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

Predictive Value of Neutrophil-Lymphocyte Ratio and Other Inflammation Indices in Febrile Seizures in Children

Objective: There is increasing evidence for the effect of inflammation on the etiology of febrile seizure (FS) patients. We aimed to investigate the role of easily accessible inflammatory markers such as the neutrophil-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), neutrophil-lymphocyte-platelet ratio (NLPR), and pan-immune-inflammation value (PIV) in febrile seizure. Methods: A total of 300 children, including 100 with febrile convulsions (FS), 100 febrile controls (FCs), and 100 healthy controls (HCs), were included in this retrospective study. The FS group was compared with the FC and HC groups in terms of these inflammatory indexes. Results: Between the FS group and the FC group, the neutrophil count was significantly higher in the FS group (p = 0.001) and the lymphocyte count was significantly lower (p < 0.001). The NLR (p < 0.001), SII (p < 0.001), SIRI (p < 0.001), NLPR (p < 0.001), and PIV (p < 0.001) were significantly higher in the FS group than in both the FC and healthy control groups. The optimal cut-off values for predicting FS in febrile conditions were 3.59> for NLR, >870.47 for SII, >1.96 for SIRI, 0.96> for NLPR, and >532.75 for PIV. Conclusions: The inflammatory indices are inexpensive, easily accessible hematological markers that can contribute to the diagnosis of FS.

Determination of systemic inflammation response index (SIRI), systemic inflammatory index (SII), HMGB1, Mx1 and TNF levels in neonatal calf diarrhea with systemic inflammatory response syndrome

The objective of this study was to examine the values of MX dynamin-like GTPase 1 (Mx1), high mobility group box-1 (HMGB1), systemic inflammatory response index (SIRI), systemic inflammatory index (SII), tumor necrosis factor (TNF), and other hematological indices in calves with systemic inflammatory response syndrome (SIRS). The study material was divided into two groups: the SIRS group (comprising 13 calves) and the control group (comprising 10 calves). The independent samples t-test and Mann-Whitney U test were employed for normally distributed and non-normally distributed data, respectively. The relationship between the two groups was determined using Spearman correlation coefficient analysis. Significant differences were identified between the SIRS group and the control group with regard to white blood cell (WBC; P < 0.05), neutrophil (NEU; P < 0.01), and neutrophil-to-lymphocyte ratio (NLR; P < 0.001) values, in addition to SIRI (P < 0.05), SII (P < 0.01) values. Furthermore, HMGB1 (P < 0.001), Mx1 (P < 0.05), and TNF values (P < 0.001) demonstrated notable disparities between the two groups. As a result of this study, it was concluded that there were significant increases in inflammatory hematological indices, as well as in the levels of HMGB1, Mx1, and TNF, in calves with SIRS.

Prognostic value of systemic inflammatory response index for acute kidney injury and the prognosis of pediatric patients in critical care units

BACKGROUND

We proposed a link between the first systemic inflammatory response index (SIRI) and acute kidney injury (AKI), as well as the prognosis of pediatric patients in intensive care units (PICU).

METHODS

This study comprised 5114 children from the pediatric-specific intensive care (PIC) database. SIRI was estimated as a neutrophil monocyte lymphocyte ratio. All patients were arbitrarily allocated to the training set (n = 3593) and the validation cohort (n = 1521) and divided into two groups depending on their SIRI levels. The diagnostic value of SIRI for pediatric ICU patients was subsequently determined using LASSO regression models.

RESULTS

After controlling for additional confounding variables in the training set, the higher SIRI value (≥ 0.59) had a greater risk of AKI (adjusted odds ratio, OR, 3.95, 95% confidence interval, 95%CI, 2.91-5.36, P<0.001) and in-hospital mortality (hazard ratio, HR, 5.01, 95%CI 2.09-12.03, P<0.001). Similar findings were discovered in the validation set. Furthermore, the suggested nomogram derived from SIRI and other clinical metrics showed outstanding calibration capability as well as therapeutic usefulness in both groups.

CONCLUSIONS

SIRI is a reliable and useful factor for AKI and fatality in pediatric ICU patients, and the proposed nomogram based on SIRI yields an appropriate prediction value for critically sick pediatric patients.

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 AIMS

The 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 RESULTS

A 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.

CONCLUSIONS

The SIRI is a promising tool for identifying MASLD individuals at risk of progressing to AHF and for predicting mortality outcomes.

