Early detection of central line-associated bloodstream infection in intensive care unit patients using the systemic inflammatory response index (SIRI)

Immunoinflammatory response can participate in the development of cancer. To investigate the relationship between pretreatment systemic immune inflammatory response index (SII), systemic inflammatory response index (SIRI), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR) and lymph node metastasis in patients with papillary thyroid carcinoma (PTC). A retrospective analysis was performed on 547 PTC patients treated in Meizhou People's Hospital from January 2018 to December 2021. Clinicopathological data were collected, including gender, age, Hashimoto's thyroiditis, maximum tumor diameter, extra-membrane infiltration, disease stage, BRAF V600E mutation, pretreatment inflammatory index levels, and lymph node metastasis. The optimal cutoff values of SII, SIRI, NLR, PLR and LMR were calculated by receiver operating characteristic (ROC) curve, and the relationship between inflammatory indexes and other clinicopathological features and lymph node metastasis was analyzed. There were 303 (55.4%) PTC patients with lymph node metastasis. The levels of SII, SIRI, NLR, and PLR in patients with lymph node metastasis were significantly higher than those in patients without lymph node metastasis, while the levels of LMR were significantly lower than those in patients without lymph node metastasis (all p<0.05). When lymph node metastasis was taken as the endpoint, the critical value of SII was 625.375, the SIRI cutoff value was 0.705, the NLR cutoff value was 1.915 (all area under the ROC curve >0.6). The results of regression logistic analysis showed that age <55 years old (OR: 1.626, 95% CI: 1.009-2.623, p=0.046), maximum tumor diameter >1cm (OR: 2.681, 95% CI: 1.819-3.952, p<0.001), BRAF V600E mutation (OR: 2.709, 95% CI: 1.542-4.759, p=0.001), SII positive (≥625.375/<625.375, OR: 2.663, 95% CI: 1.560-4.546, p<0.001), and NLR positive (≥1.915/<1.915, OR: 1.808, 95% CI: 1.118-2.923, p=0.016) were independent risk factors for lymph node metastasis of PTC. Age <55 years old, maximum tumor diameter >1cm, BRAF V600E mutation, SII positive, and NLR positive were independent risk factors for lymph node metastasis in PTC.

Early screening of central line-associated bloodstream infections: A novel comparative analysis of AISI, SII, and SIRI as predictive biomarkers.

The overwhelming inflammatory response plays a critical role in the secondary injury cascade of traumatic spinal cord injury (tSCI). The systemic immune inflammatory index (SII) and systemic inflammatory response index (SIRI) are two novel inflammatory biomarkers. The SII was calculated based on lymphocyte, neutrophil, and platelet counts, while the SIRI was calculated based on lymphocyte, neutrophil, and monocyte counts. Their prognostic value in patients with tSCI remains unclear. Patients with tSCI admitted within 24h of trauma were retrospectively and consecutively enrolled. Peripheral blood samples were collected on admission. The primary outcome was American Spinal Injury Association Impairment Scale (AIS) grade conversion at discharge. Multivariable logistic regression analysis was performed to determine the relationship between SII and SIRI and AIS grade conversion. We performed receiver operating characteristic curve (ROC) analysis to assess the discriminative ability of SII, and SIRI in predicting AIS grade conversion. Among 280 included patients, 77 (27.5%) had improved AIS grade conversion at discharge. After adjustment for confounders, SII was independently associated with AIS grade conversion (per SD, odds ratio [OR], 0.68; 95% confidence interval [CI] 0.47-0.98, p = 0.040), while the association between SIRI and AIS grade conversion was insignificant (per 1 SD, OR, 0.77; 95% CI 0.55-1.08, p = 0.130). The ROC analysis revealed that the SII had the best predictive value for AIS grade conversion (area under curve: 0.608, 95% CI 0.536-0.678). Increased SII was independently associated with a decreased likelihood of improved AIS grade conversion.

