Effects of Dapagliflozin on Novel Inflammatory Markers in Heart Failure Patients.

The incidence of heart failure (HF) remains high throughout the world, posing a serious threat to human health, with inflammation being a pivotal factor in the entire pathophysiologic process. Systemic inflammatory response index (SIRI) and systemic immune inflammation index (SII) are novel indicators for poor prognosis of HF. This paper aimed to ascertain the connection between SIRI and mortality in critically ill HF patients and to compare the prognostic value with SII. All data on HF patients were sourced from MIMIC-IV. Cox proportional hazards analysis, restricted cubic spline, and Kaplan-Meier survival analysis were utilized to determine the link between SIRI or SII and in-hospital mortality. Receiver operating characteristic curve, area under the curve (AUC), and Youden index were employed to compare the prognostic value of SIRI and SII. Subgroup analysis was conducted to confirm the predictive capability of SIRI on mortality. Propensity score matching was utilized to reveal the connection between SIRI and secondary outcomes. 754 patients were included and 45 patients (6.0%) died. There was a positive link between SIRI and in-hospital mortality in both unadjusted (p < 0.001) and adjusted models (p < 0.001 and p = 0.001, respectively), outperforming SII in all models (p > 0.05 in all models). SIRI had a higher AUC and Youden index than SII, indicating better prognostic power. In addition, hospital stay was shorter in the low SIRI group (p = 0.034). SIRI predicts in-hospital mortality in critically ill HF patients, and the prognostic power is superior to SII.

BackgroundChronic inflammatory disorders in atrial fibrillation (AF) contribute to the onset of ischemic stroke. Systemic immune inflammation index (SIII) and system inflammation response index (SIRI) are the two novel and convenient measurements that are positively associated with body inflammation. However, little is known regarding the association between SIII/SIRI with the presence of AF among the patients with ischemic stroke.MethodsA total of 526 ischemic stroke patients (173 with AF and 353 without AF) were consecutively enrolled in our study from January 2017 to June 2019. SIII and SIRI were measured in both groups. Logistic regression analysis was used to analyse the potential association between SIII/SIRI and the presence of AF. Finally, the correlation between hospitalization expenses, changes in the National Institutes of Health Stroke Scale (NIHSS) scores and SIII/SIRI values were measured.ResultsIn patients with ischemic stroke, SIII and SIRI values were significantly higher in AF patients than in non-AF patients (all p < 0.001). Moreover, with increasing quartiles of SIII and SIRI in all patients, the proportion of patients with AF was higher than that of non-AF patients gradually. Logistic regression analyses demonstrated that log-transformed SIII and log-transformed SIRI were independently associated with the presence of AF in patients with ischemic stroke (log-transformed SIII: odds ratio [OR]: 1.047, 95% confidence interval CI = 0.322–1.105, p = 0.047; log-transformed SIRI: OR: 6.197, 95% CI = 2.196–17.484, p = 0.001). Finally, a positive correlation between hospitalization expenses, changes in the NIHSS scores and SIII/SIRI were found, which were more significant in patients with AF (all p < 0.05).ConclusionsOur study suggests SIII and SIRI are convenient and effective measurements for predicting the presence of AF in patients with ischemic stroke. Moreover, they were correlated with increased financial burden and poor short-term prognosis in AF patients presenting with ischemic stroke.

