI present a compelling case for its integration into early triage protocols, particularly when rapid decision-making is essential.

The prognostic implications of SIRI were further supported by its strong association with both short-term and long-term adverse cardiovascular outcomes. In our study, patients in the highest SIRI tertile (≥1.20) experienced significantly greater incidences of myocardial infarction and major adverse cardiovascular events (MACE) within 30 days compared to those in the lowest tertile. This dose-dependent relationship reinforces the value of SIRI as a stratification tool capable of capturing dynamic cardiovascular risk. These findings are consistent with those of Yang et al., who demonstrated a parallel increase in MACE across SIRI quartiles in a large acute coronary syndrome cohort, with the highest quartile predicting over twice the event rate of the lowest (19).

Importantly, multivariable logistic regression confirmed SIRI as an independent predictor of MACE, even after adjusting for established clinical predictors such as age, comorbidities, Killip class, and SYNTAX score. Patients with SIRI values between 1.72 and 3.68 had over twice the odds of experiencing adverse events, highlighting its utility in risk modeling. Similar adjusted associations have been reported by Gao et al., who found that SIRI remained independently linked with in-hospital cardiovascular complications in ACS patients despite accounting for troponin levels, left ventricular function, and angiographic severity (20).

This study has several limitations that should be acknowledged. First, its retrospective and single-center design may introduce selection bias and limit the generalizability of the findings. Although the sample size of 129 patients provided sufficient statistical power (power > 0.80) for the primary outcomes as confirmed by post-hoc analysis, the moderate sample size restricted the power of subgroup analyses and increased the risk of type II errors, particularly for evaluating potential effect modifications by variables such as age, sex, or comorbidities. Second, although we adjusted for key clinical confounders, unmeasured variables such as renal function and medication use (e.g., statins or antiplatelets) may have influenced the results. Third, while internal validation using bootstrapping supported the model's robustness, external validation in larger, multicenter prospective cohorts is needed to confirm these findings. Finally, although hs-CRP data were collected, its inconsistent measurement in our retrospective cohort prevented meaningful correlation analysis with SIRI. The relationship between SIRI and other established inflammatory markers like hs-CRP warrants further investigation in prospective studies with standardized protocols. Despite these limitations, our findings highlight the potential utility of SIRI as a prognostic marker in UA and underscore the need for future large-scale, multicenter studies to validate these results and facilitate more robust subgroup analyses.

It is noteworthy that despite the observed correlations between SIRI and established markers such as troponin I and SYNTAX score—both indicative of disease severity—multivariable logistic regression analysis confirmed that SIRI remained an independent predictor of myocardial infarction and MACE even after adjusting for these and other clinical confounders (including age, hypertension, diabetes, Killip class, and SYNTAX score). This suggests that SIRI provides prognostic information beyond what is captured by traditional clinical and angiographic assessments alone. Its value lies not only in reflecting the inflammatory component of atherosclerosis but also in offering incremental risk stratification capability, potentially enhancing early decision-making in unstable angina patients whose troponin levels remain within the normal range.

Moreover, our study found that elevated SIRI at admission predicted adverse outcomes up to three years post-presentation. The prognostic stability of SIRI was supported by its consistent predictive value across different timepoints during hospitalization (measured at admission, 24 h, and 48 h; intraclass correlation coefficient = 0.87, p < 0.001), indicating relative stability despite potential fluctuations in individual cellular components. This extended predictive power has been echoed in geriatric and diabetic subpopulations, where high SIRI levels were associated with persistent vascular inflammation, plaque instability, and repeat ischemic events well beyond hospital discharge. Collectively, these results highlight the novel contribution of our study: demonstrating that SIRI provides independent and incremental prognostic information beyond established clinical and angiographic markers in unstable angina. Unlike previous studies focusing primarily on ACS populations including MI patients, our research specifically validates SIRI's utility in true unstable angina patients without myocardial necrosis. This distinction is clinically important as it supports SIRI's role in early triage decisions when troponin levels remain negative.

This study demonstrates that the Systemic Inflammatory Response Index (SIRI), a simple and readily available marker derived from routine blood counts, has significant prognostic value in patients presenting with unstable angina. Elevated SIRI levels were independently associated with a higher risk of myocardial infarction and major adverse cardiovascular events (MACE), and correlated strongly with established indicators of clinical and anatomical severity, including higher baseline hs-cTnI levels (within the normal range), multivessel disease, and higher SYNTAX scores. With an excellent predictive performance (AUC = 0.858) and strong sensitivity and specificity, SIRI proves to be an effective tool for early risk stratification. Its application may support timely clinical decision-making, allowing for earlier identification of high-risk patients who may benefit from more aggressive monitoring and intervention. Given its cost-effectiveness and accessibility, SIRI has the potential to be integrated into routine clinical workflows to improve outcomes in patients with unstable angina. Further prospective and multicenter studies are warranted to validate these findings and explore its utility across broader clinical settings and long-term follow-up.