Composite inflammatory markers, such as the systemic inflammatory response index (SIRI), are associated with the severity and progression of several cardiovascular diseases. However, the relationship between SIRI and chronic thromboembolic pulmonary hypertension (CTEPH) remains unclear. We hypothesized that elevated SIRI levels would correlate with disease severity and independently predict adverse clinical outcomes in patients with CTEPH.This study aimed to clarify the predictive value of SIRI in patients with CTEPH. This retrospective cohort study included 383 patients with CTEPH treated at Fuwai Hospital between June 2013 and June 2021. Receiver operating characteristic (ROC) curve analysis was used to compare the diagnostic performance of SIRI to other inflammatory indices and identify the optimal cutoff value. Kaplan-Meier analysis and Cox proportional hazard models were used to examine the relationship between SIRI and clinical worsening. During a mean follow-up period of 30.6 months, 79 participants experienced clinical worsening. The SIRI was significantly correlated with established markers of CTEPH severity, including the 6-minute walk distance, N-terminal pro-brain natriuretic peptide, and hemodynamic parameters. Kaplan-Meier curve revealed that individuals with a SIRI ≥ 0.80 exhibited significantly poorer survival rates and a shorter time to clinical worsening compared to those with a SIRI < 0.80 (P < 0.01). Adjusted Cox proportional hazards analysis revealed that SIRI remained an independent predictor of clinical worsening (hazard ratio (HR) 2.033; 95% confidence interval (CI) 1.227-3.370). ROC analysis revealed that SIRI exhibited the highest area under the curve value of 0.730 (95% CI 0.659-0.810). Incorporating SIRI into The COMPERA 2.0, the risk score improved its predictive value for adverse outcomes in patients with CTEPH. SIRI is a valuable prognostic marker for CTEPH, correlating with established markers of disease severity and independently predicting clinical worsening. SIRI provides additional prognostic predictive value when used in conjunction with the risk score of COMPERA 2.0.

The systemic inflammatory response index (SIRI), calculated from routine complete blood count parameters, has emerged as a potential marker of inflammation and a predictor of prognosis in various cardiovascular conditions. This study aimed to evaluate the utility of SIRI in differentiating non-ST-elevation myocardial infarction (NSTEMI) from unstable angina pectoris (USAP) in patients presenting with acute chest pain. In this retrospective observational study, patients admitted to the emergency department with chest pain and subsequently diagnosed with USAP or NSTEMI were included. Only patients with negative high-sensitive troponin-I levels at the time of admission were enrolled in both groups. During follow-up, those who showed an increase in troponin levels were classified as NSTEMI, whereas patients without troponin elevation were classified as USAP. The SIRI was calculated using blood samples obtained at the time of admission to the emergency department by multiplying the neutrophil and monocyte counts and dividing by the lymphocyte count. Troponin positivity was used to distinguish NSTEMI from USAP. SIRI was assessed at admission in patients with chest pain and normal troponin. Higher SIRI levels in NSTEMI suggest its potential for early differentiation from USAP. Multivariate logistic regression analysis was performed to determine independent predictors of troponin positivity, and receiver operating characteristic curve analysis was used to assess diagnostic performance. A total of 151 patients were included in the analysis. Admission SIRI values were significantly higher in the troponin-positive (NSTEMI) group compared with the troponin-negative (USAP) group (P < .001). In multivariate analysis, higher admission SIRI levels independently predicted troponin positivity (odds ratio [OR], 1.47; 95% confidence interval [CI], 1.17-1.84; P < .001). Receiver operating characteristic analysis revealed an area under the curve of 0.71 (95% CI 0.63-0.79, P < .001). A cutoff value of 1.58 for SIRI demonstrated 72% sensitivity and 69% specificity in predicting troponin positivity. SIRI, a readily available, inexpensive, and rapidly obtainable index derived from standard complete blood count parameters, may serve as a valuable adjunctive tool for the early differentiation of NSTEMI from USAP in patients with acute chest pain. Its ease of calculation within minutes of admission makes it suitable in diverse healthcare settings.

