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Background: Prognostic nutritional index (PNI) and systemic immune-inflammatory index (SII) are two novel markers that have emerged as potential candidates as an early indication of the severity of the disease in coronavirus disease 2019 (COVID-19) patients. Objective: The objective of the study is to assess the utility of the prognostic nutritional index (PNI) and systemic immune-inflammatory index (SII) as markers of severity among patients with COVID-19 infection. Methods: This is a retrospective study conducted in a tertiary care centre in South India. A total of 80 patients diagnosed with COVID-19 were included in the study. The patients were divided into mild, moderate, and severe groups based on the clinical parameters as per Indian Council of Medical Research guidelines. Lab values taken at admission were obtained from patient records, using which the PNI and SII were calculated using standard formulae. These markers were correlated with the severity of the COVID-19 illness. Results: PNI and SII were significantly elevated in the patients with severe COVID-19 illness as compared with mild COVID-19 illness. The mean PNI among subjects with mild COVID-19 and severe COVID-19 being 46.62 ± 6.51 and 34.09 ± 5.81, respectively. The mean SII among subjects with mild COVID-19 was 9,52,287.2 ± 1,42,113, and among subjects with severe COVID-19 was 15,39,461 ± 8,04,285. The cut-off value for PNI and SII for predicting severity of COVID-19 illness was 35.93 and 5,82,400, respectively. The sensitivity for PNI was 87.5, and the SII was 95. Conclusion: The present study showed a significant correlation between the SII and PNI as markers used to determine the severity of COVID-19. Based on these findings, it can be effectively used independently of other markers to predict critical illness among COVID-19 patients.

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BACKGROUND: Inflammation plays an important role in proliferation, migration, and invasion of tumor cells; therefore, many research has been done to investigate inflammation parameters including systemic immune-inflammatory index (SII). Dexamethasone, a strong anti-inflammatory, is still widely used as the main treatment in vasogenic edema. High-dose administration (16 mg/day) is recommended in patients with brain tumors with increased intracranial pressure. We performed this retrospective study to determine SII profile, dexamethasone use, and the effect of high-dose dexamethasone on SII in patients with brain tumors. METHODS: We performed a retrospective study on patients with brain tumors in 2022-2023 period who were treated with intravenous high-dose dexamethasone. Patient demographics, clinical characteristics of the brain tumor, concurrent infection, as well as dexamethasone dose and duration were recorded. Platelet, neutrophil, and lymphocyte count obtained prior to dexamethasone administration, and on the fifth to seventh day were also collected. SII was calculated by the following formula: neutrophil × platelet counts/lymphocyte. Data were then analyzed using Microsoft Excel 2019 and SPSS 29.0.2.0. RESULTS: We enrolled 56 patients with brain tumors, age 47±13.5 years, 78.6% were female, 69.6% had malignant brain tumors (brain metastases and high-grade primary brain tumors) and 26.8% had concurrent infection. High-dose dexamethasone was administered with average dose of 16.8±3.3 mg/day for average duration of 4.8±1.8 days. SII was significantly higher in malignant compared to benign brain tumors both in prior and after dexamethasone administration (P=0.02, P=0.01). SII was significantly higher in metastasis brain tumor compared to primary brain tumor (P=0.005). High-dose dexamethasone significantly increased SII and decreased lymphocyte count (P=0.006, P=0.04). CONCLUSIONS: SII was found higher in malignant brain tumor and brain metastasis. High-dose dexamethasone was administered with average dose of 16.81±3.37 mg/day for average duration of 4.78±1.84 days. SII was found to be higher after high-dose dexamethasone, due to a decrease of lymphocyte counts in peripheral blood.

