High Systemic Inflammation Response Index Research Articles

The systemic inflammation response index as a risk factor for hepatic fibrosis and long-term mortality among individuals with metabolic dysfunction-associated steatotic liver disease

Background and aimsThe systemic inflammation response index (SIRI) is associated with various diseases with inflammatory components, but its relationship with the progression of hepatic fibrosis and survival outcomes in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) is still unclear. This study was designed to investigate the potential associations between the SIRI and advanced hepatic fibrosis (AHF) as well as between the SIRI and long-term outcomes in individuals with MASLD. Methods and resultsA prospective cohort study was conducted using data gathered from the National Health and Nutrition Examination Survey (NHANES) spanning from 2005 to 2016. Weighted binary logistic regression, the Cox proportional hazards model, and time-dependent receiver operating characteristic (ROC) analyses were employed to assess the relationships among the SIRI, AHF, and mortality in patients with MASLD. Our study included a total of 5126 patients with MASLD. A higher SIRI was significantly associated with increased odds of AHF (OR 1.55, 95% CI 1.22, 1.96). According to the survival analyses, a higher SIRI was associated with greater all-cause (HR 1.19, 95% CI 1.15, 1.22) and cardiovascular mortality (HR 1.25, 95% CI 1.19, 1.32) after adjustment. The time-dependent ROC analysis indicated that the SIRI had a modest predictive value for discriminating MASLD individuals at higher versus lower mortality risk over 3-year, 5-year, and 10-year follow-up. ConclusionsThe SIRI is a promising tool for identifying MASLD individuals at risk of progressing to AHF and for predicting mortality outcomes.

Pre-treatment systemic inflammation response index and systemic immune inflammation in patients with primary central nerve system lymphoma as a useful prognostic indicator.

The systemic inflammation response index (SIRI) and systemic immune-inflammation index (SII) are based on neutrophil, monocyte, platelet, and lymphocyte counts. The SIRI and SII are used to predict the survival of patients with malignant tumors. It is well known that the inflammatory immune response is closely related to cancer occurrence and progression. In the present study, we evaluated the potential prognostic significance of SIRI and SII in patients with primary central nervous system lymphoma (PCNSL). Fifty-eight consecutive patients were enrolled in this study between November 2006 and May 2022. Among the 58 patients, 47 patients with sufficient blood test data and follow-up were analyzed. The patients with steroid intake at the time point of the blood test and higher C-reactive protein were excluded. The median follow-up and survival times were 31 and 36months, respectively. The optimal cutoff SIRI value was based on the receiver operating characteristic curve (ROC) for overall survival (OS) and stratified patients into low (< 1.43 × 109/L, n = 22) and high (≥ 1.43 × 109/L, n = 25) SIRI groups. The optimal cutoff SII value based on the ROC for OS stratified patients into low (< 694.9, n = 28) and high (≥ 694.9, n = 19) SII groups. A low SIRI value was associated with longer OS (p = 0.006). Furthermore, a low SII value was associated with longer OS (p = 0.044). The prognostic factors associated with prolonged survival in univariate analysis using the Cox proportional hazard model were age < 65years, low SIRI, and low SII. The multivariate analysis demonstrated that age < 65years and low SIRI independently predicted longer OS. Simple, less expensive, and routinely ordered preoperative blood count assessments such as SIRI and SII predict the OS of patients with PCNSL. This study demonstrated that PCNSL is associated with pre-treatment systemic immune-inflammation states.

Systemic Inflammation Response Index (SIRI) and Monocyte-to-Lymphocyte Ratio (MLR) Are Predictors of Good Outcomes in Surgical Treatment of Periprosthetic Joint Infections of Lower Limbs: A Single-Center Retrospective Analysis.

