Abstract Background The systemic inflammatory response index (SIRI) is a novel inflammatory biomarker in many diseases. Objectives The aim of this study was to examine the association between SIRI and adverse events in patients with the acute coronary syndrome (ACS) undergoing percutaneous coronary intervention. Methods A total of 1724 patients with ACS enrolled from June 2016 to November 2017 at a single centre were included in this study, and SIRI was calculated for each patient. The primary endpoint was the composite of major adverse cardiovascular events (MACE), including overall death, non-fatal myocardial infarction, non-fatal stroke, and unplanned repeat revascularization. Results During a median follow-up of 927 days, 355 patients had MACE. Multivariate Cox analysis showed that SIRI was significantly associated with MACE (hazard ratio: 1.127, 95% confidence interval: 1.034–1.229 p = .007). The results were consistent in multiple sensitivity analyses. The addition of SIRI had an incremental effect on the predictive ability of the Global Registry of Acute Coronary Events risk score for MACE (integrated discrimination improvement: 0.007, p = .040; net reclassification improvement: 0.175, p = .020; likelihood ratio test: p < .001). The restricted cubic spline showed a monotonic increase with a greater SIRI value for MACE (p < .001). Conclusion SIRI was an independent risk factor for MACE and provided incremental prognostic information in patients with ACS undergoing percutaneous coronary intervention. KEY MESSAGES The SIRI is a strong and independent risk factor for adverse outcomes in patients with ACS undergoing percutaneous coronary intervention. Higher SIRI is associated with a more severe disease status. The SIRI could increase the prognostic value of the GRACE risk score.

https://www.tandfonline.com/doi/pdf/10.1080/07853890.2022.2083671?needAccess=true

Prognostic value of systemic inflammatory response index in patients with acute coronary syndrome undergoing percutaneous coronary intervention

Background The present study aimed to clarify the effects of four inflammatory indicators (monocyte-to-high-density lipoprotein ratio [MHR], neutrophil-to-lymphocyte ratio [NLR], systematic immune-inflammation index [SII], and systemic inflammation response index [SIRI]) in evaluating the risk of metabolic diseases and cardiovascular disease (CVD), filling the gap of inflammation-metabolism system research in epidemiology. Methods We conducted a cross-sectional study and multivariable logistic regression analysis to elucidate the association between inflammatory indicators and metabolic diseases and CVD risk. Metabolic diseases were defined as metabolic disorders (MetDs) or their components, such as metabolic syndrome (MetS), dyslipidemia, and central obesity. We calculated the Framingham risk score (FRS) to evaluate 10-year CVD risk. Results Odds ratios for the third vs. the first tertile of MHR were 2.653 (95% confidence interval [CI], 2.142–3.286) for MetD, 2.091 (95% CI, 1.620–2.698) for MetS, 1.547 (95% CI, 1.287–1.859) for dyslipidemia, and 1.515 (95% CI, 1.389–1.652) for central obesity. Odds ratios for the third vs. the first tertile of SIRI were 2.092 (95% CI, 1.622–2.699) for MetD, 3.441 (95% CI, 2.917–4.058) for MetS, 1.417 (95% CI, 1.218–1.649) for dyslipidemia, and 2.080 (95% CI, 1.613–2.683) for central obesity. The odds ratio of a 10-year CVD risk of >30% for the third vs. the first tertile of MHR was 4.607 (95% CI, 2.648–8.017) and 3.397 (95% CI, 1.958–5.849) for SIRI. Conclusions MHR and SIRI had a significant association with MetD and its components, in which a higher level of MHR or SIRI tended to accompany a higher risk of metabolic diseases. Furthermore, they also correlated with CVD, and the increment of these indicators caused a gradually evaluated risk of 10-year CVD risk.

/pdf/monocyte-to-high-density-lipoprotein-ratio-and-systemic-1jd9hrip.pdf

Monocyte-to-high-density lipoprotein ratio and systemic inflammation response index are associated with the risk of metabolic disorders and cardiovascular diseases in general rural population

In the field of critical care medicine, substantial research efforts have focused on identifying high-risk patient groups. This research has led to the development of diverse diagnostic tools, ranging from basic biomarkers to complex indexes and predictive algorithms that integrate multiple methods. Given the ever-evolving landscape of medicine, driven by rapid advancements, changing treatment strategies, and emerging diseases, the development and validation of diagnostic tools remains an ongoing and dynamic process. Specific changes in complete blood count components, such as neutrophils, lymphocytes, monocytes, and platelets, are key immune system responses influenced by various factors and crucial in systemic inflammation, injury, and stress. It has been reported that indices such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and delta neutrophil index calculated using various ratios of these elements, are important predictors of various outcomes in conditions where the inflammatory process is at the forefront. In this narrative review, we concluded that NLR, PLR, SII, and SIRI show promise in predicting outcomes for different health conditions related to inflammation. While these tests are accessible, reliable, and cost-effective, their standalone predictive performance for a specific condition is limited.