Clinical value of the Systemic Inflammatory Response Index for predicting acute pancreatitis severity in Vietnamese setting

Background and Aim

Accurate prediction of severe acute pancreatitis (SAP) is crucial for timely intervention. This study focuses on the Systemic Inflammatory Response Index (SIRI) to assess its clinical value in predicting the severity of AP in the Vietnamese context.

Methods

A cross-sectional prospective study was conducted with acute pancreatitis patients at a national hospital in Ho Chi Minh City. The patients were classified into nonsevere and severe groups, and the clinical characteristics were analyzed. The predictive abilities of SIRI, calculated using neutrophil × monocyte/lymphocyte, was assessed for predictive abilities. Multivariate regression and receiver operating characteristics (ROC) curves evaluated the prognostic factors and predictive accuracy.

Results

Among 207 patients, 78.7% had nonsevere AP, and 21.3% had SAP. The severe group exhibited a significantly higher median SIRI (12.0) than the nonsevere group (4.9) (P < 0.001). Multivariate regression identified SIRI (odds ratio [OR] = 1.623) as an independent predictor of SAP. The ROC curve determined a SIRI cutoff of 7.82 with an area under the curve (AUC) of 0.737. Combining the SIRI and Bedside Index for Severity in Acute Pancreatitis (BISAP) score improved the predictive ability (AUC = 0.820) with increased sensitivity (90.91%) (P < 0.001).

Conclusion

SIRI, particularly when combined with the BISAP score, shows significant potential to predict SAP severity in the Vietnamese clinical setting, providing valuable information for effective patient management.

Diagnostic performance of acoustic radiation force impulse for acute pancreatitis: A meta-analysis

OBJECTIVE

The objective of this meta-analysis is to evaluate the diagnostic performance of acoustic radiation force impulse (ARFI) in acute pancreatitis (AP) patients.

METHODS

PubMed, Web of Science, Embase, Wanfang, Chinese Biological Medicine databases, and Chinese Biomedical Literature Service System were searched for relevant studies to explore the potential diagnostic performance of ARFI in AP from inception to November 2023. STATA 14.0 was used to analyze the standardized mean difference (SMD) with 95% confidence interval (CI), pooled sensitivity, specificity, area under the curve, meta-regression analysis, sensitivity analysis, and publication bias.

RESULTS

Nine studies, involving 533 AP patients and 585 healthy controls, were included. AP patients had significantly higher ARFI levels than healthy controls (SMD: 3.13, 95% CI: 1.88-4.39, P = .001). The area under the curve of ARFI for diagnosing AP was 0.99 (95% CI: 0.98-1.00), with 98% sensitivity and 94% specificity. Meta-regression identified the study region and study period as the sources of heterogeneity. Sensitivity analysis showed that the exclusion of any single study did not materially alter the overall combined effect. No evidence of publication bias was observed in the included studies.

CONCLUSION

This meta-analysis demonstrated that ARFI exerted satisfactory diagnostic performance in AP.

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)

OBJECTIVE

This study aimed to systematically investigate the relationship between immune-inflammatory indexes with lower urinary tract symptoms (LUTSs).

DESIGN

Cross-sectional study.

SETTING

National Health and Nutrition Examination Survey (NHANES) (2005-2008).

PARTICIPANTS

A total of 2709 men with complete information for immune-inflammatory indexes and LUTSs were included from NHANES 2005-2008.

OUTCOMES AND ANALYSES

Automated haematology analysing devices are used to measure blood cell counts, and LUTSs were presented by standard questionnaires. Non-linear and logistic regression analyses were used to estimate their association after adjustment for confounders.

RESULTS

Multivariate logistic regression showed that pan-immune-inflammation value (OR (95% CI)=1.60 (1.14 to 2.23)), systemic inflammation response index (SIRI) (OR (95% CI)=1.82 (1.21 to 2.73)), neutrophil/lymphocyte ratio (NLR) (OR (95% CI)=1.81 (1.31 to 2.49)), derived NLR (dNLR) (OR (95% CI)=1.91 (1.35 to 2.70)) and C reactive protein (CRP) (OR (95% CI)=1.71 (1.05 to 2.79)) was positively associated with LUTS. Additionally, composite immune-inflammation markers exhibited a stronger association with LUTS than any single index, with the ORs for high SIRI+high CRP, high NLR+high CRP and high dNLR+high CRP being 2.26, 2.44 and 2.16, respectively (all p<0.05). Furthermore, subgroup analyses revealed that age, smoking status and hypertension have different effects on the relationship between immune-inflammatory markers and LUTS.