Periprosthetic joint infection (PJI) is a devastating complication that develops after total joint arthroplasty (TJA), whose incidence is expected to increase over the years. Traditionally, surgical treatment of PJI has been based on algorithms, where early infections are preferably treated with debridement, antibiotics, and implant retention (DAIR) and late infections with two-stage revision surgery. Two-stage revision is considered the "gold standard" for treatment of chronic prosthetic joint infection (PJI) as it enables local delivery of antibiotics, maintenance of limb-length and mobility, and easier reimplantation. Many studies have attempted to identify potential predicting factors for early diagnosis of PJI, but its management remains challenging. In this observational retrospective study, we investigated the potential role of inflammatory blood markers (neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic inflammatory index (SII), systemic inflammatory response index (SIRI), and aggregate index of systemic inflammation (AISI)) as prognostic factors in two-stage exchange arthroplasty for PJI. A single-center retrospective analysis was conducted, collecting clinical data and laboratory parameters from patients submitted to prosthetic explantation (EP) for chronic PJI. Laboratory parameters (PCR, NLR, MLR, PLR, SIRI, SII, and AISI) were evaluated at the explantation time; at 4, 6, and 8 weeks after surgery; and at reimplantation time. The correlation between laboratory parameters and surgery success was evaluated and defined as infection absence/resolution at the last follow-up. A total of 57 patients with PJI were evaluated (62% males; average age 70 years, SD 12.14). Fifty-three patients with chronic PJI were included. Nine patients underwent DAIR revision surgery and chronic suppressive therapy; two patients died. Nineteen patients completed the two-stage revision process (prosthetic removal, spacer placement, and subsequent replanting). Among them, none showed signs of reinfection or persistence of infection at the last available follow-up. The other twenty-three patients did not replant due to persistent infection: among them, some (the most) underwent spacer retention; others (fewer in number) were submitted to resection arthroplasty and arthrodesis (Girdlestone technique) or chronic suppressive antibiotic therapy; the remaining were, over time, lost to follow-up. Of the patients who concluded the two-stage revision, the ones with high SIRI values (mean 3.08 SD 1.7 and p-value 0.04) and MLR values (mean 0.4 SD 0.2 and p-value 0.02) at the explantation time were associated with a higher probability of infection resolution. Moreover, higher variation in the SIRI and PCR, also defined, respectively, as delta-SIRI (mean -2.3 SD 1.8 and p-value 0.03) and delta-PCR (mean -46 SD 35.7 and p-value 0.03), were associated with favorable outcomes. The results of our study suggest that, in patients with PJI undergoing EP, the SIRI and MLR values and delta-SIRI and delta-PCR values could be predictive of a favorable outcome. The evaluation of these laboratory indices, especially their determination at 4 weeks after removal, could therefore help to determine which patients could be successfully replanted and to identify the best time to replant. More studies analyzing a wider cohort of patients with chronic PJI are needed to validate the promising results of this study.

Prognostic and clinicopathological value of systemic inflammation response index (SIRI) in patients with breast cancer: a meta-analysis

Background Many studies have explored the value of the systemic inflammation response index (SIRI) in predicting the prognosis of patients with breast cancer (BC); however, their findings remain controversial. Consequently, we performed the present meta-analysis to accurately identify the role of SIRI in predicting BC prognosis. Methods PubMed, Embase, Cochrane Library, and Web of Science databases were comprehensively searched between their inception and February 10, 2024. The significance of SIRI in predicting overall survival (OS) and disease-free survival (DFS) in BC patients was analyzed by calculating pooled hazard ratios (HRs) and corresponding 95% confidence intervals (CIs). Results Eight articles involving 2,997 patients with BC were enrolled in the present study. According to our combined analysis, a higher SIRI was markedly associated with dismal OS (HR = 2.43, 95%CI = 1.42–4.15, p < 0.001) but not poor DFS (HR = 2.59, 95%CI = 0.81–8.24, p = 0.107) in patients with BC. Moreover, based on the pooled results, a high SIRI was significantly related to T3–T4 stage (OR = 1.73, 95%CI = 1.40–2.14, p < 0.001), N1–N3 stage (OR = 1.61, 95%CI = 1.37–1.91, p < 0.001), TNM stage III (OR = 1.63, 95%CI = 1.34–1.98, p < 0.001), and poor differentiation (OR = 1.25, 95%CI = 1.02–1.52, p = 0.028). Conclusion According to our results, a high SIRI significantly predicted poor OS in patients with BC. Furthermore, elevated SIRI was also remarkably related to increased tumor size and later BC tumor stage. The SIRI can serve as a novel prognostic biomarker for patients with BC.

Predictive effect of the systemic inflammation response index (SIRI) on the efficacy and prognosis of neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer

BackgroundInflammation is a part of tumours, and inflammatory cells can affect the proliferation, invasion, and development of tumour cells. An increasing number of peripheral blood inflammatory markers have been found to play very important roles in the treatment and prognosis of cancer patients. The systemic inflammatory response index (SIRI) is a newer inflammatory marker, and its role in colorectal cancer, especially in locally advanced rectal cancer, is still unclear.MethodsFrom 2015 to 2020, 198 patients with locally advanced rectal cancer (LARC) who underwent surgery following neoadjuvant chemoradiotherapy (Neo-CRT) were analysed. Patients were categorized into good- and poor- response groups according to their pathological results, and clinical characteristics and baseline parameters were compared between the two groups. The optimal cutoff values for inflammatory indicators were determined using receiver operating characteristic (ROC) analysis. Univariate and multivariate analyses were performed using the Cox proportional hazard model. Survival analysis was performed via the Kaplan‒Meier method.ResultsAfter patients were grouped into good and poor response groups, indicator differences were found in CEA, neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and SIRI. According to the ROC analysis, the NLR (P = 0.015), SII (P = 0.001), and SIRI (P = 0.029) were significant prognostic factors. After univariate and multivariate analyses of the Cox proportional hazards regression model, only the SIRI was found to be an independent prognostic factor for overall survival (OS) and disease-free survival (DFS). Finally, Kaplan‒Meier survival curves also confirmed the ability of the SIRI to predict survival.ConclusionThe preoperative SIRI can be used to predict the response to Neo-CRT in LARC patients and is an independent predictor of OS and DFS in postoperative patients. A high SIRI was associated with poor radiotherapy response and predicted poor OS and DFS.