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OBJECTIVE: To assess the neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) and systemic immune-inflammatory index (SII), as diagnostic markers for neonatal sepsis. METHODS: This retrospective study involve neonates with sepsis and healthy neonates as controls. NLR, PLR, and SII were compared between groups. RESULT: In total, 60 neonates with sepsis and 60 healthy controls were involved in the study. Compared with controls, the sepsis group had higher values for NLR, PLR and SII. Logistic regression analysis suggested that the NLR, PLR and SII were independent risk factors for neonatal sepsis. In addition, receiver operating characteristic (ROC) curve analysis indicated that the NLR, PLR and SII were reliable predictors of neonatal sepsis and SII had the best predictive value. CONCLUSIONS: NLR, PLR and SII appear to be useful indicators for predicting neonatal sepsis.

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We investigated the prognostic implications of the systemic immune-inflammatory index (SII), atherogenic index of plasma (AIP), C-reactive protein/albumin ratio (CAR), neutrophil-lymphocyte ratio (NLR), prognostic nutritional index (PNI), and triglyceride/glucose index (TGI) in the MORtality predictors in the CORonary Care Units in TURKey (MORCOR-TURK) population. This is the largest registry of coronary care unit (CCU) patients in Turkey (3157 patients admitted to CCU in 50 different centers). The study population was divided into two according to in-hospital survival status; 137 patients (4.3%) died in-hospital follow-up. A significant correlation was found between death and SII, CAR, NLR, and PNI but not for AIP and TGI in logistic regression. In Model 1 (combining parameters proven to be risk predictors), the -2 log-likelihood ratio was 888.439, Nagelkerke R2 was 0.235, and AUC (area under curve) was 0.814 (95% CI: 0.771-0.858). All other models were constructed by adding each inflammatory marker separately to Model 1. Only Model 3 (CAR + Model 1) had a significantly greater AUC than Model 1 (DeLong P = .01). Our study showed that CAR, but not other inflammatory index, is a significant predictor of in-hospital mortality in CCU patients when added to proven risk predictors.

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BACKGROUND: Necrotizing pneumonia (NP) is a rare serious complication of community-acquired pneumonia (CAP) in children, which is characterized by a protracted course of the disease and a prolonged hospital stay. This study aimed to assess the role of systemic immune-inflammatory index and systemic inflammatory response index in predicting early lung necrotization in children with CAP. METHODS: This study included all children hospitalized in Pediatric Pulmonology Unit, Tanta University, Egypt, with CAP between the ages of two months and 18 years. Systemic inflammatory indices, including the neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), monocyte/lymphocyte ratio (MLR), systemic immune-inflammatory index (SII), and systemic inflammation response index (SIRI), were calculated on patients' admission. RESULTS: The study involved a total of 228 children, 42 patients had NP, 46 patients had parapneumonic effusion, and 140 patients had non-complicated CAP. Patients with NP were substantially younger (p = 0.002), stayed in the hospital longer (p < 0.001), had a longer duration of symptoms before hospital admission (p < 0.001), and had fever for a longer duration than those in the other groups (p < 0.001). Regarding the inflammatory ratios, patients with NP had significantly higher MLR, PLR, SII, and SIRI than those in the other groups (p = 0.020, p = 0.007, p = 0.001, p = 0.037, respectively). ROC curve analysis showed that the combined SII + SIRI + D-dimer showed the highest AUC with a good specificity in predicting the diagnosis of NP. CONCLUSIONS: SII, SIRI, and D-dimer may be beneficial biomarkers for predicting the occurrence of NP in children when performed on patients' admission. In addition, it was found for the first time that combined SII + SIRI + D-dimer had a good sensitivity and specificity in the diagnosis of NP.

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OBJECTIVE: Systemic inflammatory biomarkers recently studied in schizophrenia include neutrophil/lymphocyte ratio (NLR), monocyte/lymphocyte ratio (MLR), platelet/lymphocyte ratio (PLR), systemic immune inflammation index (SII), and systemic inflammation response index (SIRI). SIRI, a novel inflammatory marker, has not been studied in different stages of schizophrenia. We aimed to compare NLR, MLR, PLR, SII, and SIRI values between psychotic exacerbation and remission values of the same patients with schizophrenia and a healthy control group. METHOD: In this study, 86 patients with schizophrenia who were hospitalized due to psychotic relapse, the same patient group who were in remission after treatment, and 86 age-sex-matched healthy control subjects were analyzed. Inflammatory marker values of the patient group in both the psychotic exacerbation (PE) and the remission (R) period were analyzed and compared with healthy controls (HC). RESULTS: NLR, MLR, PLR, SII, and SIRI values were significantly higher in the schizophrenia-PE group than in the HC group. NLR, MLR, SII, and SIRI values were significantly higher in the schizophrenia-PE group than in the schizophrenia-R group. MLR values were significantly higher in the schizophrenia-R group than in the HC group. CONCLUSION: These findings may be interpreted as NLR, SII, and SIRI, which may be considered as state biomarkers, and MLR may be a trait marker for schizophrenia.

