Prognostic Significance of Admission Systemic Inflammation Response Index in Patients With Spontaneous Intracerebral Hemorrhage: A Propensity Score Matching Analysis

Machine learning based association between inflammation indicators (NLR, PLR, NPAR, SII, SIRI, and AISI) and all-cause mortality in arthritis patients with hypertension: NHANES 1999-2018

Background

This study aimed to evaluate the relationship between CBC-derived inflammatory markers (NLR, PLR, NPAR, SII, SIRI, and AISI) and all-cause mortality (ACM) risk in arthritis (AR) patients with hypertensive (HTN) using data from the NHANES.

Methods

We employed weighted multivariable logistic regression and WQS regression to explore the relationship between inflammatory markers and ACM in AR patients, as well as to determine the weights of different markers. Kaplan-Meier curves, restricted cubic splines (RCS) and ROC curves were utilized to monitor cumulative survival differences, non-linear relationships and diagnostic utility of the markers for ACM risk, respectively. Key markers were selected using XGBoost and LASSO regression machine learning methods, and a nomogram prognostic model was constructed and evaluated through calibration curves and decision curve analysis (DCA).

Results

The study included 4,058 AR patients with HTN, with 1,064 deaths over a median 89-month follow-up. All six inflammatory markers were significantly higher in the deceased group (p < 0.001). Weighted multivariable logistic regression showed these markers' elevated levels significantly correlated with increased ACM risk in hypertensive AR patients across all models (p < 0.001). Kaplan-Meier analysis linked higher marker scores to lower survival rates in AR patients with HTN (p < 0.001). WQS models found a positive correlation between the markers and hypertensive AR patients (p < 0.001), with NPAR having the greatest impact (70.02%) and SIRI next (29.01%). ROC analysis showed SIRI had the highest AUC (0.624) for ACM risk prediction, closely followed by NPAR (AUC = 0.618). XGBoost and LASSO regression identified NPAR and SIRI as the most influential markers, with higher LASSO-based risk scores correlating to increased mortality risk (HR, 2.07; 95% CI, 1.83-2.35; p < 0.01). RCS models revealed non-linear correlations between NPAR (Pnon-linear<0.01) and SIRI (Pnon-linear<0.01) with ACM risk, showing a sharp mortality risk increase when NPAR >148.56 and SIRI >1.51. A prognostic model using NPAR and SIRI optimally predicted overall survival.

Conclusion

These results underscore the necessity of monitoring and managing NPAR and SIRI indicators in clinical settings for AR patients with HTN, potentially improving patient survival outcomes.

The role of the systemic inflammatory response index in predicting postoperative atrial fibrillation

OBJECTIVE

The aim of the present study was to determine the effect of systemic inflammatory response index in predicting the development of postoperative atrial fibrillation after isolated coronary artery bypass grafting (CABG).

METHODS

The study was conducted at Nevşehir State Hospital, a secondary healthcare center. Patients who underwent elective isolated CABG between October 2018, when the first open-heart surgery was performed at our center, and December 2022 were included. The patients' data were retrospectively reviewed and recorded.

RESULTS

A total of 66 patients were included in the study (mean age: 64.14±8.59 years). Of these patients, 44 (66.7%) were male and 22 (33.3%) were female. Postoperative atrial fibrillation was present in 22 (33.3%) patients. Although the systemic inflammatory response index and systemic immune-inflammatory index values were higher in the patient group that developed postoperative atrial fibrillation, no significant difference was noted (p>0.050). Additionally, age and a family history of coronary artery disease were identified as important factors that significantly affected the development of postoperative atrial fibrillation (p=0.048 and p=0.01, respectively).

CONCLUSION

To the best of our knowledge, no study has investigated the relationship between postoperative atrial fibrillation and the systemic inflammatory response index. Although the present study did not find a statistically significant difference, our findings support the role of inflammation in predicting postoperative atrial fibrillation.

Potential blood biomarkers that can be used as prognosticators of spontaneous intracerebral hemorrhage: A systematic review and meta-analysis

BACKGROUND

Predicting nontraumatic spontaneous intracerebral hemorrhage (SICH) patient prognosis has been commonly practiced, particularly when providing informed consent and considering surgical treatment. Biomarkers might provide more real-time evaluation of SICH patients' condition than clinical prognostic scoring systems. This study aimed to evaluate the reliability of blood biomarkers in predicting prognosis in SICH patients by systematic review and meta-analysis.

METHODS

Studies that evaluated the association of blood biomarker(s) with mortality and/or functional outcome in SICH patients up to October 11, 2024, were identified through PubMed, Google Scholars, Scopus databases, and reference lists. Studies that satisfied the inclusion criteria were included in the meta-analyses. Good functional outcome was defined by patient's Glasgow Outcome Scale (GOS) ≥ 4 or modified Rankin scale mRS ≤ 2. Blood biomarkers were classified into the following categories: angiogenic factors, growth factors, inflammatory biomarkers, coagulation parameters, blood counts, and others. Individual meta-analysis was performed for every evaluation endpoint:7 days, 30 days, 3 months, 6 months, and 1 year. Meta-analyses were performed using Random Effect Mean-Difference with a 95% Confidence Interval for continuous data and visualized as forest plots in RevMan version 5.3 software. Cochrane Tool to Assess Risk of Bias in Cohort Studies was used to assess potential risk of bias of the included studies. GRADE Profiler was used to assess quality of evidence.

