High Systemic Immune-inflammation Index Research Articles

Systemic immune-inflammation index upon admission correlates to post-stroke cognitive impairment in patients with acute ischemic stroke.

The purpose of this prospective study was to evaluate the association of systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI), with PSCI in patients with acute ischemic stroke (AIS). First-onset AIS patients were consecutively included from January 1, 2022 to March 1, 2023. The baseline information was collected at admission. Fasting blood was drawn the next morning. Cognitive function was assessed by the Montreal Cognitive Assessment (MoCA) 3 months after onset. Logistic regression analysis was performed to explore the correlation between SII, SIRI, and PSCI. Receiver operating characteristic (ROC) was conducted to evaluate the predictive ability of SII. 332 participants were recruited, and 193 developed PSCI. Compared with patients without PSCI, the patients with PSCI had higher SII (587.75 (337.42, 988.95) vs. 345.66 (248.44, 572.89), P<0.001) and SIRI (1.59 (0.95, 2.84) vs. 1.02 (0.63, 1.55), P=0.007). SII and SIRI negatively correlated with MoCA scores (both P<0.05). The multivariable logistic regression analysis indicated that SII was independently associated with PSCI (P<0.001), while SIRI was not. The optimal cutoff for SII to predict PSCI was 676.83×109/L. A higher level of SII upon admission was independently correlated to PSCI three months later in AIS patients.

Lower Serum Vitamin C Is Associated with Higher Systemic Immune Inflammation Index: A Population-Based Study

Lower Serum Vitamin C Is Associated with Higher Systemic Immune Inflammation Index: A Population-Based Study

Evaluation of systemic immune-inflammation index for predicting severity of lower extremity arterial disease.

Predictive value of systemic immune-inflammation index (SII) has been shown in clinical outcomes and complexity of coronary artery disease, acute coronary syndrome, and heart failure. We sight to evaluate value of SII in patients with lower extremity arterial disease (LEAD). A total of 271 patients diagnosed with LEAD were included to our study. Blood samples of the patients were collected and analyzed for biochemical variables and complete blood count parameters. SII value of each patient was calculated. The complexity of atherosclerotic disease was classified according to Trans-Atlantic Inter-Society Consensus (TASC II) classification. Patients with TASC C-D were older than patients in TASC A-B group (63.06 ± 9.24years and 60.85 ± 8.75years, respectively). Other co-morbidities were comparable in both groups. Hemoglobin level and lymphocyte count were significantly lower, neutrophil, platelet counts, and SII values were significantly higher in patients with TASC C-D disease compared to that of patients with TASC A-B disease. SII showed significant correlation with the severity of LEAD (r = 0.363, p < .001). SII value of 664.24 predicted TASC C-D disease with a sensitivity and specificity of 60.8% and 73.3%, respectively. Results of multivariate logistic regression analysis showed that SII had higher odds ratio compared to platelet, neutrophil, and lymphocyte counts. Higher SII may indicate probability of more complex LEAD. This relationship seems plausible in terms of similar pathophysiology of coronary artery disease and peripheral artery disease.

A Clinical Nomogram for Predicting Overall Survival in Patients With T1/T2 Penile Squamous Cell Carcinoma

BackgroundTo evaluate the overall survival (OS) and construct a nomogram to predict the OS of patients with penile squamous cell carcinoma (PSCC). MethodsThis retrospective study analyzed data of patients with PSCC from the First Affiliated Hospital of Soochow University between 2012 and 2022. R software was used to explore factors influencing OS in PSCC. Kaplan–Meier method and log-rank test were employed for OS estimation. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify these factors. A nomogram was created to identify the independent prognostic factors. The model was evaluated by concordance index, receiver operating characteristic (ROC) curves, and calibration plots. ResultsA total of 159 patients with T1/T2 PSCC were included in the analysis. Patients with T2/N2 stage, older age, larger tumor size, high preoperative systemic immune-inflammation index (SII), and poor preoperative nutrition had a higher incidence of poor OS. Age, T/N stage, tumor size and SII were identified as independent prognostic indicators. A prognostic nomogram was formulated, and its predictive accuracy for estimating OS in PSCC patients was validated through ROC curves and calibration plots. ConclusionThe nomograms, based on age, T/N stage, tumor size, and high preoperative SII, provide a valuable tool for predicting 1-, 2-, and 3-year OS in patients with T1/T2 PSCC without distant metastases.