BackgroundStandard modifiable risk factors (SMuRFs) are important causative factors leading to coronary atherosclerosis. However, a significant number of individuals develop coronary atherosclerosis despite the absence of SMuRFs. Inflammation is another major cause of atherosclerosis, and this study aims to investigate the association of the novel inflammatory markers systemic immune inflammatory index (SII) and systemic inflammatory response index (SIRI) with mortality in patients with coronary heart disease (CHD) with and without SMuRFs.MethodsIn this study, we included 1708 CHD participants from the 1999–2018 National Health and Nutrition Examination Survey (NHANES). Patients were categorized into ≥ 1SMuRF and SMuRF‐less groups by questionnaire and serologic testing. SII and SIRI were categorized into four groups according to quartiles. Multivariate weighted Cox regression was used to explore the risk factors associated with mortality in patients with or without SMuRFs. Restricted cubic spline (RCS) curve was used to assess their nonlinear correlation.ResultsIn patients with ≥1 SMuRF, all‐cause mortality (SII:hazard ratio [HR] 1.47, 95% confidence interval [CI] 1.18–1.84, p < 0.001; SIRI:HR 1.66, 95%CI 1.31–2.10, p < 0.001) and cardiovascular mortality (SII:HR 1.52, 95%CI 1.07–2.17, p = 0.020; SIRI:HR 1.63, 95%CI 1.11–2.38, p = 0.011) were significantly higher in the SII Q4 and SIRI Q4 group compared to the SII Q1 and SIRI Q1 group, respectively. In patients with SMuRF‐less, the incidence of all‐cause mortality was also significantly higher in the group with higher levels of SII, SIRI (SII:HR 3.32, 95%CI 1.45–7.59, p = 0.004; SIRI:HR 4.25, 95%CI 1.67–10.80, p = 0.002), but no significant difference was observed in cardiovascular mortality for SII (SII:HR 2.21, 95%CI 0.54–8.97, p = 0.272), while a significant association was found for SIRI (SIRI:HR 11.69, 95%CI 1.43–95.21, p = 0.028). The RCS analysis showed a linear trend between high levels of SII, SIRI, and elevated all‐cause mortality, and cardiovascular mortality in patients with ≥1 SMurRF. In contrast, a positive linear trend between SII, SIRI, and all‐cause mortality, but no significant association with cardiovascular mortality was observed in the group with SMuRF‐less.ConclusionsThe findings showed that SII and SIRI were positively associated with all‐cause mortality in a population with CHD irrespective of the presence or absence of SMuRFs. The present study suggests that inflammation may be an important factor in the poor prognosis of patients with no specific cardiovascular risk factors, which needs to be further argued by more prospective studies.

Systemic immune inflammation index (SII), systemic inflammatory response index (SIRI) are new inflammation indicators calculated after integrating multiple indicators in blood routine. This study aims to investigate the correlation between the SII, SIRI and type 2 diabetic retinopathy (T2DR) and the diagnostic significance of these indices in T2DR. A retrospective analysis involved 500 patients diagnosed with type 2 diabetes (T2DM), categorized into two groups based on fundus examination results: the non-diabetic retinopathy group (NDR, n=256) and the diabetic retinopathy group (DR, n=244). We calculated SII and SIRI, and analyzed their associations with T2DR. The DR group exhibited significantly higher SII and SIRI values compared to the NDR group (P<0.001). Mantel-Haenszel's chi-square trend analysis revealed a notable linear trend (P<0.001) between SII, SIRI, and DR. SII and SIRI exhibited moderate positive correlations with DR, (r=0.354, P<0.001; r=0.469, P<0.001), respectively. Binary logistic regression analysis identified SII and SIRI as independent risk factors for DR. Restrictive cubic spline analysis demonstrated a significant linear relationship between SII and DR (P total trend <0.001, P nonlinear = 0.0657). Stratification by gender indicated that SII is more sensitive to the onset of DR in men. A significant nonlinear relationship was observed between SIRI and DR (P total trend <0.001, P nonlinear = 0.0025), with no gender-related differences in SIRI's association with DR. ROC curve analysis demonstrated that the combined use of SII and SIRI achieved the highest diagnostic accuracy for DR, with an AUC of 0.782, 74.6% sensitivity, and 69.9% specificity. Our findings suggested that SII and SIRI as independent risk factors for DR. The high accuracy of SII combined with SIRI in diagnosing DR underscores their potential as early biological indicators for DR diagnosis.

The systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI) have recently been reported as novel inflammatory markers of diabetes. However, the associations of SII and SIRI with the risk of gestational diabetes mellitus (GDM) are unclear. In our study, we explored the association between the SII and SIRI in early pregnancy and the risk of GDM in pregnant women. A prospective cohort of 1,505 pregnant women were recruited at 6-13 weeks of gestation in 2019 and 2020 in Shenzhen, China. SII and SIRI were determined by calculating the composite inflammation indicators from routine blood test results at 6-13 weeks of gestation, and an oral glucose tolerance test was conducted at 24-28 weeks of gestation to diagnose GDM. Logistic regression was used to analyse the correlations between the incidence of GDM and SII and SIRI. Using a restriction cubic spline with baseline SII and SIRI as continuous variables, the dose-response associations between the incidence of GDM and SII and SIRI were explored. Following Ln-transformation of the SII and SIRI, multivariate models showed that Ln (SII) (odds ratio [OR] = 1.759; 95% confidence interval [CI]: 1.272-2.432) and Ln (SIRI) (OR = 1.556; 95% CI: 1.187-2.042) were positively associated with the risk of GDM in a dose-dependent manner. The OR for the highest quartile of SII compared with the lowest quartile for the risk of GDM was 2.080 (95% CI: 1.447-2.990), and the OR for the highest quartile of SIRI compared with the lowest quartile was 1.694 (95% CI: 1.170-2.452). The restricted cubic spline model confirmed a linear association between Ln (SII) and Ln (SIRI) with the risk of GDM (p-nonlinear > 0.05). Higher SII and SIRI in early pregnancy are associated with an increased risk of GDM. As novel, valuable, and convenient indicators of inflammation, SII and SIRI could be used to a potential predictor for GDM in early pregnancy.