RESULTS

Seventy-seven studies fulfilled the inclusion criteria. Surviving SICH patients have significantly lower C-reactive protein (CRP), D-dimer, copeptin, S100β, white blood cell (WBC), monocyte, and glucose than non-surviving patients. SICH patients with good functional outcome have lower D-dimer, Interleukin 6 (IL-6), tumor necrosis factor α (TNF-α), WBC count, neutrophil count, monocyte count, copeptin and significantly higher lymphocyte counts and calcium levels. Out of all blood biomarkers that were evaluated, only S100β and copeptin had very high effect size and high certainty of evidence.

CONCLUSION

It is interesting to notice that many blood biomarkers significantly associated with SICH patients' outcomes are related to inflammatory responses. This suggests that modulation of inflammation might be essential to improve SICH patients' prognosis. We confidently concluded that S100β and copeptin are the most reliable blood biomarkers that can be used as prognosticators in SICH patients. On other biomarkers, in addition to heterogeneities and inconsistencies, several factors might affect the conclusions of current meta-analysis; thus, future studies to increase the certainties of evidence and effect size on other biomarkers are crucial.

Monocyte-lymphocyte ratio predicts cardiovascular diseases death in individuals with type 2 diabetes

PURPOSE

Previous studies have shown higher cardiovascular mortality risk with higher monocyte-lymphocyte ratio levels in general population. However, the levels of oxidative stress in individuals with type 2 diabetes are higher than those in the general population, which may affect the link between monocyte-to-lymphocyte ratio and cardiovascular disease deaths. And the association between the monocyte-to-lymphocyte ratio and mortality risk in people with type 2 diabetes still be unknown. This study aimed to investigate the prognostic significance of monocyte-to-lymphocyte ratio in type 2 diabetes.

METHODS

This analysis involved 2,954 individuals with type 2 diabetes from the National Health and Nutrition Examination Survey 1999-2010. The National Death Index records through December 31, 2019, was used to determine all-cause and cardiovascular mortality. The prognostic roles were determined using Cox regression models, restricted cubic spline analysis, and time-dependent receiver operating characteristic curve analysis.

RESULTS

During an average follow-up period of 12.4 years, a total of 1,007 deaths occurred, while 252 were due to cardiovascular disease. An elevated monocyte-to-lymphocyte ratio level exhibited a significant dose-response relationship with an increased risk of all-cause mortality (1.34 [95% CI 1.12, 1.60] for all-cause mortality [P trend = 0.001]). The multivariable-adjusted HR was 1.81 (95% CI 1.25, 2.63) (P trend = 0.001) for cardiovascular mortality indicating a U-shaped relationship (P nonlinear = 0.013).

CONCLUSIONS

The results of this study indicate a U-shaped relationship between the monocyte-to-lymphocyte ratio and cardiovascular mortality in individuals with diabetes. Both very low and high monocyte-to-lymphocyte ratio monocyte-to-lymphocyte ratio values were found to be associated with increased cardiovascular mortality risk.

Neutrophil-lymphocyte ratio: A simple and accurate biomarker for the prognosis of patients with intracerebral bleeding, a study of 115 cases

Background

Stroke is high in both mortality and disability; this makes stroke the world's second leading cause of death and the number one cause of long-term impairment. Surprisingly, intracerebral hemorrhage (ICH), the second largest type of stroke, is deadlier than ischemic strokes , with a high mortality rate and lack of effective treatment for ICH. This case report aims to identify and collect the various factors that increase the mortality rate of patients with ICH.

Methods

A retrospective review was done on 115 patients who experienced ICH at neurosurgical unit care between 2021 and 2024. Data were collected from medical record post admission reports. The study concentrated on factors such as the initial Glasgow coma scale (GCS) score, the volume of intracerebral bleeding, the ratio of neutrophils to lymphocytes, leukocyte count, and the administration of neuroprotective medications. We first ran univariate tests. Next, to evaluate the relationship between each component and patient mortality, we performed bivariate analyses with Spearman's correlation test. To determine the predictor factor from all the various variables that have been evaluated, we use multivariate analysis with logistic regression.

Results

Univariate analysis results show that ICH often occurs at the age of 41-50 years in males. Meanwhile, most of the patients who died were men aged 51-60 years. The results of the bivariate analysis showed that each predictor had a significant relationship with mortality. GCS has a negative relationship with mortality (-0.633 with P < 0.001). The neutrophil-to-lymphocyte ratio (NLR) (0.418), leukocyte count (0.527), and ICH blood volume (0.671) had a positive effect on ICH mortality. Multivariate analysis with logistic regression demonstrated that all predictor factors had a significant impact (P < 0.05) on mortality patients with hemorrhagic stroke. The most common neuroprotective therapy used in hemorrhagic stroke is the combination of citicoline and mecobalamin. The co-administration of citicoline and mecobalamin showed the highest number of survivors and deaths, indicating that no effective therapy for ICH has been found among all the neuroprotectants administered.

Conclusion

This study showed that GCS, ICH volume, leukocyte count, and NLR are predictors of mortality in ICH patients. At present, no ICH therapy can reduce complications and improve the physical and mental condition of ICH patients. Therefore, further research is needed to find an effective therapy for ICH.