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Background: The study aimed to examine the association between the systemic immune-inflammation index (SII), a contemporary metric of systemic inflammatory response, and biological aging, which are closely interconnected processes. Methods: This cross-sectional study utilized 10 cycles of data from the NHANES database spanning from 1990 to 2018. The study examined the relationship between the SII index, calculated as P * N/L, where P represents preoperative peripheral platelet count, N represents neutrophil count, and L represents lymphocyte count, and biological aging. Biological aging was assessed through various methods, such as phenotypic age, phenotypic age acceleration (PhenoAgeAccel), biological age, and biological age acceleration (BioAgeAccel). Correlations were analyzed using weighted linear regression and subgroup analysis. Results: Among the 7,491 participants analyzed, the average age was 45.26 ± 0.34 years, with 52.16% being female. The average phenotypic and biological ages were 40.06 ± 0.36 and 45.89 ± 0.32 years, respectively. Following adjustment for potential confounders, elevated SII scores were linked to increased phenotypic age, biological age, Phenotypic age acceleration, and Biological age acceleration. Positive correlations were observed between health behavior and health factor scores and biological aging, with stronger associations seen for health factors. In health factor-specific analyses, the ß coefficient was notably higher for high BMI. The robust positive associations between SII scores and both phenotypic age and biological age in the stratified analyses were consistently observed across all strata. Conclusion: The evidence from the NHANES data indicate that SII may serve as a valuable marker for assessing different facets of aging and health outcomes, such as mortality and the aging process. Additional research is warranted to comprehensively elucidate the implications of SII in the aging process and its utility as a clinical instrument for evaluating and addressing age-related ailments.

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Background Systemic lupus erythematosus (SLE) is a complex autoimmune disease with varied clinical manifestations affecting multiple organ systems. This study aimed to investigate the association between the systemic immune-inflammation index (SII) and disease activity, as well as proteinuria levels in patients with SLE. Methodology A total of 141 patients diagnosed with SLE and 99 control subjects were included in this retrospective study. SLE patients were divided into two groups based on the presence (52) or absence (89) of proteinuria. Demographic data, laboratory parameters, and disease activity scores were recorded. SII was calculated based on peripheral blood counts. Statistical analysis was performed to assess the relationship between SII levels and disease activity, as well as proteinuria. Results The statistical analysis among the three groups revealed that SII was significantly different in all three groups (p < 0.001). Moreover, within the SLE cohort, patients with proteinuria had significantly higher SII levels compared to those without proteinuria (p = 0.012). Correlation analysis revealed a positive association between SII and both proteinuria and Systemic Lupus Erythematosus Disease Activity Index 2000 (r = 0.215; p = 0.011 and r = 0.186; p = 0.028, respectively). Receiver operating characteristic analysis demonstrated that SII had potential clinical value in diagnosing SLE and predicting proteinuria development. Conclusions The findings of this study suggest that SII may serve as a useful biomarker for assessing disease activity and predicting proteinuria development in patients with SLE. Further research is warranted to validate these findings and explore the utility of SII in clinical practice for monitoring disease progression and treatment response in SLE.