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

Significant evidence suggests that asthma might originate from low-grade systemic inflammation. Previous studies have established a positive association between the systemic immune-inflammation index (SII) and the systemic inflammation response index (SIRI) levels and the risk of stroke. However, it remains unclear whether SII, SIRI and the prevalence of stroke are related in individuals with asthma. The present cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2018. SII was calculated using the following formula: (platelet count × neutrophil count)/lymphocyte count. SIRI was calculated using the following formula: (neutrophil count × monocyte count)/lymphocyte count. The Spearman rank correlation coefficient was used to determine any correlation between SII, SIRI, and the baseline characteristics. Survey-weighted logistic regression was employed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) to determine the association between SII, SIRI, and stroke prevalence. The predictive value of SII and SIRI for stroke prevalence was assessed through receiver operating characteristic (ROC) curve analysis, with the area under the ROC curve (AUC) being indicative of its predictive value. Additionally, clinical models including SIRI, coronary heart disease, hypertension, age, and poverty income ratio were constructed to evaluate their clinical applicability. Between 1999 and 2018, 5,907 NHANES participants with asthma were identified, of which 199 participants experienced a stroke, while the remaining 5,708 participants had not. Spearman rank correlation analysis indicated that neither SII nor SIRI levels exhibited any significant correlation with the baseline characteristics of the participants (r<0.1). ROC curves were used to determine the optimal cut-off values for SII and SIRI levels to classify participants into low- and high-level groups. Higher SII and SIRI levels were associated with a higher prevalence of stroke, with ORs of 1.80 (95% CI, 1.18-2.76) and 2.23 (95% CI, 1.39-3.57), respectively. The predictive value of SIRI (AUC=0.618) for stroke prevalence was superior to that of SII (AUC=0.552). Furthermore, the clinical model demonstrated good predictive value (AUC=0.825), with a sensitivity of 67.1% and specificity of 87.7%. In asthmatics, higher levels of SII and SIRI significantly increased the prevalence of stroke, with its association being more pronounced in individuals with coexisting obesity and hyperlipidaemia. SII and SIRI are relatively stable novel inflammatory markers in the asthmatic population, with SIRI having a better predictive value for stroke prevalence than SII.

There is limited research on the relationship between Systemic Oxidative Stress (SOS) status and inflammatory indices. Adding onto existing literature, this study aimed to examine the association between dietary Oxidative Balance Score (OBS) and lifestyle OBS (which make up the overall OBS), and Cardiovascular Disease (CVD) prevalence at different Systemic Immune Inflammation Index (SII) and Systemic Inflammatory Response Index (SIRI) levels. This study involved 9,451 subjects selected from the National Health and Nutrition Examination Survey (NHANES) 2007-2018. The OBS comprised 20 dietary and lifestyle factors. Statistical methods included Weighted Linear Regression Analysis (WLRA), Logistic Regression Analysis (LRA), Sensitivity Analysis (SA), and Restricted Cubic Spline (RCS) analysis. The multivariate WLRA revealed that OBS was significantly negatively correlated with both SII (β = -5.36, p < 0.001) and SIRI (β = -0.013, p < 0.001) levels. In SA, removing any single OBS component had no significant effect on the WLRA results of SII and SIRI. Further subgroup analyses revealed that OBS was more impactful in lowering SII in women than in men. Additionally, OBS was more significantly negatively correlated with SII and SIRI in the low-age group than in the high-age group. Moreover, RCS analysis confirmed this linear relationship. Compared to dietary OBS, lifestyle OBS exerted a more significant effect on Coronary Artery Disease (CAD) (OR: 0.794, p = 0.002), hypertension (OR: 0.738, p < 0.001), Congestive Heart Failure (CHF) (OR: 0.736, p = 0.005), Myocardial Infarction (MI) (OR: 0.785, p = 0.002), and stroke (OR: 0.807, p = 0.029) prevalence. Furthermore, SIRI exhibited a significant interaction in the relationship between overall OBS, dietary OBS, and CHF (P for interaction < 0.001). On the other hand, SII had a significant interaction in the relationship between overall OBS, dietary OBS, and MI (P for interaction < 0.05). OBS, including lifestyle and dietary OBS, were significantly negatively associated with SII and SIRI. Higher lifestyle OBS was associated with reduced risks of CAD, hypertension, CHF, MI, and stroke.