The systemic immune-inflammation index and systemic inflammation response index are useful for predicting mortality in patients with diabetic nephropathy

BACKGROUND

This study investigated the correlation between the systemic immune-inflammation index (SII) and the systemic inflammation response index (SIRI) and all-cause, cardiovascular, and kidney disease mortality in patients with diabetic nephropathy (DN). It aimed to provide a new predictive assessment tool for the clinic and a scientific basis for managing inflammation in DN.

METHODS

The data utilized in this study were obtained from the National Health and Nutrition Examination Survey (NHANES) database, spanning 1999 to 2018. A total of 2641 patients diagnosed with DN were included in the analysis. The association between SII and SIRI levels and mortality in patients with DN was investigated using multivariate Cox proportional risk regression models. These relationships were further validated by Kaplan-Meier survival curves and restricted cubic spline (RCS) modeling, and subgroup analyses were performed to explore the heterogeneity among different characteristic subgroups.

RESULTS

The multivariate Cox regression analysis indicated that SII and SIRI levels were independently associated with all-cause mortality and cardiovascular mortality in patients with DN. SIRI levels were found to be an independently associated factor with kidney disease mortality in patients with DN. Patients in the highest quartile of SII and SIRI exhibited a 1.49-fold and 1.62-fold increased risk of all-cause mortality, respectively, compared to patients in the lowest quartile. The risk of cardiovascular mortality was 1.31 and 1.73 times higher than that in patients in the lowest quartile, respectively. The risk of kidney disease mortality in patients in the highest quartile of SIRI was 2.74 times higher than that in patients in the lowest quartile. Kaplan-Meier survival curve and RCS analyses further confirmed the positive association between SII and SIRI and mortality and a significant nonlinear relationship between SII and all-cause mortality. The SII and SIRI indices offer incremental value in model predictive power for mortality in patients with DN. Subgroup analyses demonstrated that the correlation between SII and SIRI and mortality risk was stable but heterogeneous across different subgroups.

CONCLUSION

SII and SIRI can be utilized as biomarkers for forecasting the likelihood of all-cause and cardiovascular mortality in patients with DN.

Association of systemic inflammation response index with mortality risk in older patients with hip fracture: a 10-year retrospective cohort study

Objective

With a rapidly aging global population, the assessment of mortality risk following hip fracture in older adults has received increasing attention. Recently, the system inflammation response index (SIRI) has been identified as a novel prognostic marker to reflect both systemic inflammation and immune status. However, it is not yet known whether SIRI is a potential predictor of subsequent death in hip fracture patients. Therefore, this study aimed to investigate the association between SIRI and mortality in older patients with hip fracture.

Methods

A total of 1,206 older hip fracture patients undergoing surgery between January 2013 and December 2022 were consecutively derived from our longitudinal database. Patients were divided into three groups according to SIRI tertiles, calculated as neutrophil × monocyte / lymphocyte. Survival status was obtained from medical records or telephone interviews, and the study outcome was all-cause mortality after hip fracture at the longest follow-up. Multivariate Cox proportional hazard model and restricted cubic spline (RCS) regression model were used to evaluate the association between SIRI and mortality. Moreover, a series of sensitivity analyses were conducted to further validate the robustness of the association.

Results

During a median follow-up of 43.85 months, 337 patients (27.94%) died. After full adjustment, each unit increase in SIRI was significantly associated with a 2.2% increase in overall mortality (95% confidence interval [CI]: 1.001-1.042, p = 0.029). Similarly, compared with the first tertile of SIRI, the second and third tertile showed a 1.335-fold (95% CI: 1.011-1.762, p = 0.042) and 1.447-fold (95% CI, 1.093-1.917, p = 0.010) higher risk of death. Sensitivity analyses confirmed the stability of the association. Moreover, RCS analysis revealed a positive non-linear relationship between SIRI and mortality (P for nonlinearity = 0.021).

Conclusion

High SIRI level at admission was significantly and positively associated with an increased risk of death, suggesting that SIRI may be an independent predictor of mortality in older patients with hip fracture.

Neutrophil-to-lymphocyte ratio, white blood cell, and C-reactive protein predicts poor outcome and increased mortality in intracerebral hemorrhage patients: a meta-analysis

Objective

Inflammation participates in the pathology and progression of secondary brain injury after intracerebral hemorrhage (ICH). This meta-analysis intended to explore the prognostic role of inflammatory indexes, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), white blood cell (WBC), and C-reactive protein (CRP) in ICH patients.

Methods

Embase, PubMed, Web of Science, and Cochrane Library were searched until June 2023. Two outcomes, including poor outcome and mortality were extracted and measured. Odds ratio (OR) and 95% confidence interval (CI) were presented for outcome assessment.