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.

Predictive value of the systemic immune-inflammation index on one-year mortality in geriatric hip fractures.

Geriatric hip fractures are associated with a high incidence of mortality. This study examines the predictive value of the systemic immune-inflammation index (SII) on one-year mortality in elderly hip fracture patients. A single-center retrospective study was conducted between February 2017 and October 2020. Three hundred and eleven surgically treated consecutive hip fracture patients were included in the study. Admission, postoperative first day, and postoperative fifth-day SII values were calculated. The receiver operating characteristic (ROC) curve was used to calculate the cut-off values, and patients were divided into high and low groups according to these cut-off values. After univariate Cox regression analysis, significant factors were included in the multivariate Cox proportional hazards model to adjust the effect of covariates and explore independent predictive factors associated with mortality. Further subgroup analysis was performed to evaluate the accuracy of the results for different clinical and biological characteristics. The mean age was 80.7 ± 8.0 years, and women made up the majority (67.8%) of the patients. The one-year mortality rate was 28.0%. After univariate and multivariate analyses, high postoperative fifth-day SII remained an independent predictor of one-year mortality (adjusted HR 2.16, 95% CI 1.38-3.38, p = 0.001). Older age, male gender, Charlson comorbidity index (CCI) ≥ 2, and hypoalbuminemia were found to be other independent predictors. The optimal cut-off value of the postoperative fifth-day SII was calculated at 1751.9 units (p < 0.001). The postoperative fifth-day SII is a simple and useful inflammatory biomarker for predicting one-year mortality in patients with hip fracture.

The Relationship Between Composite Inflammatory Ratios and Complications of Massive Ischaemic Stroke.

To investigate the relationship between complications of massive cerebral infarction (MCI) and composite inflammatory ratios. A case-control study. Place and Duration of the Study: Department of Neurology, Affiliated Hospital of Putian University, Putian, China, from January 2019 to November 2021. Eighty-two patients with MCI underwent blood tests within 24 hours of admission. Complications such as cerebral herniation, haemorrhage transformation (HT), and stroke-associated pneumonia (SAP) were evaluated based on imaging examinations. The prognosis was assessed using the modified Rankin Scale score (mRS) at discharge. Among the 82 patients, the cerebral herniation group had higher levels of systemic immune inflammation index (SII) and neutrophil-to-lymphocyte ratio (NLR) compared to the non-cerebral herniation group. MCI patients who developed HT had higher levels of SII, NLR, mean platelet volume/platelet (MPV/PLT), and platelet-to-lymphocyte ratio (PLR). The SAP group had higher levels of MPV/PLT and NLR compared to the non-SAP group. The poor prognosis group had higher SII and NLR levels but a lower lymphocyte-to-monocyte ratio (LMR) compared to the good prognosis group. NLR showed high accuracy in predicting complications and the short-term prognosis of MCI. SII was linked to cerebral herniation, HT, and the short-term prognosis of MCI. MPV/PLT was found to be related to SAP and HT caused by MCI. LMR may act as a protective factor for the short-term prognosis of MCI. Massive cerebral infarction, Neutrophil-to-lymphocyte ratio, Systemic immune inflammation index, Prognosis.