Aims: The increasing frequency of natural disasters has led to a higher incidence of crush injuries. Consequently, with the advancement of disaster medicine in recent years, the number of crush syndrome cases has also risen. In the management of disaster medicine, there is a growing need for rapid and reliable biomarkers for the diagnosis and prognostic evaluation of such cases. Creatine kinase (CK) and C-reactive protein (CRP) are among the most commonly used biomarkers for assessing inflammatory processes. Recently, novel inflammatory indices such as the Systemic Inflammatory Response Index (SIRI), Systemic Immune-Inflammation Index (SII), and Pan-Immune Inflammation Value (PIV) have been shown to play a significant role in the rapid diagnostic and prognostic evaluation of various diseases. This study aimed to determine the diagnostic value and clinical significance of the SII, SIRI, and PIV indices in the diagnosis of crush syndrome. Methods: This retrospective observational study was conducted on patients diagnosed with crush syndrome who were affected by the earthquake that occurred in Hatay on February 6, 2023, and presented to Ankara Etlik City Hospital between January 1 and December 31, 2023. The included patients were analyzed in terms of laboratory parameters and inflammatory indices and were compared with a control group. Results: In the patient group, markers of inflammation, tissue damage, and metabolic disruption were found to be significantly elevated compared to the control group. Notably, levels of CRP, WBC, neutrophils, CK, AST, ALT, BUN, and potassium were markedly increased, while calcium and pH levels were decreased. Systemic inflammatory indices such as SII, SIRI, PIV, and NLR were also found to be higher in the patient group. In logistic regression analysis, only the SIRI variable was found to be a statistically significant independent predictor. ROC analyses demonstrated that parameters such as AST, ALT, and SIRI had high diagnostic power. These findings indicate a more pronounced systemic inflammatory and pathophysiological process in the patient group. Conclusion: The data obtained suggest that inflammatory indices play a critical role in the diagnosis of crush syndrome. In particular, the Systemic Inflammatory Response Index (SIRI) may offer stronger diagnostic value compared to other indices. Therefore, the use of SIRI as a biomarker in the early diagnosis and management of crush syndrome may be beneficial in clinical practice.

Apart from being a primary cause of morbidity and mortality globally, gastrointestinal (GI) disorders also contribute significantly to the cost of healthcare. In patients with GI diseases, the systemic inflammatory response index (SIRI) is not often used as a marker of systemic immune inflammation to assess mortality-associated risk from malignant neoplasms or all causes. Therefore, the objective of this study was to elaborate on the link between SIRI and all causes and malignant neoplasm mortality in patients with GI disorders. Retrospective analysis was performed using National Health and Nutrition Examination Survey (NHANES) data from 1999 to 2018. Restricted cubic spline (RCS) plots and multivariate Cox proportional hazards regression were used to examine the relationship between SIRI and GI patient mortality from malignant neoplasms and all causes. Data on survival were shown using Kaplan-Meier (KM) survival curves, and these correlations were further explored by subgroup and interaction analyses. Receiver operating characteristic (ROC) curves were generated to evaluate the specificity and sensitivity of SIRI in predicting mortality among patients with GI diseases. This study included 4,137 GI patients who were followed comprehensively over 20 years, during which 165 malignant neoplasm mortality and 713 all-cause mortalities were recorded. A nonlinear association between all-cause mortality and SIRI was observed, whereas in GI patients, a linear relationship was identified between SIRI and cancer-related death. The hazard ratio (HR) was 1 at a SIRI level of 1.114, indicating the low-to-high mortality risk change. Participants in the highest quartile (Q4) in the fully adjusted model (model 3) showed a significantly greater likelihood of death from both malignant neoplasms and all-cause relative to those in the lowest quartile (Q1). The mortality HR for malignant neoplasms was 1.74 [95% confidence interval (CI): 1.08-2.82], whereas the HR for all-cause mortality was 2.50 (95% CI: 1.95-3.20). Furthermore, subgroup analysis revealed that higher SIRI was linked with a higher malignant neoplasm mortality risk among male, low-income, smoking, and drinking GI patients. Comparing SIRI to the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII), the ROC curve analysis showed that SIRI had better diagnostic effectiveness. Interaction study verified that SIRI is an independent variable that significantly increases the probability of death from both all-cause and malignant neoplasms. The nonlinear positive correlation between the SIRI and the mortality from malignant neoplasms and all-cause in GI patients is highlighted by this study. Elevated SIRI levels were significantly linked to a higher mortality rate from GI disorders, including malignant neoplasms and all-cause. Thus, in GI patients, SIRI can be used as a prognostic marker for mortality and long-term health outcomes prediction.