Results

Forty-six studies with 25,928 patients were included in this meta-analysis. The high level of NLR [OR (95% CI): 1.20 (1.13-1.27), p < 0.001], WBC [OR (95% CI): 1.11 (1.02-1.21), p = 0.013], and CRP [OR (95% CI): 1.29 (1.08-1.54), p = 0.005] were related to poor outcome in ICH patients. Additionally, the high level of NLR [OR (95% CI): 1.06 (1.02-1.10), p = 0.001], WBC [OR (95% CI): 1.39 (1.16-1.66), p < 0.001], and CRP [OR (95% CI): 1.02 (1.01-1.04), p = 0.009] were correlated with increased mortality in ICH patients. Nevertheless, PLR was not associated with poor outcome [OR (95% CI): 1.00 (0.99-1.01), p = 0.749] or mortality [OR (95% CI): 1.00 (0.99-1.01), p = 0.750] in ICH patients. The total score of risk of bias assessed by Newcastle-Ottawa Scale criteria ranged from 7-9, which indicated the low risk of bias in the included studies. Publication bias was low, and stability assessed by sensitivity analysis was good.

Conclusion

This meta-analysis summarizes that the high level of NLR, WBC, and CRP estimates poor outcome and higher mortality in ICH patients.

New Inflammatory Marker Associated with Disease Activity in Gouty Arthritis: The Systemic Inflammatory Response Index

Background

The systemic immune-inflammatory index (SII) and systemic inflammatory response index (SIRI), as novel non-specific inflammatory markers, have recently drawn attention. At present, no studies have been conducted to investigate the value of SII and SIRI in gouty arthritis (GA), so we explored their possible association with GA disease activity.

Methods

The study enrolled 474 patients with acute gouty arthritis (AG), 399 patients with intercritical gouty arthritis (IG) and 194 healthy controls (HC). The differences in Monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), SII, and SIRI levels among different groups were assessed. The changes in the above indicators before and after treatment in the AG and IG groups were evaluated. Multivariate logistic regression analysis was assessed influencing factors for the acute gout attack. ROC curves were plotted to evaluate their diagnostic value for AG.

Results

Compared with the IG group, the erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), PLR, and incidence of hyperlipidemia in the AG group were significantly higher, and the duration of disease was significantly shorter (P < 0.05). The MLR, NLR, SII and SIRI in the AG group were significantly higher than those in the IG and HC groups (P < 0.05). Compared with baseline, decreased MLR, NLR, PLR, SII and SIRI were observed in the AG group after treatment (P < 0.05), while there was no significant difference in the IG group before and after treatment (P > 0.05). SIRI was positively correlated with ESR and CRP (P < 0.05). Multivariate logistic regression analysis result showed that duration of disease, hyperlipidemia, ESR, CRP, and SIRI were influencing factors of acute gout attack (P < 0.05). The AUC of ESR, CRP and SIRI on the diagnosis in AG were 0.664, 0.755, and 0.674, respectively.

Conclusion

SIRI may be used as a new inflammatory marker of disease activity with gouty arthritis.

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

BACKGROUND

Stroke, which is the main element of cerebrovascular disease (CVD), has become the foremost reason for death and disability on a global scale. The systemic inflammation response index (SIRI), a newly developed and comprehensive indicator, has demonstrated promise in forecasting clinical results for diverse ailments. Nevertheless, the uncertainty surrounding the assessment and prediction of clinical outcomes for stroke patients by SIRI persists, and the conflicting findings from the limited studies conducted on this matter further complicate the situation. Consequently, we performed a thorough systematic review and meta-analysis to explore the correlation between SIRI and the clinical results in individuals suffering from stroke.

METHODS

This research was registered in PROSPERO and carried out following the PRISMA guidelines. A thorough investigation was carried out on PubMed, Embase, the Cochrane Library, Web of Science, and Scopus databases. Furthermore, we conducted a manual search in Chinese databases, such as China national Knowledge Infrastructure (CNKI), WanFang, VIP, and China Biology Medicine (CBM). We assessed the potential for bias in the studies included by utilizing the Newcastle-Ottawa Scale (NOS) tool. Adverse clinical outcomes were the main focus of the study, with secondary endpoints including mortality, the predictive value of SIRI, SIRI values across various endpoints, and clinical parameters associated with subarachnoid hemorrhage (SAH) in relation to low and high SIRI group.

RESULTS

Following rigorous evaluation, a grand total of 22 investigations, encompassing a populace of 12,737 individuals, were considered suitable for incorporation in the final analysis. The findings from our meta-analysis indicate a strong and consistent correlation between elevated SIRI levels and adverse functional outcomes, irrespective of the method used to evaluate unfavorable outcomes. Furthermore, increased SIRI values have a strong correlation with mortality rates in both the short and long term. Besides, SIRI is a useful indicator of the severity of SAH. SIRI demonstrates strong predictive ability in identifying unfavorable outcomes and stroke-related pneumonia (SAP), as higher SIRI values are typically linked to negative endpoints. Nevertheless, the meta-analysis indicated that there was no significant increase in the risk of early neurological deterioration (END) and acute hydrocephalus (AHC) in high SIRI group when comparing to low SIRI.

CONCLUSION

This study could potentially pave the way for groundbreaking insights into the relationship between SIRI and stroke patient outcomes, as it appears to be the first meta-analysis to explore this association. Given the critical role of the inflammatory response in stroke recovery, closely monitoring patients with high SIRI levels could represent a promising strategy for mitigating brain damage post-stroke. Thus, further investigation into SIRI and its impact on clinical outcomes is essential. While our initial findings offer valuable insights into this area, continued research is necessary to fully elucidate the potential of SIRI, ideally through dynamic monitoring and large-scale, multi-center studies. Ultimately, this research has the potential to inform clinical decision-making and improve patient outcomes following stroke.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/ ; Identifier CRD42023405221.