CONCLUSIONS

This study indicated that high levels of immune-inflammatory markers were associated with an increased risk of clinical LUTS. The combination of CRP with SIRI, NLR and dNLR, respectively, showed a stronger positive correlation with clinical LUTS compared with any single index.

Relationship between SIRI and android and gynoid fat related to obesity and cardiovascular risk: a cross-sectional study of NHANES 2017-2018

OBJECTIVE

Inflammation has a crucial role in several metabolic diseases, such as obesity. The author aimed to investigate the relationship between the system inflammation response index (SIRI) and android fat composition and distribution.

METHODS

Data for individuals aged 8-59 years, SIRI, android percent fat, and android-to-gynoid ratio from the 2017 to 2018 National Health and Nutrition Examination Survey were used. Weighted multiple linear regression and smooth curve fitting were used to test for linear and nonlinear associations. Additional subgroup analyses were performed. Threshold effect analysis was performed using a two-linear regression model.

RESULTS

Multiple linear regression showed a positive correlation between SIRI and android percent fat (β 0.92, 95% confidence interval [CI] 0.25-1.59) and between SIRI and the android-to-gynoid ratio (β 0.01, 95% CI 0.00-0.03) in 3783 Americans aged 8-59 years. The results showed that the effect of factors, other than smoking status, on the relationship between SIRI and android percent fat and android-to-gynoid ratio was not significant. There was a nonlinear relationship between SIRI and both android percent fat and android-to-gynoid ratio.

CONCLUSIONS

Elevated SIRI levels were associated with an increased android percent fat and android-to-gynoid ratio. Larger prospective studies are needed to validate the findings.

Systemic inflammation response index as a prognostic factor for patients with sepsis-associated acute kidney injury: a retrospective observational study

OBJECTIVE

To assess the association between the systemic inflammation response index (SIRI) and the prognosis in patients with sepsis-associated acute kidney injury (SA-AKI).

METHODS

In this observational study, adult patients with SA-AKI were categorized into three groups based on SIRI tertiles. Survival outcomes were compared across the three groups using Kaplan-Meier survival curves. Various Cox proportional hazards regression models were developed to determine the association between the SIRI and mortality in patients with SA-AKI. Subgroup analyses were also performed to explore the association between different SIRI tertiles and all-cause mortality.

RESULTS

After adjusting for several confounders, the second SIRI tertile (2.5 < SIRI < 7.6) was found to be an independent risk factor for 30-day mortality [hazard ratio (95% confidence interval): 1.19 (1.01-1.40)], 90-day mortality [1.22 (1.06-1.41)], and 365-day mortality [1.24 (1.09-1.40)]. Furthermore, high SIRI values were associated with increased risks of 30-day, 90-day, and 365-day mortality in patients with SA-AKI across all three models. The third tertile showed a significant association with adverse outcomes in most subgroups.

CONCLUSIONS

The SIRI serves as a comprehensive biomarker for predicting all-cause mortality of critically ill patients with SA-AKI.

Association between systemic inflammation response index and chronic kidney disease: a population-based study

Introduction

Our objective was to explore the potential link between systemic inflammation response index (SIRI) and chronic kidney disease (CKD).

Methods

The data used in this study came from the National Health and Nutrition Examination Survey (NHANES), which gathers data between 1999 and 2020. CKD was diagnosed based on the low estimated glomerular filtration rate (eGFR) of less than 60 mL/min/1.73 m2 or albuminuria (urinary albumin-to-creatinine ratio (ACR) of more than 30 mg/g). Using generalized additive models and weighted multivariable logistic regression, the independent relationships between SIRI and other inflammatory biomarkers (systemic immune-inflammation index (SII), monocyte/high-density lipoprotein ratio (MHR), neutrophil/high-density lipoprotein ratio (NHR), platelet/high-density lipoprotein ratio (PHR), and lymphocyte/high-density lipoprotein ratio (LHR)) with CKD, albuminuria, and low-eGFR were examined.