Systemic Inflammation Response Index and Systemic Immune-inflammation Index for Prediction of Pregnancy Loss: a Case-control Study.

The systemic inflammation response index (SIRI) and systemic immune inflammation index (SII) have recently been investigated as new prognostic markers for obstetric morbidities. However, there are few studies on their predictive role in patients with pregnancy loss. Predicting miscarriages may be useful to support and prevent selected cases.The aim of this study was to investigate the role of SIRI and SII in the prediction of pregnancy loss. A total of 800 patients were included in the retrospective case-control study at a tertiary hospital.Group 1 consisted of 200 patients who had a pregnancy loss for the first time; group 2 consisted of 200 patients with recurrent pregnancy loss; the control group consisted of 400 patients who had a healthy pregnancy. The groups were compared in terms of maternal characteristics, SIRI and SII. Receiver operating characteristic analysis was performed to determine optimal cut-off values for SIRI and SII in predicting pregnancy loss. SIRI and SII were higher in the group with recurrent pregnancy loss than in the control group (p < 0.001).SIRI was higher in the first pregnancy loss group than in the control group (p < 0.001).To predict recurrent pregnancy loss, optimal cut-off values were 1.57 (80% sensitivity, 70% specificity) and 924.12 (74% sensitivity, 57% specificity) for SIRI and SII, respectively. For first pregnancy loss prediction, the optimal cut-off value was 1.38 for SIRI, with 75% sensitivity and 60% specificity. SIRI and SII may be used as inflammatory markers to predict recurrent pregnancy loss. High SIRI values can also help to predict first pregnancy loss.

Prognostic significance of inflammation scores in malignant mesothelioma.

The relationship between inflammatory markers and survival in many cancers has been investigated previously. Inflammatory markers may also offer the possibility of predicting surveillance in patients with malignant mesothelioma. Our study seeks to enhance comprehension of how variables such as the nutritional status and inflammation indices of malignant mesothelioma patients impact the disease's progression and prognosis. This study included patients who were treated at the Erciyes University Medical Oncology Clinic between 2010 and 2022 and diagnosed with malignant mesothelioma. This is a retrospective single-center cohort study. Receiver Operating Characteristic (ROC) analysis was applied to determine the inflammation markers' optimal cut-off values with high sensitivity and specificity. Patients were categorized based on these values. The differences in overall survival (OS) and progression-free survival (PFS) between categorized groups were assessed using Log-rank curves and Kaplan-Meier tests. Multivariate analysis was performed using Cox regression analysis on statistically significant data. The relationship between inflammation markers and malignant mesothelioma survival was evaluated. There are 115 patients in this study. Pre-treatment high neutrophil to lymphocyte ratio (NLR) (HR: 1.34, 95% CI: 1.12-2.83, p=0.04), high pan-immune inflammation value (PIIV) (HR: 2.01, 95% CI: 1.32-4.79, p=0.03), and high systemic inflammation response index (SIRI) (HR: 1.34, 95% CI: 1.2-2.78, p=0.04) were associated with poor OS. Conversely, high advanced lung cancer inflammation index (ALI) (HR: 0.73, 95% CI: 0.53-0.84, p=0.03) and high hemoglobin-albumin-lymphocyte and platelet (HALP) (HR: 0.67, 95% CI: 0.23-0.78, p=0.02) were associated with favorable survival. Our study investigated the prognostic value of various inflammation markers in malignant mesothelioma patients and suggests that composite formulas like NLR, PIIV, SIRI, ALI, and HALP that incorporate CBC cells and nutritional parameters like albumin, height, and weight could more consistently and accurately predict malignant mesothelioma prognosis.

Association between immune-inflammatory indexes and lower urinary tract symptoms: an analysis of cross-sectional data from the US National Health and Nutrition Examination Survey (2005–2008)

ObjectiveThis study aimed to systematically investigate the relationship between immune-inflammatory indexes with lower urinary tract symptoms (LUTSs).DesignCross-sectional study.SettingNational Health and Nutrition Examination Survey (NHANES) (2005–2008).ParticipantsA total of 2709 men with...