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

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Rheumatoid arthritis (RA) is a chronic systemic inflammatory autoimmune disease. However, the relationship between the systemic immune-inflammation index (SII) and the prognosis of RA patients remains unclear. This study aimed to investigate the association between inflammatory biomarker SII and all-cause and cardiovascular mortality in RA patients. A retrospective analysis was conducted using data from the National Health and Nutrition Examination Survey database spanning from 1999 to March 2020. We assessed the association between the SII and all-cause as well as cardiovascular mortality in RA patients employing multivariable Cox proportional hazards regression analysis and restricted cubic spline plots. Receiver operating characteristic curves were employed to evaluate the prognostic capacity of SII in predicting outcomes in both the RA patients and the general population, alongside its predictive performance compared to other markers. This study comprised 2247 RA patients and a control cohort of 29,177 individuals from the general population. Over a 20-year follow-up period, 738 all-cause deaths and 215 deaths attributable to cardiovascular disease were documented in RA patients. We observed a nonlinear positive correlation between the SII and both all-cause and cardiovascular mortality in RA patients. Of significance, at an SII level of 529.7, the hazard ratio reached 1, signifying a transition from low to high mortality risk. Moreover, subgroup analysis did not reveal any potential interactions. Our study findings indicate a nonlinear positive correlation between the inflammatory biomarker SII and both all-cause and cardiovascular mortality in patients with RA.

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Introduction: The systemic immune inflammation index (SII), based on lymphocyte, neutrophil, and platelet counts, has been shown to be an independent indicator of no-reflow phenomenon during percutaneous intervention. However, the relationship between SII and no-reflow phenomenon (NRP) that develops after the procedure of saphenous vein grafts is unknown. Aim: In this study, we aimed to investigate the relationship between no-reflow phenomenon and SII during percutaneous intervention on saphenous vein grafts. Material and methods: A total of 133 patients who underwent percutaneous intervention for saphenous vein grafts due to acute coronary syndrome between 2019 and 2022 were included in this study. The receiver-operating characteristics (ROC) curve was used to determine the cut-off value of SII to predict the no-reflow. The multivariate regression was used to analyse the correlation between no-reflow and SII. Results: The median value of SII was significantly higher in patients with no-reflow in comparison with normal reperfusion (543 (447, 717) vs. 861 (642, 1272), p < 0.001). The optimal threshold for SII in predicting the no-reflow phenomenon was 613, with sensitivity and specificity of 84% and 66%, respectively. The area under the ROC curve (AUC) was 0.80 (95% CI: 0.73-0.89, p < 0.001). In multivariate analysis, SII ≥ 613 showed an independent predictive value for the no-reflow (OR = 4.02, 95% CI: 1.40-11.57, p < 0.001). Conclusions: Our results showed that high SII levels were independently associated with the development of no-reflow phenomenon in patients presenting with acute coronary syndrome and undergoing percutaneous intervention to the SVG.

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Systemic Immune Inflammatory Index (SII) is a novel indicator of inflammation. However, no studies have reported the effect of SII on the association between metals and total fat (TOFAT). We aim to investigate the mediated effect of SII on the relationship between urinary metals and TOFAT in a US adult population. This cross-sectional study was conducted among adults with complete information on SII, urine metal concentrations, and TOFAT from the 2011-2018 National Health and Nutrition Examination Survey (NHANES). Multifactorial logistic regression and restricted cubic splines were used to explore the association between urine metal levels and TOFAT. Furthermore, serial mediation analyses were used to investigate the mediating effect of SII on metals and TOFAT. A total of 3324 subjects were included in this study. After adjusting for confounders, arsenic (As), cadmium (Cd), cobalt (Co), cesium (Cs), inorganic mercury (Hg), molybdenum (Mo), manganese (Mn), lead (Pb), antimony (Sb), and thallium(Tl) had negative decreased trends of odds ratios for TOFAT (all P for trend < 0.05). In the total population, we found that Cd, Co, and Tu were positively associated with SII (ß = 29.70, 79.37, and 31.08), whereas As and Hg had a negative association with SII. The mediation analysis showed that SII mediated the association of Co with TOFAT, with the ß of the mediating effect being 0.9% (95%CI: 0.3%, 1.6%). Our findings suggested that exposure to As, Cd, and Hg would directly decrease the level of TOFAT. However, Co would increase TOFAT, completely mediated by SII, mainly exerted in females rather than males.