Association of systemic inflammatory markers with postoperative arrhythmias in esophageal cancer: a propensity score matching

BackgroundThe severity and prognosis of an array of inflammatory diseases have been predicted using systemic inflammatory indices, such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio (LMR), derived neutrophil-to-lymphocyte ratio (dNLR), and systemic immune inflammation index (SII). The purpose of this study was to examine the association between systemic inflammatory markers and postoperative arrhythmias (PA) in esophageal cancer patients.MethodsIn the study, laboratory-related parameters were gathered and examined in 278 patients (non-PA = 221, PA = 57). Fit separate propensity score matching (PSM) within subgroup strata (surgery approaches); match within strata, and aggregate for main analysis. Finally, we established a 1:1(57:57) model. The ability of inflammatory makers on the first post-esophagectomy day to distinguish PA from postoperative non-arrhythmia (non-PA) by receiver operating characteristic (ROC) analysis.ResultsOn the first post-esophagectomy day, there was a greater difference between PA and non-PA in terms of white blood cell (WBC) and neutrophil (NE), Neutrophil percentage (NE%), NLR, dNLR, LMR, and SII. After PSM, the following variables were substantially different between non-PA and PA: NE%, NLR, dNLR, and SII. It was found that WBC, NE, NE%, NLR, dNLR, LMR, and SII had the area under the curve (AUC) that was higher than 0.500 in ROC analysis, with NLR and SII having the highest AUC (AUC = 0.661). The indicators were subjected to binary logistic regression analysis, which increased the indicators' predictive ability (AUC = 0.707, sensitivity = 0.877).ConclusionOn the first post-esophagectomy day, systemic inflammatory indicators were significantly correlated with both PA and non-PA, and high SII and NLR are reliable markers of PA.

Systemic immune-inflammation index as a prognostic marker in HER2-positive breast cancer patients undergoing trastuzumab therapy

The prognostic value of SII (Systemic Immune-Inflammation Index) in HER-2-positive breast cancer (BC) patients, regardless of whether they receive trastuzumab treatment, and its potential value to distinguish patients who may benefit from trastuzumab therapy, warrant further investigation. Clinical data was collected from 797 HER-2-positive BC patients between July 2013 and March 2018. Baseline data differences were adjusted with propensity score matching. Univariate and multivariate analyses explored the correlation between clinical pathological factors, SII, and DFS. Four groups were established. Based on the baseline SII values of the participants, patients who did not receive trastuzumab treatment were divided into Group 1 (Low-SII) and Group 2 (High-SII), where SII had no predictive value for prognosis between groups. Participants who received trastuzumab treatment were also divided into two groups: the Low-SII group (Group 3) and the High-SII group (Group 4). The 5-year DFS was significantly higher in Group 3 than in Group 4 (91.76% vs. 82.76%, P = 0.017). Furthermore, multivariate analysis demonstrated a significant association between high SII and shorter DFS (HR = 3.430, 95% CI = 1.830–6.420, P < 0.001). In HER-2-positive BC patients treated with trastuzumab, those with lower SII showed a longer DFS, suggesting that SII may help in identifying patients who benefit from trastuzumab therapy.

The relationship between disease activity with pan-immune-inflammatory value and systemic immune-inflammation index in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic, systemic inflammatory disease. Immune system cells have an important role in RA. Our aim was to investigate the relationship between disease activity, systemic immune-inflammation index (SII), and pan-immune-inflammation value (PIV) levels in RA patients. We planned to investigate whether these 2 measurements have an advantage over each other. About 67 patients diagnosed with RA and 49 healthy controls included in this study. RA was diagnosed based on 2010 ACR classification criteria. In this cross-sectional study, peripheral blood tests, C-reactive protein (CRP), hemogram, and erythrocyte sedimentation rate levels were noted after the physical examination of all participants. PIV was calculated with the formula: (neutrophil count × platelet count × monocyte count) / lymphocyte count. SII was calculated as follows: (neutrophil count × monocytes count) / lymphocyte count. The disease activity score 28 (DAS28) were noted in patients with RA. CRP values of active RA group were significantly higher than remission RA and control groups (P < .001), control and remission RA groups were similar (P = .86). PIV and SII are significantly higher in active RA than remission RA and control (P < .001, P < .001) higher in remission RA than control (P < .001, P < .001). Receiver operating characteristic curve analysis in predicting remission compared to the control group, CRP was not significant, PIV and SII was significant and PIV has higher sensitivity and sensitivity, a PIV value of > 217.31 have sensitivity 75.0% and specificity 85.7%. CRP, PIV, and SII are statistically significant in predicting active RA compared to the remission RA and control group. Our findings show that PIV, and SII are easy, inexpensive and reliable markers predicting remission in RA patients. CRP was not significant compared to remission RA and control group, PIV and SII was significant and PIV has higher sensitivity and specificity than SII in the remission group in RA. Patients with high disease activity, PIV, SII, and CRP levels were effective in showing disease activity compared to RA remission group and healthy controls.