To evaluate the association of systemic immune-inflammation index (SII) and systemic inflammatory response index (SIRI) with Behçet disease uveitis (BU), and to assess their predictive value for inflammatory activity and clinical prognosis in BU patients. There were 194 patients diagnosed with Behçet disease (BD) and 122 healthy controls. The BD patients were classified into two subgroups based on disease activity: An active phase cohort (n=90) and a stable phase cohort (n=104). Furthermore, the patients were categorized according to the presence or absence of uveitis into two cohorts: BU (n=49) and non-BU (n=145). Among the BU cohort, 26 patients were in the active inflammatory stage, while 23 patients were in the quiescent inflammatory stage. SII and SIRI were calculated using routine blood parameters, including platelet, neutrophil, lymphocyte, and monocyte counts. Spearman correlation analysis was performed to assess the associations of SII and SIRI with BU onset, inflammatory activity, and inflammatory markers. Receiver operating characteristic (ROC) curve analysis was conducted to determine the optimal thresholds and predictive accuracy of SII and SIRI for BU onset and inflammatory activity. SII and SIRI levels were significantly elevated in BD patients with ocular and vascular manifestations compared to those with stable disease (P < 0.05). No significant differences were observed in SII or SIRI levels among the patients with other clinical manifestations of BD. In the patients with BU, both SII and SIRI were significantly higher than in the non-BU and healthy control the groups (P < 0.001). Moreover, SII and SIRI levels were higher during the active inflamma-tory stage than in the inactive stage of BU (P=0.004). Spearman correlation analysis revealed that SII was positively associated with BD disease activity (ρ=0.303, P < 0.001), BU onset (ρ=0.442, P < 0.001), inflammatory activity (ρ=0.392, P=0.005), C-reactive protein (CRP, ρ=0.272, P < 0.001), and erythrocyte sedimentation rate (ESR, ρ=0.285, P < 0.001). SIRI was only positively correlated with BU onset (ρ=0.301, P=0.006). Logistic regression analysis demonstrated that eleva-ted SII was an independent risk factor for BU onset (OR=1.003, 95% CI: 1.001-1.004, P < 0.001). ROC curve analysis indicated that the optimal thresholds for SII were 711.800 [area under curve (AUC)=0.752] for predicting BU onset, 1 622.300 (AUC=0.741) for predicting inflammatory activity, and 1 634.200 (AUC=0.726) for predicting poor prognosis. The corresponding thresholds for SIRI were 1.260 (AUC=0.709), 1.390 (AUC=0.704), and 2.790 (AUC=0.678), respectively. Kaplan-Meier analysis indicated that elevated SII independently predicted adverse prognostic events (HR=3.440, 95%CI: 1.040-11.410, P=0.043). SII and SIRI may serve as potential clinical indicators for predicting inflammatory activity and prognosis in BD patients with uveitis. SII, in particular, demonstrates superior predictive performance for BU onset and disease activity, providing a basis for early identification of high-risk patients and clinical decision-making.