Introduction: Inflammation plays an important role in the pathogenesis of coronary artery disease and Acute Coronary Syndrome (ACS). Inflammatory indicators such as neutrophil count and monocyte count potentially may predict patients’ outcomes and prognosis in ACS. White blood cells count is an affordable and accessible way to assess the systemic immune response. Considering their multidirectional effect on atherosclerosis, new inflammatory biomarkers integrating various leukocyte subgroups have been proposed to calculate the systemic inflammatory response index (SIRI) and systemic inflammatory index (SII). Aim: The aim of this study was to assess the association between the systemic inflammatory response index (SIRI) and Systemic inflammatory index (SII) at admission with major adverse cardiovascular events (MACE) 30-days after Primary Percutaneous Coronary Intervention (PPCI) among patients with Acute Coronary Syndrome (ACS) at one referral hospital in Jordan. Method: A Prospective design was used to assess and follow 150 adults presented with ACS and received PPCI at one referral hospital in Jordan. Data was collected from patients and their medical records during hospital stay using a structured data collection form. The MACE was assessed 30-days after PPCI through phone calls with patients and confirmed from medical records. Results: The study included 150 patients with ACS, 82.7% (n= 124) of them were males. The mean age of patients was 57.68 (SD= 11.19) years. Types of ACS include stable angina 5.3% (n=8), unstable angina 24% (n=36), NSTEMI 28.7% (n=43), and STEMI 24% (n=36). All patients had interventional PCI with balloon and stent insertion. The mean of SIRI was 24.45 (SD=25.49) and the mean of SII was 663.30 (SD= 403.75). Rate of MACE as composite outcome 30-days after PPCI as 24.7% (n=37). The most MACE was unplanned repeat revascularization (n=14, 38% of MACE). Significant association between SIRI and SII, and MACE was found SIRI:(Χ2(2)&gt; = 12.63, p = 0.001), SII:(Χ2(2)&gt; = 4.23, p = 0.03). Conclusion: The SIRI and SII are inflammatory biomarkers that should be studied as potentially predictors of MACE among patients presented with ACS.

This study aimed to explore the predictive value of the systemic inflammatory response index (SIRI) and the pan-immune-inflammatory value (PIV) in assessing the risk of myocardial infarction (MI) among UA cases. The risk factors were identified by univariate and binary logistic regression analyses, and the relationship between variables was analyzed using Pearson correlation analysis. The receiver operating characteristic (ROC) curve analysis was used to assess the predictive value of the indicators for MI in UA cases. No significant difference was found in gender, age, hypertension, body mass index (BMI), diabetes, alcohol consumption, smoking status, total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), or hemoglobin (Hb) between the two groups (P > 0.05). Nevertheless, statistical differences were found in monocyte (MON), N-terminal pro-B-type natriuretic peptide (NT-proBNP), platelet count (PLT), lymphocyte count (LYM), neutrophil count (NEU), SIRI, and PIV (P < 0.05). Pearson correlation analysis indicated positive correlations between SIRI and PIV (r = 0.807), SIRI and NT-proBNP (r = 0.116), and PIV and NT-proBNP (r = 0.176) (all P < 0.05). Binary logistic regression analysis identified NT-proBNP, SIRI, and PIV as significant predictors of MI in UA cases (P < 0.05). ROC curve analysis demonstrated that SIRI achieved an area under the curve (AUC) of 0.851 (standard error (SE) = 0.027, 95% confidence interval (CI): 0.798–0.904), and the Youden index was 0.58 (specificity, 74.58%; sensitivity, 83.83%). PIV yielded an AUC of 0.902 (SE = 0.020, 95% CI: 0.863–0.940), and the Youden index was 0.68 (specificity, 80.97%; sensitivity, 86.76%). The united SIRI + PIV model yielded an AUC of 0.920 (SE = 0.016, 95% CI: 0.889–0.951), and the Youden index was 0.71 (specificity, 79.93%; sensitivity, 91.18%). Applying the optimal cutoff thresholds, the incidence of MI was lower in cases with SIRI ≤ 1.23 compared to SIRI > 1.23, and it was also found in cases with PIV ≤ 215.88 compared to PIV > 215.88 (P < 0.05). SIRI and PIV were found highly effective in predicting MI risk in UA cases, and their combination could further enhance the predictive performance.

The prognostic significance of utilizing both the systemic inflammatory response index (SIRI) and pulse pressure (PP) collectively in assessing cardiovascular mortality (CVM) across populations remains to be elucidated. Multivariate Cox proportional hazards analysis investigated the SIRI, PP, and CVM association. Receiver operating characteristic (ROC) curves evaluated the predictive performance of the combined SIRI and PP for CVM in the broader demographic. Subsequently, the area under the ROC curve (AUC) was compared using the Z-test, and a novel nomogram was developed to assess its accuracy in predicting CVM. Restricted cubic spline (RCS) was used to evaluate the association between SIRI and PP. The study involved 19,086 NHANES database individuals, with 9,531 males (49.94%). During the follow-up period, 456 CVM instances (2.39%) occurred. Multivariate Cox proportional hazards analysis revealed both the SIRI [adjusted hazard ratio (HR) 1.16, P < 0.001] and PP (HR = 1.01, P = 0.004) as independent CVM predictors. A 0.1-unit SIRI increase and 10 mmHg PP escalation correlated with 2% (adjusted HR = 1.02, P < 0.001) and 7% (adjusted HR = 1.07, P = 0.004) CVM enhancements, respectively. The combined SIRI and PP area under the curve was 0.77, ranging from 0.77 to 0.79 in female cohorts, non-smokers, and non-pathological contexts. High SIRI and PP, either high SIRI or PP, were associated with 3 and 2 times the CVM risk compared to low SIRI and PP. Adding the SIRI and PP to general risk factors improved CVM predictive efficacy (Z = 4.17, P < 0.001). The novel nomogram's concordance index was 0.90, indicating excellent discrimination. The predicted probabilities' calibration plot aligned with actual CVM rates at 1, 5, and 10 years. RCS showed an S-shaped relationship between SIRI and PP. Integrating the SIRI with PP demonstrates substantial predictive efficacy for CVM within the broader United States community, notably in female cohorts, non-smokers, and non-pathological contexts.