The predictive role of systemic immune-inflammation index in non-ischemic cardiomyopathy

Aims: The systemic immune-inflammation index (SII), a useful marker of systemic inflammation, has been shown to be associated with cardiovascular diseases in previous studies. Inflammation is known to have a significant role in heart failure, but no study has evaluated the relationship between inflammatory parameters and prognosis in patients with non-ischemic cardiomyopathy (NICM). This study aimed to explore the relationship between SII and long-term mortality in patients with non-ischemic cardiomyopathy.&#x0D; Methods: The study enrolled 326 consecutive patients with NICM. The median 25-month follow-up mortality results of the patients were recorded retrospectively. SII, a combined index based on the count of three parameters, was calculated as follows: neutrophil count x platelet count/lymphocyte count. Patients with a higher SII value than the median SII were accepted as having a high SII, and the remaining patients were defined as having a low SII. The survival curves of the patients with high and low SII values during the study period were analyzed using the Kaplan-Meier method.&#x0D; Results: The mean age of the participants was 46.6 years. The mean SII value was 598.4 in patients without mortality and 722.7 in those with mortality. In the multivariate logistic regression analysis, SII was found to be an independent predictor of mortality. The median SII value of the patients who participated in the study was 644. Upon dividing the patients into two groups according to the median SII value, the mortality rate was determined to be 48.4% in the high SII group and 27.4% in the low SII group.&#x0D; Conclusion: High SII values were observed to be associated with long-term mortality in patients with NICM. SII, which is easily accessed and simply calculated, can be used to predict mortality risk in these patients. Prospective and larger cohort studies are needed to clarify the causality of this relationship.

Systemic immune-inflammation Index is associated with chronic kidney disease in the U.S. population: insights from NHANES 2007-2018.

The systemic immune-inflammation index (SII), a novel and systematic inflammatory biomarker that is associated with chronic kidney disease (CKD), has not received much attention. This study aimed to investigate the relationship between SII and CKD in the United States (U.S.) population. Our study ultimately included a nationally representative sample of 10,787 adults who participated in the 2007-2018 National Health and Nutrition Examination Survey. Weighted multivariate logistic regression was used to assess the correlation between SII and CKD, and a restricted cubic spline (RCS) model was subsequently used to explore the non-linear relationship between SII and CKD. Subgroup analyses were performed to further the effects of other covariates on the relationship between SII and CKD. Following confounder adjustment, a higher SII was related to the incidence of CKD (OR =1.36; 95% CI, 1.07-1.73; p =0.01), as validated by multivariable logistic regression. The RCS curve revealed a non-linear positive correlation between SII/1000 and CKD incidence (p for non-linear =0.0206). Additionally, subgroup analysis confirmed a stronger correlation for male participants (OR =2.628; 95% CI, 1.829-3.776) than for female participants (OR =1.733; 95% CI, 1.379-2.178) (p for interaction =0.046). SII is positively associated with the incidence of CKD among U.S. adults, especially in males. However, further studies are needed to confirm our findings and explore the causal factors that can contribute to the prevention and treatment of CKD.

Inflammation mediates the relationship between diet quality assessed by healthy eating index-2015 and metabolic syndrome.