The associations of two novel inflammation biomarkers, systemic inflammation response index (SIRI) and systemic immune inflammation index (SII), with mortality risk in patients with chronic heart failure (CHF) are not well-characterized. This retrospective cohort study included patients with CHF in two medical centers of Chinese People's Liberation Army General Hospital, Beijing, China. The outcomes of this study included in-hospital mortality and long-term mortality. Associations of SIRI and SII with mortality were assessed using multivariable regressions and receiver operating characteristic (ROC) analyses. A total of 6232 patients with CHF were included in the present study. We documented 97 cases of in-hospital mortality and 1738 cases of long-term mortality during an average 5.01-year follow-up. Compared with patients in the lowest quartile of SIRI, those in the highest quartile exhibited 134% higher risk of in-hospital mortality (adjusted odds ratio, 2.34; 95% confidence interval [CI], 1.16-4.72) and 45% higher risk of long-term mortality (adjusted hazard ratio, 1.45; 95% CI, 1.25-1.67). Compared with patients in the lowest quartile of SII, those in the highest quartile exhibited 27% higher risk of long-term mortality (adjusted hazard ratio, 1.27; 95% CI, 1.11-1.46). In ROC analyses, SIRI showed better prognostic discrimination than C-reactive protein (area under the curve: 69.39 vs 60.91, P = 0.01, for in-hospital mortality; 61.82 vs 58.67, P = 0.03, for 3-year mortality), whereas SII showed similar prognostic value with C-reactive protein. SIRI and SII were significantly associated with mortality risk in patients with CHF. SIRI may provide better prognostic discrimination than C-reactive protein.

Background: With the increase in pediatric obesity, the prevalence of metabolic syndrome (MetS) is rising worldwide. Early identification of children with obesity who are prone to developing MetS is important. Objectives: This study aimed to evaluate the value of the Systemic Immune–Inflammation Index (SII) and the Systemic Inflammatory Response Index (SIRI) in predicting MetS in obese children and adolescents. Methods: This prospective single-center cross-sectional study involved 99 children and adolescents with obesity. The patients were assigned to two groups, MetS+ (n = 42) and MetS- (n = 57), based on the presence of MetS. Complete blood count results from the first visit were evaluated. Results: The white blood cell (WBC), platelet, and neutrophil counts were higher in the MetS+ group (P = 0.003, P = 0.022, and P &lt; 0.001, respectively), while no significant difference was observed in lymphocyte (P = 0.865) and monocyte counts (P = 0.488) between the two groups. When inflammatory parameters were compared, SII (P &lt; 0.001), platelet-to-lymphocyte ratio (PLR) (P = 0.024), neutrophil-to-lymphocyte ratio (NLR) (P = 0.002), and SIRI (P = 0.012) were significantly elevated in the MetS+ group compared to the MetS- group. Binary logistic regression analysis revealed that SII and homeostasis model assessment of insulin resistance (HOMA-IR) were statistically significant risk factors for the presence of MetS (P = 0.003, P = 0.012, respectively). Additionally, a significant positive correlation was found between SII and diastolic blood pressure (DBP) (P = 0.024), high-density lipoprotein cholesterol (HDL-C) (P = 0.019), and fasting plasma glucose (FPG) (P = 0.048), as well as between SIRI and HDL-C (P = 0.044) and FPG (P &lt; 0.001). Receiver operating characteristic analysis of the SII and SIRI ability to predict MetS in adolescents and children with obesity showed that the SII was more discriminative than the SIRI, with a specificity of 0.82, sensitivity of 0.57, and an area under the curve of 0.708. Conclusions: The SII and SIRI can be used for the early diagnosis of MetS in pediatric obesity patients.

Inflammation is important in the development of systemic lupus erythematosus (SLE). Systemic inflammation response index (SIRI) and systemic immune-inflammation index (SII) are novel clinical markers of inflammation with prognostic value in different diseases. However, the value of SIRI and SII as inflammation predictors in SLE remains unclear. This study explores the SIRI and SII as potential biomarkers for SLE. Data from 280 individuals, including newly diagnosed SLE patients and healthy controls, were collected and divided into three groups: SLE without lupus nephritis (NLN) group (n=93), lupus nephritis (LN) group (n=96) and healthy control group (n=91). Differences in SIRI and SII among the three groups were compared. Logistic regression and Pearson linear analysis were used to analyze the predictive value and correlation of SIRI and SII with SLE and systemic lupus erythematosus disease activity index 2000 (SLEDAI-2K). Receiver operating characteristic (ROC) curves evaluated SIRI and SII in predicting SLE, SLE disease activity, and LN. The SIRI and SII values were significantly higher in the LN group compared to the NLN group (p<0.01). SII had the largest area under the ROC curve for predicting LN (AUC: 0.6775, 95%CI: 0.6020 - 0.7531). Logistic regression analysis showed SIRI and SII as independent risk factors for LN. Pearson linear analysis indicated SIRI and SII were positively correlated with SLEDAI-2K (rSIRI=0.25, rSII=0.24, p<0.05). SIRI and SII are biomarkers of disease activity and renal involvement in SLE patients that can be used to evaluate and predict for SLE occurrence, disease activity, and lupus nephritis occurrence assessment.