Systemic inflammation response index as a clinical outcome evaluating tool and prognostic indicator for hospitalized stroke patients: a systematic review and meta-analysis.

Stroke, which is the main element of cerebrovascular disease (CVD), has become the foremost reason for death and disability on a global scale. The systemic inflammation response index (SIRI), a newly developed and comprehensive indicator, has demonstrated promise in forecasting clinical results for diverse ailments. Nevertheless, the uncertainty surrounding the assessment and prediction of clinical outcomes for stroke patients by SIRI persists, and the conflicting findings from the limited studies conducted on this matter further complicate the situation. Consequently, we performed a thorough systematic review and meta-analysis to explore the correlation between SIRI and the clinical results in individuals suffering from stroke. This research was registered in PROSPERO and carried out following the PRISMA guidelines. A thorough investigation was carried out on PubMed, Embase, the Cochrane Library, Web of Science, and Scopus databases. Furthermore, we conducted a manual search in Chinese databases, such as China national Knowledge Infrastructure (CNKI), WanFang, VIP, and China Biology Medicine (CBM). We assessed the potential for bias in the studies included by utilizing the Newcastle-Ottawa Scale (NOS) tool. Adverse clinical outcomes were the main focus of the study, with secondary endpoints including mortality, the predictive value of SIRI, SIRI values across various endpoints, and clinical parameters associated with subarachnoid hemorrhage (SAH) in relation to low and high SIRI group. Following rigorous evaluation, a grand total of 22 investigations, encompassing a populace of 12,737 individuals, were considered suitable for incorporation in the final analysis. The findings from our meta-analysis indicate a strong and consistent correlation between elevated SIRI levels and adverse functional outcomes, irrespective of the method used to evaluate unfavorable outcomes. Furthermore, increased SIRI values have a strong correlation with mortality rates in both the short and long term. Besides, SIRI is a useful indicator of the severity of SAH. SIRI demonstrates strong predictive ability in identifying unfavorable outcomes and stroke-related pneumonia (SAP), as higher SIRI values are typically linked to negative endpoints. Nevertheless, the meta-analysis indicated that there was no significant increase in the risk of early neurological deterioration (END) and acute hydrocephalus (AHC) in high SIRI group when comparing to low SIRI. This study could potentially pave the way for groundbreaking insights into the relationship between SIRI and stroke patient outcomes, as it appears to be the first meta-analysis to explore this association. Given the critical role of the inflammatory response in stroke recovery, closely monitoring patients with high SIRI levels could represent a promising strategy for mitigating brain damage post-stroke. Thus, further investigation into SIRI and its impact on clinical outcomes is essential. While our initial findings offer valuable insights into this area, continued research is necessary to fully elucidate the potential of SIRI, ideally through dynamic monitoring and large-scale, multi-center studies. Ultimately, this research has the potential to inform clinical decision-making and improve patient outcomes following stroke. https://www.crd.york.ac.uk/prospero/ ; Identifier CRD42023405221.

Interpretable machine learning model based on the systemic inflammation response index and ultrasound features can predict central lymph node metastasis in cN0T1-T2 papillary thyroid carcinoma.

It is arguable whether individuals with T1-T2 papillary thyroid cancer (PTC) who have a clinically negative (cN0) diagnosis should undergo prophylactic central lymph node dissection (pCLND) on a routine basis. Many inflammatory indices, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and systemic immune-inflammatory index (SII), have been reported in PTC. However, the associations between the systemic inflammation response index (SIRI) and the risk of central lymph node metastasis (CLNM) remain unclear. Retrospective research involving 1,394 individuals with cN0T1-T2 PTC was carried out, and the included patients were randomly allocated into training (70%) and testing (30%) subgroups. The preoperative inflammatory indices and ultrasound (US) features were used to train the models. To assess the forecasting factors as well as drawing nomograms, the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were utilized. Then eight interpretable models based on machine learning (ML) algorithms were constructed, including decision tree (DT), K-nearest neighbor (KNN), support vector machine (SVM), artificial neural network (ANN), random forest (RF), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and categorical boosting (CatBoost). The performance of the models was evaluated by incorporating the area under the precision-recall curve (auPR) and the area under the receiver operating characteristic curve (auROC), as well as other conventional metrics. The interpretability of the optimum model was illustrated via the shapley additive explanations (SHAP) approach. Younger age, larger tumor size, capsular invasion, location (lower and isthmus), unclear margin, microcalcifications, color Doppler flow imaging (CDFI) blood flow, and higher SIRI (≥0.77) were independent positive predictors of CLNM, whereas female sex and Hashimoto thyroiditis were independent negative predictors, and nomograms were subsequently constructed. Taking into account both the auROC and auPR, the RF algorithm showed the best performance, and superiority to XGBoost, CatBoost and ANN. In addition, the role of key variables was visualized in the SHAP plot. An interpretable ML model based on the SIRI and US features can be used to predict CLNM in individuals with cN0T1-T2 PTC.