Metabolic syndrome is a cluster of metabolic disorders, including obesity, hypertension, hyperglycemia, and abnormal lipid levels. However, researches on the association between overall dietary quality measured by the Healthy Eating Index-2015 (HEI-2015) and the risk of metabolic syndrome is still lacking. This study utilized data from four cycles (2011-2018) of the National Health and Nutrition Examination Survey (NHANES) database, including 17,582 participants. Logistic regression analysis was employed to explore the correlation between HEI and the risk of metabolic syndrome. Additionally, mediation analysis was conducted to examine the effects of Systemic Immune-Inflammation Index (SII) and serum uric acid as potential mediators between HEI and metabolic syndrome risk. Weighted quantile sum (WQS) regression evaluated the composite exposure impact of the 13 components of the HEI on metabolic syndrome, as well as the proportion of their weights. Higher dietary quality measured by HEI-2015 (at the 75th percentile) was negatively correlated with the risk of metabolic syndrome (OR=0.80, 95%CI=0.72-0.89, P=0.003). Higher SII and serum uric acid levels were identified as risk factors for metabolic syndrome (P for trend<0.001). Approximately 37.5% of the effect of HEI on metabolic syndrome occurrence was mediated by SII (Indirect effect=-0.002, 95%CI (-0.003,-0.001), Direct effect=-0.022, 95%CI (-0.0273,-0.015)). Additionally, 25% of the effect of HEI on metabolic syndrome occurrence was mediated by serum uric acid levels (Indirect effect=-0.006, 95%CI (-0.010,-0.012), Direct effect=-0.024, 95%CI (-0.041,-0.009)). WQS regression analysis revealed the highest weighted proportions for seafood and plant proteins (25.20%) and sodium (17.79%), while the weight for whole fruit was the lowest (0.25%). Better dietary quality measured by HEI-2015 was associated with a lower likelihood of metabolic syndrome. Higher SII and serum uric acid levels were identified as risk factors for metabolic syndrome and potential mediators.

Association of blood cell-based inflammatory markers with gut microbiota and cancer incidence in the Rotterdam study.

The immune response-gut microbiota interaction is implicated in various human diseases, including cancer. Identifying the link between the gut microbiota and systemic inflammatory markers and their association with cancer will be important for our understanding of cancer etiology. The current study was performed on 8090 participants from the population-based Rotterdam study. We found a significant association (false discovery rate [FDR] ≤0.05) between lymphocytes and three gut microbial taxa, namely the family Streptococcaceae, genus Streptococcus, and order Lactobacillales. In addition, we identified 95 gut microbial taxa that were associated with inflammatory markers (p < 0.05). Analyzing the cancer data, we observed a significant association between higher systemic immune-inflammation index (SII) levels at baseline (hazard ratio (HR): 1.65 [95% confidence interval (CI); 1.10-2.46, p ≤ 0.05]) and a higher count of lymphocytes (HR: 1.38 [95% CI: 1.15-1.65, p ≤ 0.05]) and granulocytes (HR: 1.69 [95% CI: 1.40-2.03, p ≤ 0.05]) with increased risk of lung cancer after adjusting for age, sex, body mass index (BMI), and study cohort. This association was lost for SII and lymphocytes after additional adjustment for smoking (SII = HR:1.46 [95% CI: 0.96-2.22, p = 0.07] and lymphocytes = HR: 1.19 [95% CI: 0.97-1.46, p = 0.08]). In the stratified analysis, higher count of lymphocyte and granulocytes at baseline were associated with an increased risk of lung cancer in smokers after adjusting for age, sex, BMI, and study cohort (HR: 1.33 [95% CI: 1.09-1.62, p ≤0.05] and HR: 1.57 [95% CI: 1.28-1.92, p ≤0.05], respectively). Our study revealed a positive association between gut microbiota, higher SII levels, and higher lymphocyte and granulocyte counts, with an increased risk of developing lung cancer.