Introduction. The pathogenesis of aortic stenosis includes the processes of chronic inflammation, calcification, lipid metabolism disorders, and congenital structural changes. The goal of our study was to determine the predictive value of novel biomarkers of systemic inflammation and some hematological indices based on the numbers of leukocytes and their subtypes in the development of early hospital medical conditions after mechanical aortic valve replacement in patients with aortic stenosis. Materials and methods. This was a cohort study involving 363 patients who underwent surgical intervention for aortic valve pathology between 2014 and 2020. The following markers of systemic inflammation and hematological indices were studied: SIRI (Systemic Inflammation Response Index), SII (Systemic Inflammation Index), AISI (Aggregate Index of Systemic Inflammation), NLR (Neutrophil/Lymphocyte Ratio), PLR (Platelet/Lymphocyte Ratio), and MLR (Monocyte/Lymphocyte Ratio). Associations of the levels of these biomarkers and indices with the development of in-hospital death, acute kidney injury, postoperative atrial fibrillation, stroke/acute cerebrovascular accident, and bleeding were calculated. Results. According to an ROC analysis, an SIRI > 1.5 (p < 0.001), an SII > 718 (p = 0.002), an AISI > 593 (p < 0.001), an NLR > 2.48 (p < 0.001), a PLR > 132 (p = 0.004), and an MLR > 0.332 (p < 0.001) were statistically significantly associated with in-hospital death. Additionally, an SIRI > 1.5 (p < 0.001), an NLR > 2.8 (p < 0.001), and an MLR > 0.392 (p < 0.001) were associated with bleeding in the postoperative period. In a univariate logistic regression, SIRI, SII, AISI, and NLR were statistically significant independent factors associated with in-hospital death. In a multivariate logistic regression model, SIRI was the most powerful marker of systemic inflammation. Conclusion. SIRI, SII, AISI, and NLR as novel biomarkers of systemic inflammation were associated with in-hospital mortality. Of all markers and indices of systemic inflammation in our study, SIRI was the strongest predictor of a poor outcome in the multivariate regression model.

PurposeSystemic inflammatory response index (SIRI) was an independent predictor of the prognosis of many diseases. Inflammatory prognostic index (IPI) was a new inflammatory prognostic marker with certain clinical significance. We aimed to explore the association between SIRI, IPI and early stage severity of stroke as well as 3-month outcome of AIS patients.Patients and MethodsA total of 63 AIS patients who treated with alteplase were selected. The patients were divided into mild group and moderate to severe group according to the National Institutes of Health Stroke Scale (NIHSS) scores. According to the modified Rankin scale (mRS) score, patients were divided into the good prognosis group and the poor prognosis group. Spearman correlation statistically analyzed the correlation between SIRI, IPI and NIHSS score. Univariate and multivariate logistic regression analyzed the risk factors of 3-month prognosis. ROC curve was adopted to predict the effect of SIRI and IPI levels on poor prognosis in AIS patients.ResultsSpearman analysis showed that there was positively correlated with NIHSS score and IPI in mild AIS group (r=0.541, P<0.05). Compared with the mild group, SIRI and IPI in the moderate to severe group was significantly higher (P<0.05). The SIRI and IPI in the poor prognosis group were significantly higher than those in the good prognosis group (P<0.05). Univariate and multivariate logistic regression analysis showed that SIRI and IPI were independent prognostic factors for the 3-month prognosis of AIS patients (P< 0.05). The ROC curve showed that the areas under the 3-month prognosis curve predicted by SIRI and IPI were 0.685, 0.774 respectively.ConclusionIPI is correlated with stroke severity at admission. SIRI and IPI are independent predictors of short-term prognosis in AIS patients. SIRI and IPI can be a novel the good short-term prognostic biomarker for AIS patients treated with intravenous thrombolysis.