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

BackgroundThe aim of this study was to explore the association of systemic inflammatory biomarkers (systemic immune-inflammation (SII) index and systemic inflammatory response index (SIRI)) with the prevalence of ocular disease in the general population of the United States (U.S.).MethodsWe conducted a cross-sectional study of subjects in the National Health and Nutrition Examination Survey 2005–2008 years. For the analysis of the association of SII index, and SIRI with the prevalence of ocular disease (glaucoma, cataract, age-related macular degeneration (ARMD), and diabetic retinopathy), the restricted cubic spline (RCS) plot, multivariable logistic regression models, and subgroup analysis were performed.ResultsThere was a total of 5377 individuals. As shown by the RCS plot, SII index and SIRI were linked with ARMD risk in a U-shaped pattern. Additionally, the SII index and SIRI were linearly positive with glaucoma and cataract. Finally, the risk of diabetic retinopathy was associated with the L-shaped and N-shaped curves of the SII index and SIRI, respectively.ConclusionsTwo new systemic inflammatory biomarkers, SII index and SIRI, are closely related to the risk of eye disease. There are different associations between SII index and different ocular diseases. This should raise more concerns and lead to better prevention strategies for systemic inflammation.

There are many applications to emergency services due to acute colonic diverticulitis. It is necessary to decide whether these patients are complicated, to quickly predict their prognosis, and to decide whether medical or invasive treatment is necessary. We planned to research effectiveness NLR, NLR, SII, and SIRI values calculated using hemogram data can predict the prognosis of acute diverticulitis. We managed a retrospective scanning with patients who applied with a diagnosis of acute diverticulitis between 06/2020 and 04/2023. Demographic data (age, gender, previous surgery, comorbid diseases), tomographic Hinchey classification, location of diverticulitis, applied treatment, and obtained from blood parameters at presentation to the emergency department WBC, CRP, NLR, dNLR, SII, SIRI parameters were recorded from the electronically registered patient files. According to the Hinchey classification, those with Hinchey 0 and 1a were included in the noncomplicated group A class because they were followed up with outpatient medical follow-up. Those with Hinchey 1b,2,3,4 were included in the complicated GROUP B class. Differences in WBC, CRP, NLR, dNLR, SIRI, SII values between the complicated and noncomplicated groups were evaluated statistically. There were 286 patients with acute diverticulitis on the dates indicated. The number of patients eligible for the study was eighty-two. According to Hinchey's classification, 56 patients had noncomplicated acute diverticulitis (SAD) and 26 patients had complicated diverticulitis (CAD). These diagnoses were given based on tomography findings and clinical evaluations. The hospital stay was longer in the CAD group compared to the SAD group (p < 0.001) statistically significantly. The rate of surgical procedures and percutaneous interventions in the CADs was higher than SADs (p: 0.040) statistically significantly. WBC (white blood cell), NLR, dNLR, SIRI, SII and CRP parameters were higher in CADs than in SADs as statistically significant. Spearman's correlation analysis showed between the Hinchey classification and the NLR, dNLR, SII, SIRI, CRP, WBC parameters with high correlation as positive. Determination of values SIRI (2.42), NLR (3.35), SII (907.44) dNLR (4.63), CRP (15.25) WBC (11.16) and specificity and fractionation of these values ROC analysis was performed for this purpose. Highest AUC (area under the curve) value was found in WBC [0.807 0.703-0.910)], SIRI [0.786 (, 0.681-0.892)], SII [0.767 (0.654-0.880)], NLR [0.740 (0.624-0.854)], dNLR [0.739 (0.625-0.853)]. This study showed that there are SII, SIRI dNLR, NLR, CRP, and WBC values in patients presenting with acute diverticulitis a very high correlation with Hinchey classification in distinguishing complicated and non-complicated acute diverticulitis (p < 0.01). These data were higher in CADs than in SADs statistically significantly. The use of these data can both prevent unnecessary radiation in patients suspected of acute diverticulitis by reducing unnecessary tomography scans and can be valuable in predicting the prognosis of diverticulitis at a low cost.