Multivariate analysis of prognostic factors in patients with lip squamous cell carcinoma after surgery

BackgroundLip squamous cell carcinoma (LSCC) was one of the most common cancer types of head and neck tumors. This study aimed to find more predictors of the prognosis in postoperative LSCC patients.MethodsA total of 147 LSCC patients between June 2012 and June 2018 were collected from two tertiary care institutions. There were 21 clinicopathological factors included and analyzed in our study. The univariate and multivariate Cox regression analyses were performed to find the independent prognostic factors for predicting progression-free survival (PFS) and overall survival (OS) in postoperative LSCC patients. The role of adjuvant radiotherapy in various subgroups was displayed by Kaplan–Meier plots.ResultsThe 1-, 3-, and 5-year PFS of postoperative LSCC patients were 88.4%, 70.1%, and 57.8%, respectively. Similarly, the 1-, 3-, and 5-year OS of postoperative LSCC patients were 94.6%, 76.9%, and 69.4%, respectively. The results suggested that postoperative LSCC patients with age at diagnosis ≥ 70 years, grade with moderate or poor differentiate, the American Joint Committee on Cancer (AJCC) stage IV, higher systemic immune-inflammation index (SII), surgical margin < 5, and age-adjusted Charlson Comorbidity Index (ACCI) ≥ 5 tend to have a poorer PFS (all P < 0.05). Besides, postoperative LSCC patients with age at diagnosis ≥ 70 years, AJCC stage IV, higher GPS, higher SII, and ACCI ≥ 5 tend to have a worse OS (all P < 0.05). Additionally, postoperative patients with LSCC in the subgroup of ACCI < 5 and AJCC III–IV stage was more likely to benefit from adjuvant radiotherapy, but not for the other subgroups.ConclusionWe identified a series of significant immune-inflammation-related and comorbidity-related clinicopathological factors associated with the prognosis of postoperative LSCC patients by local data from two tertiary care institutions in China, which can be helpful for patients and surgeons to pay more attention to nutrition, inflammation, and complications and finally obtained a better prognosis.

Relationship between systemic immune inflammation index and development of complete atrioventricular block in patients with ST-elevation myocardial infarction undergoing primary percutaneous coronary intervention

BackgroundThe systemic immune-inflammation index (SII), based on white blood cell, neutrophil, and platelet counts, is a proposed marker of systemic inflammation and immune activation. This study aimed to explore the relationship between SII and complete atrioventricular block (CAVB) development in STEMI patients undergoing primary PCI.MethodsWe retrospectively analyzed data from 883 patients who underwent primary PCI for STEMI between January 2009 and December 2017. Patients were categorized into two groups based on CAVB development. SII levels were calculated from blood samples taken on admission.ResultsOf the included patients, 48 (5.03%) developed CAVB. SII was higher in patients with CAVB compared to those without CAVB (1370 [1050–1779]x109/L vs. 771 [427–1462] x109/L, p < 0.001). Multivariate analysis showed a significant positive correlation between SII and the risk of CAVB development (OR:1.0003, 95%CI:1.0001–1.0005, P = 0.044). The cut-off value for the SII in the estimation of CAVB was 1117.7 × 109/L (area under the ROC curve [AUC]: 0.714, 95% CI = 0.657–0.770 with a sensitivity of 70.8% and specificity of 65.6%, p < 0.001).ConclusionThis study showed a significant link between high SII levels and CAVB development in STEMI patients undergoing PCI. Our findings suggest that SII may be a valuable, routinely available, and inexpensive marker for identifying patients at increased risk of CAVB.