Predictive value of admission red cell distribution width-to-platelet ratio for 30-day death in patients with spontaneous intracerebral hemorrhage: an analysis of the MIMIC database

Aim

Prognostic assessment plays an important role in the effective management of patients with spontaneous intracerebral hemorrhage (ICH). The study aimed to investigate whether elevated red cell distribution width-to-platelet ratio (RPR) at admission was related to 30-day death in patients with spontaneous intracerebral hemorrhage (ICH).

Methods

This retrospective cohort study included 2,823 adult patients with ICH from the Multiparameter Intelligent Monitoring in Intensive Care (MIMIC) III and IV databases between 2001 and 2019. The Cox proportional hazard model was utilized to evaluate the relationship between RPR levels and 30-day death risk. The area under receiver-operating characteristic curve (AUC) was used to assess the predictive ability of RPR for 30-day death in patients with ICH.

Results

At the end of the 30-day follow-up, 799 (28.30%) patients died, and the median RPR level was 0.066 (0.053, 0.087). After adjusting for confounders, the tertile 3 of RPR levels [hazard ratio (HR) = 1.37, 95% confidence interval (CI): 1.15-1.64] were associated with a higher risk of 30-day death in patients with ICH compared with tertile 1. In the stratified analyses, elevated RPR levels were found to be associated with an increased risk of 30-day death in patients aged <65 years (HR = 1.77, 95%CI: 1.29-2.43), aged ≥65 years (HR = 1.30, 95%CI: 1.05-1.61), with Glasgow Coma Score (GCS) <14 (HR = 1.65, 95%CI: 1.27-2.14), with Charlson comorbidity index (CCI) ≥4 (HR = 1.45, 95%CI: 1.17-1.80), with (HR = 1.66, 95%CI: 1.13-2.43) or without sepsis (HR = 1.32, 95%CI: 1.08-1.61), and female patients (HR = 1.75, 95%CI: 1.35-2.26) but not in male patients (P = 0.139) and patients with GCS ≥14 (P = 0.058) or CCI <4 (P = 0.188). The AUC for RPR to predict 30-day death in patients with ICH was 0.795 (95%CI: 0.763-0.828) in the testing set, indicating a good predictive ability.

Conclusion

Elevated RPR levels were correlated with an increased risk of 30-day death in patients with ICH, and RPP levels showed good predictive ability for 30-day death.

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.

Systemic immune-inflammation index may predict the acute kidney injury and prognosis in patients with spontaneous cerebral hemorrhage undergoing craniotomy: a single-center retrospective study

BACKGROUND

The systemic immune-inflammation index (SII) is an emerging prognostic marker of cancer. We aimed to explore the predictive ability of the SII on acute kidney injury (AKI) and prognosis in patients with spontaneous cerebral hemorrhage (SCH) who underwent craniotomy.

METHODS

Patients with SCH who underwent craniotomy between 2014 and 2021 were enrolled in this study. The epidemiology and predictive factors for AKI after SCH were analyzed. The prognostic factors for clinical outcomes in patients with SCH and AKI were further investigated. The prognostic factors were then analyzed using a logistic regression model and a receiver operating characteristic curve.

RESULTS

In total, 305 patients were enrolled in this study. Of these, 129 (42.3%) patients presented with AKI, and 176 (57.7%) patients were unremarkable. The SII (odds ratio [OR], 1.261; 95% confidence interval [CI], 1.036-1.553; P = 0.020) values and serum uric acid levels (OR, 1.004; 95% CI, 1.001-1.007; P = 0.005) were significant predictors of AKI after SCH craniotomy. The SII cutoff value was 1794.43 (area under the curve [AUC], 0.669; 95% CI, 0.608-0.730; P < 0.001; sensitivity, 65.9%; specificity, 65.1%). Of the patients with AKI, 95 and 34 achieved poor and good outcomes, respectively. SII values (OR, 2.667; 95% CI, 1.167-6.095; P = 0.020), systemic inflammation response index values (OR, 1.529; 95% CI, 1.064-2.198; P = 0.022), and Glasgow Coma Scale (GCS) scores on admission (OR, 0.593; 95% CI, 0.437-0.805; P = 0.001) were significant in the multivariate logistic regression analysis. The cutoff SII value was 2053.51 (AUC, 0.886; 95% CI, 0.827-0.946; P < 0.001; sensitivity, 78.9%; specificity, 88.2%).

CONCLUSIONS

The SII may predict AKI in patients with SCH who underwent craniotomy and may also predict the short-term prognosis of these patients.

Systemic inflammation and immune index predicting outcomes in patients with intracerebral hemorrhage

OBJECT

Recent evidence has suggested that systemic inflammatory and immune index (SIRI) and systematic inflammation index (SII) could predict prognosis in stroke patients. This study aimed to determine the effects of SIRI and SII on predicting in-hospital infections and unfavorable outcomes in patients with acute intracerebral hemorrhage (ICH).