Development of a nomogram for predicting survival of breast cancer patients with neoadjuvant chemotherapy: a dynamic analysis for systemic inflammation response index.

The systemic inflammation response index (SIRI) has been reported to associate with survival outcomes in breast cancer patients. However, the effects of baseline SIRI and SIRI change after neoadjuvant chemotherapy (NACT) have not been thoroughly investigated. This study aimed to evaluate the role of baseline SIRI and SIRI change after NACT in predicting survival outcomes, and establish a nomogram based on SIRI. A total of 260 patients diagnosed with breast cancer who received NACT between January 2014 and December 2018 at our hospital were included. The clinical data were retrospectively collected from the medical records management system. The associations between clinicopathological factors and baseline SIRI, pathological complete response (pCR) were analyzed by Student's t-test, Chi-squared test, or Fisher's exact test. The association between clinicopathological factors and disease-free survival (DFS) was evaluated by univariate and multivariate Cox regression analyses. Patients with a tumor-node-metastasis (TNM) stage of I, II, and III were 1.9%, 20.0%, and 78.1% respectively. The median follow-up time was 40 months, and 74 (28.5%) patients had cancer recurrence during the follow-up. Both in the univariate and multivariate analysis, Ki-67, pCR, and baseline SIRI were independent factors associated with DFS. Patients with low baseline SIRI had prolonged DFS compared with those with high baseline SIRI [≤1.6×109 vs. >1.6×109, hazard ratio (HR) =0.545, P=0.028]. In addition, SIRI change after NACT was also an independent factor associated with DFS, and patients with minor SIRI change had longer DFS than patients with major SIRI change (>50% or <-30% vs. ≤50% and ≥-30%, HR =1.721, P=0.037). Nomograms were established based on Ki-67, pCR, and baseline SIRI or SIRI change after NACT with a concordance index of 0.665 and 0.663 respectively, and the nomogram provided a convenient tool for predicting the probability of DFS. The baseline SIRI and SIRI change after NACT could act as potential biomarkers for predicting survival outcomes in breast cancer. Besides, the nomogram with SIRI is an economic and convenient tool for predicting DFS. Larger prospective studies are needed to verify the results.

Prognostic value of systemic inflammation response index in hepatoblastoma patients receiving preoperative neoadjuvant chemotherapy.

Inflammation is closely associated with tumor development and patient prognosis. The objective of this study is to assess the prognostic value of the preoperative inflammatory indexes in pediatric hepatoblastoma patients who receive neoadjuvant chemotherapy. A retrospective analysis was performed on clinical and pathological data of 199 hepatoblastoma patients who underwent hepatectomy with preoperative neoadjuvant chemotherapy from January 2015 to June 2020. The receiver operating characteristic curve was used to evaluate the prognostic value of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) in predicting OS and EFS. Patients were grouped based on optimal cutoff values of preoperative inflammatory indexes. Survival rates were calculated using the Kaplan-Meier method, and survival outcomes were compared between groups using the log-rank test. Univariate and multivariate Cox proportional hazards regression models were used to identify independent prognostic factors, and a nomogram was constructed using R software to predict the probability of OS. The receiver operating characteristic curve showed prognostic value for OS, not EFS, in preoperative inflammatory indexes. Patients were categorized into low/high groups: SII ≤ 266.70/higher, NLR ≤ 1.24/higher, PLR ≤ 85.25/higher, and SIRI ≤ 0.72/higher. High NLR, PLR, SII, and SIRI groups had significantly lower 5-year OS than their low counterparts (all p-value < 0.05). The Cox analysis identified four independent prognostic factors: SIRI (HR=2.997, 95% CI: 1.119-8.031), microvascular invasion (HR=2.556, 95% CI: 1.14-5.73), the post-treatment extent of disease (POSTTEXT) staging (IV vs. I: HR=244.204, 95% CI:11.306-5274.556), and alpha-fetoprotein (>100 ng/ml: HR=0.11, 95% CI: 0.032-0.381) for hepatoblastoma patients with neoadjuvant chemotherapy. High SIRI group had more patients with adverse NLR, SII, and POSTTEXT III (all p-value < 0.05). Independent prognostic factors led to an OS nomogram with a concordance index of 0.85 (95% CI: 0.78-0.91, p-value = 1.43e-27) and the calibration curve showed a good fit between the prediction curve and the true curve. SIRI is an independent prognostic factor of hepatoblastoma patients receiving neoadjuvant chemotherapy. The OS nomogram based on SIRI, POSTTEXT staging, MiVI, and AFP can be used to assess the prognosis of those patients.