Unraveling the clinical significance and prognostic value of the neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, systemic immune-inflammation index, systemic inflammation response index, and delta neutrophil index: An extensive literature review

Abstract Objectives: The inflammatory response is critically important in acute pancreatitis (AP). Systemic immune-inflammation (SII) index and systemic inflammation response index (SIRI), which are novel inflammatory markers, have been linked to determining outcomes in various diseases. The goal of the current study was to examine the relation of the SII index and SIRI with disease severity and acute kidney injury (AKI) in subjects with AP. Methods: A total of 332 subjects with AP were analyzed retrospectively. SII index was calculated using the formula; platelet (P)×neutrophil (N)/lymphocyte (L), while SIRI was calculated as N × monocyte (M)/L count. Multivariate regression (MR) was done to determine the independent risk factors for AKI and severe AP (SAP). Results: Statistical analyses showed that both median SII index and median SIRI increased gradually with higher AP severity (p < 0.001). Both SII index and SIRI were higher in subjects with AKI compared to controls (p < 0.001). Using MR analysis, the SII index was found to independently predict both SAP (OR = 1.004, 95% CI: 1.001–1.008, p = 0.018) and AKI (OR = 1.005, 95% CI: 1.003–1.008, p < 0.001). ROC analysis showed that the SII index could accurately differentiate SAP (AUC = 0.809, p < 0.001) and AKI (AUC = 0.820, p = 0.001) in patients with acute pancreatitis. ROC analysis also showed that SIRI could also accurately differentiate SAP (0.782, p < 0.001) and AKI (AUC = 0.776, p = 0.001). Conclusions: SIRI and the SII indexes can be used as potential biomarkers in predicting both disease severity and AKI development in subjects with AP.

Systemic Inflammation Response Index and Systemic Immune Inflammation Index Are Associated with Clinical Outcomes in Patients with Acute Pancreatitis?

Background Heart failure (HF) is a clinical syndrome caused by ventricular dysfunction, which leads to the decline of activity tolerance and repeated hospitalization, which seriously affects the quality of life and is the main cause of death of the elderly. It has long been observed that the pathophysiological mechanism of HF is associated with systemic inflammation. This study aims to explore the association between the systemic inflammation response index (SIRI), a novel biomarker of inflammation, and outcomes in elderly patients with HF. Methods Data was extracted from the Medical Information Mart data for Intensive Care III (MIMIC-III) database and the Second Affiliated Hospital of Wenzhou Medical University. The primary outcome was 90-day all-cause mortality. The secondary outcomes included 1-year all-cause mortality, the length of hospital or intensive care unit (ICU) stay, and the need for renal replacement therapy (RRT). Cox proportional hazards regression, linear regression, and logistic regression models were used to assess the association between SIRI levels and all-cause mortality, the length of hospital or ICU stay, the need for RRT, respectively. Moreover, Pearson correlation analysis was conducted to evaluate the correlation between SIRI and C-reactive protein (CRP). Results This study cohort included 3,964 patients from the MIMIC-III database and 261 patients from the Second Affiliated Hospital of Wenzhou Medical University. The result suggested that SIRI was independently associated with the 90-day, and 1-year all-cause mortality in elderly patients with HF (tertile 3 vs. tertile 1: adjusted HR, 95% CI: 1.41 (1.18, 1.68), 1.19 (1.03, 1.37); p trend = 0.0013, 0.0260; respectively). Elevated SIRI was associated with increased the length of hospital or ICU stay after adjusting for multiple confounders (tertile 3 vs. tertile 1: β, 95% CI: 0.85 (0.16, 1.54); 0.62 (0.18, 1.06); p trend = 0.0095, 0.0046; respectively). Furthermore, we found that patients with higher SIRI levels were more likely to require RRT (tertile 3 vs. tertile 1: OR, 95% CI: 1.55 (1.06, 2.28); p trend = 0.0459). Moreover, we confirmed that SIRI was statistically positively correlated with CRP (correlation coefficient r = 0.343, p <0.001). Conclusions SIRI could be a novel promising inflammatory biomarker for predicting all-cause mortality in elderly patients with HF. And the patients with higher SIRI values had the longer length of hospital or ICU stay and were more likely to require for RRT. Of note, this study also verified a statistically significant positive correlation between SIRI and the inflammatory marker CRP, highlighting the importance of systemic inflammation as a determinant of outcome in patients with HF.

/pdf/systemic-inflammation-response-index-is-a-promising-2sv47156.pdf

Systemic Inflammation Response Index Is a Promising Prognostic Marker in Elderly Patients With Heart Failure: A Retrospective Cohort Study

/pdf/the-predictive-role-of-systemic-inflammation-response-index-z3m4j6ltwf.pdf

The Predictive Role of Systemic Inflammation Response Index (SIRI) in the Prognosis of Stroke Patients

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The Predictive Role of Systemic Inflammation Response Index (SIRI) in the Prognosis of Stroke Patients