METHODS

We used the data from a prospective and registry-based study recruiting ICH patients between January 2014 and September 2016 in a single comprehensive stroke center. All patients were stratified by quartiles of SIRI or SII. Logistic regression analysis was used to estimate the associations with follow-up prognosis. The receiver operating characteristics (ROC) curves were performed to examine the predictive utility of these indexes for infections and prognosis.

RESULTS

Six hundred and forty spontaneous ICH patients were enrolled in this study. Compared with the lowest quartile (Q1), SIRI or SII values both showed positive correlations with increased risks for poor 1-month outcomes (adjusted ORs in Q4 was 2.162 [95% CI: 1.240-3.772] for SIRI, 1.797 [95% CI: 1.052-3.070] for SII). Additionally, a higher level of SIRI, but not SII, was independently associated with a higher risk of infections and an unfavorable 3-month prognosis. The C-statistic for the combined SIRI and ICH score was higher than SIRI or ICH score alone for predicting in-hospital infections and poor outcomes.

CONCLUSION

Elevated SIRI values were associated with in-hospital infections and poor functional outcomes. It may provide a new biomarker for ICH prognosis prediction, especially in the acute stage.

Associations between dietary and blood inflammatory indices and their effects on cognitive function in elderly Americans

OBJECTIVE

To determine the correlations between dietary and blood inflammation indices in elderly Americans and their effects on cognitive function.

METHODS

This research extracted data from the 2011-2014 National Health and Nutrition Examination Survey for 2,479 patients who were ≥60 years old. Cognitive function was assessed as a composite cognitive function score (Z-score) calculated from the results of the Consortium to Establish a Registry for Alzheimer's Disease Word Learning and Delayed Recall tests, the Animal Fluency test, and the Digit Symbol Substitution Test. We used a dietary inflammatory index (DII) calculated from 28 food components to represent the dietary inflammation profile. Blood inflammation indicators included the white blood cell count (WBC), neutrophil count (NE), lymphocyte count (Lym), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), neutrophil-albumin ratio (NAR), systemic immune-inflammation index [SII, calculated as (peripheral platelet count) × NE/Lym], and systemic inflammatory response index [SIRI, calculated as (monocyte count) × NE/Lym]. WBC, NE, Lym, NLR, PLR, NAR, SII, SIRI, and DII were initially treated as continuous variables. For logistic regression, WBC, NE, Lym, NLR, PLR, NAR, SII, and SIRI were divided into quartile groups, and DII was divided into tertile groups.

RESULTS

After adjusting for covariates, WBC, NE, NLR, NAR, SII, SIRI, and DII scores were markedly higher in the cognitively impaired group than in the normal group (p < 0.05). DII was negatively correlated with the Z-score when combined with WBC, NE, and NAR (p < 0.05). After adjusting for all covariates, DII was positively correlated with SII in people with cognitive impairment (p < 0.05). Higher DII with NLR, NAR, SII, and SIRI all increased the risk of cognitive impairment (p < 0.05).

CONCLUSION

DII was positively correlated with blood inflammation indicators, and higher DII and blood inflammation indicators increased the risk of developing cognitive impairment.

Systemic inflammation response index predicts 3-month outcome in patients with mild acute ischemic stroke receiving intravenous thrombolysis

Introduction

A crucial aspect of stroke progression is the inflammatory response. As novel inflammatory and prognostic markers, the systemic immune inflammation index (SII) and the systemic inflammation response index (SIRI) have recently been studied. The objective of our study was to evaluate the prognostic value of SII and SIRI in mild acute ischemic stroke (AIS) patients following intravenous thrombolysis (IVT).

Methods

Our study screened the clinical data of patients with mild AIS admitted to the Minhang Hospital of Fudan University for retrospective analysis. The SIRI and SII were examined by the emergency laboratory before IVT. Functional outcome was evaluated 3 months after the onset of stroke using the modified Rankin Scale (mRS). mRS ≥ 2 was defined as an unfavorable outcome. The relationship between SIRI and SII and the 3-month prognosis was determined using both univariate and multivariate analysis. Receiver operating characteristic curve was performed to evaluate the predictive value of SIRI for AIS prognosis.

Results

A total of 240 patients were included in this study. Both SIRI and SII were higher in the unfavorable outcome group than in the favorable outcome group [1.28 (0.70-1.88) vs. 0.79 (0.51-1.08), P < 0.001 and 531.93 (377.55-797.12) vs. 397.23 (263.32-577.65), P < 0.001]. Multivariate logistic regression analyses showed that SIRI was significantly associated with 3-month unfavorable outcome of mild AIS patients [odds ratio (OR) = 2.938, 95% confidence interval (CI) = 1.805-4.782, P < 0.001], conversely, SII had no prognostic value. When SIRI combined with the established clinical factors, the area under the curve (AUC) showed a significant improvement (0.773 vs. 0.683, P for comparison = 0.0017).

Conclusions

Higher SIRI could be valuable in predicting poor clinical outcomes for patients with mild AIS following IVT.