Prognostic significance of the systemic inflammation response index in gastrointestinal malignancy patients: a pooled analysis of 10,091 participants.

Background: We performed a meta-analysis to investigate the association of the systemic inflammation response index (SIRI) with long-term survival outcomes in patients with gastrointestinal malignancy. Methods: PubMed, Web of Science and Embase were searched for relevant studies evaluating the prognostic significance of the SIRI in gastrointestinal malignancies until May 2023. Results: 30 studies with 10,091 patients were included. The pooled results identified that patients in the high SIRI group had a worse overall survival and disease-free survival, which was observed across various tumor types, tumor stages and primary treatments. Conclusion: An elevated SIRI is negatively associated with worse survival outcomes of gastrointestinal malignancy patients and can be used as a risk stratification index for gastrointestinal malignancies.

High systemic inflammation response index level is associated with an increased risk of lower extremity deep venous thrombosis: a large retrospective study

Background The association between inflammation and venous thromboembolism (VTE) has attracted increasing research interest. Recently, the systemic inflammation response index (SIRI) has been proposed as a novel inflammatory biomarker, but its potential association with lower extremity deep venous thrombosis (LEDVT) has not been investigated. Thus, this study aimed to explore the association between SIRI and LEDVT risk in a large sample over a 10-year period (2012–2022). Methods All hospitalized patients who underwent lower extremity compression ultrasonography (CUS) examinations were consecutively identified from our hospital information system database. Multivariate logistic regression analysis was used to investigate the association between SIRI and LEDVT risk. Sensitivity, restricted cubic spline and subgroup analyses were also performed. Results In total, 12643 patients were included, and 1346 (10.6%) LEDVT events occurred. After full adjustment, a higher SIRI level was significantly associated with an increased risk of LEDVT (odds ratio [OR] = 1.098, 95% confidence interval [CI]: 1.068–1.128, p < 0.001), and patients in quartile 4 had a 2.563-fold higher risk of LEDVT than those in quartile 1 (95% CI: 2.064–3.182, p < 0.001). A nonlinear relationship was observed (P for nonlinearity < 0.001), with an inflection point of 4.17. Below this point, each unit increase in SIRI corresponded to a 35.3% increase in LEDVT risk (95% CI: 1.255–1.458, p < 0.001). No significant difference was found above the inflection point (OR = 1.015, 95% CI: 0.963–1.069, p = 0.582). Sensitivity and subgroup analyses confirmed the robustness of the association. This association also existed in both distal and proximal LEDVT. Conclusion A High SIRI is significantly associated with an increased risk of LEDVT in hospitalized patients. Given that the SIRI is a readily available biomarker in clinical settings, its potential clinical use deserves further exploration.

The change of systemic inflammation response index in the treatment of patients with myasthenia gravis undergoing thymectomy: A retrospective, follow-up study

Background: This study aims to investigate the role of neutrophil-tolymphocyte ratio, platelet-to-lymphocyte ratio, monocyte-to-lymphocyte ratio, and systemic inflammation response index in patients with myasthenia gravis, thymomas and thymic hyperplasia and to identify the relationship between the inflammation response and disease activity. Methods: Between January 2010 and December 2018, a total of 97 patients (71 males, 26 females; mean age: 36.7±16.3 years; range, 15 to 76 years) who underwent extended thymectomy with the diagnosis of myasthenia gravis were retrospectively analyzed. The patients were divided into two groups as the patient group (n=42) and the control group (n=55). Neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, monocyteto-lymphocyte ratio, and systemic inflammation response index were measured one day prior to and one month after surgery. Results: The patients with thymoma were older with a higher mean pre-systemic inflammation response index value. Preoperative systemic inflammation response index, neutrophil-to-lymphocyte ratio, and monocyte-to-lymphocyte ratio were significantly higher in patients with thymoma. A preoperative systemic inflammation response index value of less than 0.62 was accepted to indicate thymic hyperplasia and a postoperative systemic inflammation response index value higher than 2.94 was indicative of thymoma. In myasthenic patients whose steroid dose was increased and/or remained the same at the first month after surgery, postoperative monocyte-to-lymphocyte ratio and systemic inflammation response index values were found to be higher compared to preoperative values (p=0.006 and p=0.032, respectively). Patients whose pyridostigmine dose was increased and/or remained the same had significantly higher systemic inflammation response index values postoperatively (p=0.029). Conclusion: The precise cut-off values of systemic inflammation response index may be helpful for the surgeon to predict the surgical outcome and post-systemic inflammation response index may be a predictive marker for estimating postoperative treatment changes.