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Chronic kidney disease (CKD) is characterized by chronic inflammation, which mediates the progressive replacement of functional nephrons by fibrotic tissue. Hemogram-derived inflammatory markers are known to serve as markers of pathological conditions; however, their diagnostic value in feline CKD is still unknown. The aim of this retrospective study was to investigate selected hemogram-derived inflammatory markers (neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR) and the systemic immune-inflammatory index (SII)) in cats at different clinical stages of CKD. Eighty-eight client-owned cats with CKD and thirty-two healthy control cats were included. Cats with CKD were divided into two groups: early CKD (IRIS stage 1 and 2; 62 cats) and progressed CKD (IRIS stage 3 and 4; 26 cats). The values of inflammatory markers were compared between the two CKD groups and the control group. All investigated hemogram-derived inflammatory markers were significantly (p < 0.05) greater in cats with advanced CKD than in those in the other two groups. Additionally, we demonstrated a statistically significant weak to moderate correlation between serum urea, creatinine, selected hematologic and urinary parameters, and the investigated inflammatory markers in cats with CKD. Chronic inflammation can be easily and inexpensively assessed with hemogram-derived markers.

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Background: Psoriasis is a chronic dermatological condition characterized by a complex pathogenesis that impacts approximately 3% of adults in the United States and brings enormous social burdens. For many diseases, the systemic immune-inflammatory index (SII), defined as neutrophils × platelets/lymphocytes, has been recognized as a prognostic indicator. Therefore, we conducted a cross-sectional study to assess the association between SII and psoriasis among outpatient US adults. Methods: In this cross-sectional study, we used data on the US adults 20 to 59 years of age from the National Health and Nutrition Examination Survey (NHANES) spanning 2003-2006 and 2009-2014. Sample-weighted logistic regression and stratified analysis of subgroups were used. Results: Among the 16,831 adults, there were 8,801 women and 8,030 men, with a psoriasis prevalence rate of 3.0%. A fully adjusted model revealed a positive association between a SII higher than 479.15 × 109/L and a high risk of psoriasis. According to subgroup analysis and interaction testing (p for interaction > 0.05), age, sex, alcohol drinking status, marital status, and body mass index (BMI) were not significantly correlated with this positive association. Conclusion: Our findings suggested that SII higher than 479.15 × 109/L was positively associated with a high risk of psoriasis among outpatient US adults. To the best of our knowledge, this is the first cross-sectional study using NHANES data focused on the risk of higher SII on psoriasis among outpatient US adults. The outcomes of this cross-sectional serve to supplement previous research, indicating a need for larger-scale prospective cohorts for further validation.

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The systemic immune-inflammation index (SII), an integrated and ground-breaking inflammatory measure, has been widely used in various fields. We aimed to assess the association between the systemic immune-inflammation index (SII) and α-Klotho (a new anti-aging biomarker). In this cross-sectional investigation, people with complete information on SII and α-Klotho from the National Health and Nutrition Examination Survey (NHANES) between 2007 and 2016 were the study's subject population. SII was calculated by platelet count × neutrophil count/lymphocyte count. The association between SII and α-Klotho was investigated using multivariable linear regression and a generalized additive model. In order to explore the non-linear connection, we employed smoothed curve fitting. Subgroup analysis were also performed. A total of 13,701 participants with an average age of 57.73 ± 10.86 years were enrolled, of whom 51.53% were female. After fully adjustment, SII was negatively associated with serum soluble α-Klotho [ß(95% CI) = - 0.07 (- 0.08, - 0.05)]. Furthermore, we found L-shaped association between SII and klotho protein level, with the inflection point at 255 pg/ml. Subgroup analysis and interaction test revealed that there was no discernible dependence on gender, age, race, smoking, alcohol, diabetes and hypertension (all p for interaction > 0.05). SII level was negatively associated with serum klotho protein concentration in American adults. To verify our findings, more large-scale prospective investigations are still required.