Systemic Immune Inflammation Index (SII), System Inflammation Response Index (SIRI) and Risk of All-Cause Mortality and Cardiovascular Mortality: A 20-Year Follow-Up Cohort Study of 42,875 US Adults

BACKGROUND AND AIM

Chronic low-grade inflammation is associated with various health outcomes, including cardiovascular diseases (CVDs) and cancers. Systemic immune inflammation index (SII) and system inflammation response index (SIRI) have lately been explored as novel prognostic markers for all-cause mortality and cardiovascular mortality. However, studies on prediction value in nationwide representative population are scarce, which limit their generalization. To bridge the knowledge gap, this study aims to prospectively assess the association of SII, SIRI with all-cause mortality and cardiovascular mortality in the National Health and Nutrition Examination Survey (NHANES).

METHODS

From 1999 to 2018, 42,875 adults who were free of pregnancy, CVDs (stroke, acute coronary syndrome), cancers, and had follow-up records and participated in the NHANES were included in this study. SII and SIRI were quantified by calculating the composite inflammation indicators from the blood routine. To explore the characteristics of the population in different SII or SIRI levels, we divided them according to the quartile of SII or SIRI. The associations between SII, SIRI, and all-cause mortality and cardiovascular mortality events were examined using a Cox regression model. To investigate whether there was a reliable relationship between these two indices and mortalities, we performed subgroup analysis based on sex and age.

RESULTS

A total of 42,875 eligible individuals were enrolled, with a mean age of 44 ± 18 years old. During the follow-up period of up to 20 years, 4250 deaths occurred, including 998 deaths from CVDs. Cox proportional hazards modeling showed that adults with SII levels of >655.56 had higher all-cause mortality (hazard ratio [HR], 1.29; 95% confidence interval [CI], 1.18-1.41) and cardiovascular mortality (HR, 1.33; 95% CI, 1.11-1.59) than those with SII levels of <335.36. Adults with SIRI levels of >1.43 had higher risk of all-cause (HR, 1.39; 95% CI, 1.26-1.52) and cardiovascular death (HR, 1.39; 95% CI, 1.14-1.68) than those with SIRI levels of <0.68. In general population older than 60 years, the elevation of SII or SIRI was associated with the risk of all-cause death.

CONCLUSION

Two novel inflammatory composite indices, SII and SIRI, were closely associated with cardiovascular death and all-cause death, and more attention should be paid to systemic inflammation to provide better preventive strategies.

Inflammatory response biomarkers nomogram for predicting pneumonia in patients with spontaneous intracerebral hemorrhage

Objectives

Inflammatory response biomarkers are promising prognostic factors to improve the prognosis of stroke-associated pneumonia (SAP) after ischemic stroke. This study aimed to investigate the prognostic significance of inflammatory response biomarkers on admission in SAP after spontaneous intracerebral hemorrhage (SICH) and establish a corresponding nomogram.

Methods

The data of 378 patients with SICH receiving conservative treatment from January 2019 to December 2021 at Taizhou People's Hospital were selected. All eligible patients were randomized into the training (70%, 265) and validation cohorts (30%, 113). In the training cohort, multivariate logistic regression analysis was used to establish an optimal nomogram, including inflammatory response biomarkers and clinical risk factors. The area under the receiver operating characteristic (ROC) curve (AUC), calibration curve, and decision curve analysis (DCA) were used to evaluate the nomogram's discrimination, calibration, and performance, respectively. Moreover, this model was further validated in a validation cohort.

Results

A logistic regression analysis showed that intraventricular hemorrhage (IVH), hypertension, dysphagia, Glasgow Coma Scale (GCS), National Institute of Health Stroke Scale (NIHSS), systemic inflammation response index (SIRI), and platelet/lymphocyte ratio (PLR) were correlated with SAP after SICH (P < 0.05). The nomogram was composed of all these statistically significant factors. The inflammatory marker-based nomogram showed strong prognostic power compared with the conventional factors, with an AUC of 0.886 (95% CI: 0.841-0.921) and 0.848 (95% CI: 0.799-0.899). The calibration curves demonstrated good homogeneity between the predicted risks and the observed outcomes. In addition, the model has a significant net benefit for SAP, according to DCA. Also, internal validation demonstrated the reliability of the prediction nomogram. The length of hospital stay was shorter in the non-SAP group than in the SAP group. At the 3-month follow-up, clinical outcomes were worse in the SAP group (P < 0.001).

Conclusion

SIRI and PLR at admission can be utilized as prognostic inflammatory biomarkers in patients with SICH in the upper brain treated with SAP. A nomogram covering SIRI and PLR can more accurately predict SAP in patients' supratentorial SICH. SAP can influence the length of hospital stay and the clinical outcome.

Systemic inflammation response index as a prognostic predictor in patients with acute ischemic stroke: A propensity score matching analysis

Background

Acute ischemic stroke (AIS), the most common type of stroke, is a major cause of morbidity and mortality worldwide. A growing number of studies have demonstrated that inflammation is a critical mechanism in AIS. Being an easily available and effective inflammatory marker, the systemic inflammation response index (SIRI) shows a high association with mortality in patients with cancer and intracerebral hemorrhage. In this study, we evaluated the potential prognostic role of SIRI in critically ill patients with AIS.

Methods

Clinic data were extracted from the Medical Information Mart data for the Intensive Care IV (MIMIC-IV) database. The optimal cutoff value of SIRI was determined by X-tile software. The primary outcome was the 90-day all-cause mortality, and the secondary outcomes were 30-day and 1-year all-cause mortality of patients with AIS. Cox proportional hazards regression analyses were used to assess the association between SIRI levels and all-cause mortality, and survival curves were estimated using the Kaplan-Meier method. Furthermore, a 1:1 propensity score matching (PSM) method was performed to balance the influence of potential confounding factors.