The association and prognostic value of systemic inflammatory response index with short and long-term mortality in patients with sepsis.

This study evaluated the association and prognostic significance of the systemic inflammation response index (SIRI) with mortality in sepsis. In this cohort study, the sepsis patients were retrieved from the Medical Information Mart for Intensive Care III (MIMIC-III) and MIMIC-IV intensive care unit (ICU) databases. SIRI was calculated by using the neutrophil, monocyte, and lymphocyte counts. The outcomes were 28-day mortality, 1-year mortality, and 28 days to 1-year mortality. The Cox proportional hazards model with a hazard ratio (HR) and a 95% confidence interval (CI) was used to investigate the association and prognostic value of SIRI with mortality in sepsis. Subgroup analyses of the associations of SIRI with 28-day and 1-year mortality in sepsis were based on age, gender, Simplified Acute Physiology Score II (SAPSII), Sequential Organ Failure Assessment (SOFA), and presence or absence of septic shock. The receiver operating characteristic (ROC) curve was used to compare the predictive performances of SIRI, SOFA and SAPS II for mortality in sepsis. Of the 4239 patients included, 1339 patients suffered from 28-day mortality, 2085 patients suffering from 1-year mortality, and 746 (25.72%) suffered from 28 days to 1-year mortality. High SIRI levels exhibited higher risks of 28-day mortality (HR: 1.15, 95% CI: 1.03-1.29, P = .010), 1-year mortality (HR: 1.14, 95% CI: 1.04-1.24, P = .003), and 28 days to 1-year mortality (HR: 1.16, 95% CI: 1.01-1.35, P = .047) in sepsis. A higher SIRI was reported related to 28-day mortality and 1-year mortality in sepsis patients with female gender, with SOFA < 8, with SAPS II < 44, and in sepsis patients without sepsis shock. The AUC of SIRS, SOFA, and SAPS II in predicting 28-day mortality in sepsis were 0.726, 0.591, and 0.644, respectively. The AUC of SIRI in predicting 1-year mortality in sepsis was 0.761, higher than the AUC values of SOFA and SAPS II. A higher AUC value of SIRI compared with SOFA, and SAPS II in predicting 28 days to 1-year mortality was observed. Elevated SIRI was associated with an increased risk of mortality in sepsis. SIRI is an independent prognostic biomarker of mortality in sepsis.

The systemic inflammation indexes predict all-cause mortality in peritoneal dialysis patients

Background Chronic inflammation is a common complication in peritoneal dialysis (PD) patients. The aim of this study is to investigate the capacity of aggregate index of systemic inflammation (AISI), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) to predict all-cause mortality in PD patients. Methods This was a single-center retrospective study. The optimal cutoff values were identified by receiver operating characteristic (ROC) curve analysis. The area under the curve (AUC) was calculated to evaluate the predictive ability of these indexes. The Kaplan–Meier curves and log-rank test were performed to estimate cumulative survival rate. Cox proportional hazards regression analyses were conducted to determine the independent prognostic power of inflammation indexes. Results A total of 369 incident PD patients were involved. During a median follow-up period of 32.83 months, 65 patients (24.2%) died. The ROC analysis indicated the largest value of AUC was obtained for SII (AUC = 0.644, 95% CI = 0.573–0.715, p < .001), followed in order by AISI (AUC = 0.617, 95% CI = 0.541–0.693, p = .003), and SIRI (AUC = 0.612, 95% CI = 0.535–0.688, p  = .004). The Kaplan–Meier survival curves revealed significantly lower survival rate with higher AISI (p  = .001), higher SSI (p  = .001), and higher SIRI (p  = .003). Even after adjustment for the confounding factors, higher AISI [hazard ratio (HR)=2.508, 95% confidence intervals (CI)=1.505–4.179, p < .001), SII (HR = 3.477, 95% CI = 1.785–6.775, p < .001), and SIRI (HR = 1.711, 95% CI = 1.012–2.895, p  = .045) remained as independent predictors of all-cause mortality. Conclusions The higher AISI, SII, and SIRI were independent indicators of all-cause mortality in PD patients. Furthermore, they could provide comparable predictive value and assist clinicians to ameliorate PD management.

