This study is a single-center cohort study among patients diagnosed with STEMI who were treated by PCI in Beijing Anzhen Hospital between January 2019 to December 2021. Patients who met all the following criteria were included in the study: (1) age $>$18 years old; (2) diagnosed with STEMI according to 2017 ESC guidelines for the management of STEMI [12]; (3) underwent drug-eluting stent (DES) planting after diagnosis. Those who met any of the following criteria were excluded: (1) history of coronary artery bypass grafting; (2) neutrophil data missing; (3) lymphocyte data missing; (4) monocyte data missing; (5) malignant tumor affecting survival; (6) procedure failure of PCI; (7) patients with cardiogenic shock or cardiac arrest before PCI. Finally, 1312 patients were included in the analysis. Informed consent was obtained from every participant in our study.

The following data were recorded in this study: demographics (age, sex), smoking status, weight, vital signs (heart rate, systolic blood pressure), left ventricular ejection fraction (LVEF), laboratory parameters (white blood cell, neutrophil, lymphocyte, monocyte, hemoglobin, platelet, creatinine, blood nitrogen urea, alanine aminotransferase (ALT), aspartate aminotransferase (AST), sodium, potassium, triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), high sensitive C reactive protein (hs-CRP)), medication use (aspirin, clopidogrel, ticagrelor, beta-blockers, angiotensin-converting enzyme inhibitor (ACEI), angiotensin receptor blocker (ARB), statins), comorbidities and medical history (hypertension, diabetes, cerebrovascular disease, pneumonia, autoimmune disease), life support equipment (extracorporeal membrane oxygenation (ECOM), Impella, intra-aortic balloon pump (IABP), mechanical ventilation), Killip classification, coronary angiography results (Culprit vessel (left anterior descending artery (LAD); left circumflex artery (LCX); right coronary artery (RCA); left main coronary artery (LM)), number of stents), thrombolysis in myocardial infarction (TIMI) grades. Coronary angiographic data were analyzed and evaluated by optical measurements, and results were recorded and validated by at least two experienced cardiologists.

Systemic inflammation response index (SIRI) was defined as neutrophils $\times$ monocytes/lymphocytes [9]. All the serological results were obtained from the first blood test report after admission before PCI. According to the SIRI quartiles, all enrolled patients were divided into four groups. The primary outcome was a composite outcome of a 30-day major adverse cardiovascular event (MACE), which included all-cause mortality, non-fatal myocardial infarction (MI), stroke, incident heart failure (HF), cardiogenic shock, and cardiac arrest.

Normally distributed continuous variables were expressed as mean $\pm$ standard deviation (SD) and compared between groups using analysis of variance. Skewed data were expressed as median (interquartile range (IQR)) and compared using the Kruskal-Wallis test. Categorical variables were expressed as numbers (percentages) and compared between groups using the Chi-square test.

Multiple logistic regression analysis was used to analyze the relationship between SIRI and 30-day MACE after adjustment for covariates. And the results were expressed as odds ratio (OR) and 95% confidence interval (CI). p for trend was calculated. The covariates with p 0.05 in the univariate logistic regression analysis were included in the multivariate logistic regression model. Further, univariate logistic regression analysis was used to explore the relationship between SIRI and 30-day MACE in different inflammatory statuses: status 1: Patients without pneumonia and autoimmune disease; status 2: Patients with WBC (white blood cell) $\ge$10 $\times$ 10${}^9$/L or 4 $\times$ 10${}^9$/L and hs-CRP $\ge$20 mg/L; status 3: Patients with 4 $\times$ 10${}^9$/L WBC $\le$10 $\times$ 10${}^9$/L and hs-CRP 20 mg/L.

Subgroup analysis was used to determine the relationship between SIRI as a continuous variable and 30-day MACE in different subgroups, and p for interaction was calculated. The median was considered as the cut-off value in the continuous variable of the subgroup in order to avoid the situation of too few people in a certain subgroup. Univariate logistic analysis was used in subgroup analysis to calculate OR values. In addition, according to the multivariate logistic regression model, we drew the restricted cubic spline (RCS) curve to investigate the association between SIRI as a continuous scale and 30-day MACE. Three knots were chosen for the analysis. Receiver operating characteristic (ROC) analysis was applied to assess the ability of SIRI, NLR, and hs-CRP in predicting the incidence of 30-day MACE. Differences between the area under the ROC curve (AUC) of them were compared using the DeLong test.

All tests were two-sided, and p 0.05 was considered statistically significant. Relevant guidelines and regulations are carried out for all methods. All data analyses were performed by Stata V.15.1 (Statistical Analysis System, Raleigh, NC, USA).