Objectives:To uncover the predictive value of systemic immune-inflammatory index (SII) and systemic inflammatory response index (SIRI) on early pregnancy loss.Methods:A total of 535 individuals were enrolled in this retrospective analysis. The early pregnancy losses (EPL) group included patients between 18-35 years old who experienced EPL. The control group comprised healthy pregnant women who gave birth at ≥37 weeks.Results:The EPL group had significantly lower plateletcrit (p=0.04), platelet distribution width (PDW, p<0.0001), and RDW (p<0.0001) and higher monocyte (p<0.0001) and SIRI (p<0.0001) values than the control group. The hemoglobin, white blood cells, platelet count, neutrophil count, lymphocyte count, mean platelet volume, neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and SII values were not significantly different between the EPL and control groups (p>0.05). The cut-off value for the SIRI that offers the best sensitivity/specificity balance was 1.48 (sensitivity of 63%; specificity of 63%) in the receiver operating characteristics curve. Among the inflammatory parameters for predicting EPL, PDW had highest specificity (84%), and RDW had the highest sensitivity (80%).Conclusion:This study provides compelling evidence that various inflammatory pathways may significantly contribute to EPL pathogenesis. Moreover, our findings suggest that SIRI could be a more effective marker than NLR, PLR, MLR, and SII in predicting EPL in an ongoing pregnancy, thereby potentially revolutionizing early pregnancy loss diagnostics.

The systemic inflammatory response index (SIRI), a straightforward and easily accessible measure of inflammation and prognosis, has drawn more attention lately. It is unknown, however, if SIRI is important for IgA nephropathy (IgAN) patients' outcomes. To better clarify these concerns, we conducted this investigation. This retrospective study involved 981 patients with biopsy-confirmed IgAN from West China Hospital of Sichuan University between 2008 and 2019. The patients were divided into two groups based on the SIRI's optimal cut-off value calculated by the X-tile: the low SIRI group (SIRI ≤ 0.63, n = 312) and the high SIRI group (SIRI > 0.63, n = 669). Basic clinical characteristics at the time of renal biopsy were evaluated, and the relationship between SIRI and the combined endpoint was analyzed. We also used the Cox proportional hazard model and Kaplan‒Meier curve to evaluate the renal prognosis of IgAN. A total of 981 IgAN patients were included. During a median follow-up period of 56.7months (36.8-80.4months), 122 patients progressed to the combined endpoint (12.4%). Patients were divided into a low SIRI group (SIRI ≤ 0.63, n = 312) and a high SIRI group (SIRI > 0.63, n = 669) according to the optimal cut-off value of the systemic inflammatory response index (SIRI). Further analysis showed that a higher SIRI value was significantly associated with the risk of IgAN patients reaching the composite endpoint (HR 1.62, 95% CI 1.02-2.56, p = 0.041). High SIRI is a significant and independent risk factor for renal disease progression in IgAN patients.

ObjectivePostoperative delirium (POD) is a common complication following off-pump coronary artery bypass grafting (OPCABG) and is associated with significant morbidity. This study aims to evaluate the correlation of systemic immune inflammatory index (SII) and systemic inflammatory response index (SIRI) with postoperative delirium (POD) in patients with cerebral infarction undergoing OPCABG.MethodsThe perioperative cohort study included 321 patients who underwent OPCABG. Patients were divided into two groups based on the occurrence of POD: the delirium group (n = 113) and the non-delirium group (n = 208). Baseline characteristics, including gender, left ventricular ejection fraction (LVEF), surgery duration, hypertension, age, and smoking history were analyzed. SII and SIRI values were calculated preoperatively, and their association with POD was assessed using univariate and multivariate logistic regression analyses. Receiver operating characteristic (ROC) curves were used to evaluate the predictive accuracy of SII and SIRI.ResultsStatistical differences between SII and SIRI in the two groups (P < 0.05) were observed. Multivariate analysis confirmed that SII and SIRI, age and preoperative smoking history were predictors of POD. ROC curve analysis demonstrated that SII and SIRI had considerable predictive power, with AUC values of 0.73 (0.67–0.79) for SII and 0.75 (0.69–0.81) for SIRI.ConclusionSII and SIRI were found to be associated with an increased risk of POD in patients undergoing OPCABG, but further research is needed to confirm these findings and determine their independence as risk factors.