Results

Among the recruited 41,089 participants, males accounted for 49.77% of the total. Low-eGFR, albuminuria, and CKD were prevalent in 8.30%, 12.16%, and 17.68% of people, respectively. SIRI and CKD were shown to be positively correlated in the study (OR = 1.24; 95% CI: 1.19, 1.30). Furthermore, a nonlinear correlation was discovered between SIRI and CKD. SIRI and CKD are both positively correlated on the two sides of the breakpoint (SIRI = 2.04). Moreover, increased SIRI levels were associated with greater prevalences of low-eGFR and albuminuria (albuminuria: OR = 1.27; 95% CI: 1.21, 1.32; low-eGFR: OR = 1.11; 95% CI: 1.05, 1.18). ROC analysis demonstrated that, compared to other inflammatory indices (SII, NHR, LHR, MHR, and PHR), SIRI exhibited superior discriminative ability and accuracy in predicting CKD, albuminuria, and low-eGFR.

Discussion

When predicting CKD, albuminuria, and low-eGFR, SIRI may show up as a superior inflammatory biomarker when compared to other inflammatory biomarkers (SII, NHR, LHR, MHR, and PHR). American adults with elevated levels of SIRI, SII, NHR, MHR, and PHR should be attentive to the potential risks to their kidney health.

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

Objective

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.

Methods

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.

Results

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.

Conclusion

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.

Association between admission systemic immune-inflammation index and mortality in critically ill patients with sepsis: a retrospective cohort study based on MIMIC-IV database

Systemic immune-inflammation index (SII) has been identified as a prognostic biomarker for various diseases. Our study aimed to investigate the association between SII and mortality risk in critically ill patients with sepsis, thus exploring possible tools for rapid screening. This retrospective cohort study was conducted using clinical data extracted from the Medical Information Mart for Intensive Care Database. The study included only patients diagnosed with sepsis admitted to the intensive care unit for the first time. We used the restricted cubic splines to explore the relationship between SII and 28-day mortality. Kaplan-Meier curve and Cox regression models were performed to evaluate the association between SII and mortality. Subgroup analysis was performed to explore the stability of the primary results. A total of 16,007 patients with sepsis were eligible in the final analysis. We found a J-shaped relationship between SII and mortality risk. The SII level associated with the lowest mortality risk was 774.46*109/L. Compared with the reference group (second SII quartile), the 28-day mortality was increased in the highest quartile and third quartile groups of SII levels; fully adjusted HRs were 1.16 (1.02 to 1.32) and 1.40 (1.23 to 1.58), respectively. However, although the lower SII (Q1 group) also showed a trend toward a higher hazard of 28-day mortality, there was no statistical difference, with a fully adjusted HR of 1.05 (0.92 to 1.21). In the population of critically ill patients with sepsis, low and high SII levels were associated with an increased risk of short-term mortality. The 28-day mortality risk was lowest at SII levels of 774.46*109/L.

Development of a nomogram prediction model for severity of acute pancreatitis based on echocardiography parameters and systemic immunoinflammatory index

BACKGROUND

Early, rapid, and accurate prediction of the severity of acute pancreatitis (AP) and screening high-risk populations have significant practical significance in reversing the progression of the disease. This study developed a nomogram prediction model for AP severity based on echocardiography and the systemic immunoinflammatory index (SⅡ), in order to provide new ideas for personalized disease assessment and treatment.

AIM

To investigate the ability of echocardiography combined with systemic immunoinflammatory index (SⅡ) to predict the severity and stratify the risk of AP.

METHODS

Three hundred and fifty AP patients admitted to our hospital from January 2019 to December 2022 were randomly divided into either a modeling group (n = 245) or a verification group (n = 105) in a 7:3 ratio, and they were divided into a severe AP subgroup (SAP subgroup) and non-severe AP subgroup (NSAP subgroup) according to the severity of AP. General data, laboratory tests, SⅡ score, and echocardiography parameters were statistically analyzed. The influencing factors of SAP morbidity were analyzed by Logistic regression, and regression equations were obtained according to the indicators with a statistical difference. A nomogram was obtained and verified by visual processing of the logistic regression model with R software.

RESULTS

After multiple linear exclusion of Th17 cells and Treg cells, logistic regression showed that SII, BISAP score, CXC chemokine ligand 13 (CXCL-13), N-terminal pro-brain natriuretic peptide (NT-proBNP), left ventricular ejection fraction (LVEF), stroke volume (SV), and early diastolic peak velocity of lateral mitral valve opening/late diastolic peak velocity of lateral mitral valve opening (E/A) were the factors influencing the development of SAP (P < 0.05). The C index of the prediction model in the modeling group and the verification group was 0.955 and 0.979, the net reclassification index (NRI) value was 0.590 and 0.572, and the integrated discrimination improvement (IDI) value was 0.091 and 0.089, respectively. The SAP calibration curve was close to the 45° reference line.