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Blood urea nitrogen (BUN) level is one of the commonly used indicators to assess renal function and systemic immune-inflammatory status. In the adolescent population, changes in BUN levels may be associated with a variety of factors, including physiologic dehydration, lifestyle influences such as nutritional intake, physical activity, and possible endocrine or metabolic disorders. In recent years, more and more studies have shown that BUN levels are not only a reflection of kidney function, but it may also be related to the inflammatory state of the body. The Systemic Immune Inflammatory Index (SII) is a comprehensive index that takes into account platelet counts, neutrophil and lymphocyte counts, and is thought to be effective in reflecting the body's immune status and inflammatory response. However, research on the relationship between the two, SII and BUN, remains understudied in the adolescent population. The purpose of this study was to examine the relationship between SII and BUN levels in a population of American adolescents and to further analyze the factors that influence it. We conducted a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES) database. Using descriptive statistics, correlation analysis, and regression analysis, we explored the relationship between SII and BUN levels. We found a significant negative correlation between SII and BUN levels, with BUN levels decreasing when SII levels increased (BUN as the dependent variable and SII as the outcome variable). We performed a multiple regression analysis of this relationship, controlling for possible confounders such as gender, age, race, and BMI, and found that this negative correlation remained significant. Our findings reveal an important relationship between SII and BUN levels and provide new perspectives for understanding adolescent health.

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AIMS: The value of the systemic immune-inflammatory index (SII) in assessing adverse outcomes in various cardiovascular diseases has been extensively discussed. This study aims to evaluate the predictive value and risk stratification ability of SII for 30 day mortality in patients with acute decompensated heart failure (ADHF). METHODS: This analysis included 1452 patients hospitalized for ADHF, all the participants being part of the China Jiangxi-acute decompensated heart failure1 project. The risk stratification capability of the SII in patients with ADHF, as well as its correlation with the 30 day mortality risk among ADHF patients, was evaluated utilizing Kaplan-Meier survival analysis and multivariable Cox regression models. A restricted cubic spline was employed to model the dose-response relationship between the two, and the receiver operating characteristic curve was utilized to assess the predictive ability of SII for 30 day mortality. RESULTS: The Kaplan-Meier analysis revealed that the risk of mortality in the high SII group (SII ≥ 980 × 109/L) was significantly greater than that in the low SII group (SII < 980 × 109/L, log-rank P < 0.001). After adjusting for various confounding factors, a higher SII was associated with an increased risk of 30 day mortality in ADHF patients [hazard ratio (HR) = 2.03, 95% confidence interval (CI): 1.34-3.08]. Further restricted cubic spline analysis revealed a non-linear dose-response relationship between the two (P for non-linear = 0.006). Receiver operating characteristic analysis demonstrated that SII had a high accuracy in predicting 30 day mortality events in ADHF patients (AUC = 0.7479), and the optimal predictive threshold was calculated to be 980 × 109/L, a sensitivity of 0.7547 and a specificity of 0.7234. CONCLUSIONS: This study found a significant positive association between SII and 30 day all-cause mortality in ADHF patients. We determined the SII cut-off point for predicting 30 day all-cause mortality in patients with ADHF to be 980 × 109/L.