Exploring the relationship between malnutrition and the systemic immune-inflammation index in older inpatients: a study based on comprehensive geriatric assessment

BackgroundMalnutrition is a prevalent and major challenge among senior citizens, possibly due to the continual low-grade inflammatory state of the body. A novel inflammatory parameter, the systemic immune-inflammation index (SII), is highly valuable in evaluating and predicting the prognosis of a wide range of diseases. This study aims to explore the significance of the SII in assessing malnutrition in older inpatients.MethodsThis retrospective study included 500 senior hospitalized patients who met the inclusion and exclusion criteria from the Comprehensive Geriatric Assessment database of the First Hospital of Jilin University. The Mini-Nutritional Assessment (MNA) questionnaire was used to evaluate the nutritional status of patients. The SII was calculated using complete blood counts, and we performed natural logarithm transformation of the SII [ln(SII)]. Multivariable logistic regression analysis was used to identify the association between ln(SII) and malnutrition. To ensure the stability of the findings, a sensitivity analysis was conducted.ResultsThe 500 patients had a mean age of 77.29 ± 9.85 years, and 68.6% were male. In accordance with the MNA, 30.4% of the patients were malnourished or at risk of malnutrition, and patients in this group had considerably greater levels of ln(SII) than patients with adequate nutrition (P < 0.001). The optimum ln(SII) cutoff value for patients with malnutrition or at risk of malnutrition was 6.46 (SII = 635.87) with 46.7% sensitivity and 80.2% specificity [95% CI: 0.613–0.721, AUC: 0.667, P < 0.001]. Multivariable logistic regression demonstrated that ln(SII) was an independent risk factor for the risk of malnutrition or malnutrition in older individuals (OR 3.984, 95% CI: 2.426–6.543, P < 0.001). Other metrics from the geriatric comprehensive assessment, including body mass index, calf circumference, fat ratio, activities of daily living and instrumental activities of daily living, and geriatric depression scale scores, were also independently correlated with nutritional status.ConclusionsAccording to our research, a high SII is an independent predictor of older inpatient malnutrition, and the SII aids in screening for malnutrition and may be a potential target for intervention. Comprehensive geriatric assessment parameters such as BMI, calf circumference, fat ratio, activities of daily living and depression were also linked to malnutrition.

Association of systemic immune-inflammation index with diabetic kidney disease in patients with type 2 diabetes: a cross-sectional study in Chinese population.

Systemic immune-inflammation index (SII), a novel inflammatory marker, has been reported to be associated with diabetic kidney disease (DKD) in the U.S., however, such a close relationship with DKD in other countries, including China, has not been never determined. We aimed to explore the association between SII and DKD in Chinese population. A total of 1922 hospitalized patients with type 2 diabetes mellitus (T2DM) included in this cross-sectional study were divided into three groups based on estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (ACR): non-DKD group, DKD stages 1-2 Alb group, and DKD-non-Alb+DKD stage 3 Alb group. The possible association of SII with DKD was investigated by correlation and multivariate logistic regression analysis, and receiver-operating characteristic (ROC) curves analysis. Moving from the non-DKD group to the DKD-non-Alb+DKD stage 3 Alb group, SII level was gradually increased (P for trend <0.01). Partial correlation analysis revealed that SII was positively associated with urinary ACR and prevalence of DKD, and negatively with eGFR (all P<0.01). Multivariate logistic regression analysis showed that SII remained independently significantly associated with the presence of DKD after adjustment for all confounding factors [(odds ratio (OR), 2.735; 95% confidence interval (CI), 1.840-4.063; P < 0.01)]. Moreover, compared with subjects in the lowest quartile of SII (Q1), the fully adjusted OR for presence of DKD was 1.060 (95% CI 0.773-1.455) in Q2, 1.167 (95% CI 0.995-1.368) in Q3, 1.266 (95% CI 1.129-1.420) in the highest quartile (Q4) (P for trend <0.01). Similar results were observed in presence of DKD stages 1-2 Alb or presence of DKD-non- Alb+DKD stage 3 Alb among SII quartiles. Last, the analysis of ROC curves revealed that the best cutoff values for SII to predict DKD, Alb DKD stages 1- 2, and DKD-non-Alb+ DKD stage 3 Alb were 609.85 (sensitivity: 48.3%; specificity: 72.8%), 601.71 (sensitivity: 43.9%; specificity: 72.3%), and 589.27 (sensitivity: 61.1%; specificity: 71.1%), respectively. Higher SII is independently associated with an increased risk of the presence and severity of DKD, and SII might be a promising biomarker for DKD and its distinct phenotypes in Chinese population.