CONCLUSION

The nomogram prediction model for AP severity developed based on SⅡ, BISAP score, CXCL-13, NT-proBNP, LVEF, SV, and E/A has reliable predictive value, which can help to guide the clinical diagnosis and treatment and control the disease progression.

An S-like curve relationship between systemic inflammation response index (SIRI) and respiratory failure in GBS patients

BACKGROUND

Our study examined the association between the initial systemic inflammation response index (SIRI) and respiratory failure in patients with Guillain-Barré syndrome (GBS).

METHODS

The weighted linear regression model, weighted chi-square test, logistic regression models, smooth curve fittings, and the two-piece linear regression model were utilized for data analysis.

RESULTS

Among the 443 GBS patients, 75 (6.9%) had experienced respiratory failure. According to logistic regression models, there existed no consistent linear relationship between respiratory failure and SIRI in model 1 (OR = 1.2, p < 0.001), model 2 (OR = 1.2, p < 0.001), and model 3 (OR = 1.3, p = 0.017). However, smooth curve fittings found an S-like curve relationship between SIRI and respiratory failure. Furthermore, when SIRI was < 6.4, there existed a positive correlation between SIRI and respiratory failure in model 1 (OR = 1.5, 95% CI = (1.3, 1.8), p < 0.0001), higher correlation in model 2 (OR = 1.6, 95% CI = (1.3, 1.8), p < 0.0001), and highest correlation in model 3 (OR = 1.6, 95% CI = (1.3, 2.5), p < 0.0001).

CONCLUSIONS

SIRI can be used as a predictor of respiratory failure in GBS, and an S-like relationship exists between SIRI and respiratory failure at an infliction point of 6.4. When the SIRI was less than 6.4 and increased, SIRI was associated with a higher occurrence of respiratory failure. The risk of respiratory failure was no longer increased when the SIRI was over 6.4.

A nonlinear relationship between systemic inflammation response index and short-term mortality in patients with acute myocardial infarction: a retrospective study from MIMIC-IV

Background

This investigation aimed to evaluate the efficacy of the Systemic Inflammatory Response Index (SIRI) in prognosticating short-term all-cause mortality among patients diagnosed with acute myocardial infarction (AMI) in the intensive care unit (ICU).

Methods and Results

Clinical data were obtained from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database. A total of 4,291 patients were included in the cohort. Results from multivariate regression analyses showed that the quartile of the natural logarithm of SIRI (ln-SIRI) was independently associated with mortality. Compared to patients in the first quartile (Q1), patients in the second quartile (Q2) and fourth quartile (Q4) were significantly associated with an increased risk of 30-day (HR = 2.031, 95% CI: 1.604-2.571, p < 0.001 and HR = 1.703, 95% CI: 1.32-2.195, p < 0.001) and 90-day all-cause mortality (HR = 2.063, 95% CI: 1.68-2.532, p < 0.001 and HR = 1.788, 95% CI: 1.435-2.227, p < 0.001), which is consistent with the results of the Kaplan-Meier analysis and the results of multivariate regression analyses by classifying into 12 groups based on dodeciles of SIRI. Curve fitting showed a curvilinear relationship and further threshold saturation effects showed that, for 90-day mortality, each unit increased in ln-SIRI, when the ln-SIRI level is less than 2.9, the patient's mortality increases by 23.2% (OR: 1.232; 95% CI: 1.111-1.367; p < 0.001); when the ln-SIRI is greater than 2.9 and less than 4.6, the patient's mortality decreases by 44.4% (OR: 0.554; 95% CI: 0.392-0.789; p = 0.001); when ln SIR > 4.6, the patient's mortality increases by 24.7% (OR: 1.247; 95% CI: 1.108-1.404; p < 0.001). Moreover, the length of stay in the hospital was lower in patients in the third quartile (Q3) (coefficient: -1.999; 95% CI: -2.834 - -1.165, p < 0.001). The length of stay in the ICU was higher in patients in Q2 and Q4 (coefficient: 0.685;95% CI: 0.243-1.128; p = 0.0024 and coefficient: 0.989;95% CI: 0.528-1.451; p < 0.001). Furthermore, SIRI may outperform NLR in predicting short-term mortality.

Conclusion

SIRI is an independent risk factor for 30- and 90-day mortality, and length of stay in ICU for critical AMI patients.

