This retrospective analysis found that SII, a novel inflammatory marker, was associated with the occurrence of hospitalization and discharge outcomes in patients with acute STEMI after PPCI. Between the event and non-event groups, SII levels responded differently to high and low inflammatory status, which had an impact on prognosis. Patients with a high inflammatory state had a relatively poorer prognosis.
Inflammation plays a key role in the evolution of atherosclerosis, acute myocardial infarction and poor prognosis after myocardial infarction. Plaque rupture can trigger an inflammatory response that releases highly thrombogenic plaque components and promotes thrombus formation[15]. In the acute phase of myocardial infarction, the inflammatory response becomes significant with acute exacerbation, and the higher the degree of inflammation, the larger the area of myocardial ischemic necrosis. A COLCOT trial showed that the use of low-dose colchicine within 3 days after myocardial infarction(MI) reduced the occurrence of ischemic cardiovascular events. Patients can benefit from early in-hospital use of colchicine after MI [16]. This suggests that the occurrence of MI is associated with inflammatory involvement and that early suppression of inflammation after MI provides even greater benefits.
Leukocytes and their subtypes, such as neutrophils, monocytes, lymphocytes and platelets, as important inflammatory cells in the circulation, have been shown in several studies to be associated with prognosis of patients with acute myocardial infarction. Leukocyte count is an independent predictor of acute myocardial infarction (AMI) [17], and elevated leukocyte levels are associated with increased mortality in STEMI patients [18]. During inflammation, pre-stimulated neutrophils infiltrating the vessel wall release reactive oxygen species, cytokines, and myeloperoxidases that damage the vascular endothelium to promote inflammation progression, and elevated neutrophil counts are associated with a high risk of ischemic events [19] and AMI mortality [20]. In the inflammatory stress state of acute myocardial infarction, cortisol levels are elevated in the body, and lymphocytes are affected by cortisol levels, resulting in decreased lymphocyte levels [21]. Lymphocytopenia is independently associated with mechanical complications and mortality in patients with acute STEMI [22]. Monocytes, one of the basic components of the immune system, are considered to be predictors of coronary events [23], and an increase in their number has been shown to correlate with the prognosis of AMI [24]. Platelets play a role in inflammatory and immune responses through the release of pro-inflammatory cytokines and interactions with endothelial cells, leukocytes, and smooth muscle cells [25, 26] and are significantly associated with inflammation and atherothrombosis[27].
It is proposed to monitor several inflammatory markers in the peripheral blood to assess cardiovascular risk in patients with acute myocardial infarction. Some such as neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and lymphocyte/monocyte ratio (LMR) had been introduced as new markers. It was found that high NLR levels are very importantly associated with cardiovascular and all-cause mortality in patients with ST-segment elevation myocardial infarction during hospitalization or in the long term [28, 29]. Low LMR is correlated with bad outcomes in AMI patients[30]. Platelet/lymphocyte ratio (PLR) is related to long-term mortality in STEMI patients [31]. Recently, Hu et al. developed an innovative predictable marker called the systemic Immune inflammation Index (SII) based on a prospective cohort study[32]. The systemic immune inflammation index (SII) is a novel inflammatory parameter calculated as (N × P)/L (N, P, and L represent neutrophil count, platelet count, and lymphocyte count, respectively), and represents three important immune response pathways, namely, inflammatory response, thrombosis and organismal stress response. It is a prognostic indicator of poor outcomes in various cancer types [33, 34]. Its study in cardiovascular diseases has also been noticed. SII was found to predict clinical outcomes in patients with coronary artery disease[35]. Su et al [36] demonstrated that high SII was independently associated with all-cause mortality at 30 days, 90 days, and 1 year in patients with acute coronary syndrome. Lütfi Öcal et al [37] demonstrated that SII was independently associated with all-cause mortality and adverse cardiovascular events during hospitalization and in 3-year follow-up after PPCI in patients with acute ST-segment elevation infarction. Additionally,other specific studies had already shown that the SII may indicate short- and long-term mortality in patients with heart failure (HF) reduced with ejection fraction (HFrEF) and acute type A aortic dissection (ATAD) patients undergoing surgery and infective endocarditis [38–40]. All those studies used a single SII level at baseline, and illustrated that higher SII level was interrelated with poorer prognosis.
Our study differs in that we assessed the process of dynamic changes in SII levels compared with the above studies. The process of inflammatory activity is dynamic, and during intraoperative and postoperative period the stent as a foreign object stimulates endothelial cells and increases inflammatory radical responses, which may manifest as an increase in inflammatory indexes. During hospitalization and after hospital discharge, patients were treated with appropriate anti-platelet, and lipid-regulating drugs, which also had an impact on the inflammatory process. Therefore, dynamic changes in SII levels can better reflect the overall situation than a single SII level alone. In our study, we tried to see if dynamic changes in SII were related with in-hospital and out-of hospital outcomes taken place in STEMI patients undergoing PPCI. The study analyzed the relationship between serial changes in SII during the perioperative period of PPCI and the occurrence of the primary endpoint by univariable and multivariable logistic regression. The results showed that high SII levels were independently associated with the occurrence of the primary endpoint during the post-operative follow-up period of patients (P < 0.05). In contrast, patients with high SII levels had lower survival rates than those with low SII levels. By dynamically analyzing SII levels in six groups, including 12h before PPCI, 12h after PPCI(T1),24h after PPCI, 48h after PPCI, the last time before hospital discharge(T2),1 month after hospital discharge(T1M),hs-CRPmax, cTnImax,CK-MBmax, and making ROC curves at each node, the analysis showed that SII 12h after PPCI(T1) and 1 month after hospital discharge(T1M) had excellent predictive value for the occurrence of in-hospital and out-of hospital outcomes. This can be due to at least two reasons. First, inflammation may be closely related to the prognosis of in-hospital outcomes in STEMI patients because of the intense inflammatory response in the phase of acute myocardial infarction. Second, at 1 month after hospital discharge, most patients benefited from the appropriate use of anti-platelet, and lipid-regulating drugs which can improve the local inflammatory state of myocardium, while a small number of patients still had local myocardial inflammation, thus leading different prognosis. This inspired us that paying attention to the peak SII level during hospitalization was necessary. When the peak in-hospital SII level higher than 1915.77, timely intervention is required to effectively reduce in-hospital outcomes’s occurrence. Meanwhile, focusing on the lowest level of SII at 1 month after hospital discharge and keeping it below than 696.43 can effectively reduce the occurrence of out-of hospital outcomes. Thus, it provided guidance for improving the prognosis of patients.
However, as there are few studies on the correlation between dynamic changes in SII levels during the perioperative period of PPCI and the primary endpoint occurrence in STEMI patients, several limitations were as follows : 1. There was a study with single-center, retrospective and a small sample size. The conclusions may be affected by selection bias. 2.Other conventional factors that respond to inflammatory statuses such as calcitoninogen, IL-6, and myeloperoxidase were not included in this study. 3.Although independent risk factors were identified by multi-variable regression, some undefined factors still existed, which affected the study results. We have a vision that future prospective studies with large sample sizes and multi-center could confirm the inflammatory status to meet the control standard and thus reduce major cardiovascular events occurring, similar to the application of lipid-regulating medications to lower lipid levels and bring lipids into general standard.