Systemic inflammation response index and systemic immune-inflammation index are associated with severity of acute pancreatitis

&lt;b&gt;Aim: &lt;/b&gt;Acute pancreatitis (AP) is a disease with inflammation, and patients present with severe acute upper abdominal pain in emergency departments. AP can result in higher mortality as its clinical severity increases. Therefore, in this study, we want to investigate the clinical utility of the systemic inflammation response index (SIRI) and systemic immune-inflammation index (SII) in showing the severity of AP.&lt;br /&gt; &lt;b&gt;Material and methods:&lt;/b&gt; Among the patients admitted to our emergency department between January 2020 and December 2022, 201 patients diagnosed with AP were included in the study. These patients were divided into two groups according to the severity of the disease as mild and severe AP (MAP and SAP). Demographic data and laboratory data of the patients (white blood cell count, such as SIRI, SII and C-reactive protein, SIRI, SII and C-reactive protein) were recorded. Differences between groups of AP patients divided according to disease severity were analyzed.&lt;br /&gt; &lt;b&gt;Results: &lt;/b&gt;165 (82.1%) patients had MAP and 36 (17.9%) patients had SAP. 52.8% of the patients were male. The mean of the SAP group was significantly higher than the SII MAP group (3165.71±3058.42 vs.1043.31±849.15; p&amp;lt;0.001). In addition, SII levels were significantly higher in the SAP group compared to MAP (11.19±6.27 vs. 3.12±3.01; p&amp;lt;0.001). In regression analysis, CRP, SIRI and SII was found to be able to predict SAP in patients with AP. &amp;nbsp;The power of SIRI and SII were found to be higher in predicting SAP [AUC for SIRI: 0.890; [AUC for SII: 0.859].&lt;br /&gt; &lt;b&gt;Conclusion: &lt;/b&gt;High SII and SIRI are useful markers that can show the severity of AP.&lt;br /&gt; &lt;b&gt;Key words: &lt;/b&gt;acute pancreatitis severity, SII, SIRI, biomarker

Prognostic Value of Systemic Inflammation Response Index in Acute Type A Aortic Dissection.

The study aimed to evaluate the prognostic value of preoperative systemic inflammation response index (SIRI) for acute type A aortic dissection (ATAD) following open surgery. Totally, 410 ATAD patients underwent open surgery from 2019 to 2021 were enrolled in the study. Among the patients, the in-hospital mortality was 14.4%. Cox regression (95%CI 1.033-1.114p < 0.001) and receiver operating characteristic curve analysis (AUC = 0.718, p < 0.001) demonstrated the prognostic role of SIRI for in-hospital mortality after surgery. The optimal cut-off value of SIRI for in-hospital mortality was identified as 9.43 by maximally selected Log-Rank statistics. The patients were divided into high SIRI group (SIRI ≥ 9.43) and low SIRI group (SIRI < 9.43)) after the linear inverse relationship between SIRI and hazard ratio for in-hospital mortality was demonstrated by restricted cubic spline analysis (p = 0.0742). The Kaplan-Meier analysis illustrated that in-hospital mortality increased significantly in high SIRI group (p < 0.001). In addition, elevating SIRI was significantly associated with the incidence of coronary sinus tear (95%CI 1.020-4.475p = 0.044). Furthermore, the incidence rate of postoperative complications including renal failure (p < 0.001) and infection (p = 0.019) was higher in high SIRI group. The study indicated that preoperative SIRI could provide strong prognostic value for in-hospital mortality in ATAD patients following open surgery. Thus, SIRI was a promising biomarker for risk stratification and management prior to open surgery.

The systemic inflammation response index: An independent predictive factor for survival outcomes of bladder cancer stronger than other inflammatory markers.

We aimed to evaluate the prognostic value of the preoperative systemic inflammation response index (SIRI) to predict the outcomes after open radical cystectomy (RC). We conducted a retrospective analysis of the institutional cystectomy database and identified 241 consecutive RC patients. Patient demographics and oncologic outcomes were noted. We calculated the SIRI as previously described (NeutrophilxMonocytes/Lymphocytes), based on the blood-tests at the day before surgery and a minimum >30-day later. Median follow-up time was 20 months (interquartile range 9-52). Two, 3 and 5 years recurrence free (RFS) and overall survival (OS) rates were 60.6%, 57.1%, 48.9%, and 54.7%, 47.0%, 37.2%, respectively. Patients with preoperative SIRI >1.91 had significantly higher recurrence rates (P < 0.001) and lower OS (P < 0.001). For internal validation, we evaluated postoperative SIRI >1.91 (repeatability testing), and again found significantly higher recurrence rates (P < 0.001) and lower OS (P = 0.004). Persistently high SIRI increased the recurrence and death risk 5.79 and 2.87 fold, respectively. SIRI was also a significant independent predictive factor for RFS and OS in the multivariable cox regression analyses (P < 0.05). SIRI improved the discriminative ability of the models 1.5% to 4.2% and this was quite higher than other inflammatory markers (NLR, MLR, PLR, SII) in all models. Patients with SIRI >1.91 had significantly higher recurrence and lower OS rates. The cut-off value is validated internally. SIRI is an independent predictive factor for RFS and OS. The contribution of SIRI in the cox models is higher than other inflammatory markers.