Systemic immune-inflammation index predicts the clinical outcomes in patients with acute uncomplicated type-B aortic dissection undergoing optimal medical therapy

BackgroundOptimal medical therapy (OMT) for uncomplicated type B aortic dissection (uTBAD) provides excellent short-term outcomes during follow up; however, its long-term therapeutic effectiveness is unsatisfactory. This study evaluated the predictive value of systemic immune-inflammation index (SII) for adverse events among patients with acute uTBAD undergoing OMT.MethodsWe performed a retrospective analysis of a prospectively maintained database between 2013 and 2020. The primary end point in this study was composite outcomes including aortic intervention, all-cause mortality, retrograde type A aortic dissection (rTAAD) and aortic diameter growth > 5 mm. The patients were divided into high and low SII groups according to the optimal cut-off value of SII as determined using the receiver operating characteristic curve. Cox proportional hazards models were constructed to estimate the hazards ratios and identify the predictors of composite outcomes.ResultsA total of 124 patients with acute uTBAD who underwent OMT were enrolled. One patient died during hospitalisation. At the end of a mean follow-up duration of 51 ± 23 months, 53 (43.1%) patients experienced composite outcomes, 15 patients (12.2%) died, 31 (25.2%) underwent aortic intervention, 21 (17.1%) exhibited diameter growth of > 5 mm, and 2 developed rTAAD. The patients were divided into low SII group (n = 78, 62.9%) and high SII group (n = 46, 37.1%) as per the optimal cut-off SII value of 1449. The incidence of composite outcomes in high SII group was significantly higher than that in low SII (28 [60.9%] vs. 26[33.3%], p < 0.01). Patients with high SII demonstrated significantly higher mortality rate than those with a low SII (11 [23.9%] vs. 5 [6.4%], respectively; p < 0.01). In addition, the high SII group had significantly higher rate of aortic-related reinterventions than the low SII group (16 [34.8%] vs. 15 [19.2%], p = 0.03). Multivariable Cox analyses showed that a high SII score was independently associated with composite outcomes rate (hazard ratio, 2.15; 95% confidence interval, 1.22–3.78; p < 0.01).ConclusionsThe long-term therapeutic effectiveness of OMT alone in patients with acute uTBAD is unsatisfactory. An SII > 1449 at the time of diagnosis is an independent predictor of OMT failure.

Prognostic role of the systemic immune-inflammation index and pan-immune inflammation value for outcomes of breast cancer: a systematic review and meta-analysis.

This review examined the literature for evidence on the prognostic ability of systemic immune-inflammation index (SII) and pan-immune inflammation value (PIV) for predicting overall survival (OS) and disease-free survival (DFS) in breast cancer patients. PubMed, Embase, Scopus, and Web of Science were searched with Google Scholar for gray literature. All types of studies reporting the association between SII or PIV and OS or DFS of breast cancer were eligible. 13 studies on SII and 4 studies on PIV were included. Meta-analysis showed that a high SII was a significant predictor of OS (HR: 1.97 95% CI: 1.54, 2.52 I2=76%) and DFS (HR: 2.07 95% CI: 1.50, 2.86 I2=79%) in breast cancer patients. These results did not change on sensitivity analysis and were more or less stable on multiple subgroup analyses. Pooled analysis showed that high PIV was also a significant predictor of poor OS (HR: 2.63 95% CI: 1.46, 4.74 I2=71%) and DFS (HR: 1.64 95% CI: 1.23, 2.17 I2=0%) in breast cancer patients. High SII and PIV can predict poor OS and DFS in breast cancer patients. High heterogeneity and the observational nature of data are important limitations of the review. Further studies are needed specifically on PIV to increase the strength of the evidence.