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BACKGROUND: Interstitial lung disease frequently coincides with pneumonia in clinical settings, and both conditions are closely associated with immunoinflammation. The Systemic Immune Inflammatory Index (SII) is a recently identified marker, and its connection to the prognosis of individuals suffering from interstitial lung disease and concurrent pneumonia remains unclear. The objective of this study was to scrutinize the correlation between varying SII levels and unfavorable outcomes in patients grappling with interstitial lung disease complicated by pneumonia. METHODS: This study encompassed a retrospective multicenter cohort of 324 patients diagnosed with interstitial lung disease and pneumonia, all receiving glucocorticoid treatment during their hospitalization. We initially conducted ROC analysis to determine the optimal SII threshold. Subsequently, we examined disparities in clinical symptoms, physical signs, clinical test data, and other clinical attributes among patients with differing SII levels. Later, we employed the Kaplan-Meier survival curve method to assess the association between distinct SII levels and the 30-day and 90-day mortality rates in patients dealing with interstitial lung disease complicated by pneumonia. Finally, a Cox regression model was employed to identify factors influencing adverse prognosis in these patients. RESULTS AND DISCUSSION: The findings demonstrated that the optimal SII threshold for predicting 30-day mortality was 1416.97, with an AUC of 0.633 (95% CI: 0.559-0.708) and a P value of <0.001. For 90-day mortality, the optimal SII threshold was 994.59, yielding an AUC of 0.628 (95% CI: 0.56-0.697) and a P value of <0.001. Noteworthy statistical distinctions emerged in dyspnea, cyanosis, and oxygenation index among patients with varying SII levels. Additionally, invasive mechanical ventilation, non-invasive ventilation, and extended infection duration independently constituted 30-day and 90-day mortality risk factors. Elevated heart rate and higher SII levels emerged as independent risk factors for 90-day mortality. CONCLUSION: To some extent, SII levels exhibit correlations with the clinical manifestations in patients grappling with interstitial lung disease complicated by pneumonia. Notably, a high SII level is an independent predictor for an unfavorable prognosis in these patients. Nevertheless, these findings warrant further validation through prospective cohort studies.

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Objectives: This study aimed to demonstrate how the prognostic nutritional index (PNI) and systemic immune-inflammatory index (SII) help predict the severity and prognosis of patients with type 2 diabetes (T2DM) and coronavirus disease (COVID-19). Methods: This retrospective cohort study included 501 T2DM patients (male, 42.1%; female, 57.9%) who were hospitalized due to COVID-19 between April 2020 and December 2020. The patients were divided into survivors and non-survivors. After comparing demographic and laboratory data between the groups, the correlation of PNI and SII with clinical and laboratory data was evaluated. Results: The median (interquartile) ages of the non-survivor and survivor groups were 74 (15) and 69 (14) years, respectively, and the difference was significant (p<0.001). The PNI was significantly lower in the non-survivor group than in the survivor group (p<0.001). The SII was significantly higher in the non-survivor group than in the survivor group (p<0.001). PNI was negatively correlated with glucose levels (r=-0.115, p=0.011). If the cut-off PNI value of 29.1 was used, it had a sensitivity and specificity of 76.2% and 76.3%, respectively, in predicting the severity of the illness and the risk of death in T2DM patients. Conclusion: Consequently, the PNI and SII levels are effective in predicting survival and disease severity in patients with COVID-19 and T2DM.

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Background: A novel inflammatory marker that measures the degree of systemic immunoinflammation, the systemic immuno-inflammation index (SII) is frequently used to forecast a number of illnesses. According to earlier studies, inflammation may play a role in the pathophysiology of hearing loss (HL). Methods: A sample from the National Health and Nutrition Examination Survey (NHANES) covering the years 2009 to 2018 was used in the current cross-sectional survey. Subgroup analysis and weighted multiple linear regression models were used to examine the independent linear correlation between SII and HL. Fitted smoothed curve analyses were also conducted to show the non-linear relationship between the two variables. Results: Among the 8,535 participants, the mean age was 40.92 ± 18.6 years, with 49.01% being male. Notably, individuals with hearing loss demonstrated an SII of 530.00 ± 320.72, while those with normal hearing displayed an SII of 491.21 ± 265.15. The mean ± SD values of low-frequency, speech-frequency, and high-frequency Pure Tone Average (PTA) hearing thresholds were 10.33 ± 9.79, 12.20 ± 11.11, and 22.48 ± 19.49 dB, respectively. A positive dose-response relationship between higher SII and hearing thresholds was observed after adjusting for potential confounders. Furthermore, the interaction analysis did not reveal any significant impact on this positive correlation. Conclusion: The results of our investigation suggest that the Systemic Inflammatory Index may serve as a potential biomarker for the likelihood of hearing loss. However, additional research is required to further elucidate the nature of this association.