An Evaluation of the Efficacy of Systemic Immune-Inflammation Index in Predicting Enterobius-Associated Appendicitis Preoperatively

Objective

Our study aimed to retrospectively evaluate Enterobius-associated appendicitis cases and compare them with acute appendicitis cases in terms of parameters such as the neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP)-to-lymphocyte ratio (CLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII). We primarily aimed to evaluate the utility of SII in the differential diagnosis of Enterobius-associated appendicitis.

Methods

The appendectomy specimens of pediatric patients who were operated on for acute appendicitis between June 2016 and August 2022 were retrospectively evaluated. Enterobius-associated appendicitis cases were included for analysis. All patients were evaluated regarding age, gender, blood count, surgery, and pathology reports. Pathology reports were evaluated for the presence of histological signs of acute appendicitis. The patients were classified into an Enterobius-associated appendicitis group and a regular acute appendicitis group. CRP, white blood cell (WBC), red cell distribution width (RDW), neutrophils, lymphocytes, NLR, monocytes, eosinophils, platelet (PLT), PLR, CLR, and SII values were compared between the two groups.

Results

Eleven cases of Enterobius-associated appendicitis were identified out of 430 total cases (2.55%) examined. The mean age of the group with acute appendicitis was 12.83 ±3.16 years, while the mean age of the group with Enterobius-associated appendicitis was 8.55 ±2.54 years. There was no statistically significant difference in terms of CRP, WBC, RDW, lymphocytes, neutrophils, NLR, monocytes, eosinophils, PLT, PLR, and CLR values between the two groups (p>0.05). However, when the SII values of the participants were analyzed, it was observed that the SII values of the participants in the regular appendicitis group were significantly higher than those of the participants in the Enterobius group (p<0.05). Among the 11 Enterobius-associated appendicitis patients, seven appendectomy specimens revealed no inflammation and were regarded as negative appendectomy (63.63%).

Conclusion

This is the first study to demonstrate the utility of preoperative SII evaluation in Enterobius-associated appendicitis. SII is a simple, easy-to-calculate indicator of Enterobius-associated appendicitis and aids in the preoperative differential diagnosis of acute appendicitis.

Associations between Systemic Immune-Inflammation Index and Diabetes Mellitus Secondary to Pancreatic Ductal Adenocarcinoma

BACKGROUND

There is a high prevalence of diabetes mellitus (DM) in patients with pancreatic ductal adenocarcinoma (PDAC). An inflammatory response is considered as a potential mechanism involved in the process. The systemic immune-inflammation (SII) index is an integrated and novel inflammatory indicator developed in recent years. The purpose of this study was to determine the relationship between the SII and DM secondary to PDAC.

METHOD

Patients with a confirmed diagnosis of PDAC were analyzed in this cross-sectional study. Anthropometric measures, glucose-related data (including fasting glucose, 2 h OGTT, glycated hemoglobin, fasting insulin, and fasting c-peptide), tumor characteristics (tumor volumes, location and stages), and the periphery blood inflammatory index (white blood cell count, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and SII) were recorded. The inflammation index was analyzed for its association with glucose-related parameters. Multivariable logistic regression analysis was used to analyze the association between SII levels and DM secondary to PDAC.

RESULTS

Blood cell results showed that the white blood cell count, neutrophils, lymphocytes, monocytes, platelets, the neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio were higher in patients with diabetes. It was worth noting that SII significantly increased in patients with diabetes secondary to PDAC (4.41 vs. 3.19, p < 0.0001). Multivariable logistic regression analysis showed that SII (OR: 2.024, 95%CI: 1.297, 3.157, p = 0.002) and age (OR: 1.043, 95%CI: 1.01, 1.077, p = 0.011) were the risk factors for DM secondary to PDAC after adjusting for covariates. According to Spearmen correlation analysis, SII was positively correlated with fasting glucose (r = 0.345, p < 0.0001), 2 h OGTT (r = 0.383, p < 0.0001), HbA1c (r = 0.211, p = 0.005), fasting insulin (r = 0.435, p < 0.0001), fasting C-peptide (r = 0.420, p < 0.0001), and HOMA2-IR (r = 0.491, p < 0.0001).

CONCLUSIONS

In conclusion, SII is significantly increased among patients with DM secondary to PDAC and is associated with the DM in patients with PDAC (OR: 2.382, 95% CI: 1.157, 4.903, p = 0.019). Additionally, SII is significantly correlated with insulin resistance. We are the first to investigate the relationship between SII and diabetes secondary to PDAC and further confirm the role of an inflammatory response in this process. More studies need to be designed to clarify how inflammatory responses participate.