A total of 1312 STEMI patients who received PCI treatment were included in the study. All the participants were stratified into four groups according to SIRI quartiles: SIRI 1.58 (n = 328), 1.58$\le$ SIRI 3.28 (n = 328), 3.28$\le$ SIRI 7.80 (n = 328), SIRI $\ge$7.80 (n = 328). The characteristics of different groups are summarized in Table 1. Patients in higher SIRI quartiles were more likely to be smokers. Regarding laboratory parameters, patients with a higher SIRI had a higher white blood cell count, neutrophil count, monocyte count, hemoglobin, platelet, creatinine, blood nitrogen urea, ALT, AST, and potassium, whereas lymphocyte count and sodium were lower.

As shown in Table 2, the incidence of 30-day MACE was 11.2%, and a higher SIRI was related to a significant increase in the rate of 30-day MACE (quartile 4 vs. quartile 1: 17.1% vs. 6.1%, p 0.001). The rate of incident HF was 4.2%, and we found a significant trend toward increased risk of incident HF with increasing SIRI (quartile 4 vs. quartile 1: 6.4% vs. 1.8%, p = 0.027). The rates of all-cause death, non-fatal MI, stroke, cardiogenic shock, and cardiac arrest were 4.4%, 1.1%, 0.8%, 3.1%, and 2.3%, respectively. However, we failed to demonstrate that an elevated SIRI quartile was significantly associated with an increased rate of all-cause death (quartile 4 vs. quartile 1: 5.5% vs. 3.7%, p = 0.583), non-fatal MI (quartile 4 vs. quartile 1: 2.1% vs. 0.3%, p = 0.105), stroke (quartile 4 vs. quartile 1: 1.2% vs. 0.3%, p = 0.305), cardiogenic shock (quartile 4 vs. quartile 1: 5.2% vs. 2.1%, p = 0.097) and cardiac arrest (quartile 4 vs. quartile 1: 2.7% vs. 1.8%, p = 0.746).

In multiple logistic regression analysis, adjusted for confounding variables, a positive correlation was noted between SIRI and 30-day MACE (quartile 4 vs. quartile 1: OR, 95% CI: 3.30, 1.55–7.03, p = 0.002, p for trend 0.001). In addition, we found that diabetes (OR, 95% CI: 1.53, 1.04–2.25, p = 0.029), higher LDL-C (OR, 95% CI: 1.01, 1.00–1.01, p = 0.002), and Killip class (OR, 95% CI: 1.48, 1.15–1.91, p = 0.003) were significantly associated with an increased risk of 30-day MACE respectively. While women (female vs. male: OR, 95% CI: 0.56, 0.35–0.90, p = 0.016), higher systolic blood pressure (OR, 95% CI: 0.99, 0.98–1.00, p = 0.002) and LVEF (OR, 95% CI: 0.94, 0.93–0.96, p 0.001) were significantly related to the reduction in the risk of 30-day MACE respectively (Table 3).

In Fig. 1, we used the RCS model to analyze the nonlinear relationship between 30-day MACE and SIRI as a continuous variable (Non-linear p = 0.002). The results showed a positive relationship between SIRI and the risk of 30-day MACE after adjustment for potential confounders in the model.

Fig. 1.

RCS model showing the association between the SIRI and MACE. Abbreviation: SIRI, systemic inflammation response index; MACE, major adverse cardiovascular event; RCS, restricted cubic spline.

The association between SIRI and the incidence of 30-day MACE in a different state of inflammation is shown in Table 4. We found that higher quartiles of SIRI were significantly associated with an increased risk of 30-day MACE in all statuses except status 2, suggesting that SIRI was a significant prognosis marker of 30-day MACE in mild or non-inflammatory status.

The ability to predict the 30-day MACE of SIRI, NLR and hs-CRP was presented in Fig. 2. The AUCs of SIRI for 30-day MACE was 0.622, which was larger than the AUC of the NLR (De-long test, p = 0.046) and hs-CRP (De-long test, p = 0.015) respectively, suggesting that SIRI had the better predictive accuracy of adverse outcomes in patients with STEMI.

Fig. 2.

ROC curves for the prediction of 30-day MACE of SIRI, NLR and hs-CRP. Abbreviation: ROC, receiver operating characteristic; MACE, major adverse cardiovascular event; SIRI, systemic inflammation response index; NLR, neutrophil to lymphocyte ratio; hs-CRP, high sensitive C reactive protein.

In subgroup analysis, the numerical SIRI was positively associated with a higher risk of 30-day MACE in all subgroups. Moreover, no significant interactions were observed in all subgroup analyses (Fig. 3).

Fig. 3.

Subgroup analysis of the association between 30-day MACE and SIRI as a continuous variable. Abbreviation: OR, odds ratio; CI, confidence interval; SIRI, systemic inflammation response index; MACE, major adverse cardiovascular event.

First, our study was a retrospective observational study with patients from one center. Some selection bias might be inevitable. Second, factors influencing AMI outcomes were various, and variables in our study might have been inadequately collected. Finally, we only had the short-term outcome of 30-day MACE in our study; the relationship between long-term outcomes and SIRI should be further explored.