Results

A total of 2,043 patients were included in our study. X-tile software indicated that the optimal cutoff value of the SIRI for 90-day mortality was 4.57. After PSM, 444 pairs of score-matched patients were generated. Cox proportional hazard model showed that after adjusting for possible confounders, high SIRI level (≥4.57) was independently associated with the 90-day all-cause mortality in the cohort before PSM (HR = 1.56, 95% CI: 1.30-1.89, p < 0.001) and the PSM subset (HR = 1.47, 95% CI: 1.16-1.86, p = 0.001). The survival curves showed that patients with SIRI ≥4.57 had a significantly lower 90-day survival rate in the cohort before PSM (56.7 vs. 77.3%, p < 0.001) and the PSM subset (61.0 vs. 71.8%, p = 0.001). Consistently, AIS patients with high SIRI levels (≥4.57) presented a significantly high risk of 30-day and 1-year all-cause mortality before and after PSM.

Conclusion

A higher SIRI (≥4.57) was associated with a higher risk of 90-day, 30-day, and 1-year mortality and was an independent risk factor of mortality in patients with acute ischemic stroke.

The predictive role of systemic inflammation response index in the prognosis of traumatic brain injury: A propensity score matching study

BACKGROUND

We aimed to evaluate the predictive power of systemic inflammation response index (SIRI), a novel biomarker, to predict all-cause mortality in patients with traumatic brain injury (TBI) in the intensive care unit (ICU).

METHODS

Clinical data were retrieved from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database. Kaplan-Meier (KM) methods and cox proportional hazard models were performed to examine the association between SIRI and all-cause mortality. The predictive power of SIRI was evaluated compared to other leukocyte-related indexes including neutrophils, lymphocytes, monocytes and white blood cells (WBC) by the Receiver Operating Characteristic (ROC)curve for 30-day mortality. In addition, propensity score matching (PSM) was conducted to reduce confounding.

RESULTS

A total of 350 TBI patients were enrolled overall in our study. The optimal cutoff point of SIRI was determined at 11.24 × 109/L. After 1:1 PSM, 66 matched pairs (132 patients) were generated. During the 30-day, in-hospital and 365-day follow-up periods, patients with low SIRI level were associated with improved survival (p < 0.05) compared with patients with high SIRI level. Cox regression analysis identified that higher SIRI values was an independent risk factor for all-cause mortality and results were stable on multiple subgroup analyses. Furthermore, ROC analysis indicated that the area under the curve of SIRI [0.6658 (95% Confidence Interval, 0.5630-0.7687)] was greater than that of neutrophils, monocytes, lymphocytes and WBC. The above results were also observed in the matched cohort.

CONCLUSION

It was suggested that TBI patients with high SIRI level would suffer from a high risk of 30-day, in-hospital and 365-day mortality. SIRI is a promising inflammatory biomarker for predicting TBI patients' prognosis with relatively better predictive power than other single indicators related to peripheral differential leukocyte counts.

Association of Dietary Inflammatory Potential with Blood Inflammation: The Prospective Markers on Mild Cognitive Impairment

Inflammation is known as an important mechanism of cognitive dysfunction. Systemic immune inflammation index (SII) and system inflammation response index (SIRI) are two blood inflammatory markers, which are related to many chronic diseases including cognitive impairment. It is recognized that dietary inflammatory index (DII), which is used to estimate the overall inflammatory potential of diet, may be related to mild cognitive impairment (MCI) as well. This study aimed to explore the relationship between SII, SIRI and DII, as well as the role of these inflammatory indexes on MCI in elderly people. A total of 1050 participants from Beijing were included. Neuropsychological tests were used for cognitive evaluation. Energy-adjusted DII scores were calculated based on semi-quantitative food frequency questionnaire. Blood samples were tested for calculating SII and SIRI. Log-binomial regression models were used to estimate the correlation of indexes. After adjusting demographic characteristics, SII and SIRI in MCI individuals were higher than controls (p ≤ 0.001). DII, SII and SIRI had positive relationship with MoCA scores (p < 0.005). DII also correlated with SIRI in MCI (β = 0.11, p = 0.031). Higher DII and SIRI could definitely increase the risk of MCI, as well as DII and SII (p < 0.005). In conclusion, DII was positively correlated with blood inflammation. The elderly with higher level of DII and SIRI, or DII and SII could be considered as people with higher risk of developing MCI.

Inflammatory indices obtained from routine blood tests show an inflammatory state associated with disease progression in engineered stone silicosis patients

Patients with silicosis caused by occupational exposure to engineered stone (ES) present a rapid progression from simple silicosis (SS) to progressive massive fibrosis (PMF). Patient classification follows international rules based on radiology and high-resolution computed tomography (HRCT), but limited studies, if any, have explored biomarkers from routine clinical tests that can be used as predictors of disease status. Our objective was thus to investigate circulating biomarker levels and systemic inflammatory indices in ES silicosis patients whose exposure to ES dust ended several years ago. Ninety-one adult men, ex-workers in the manufacturing of ES, 53 diagnosed with SS and 38 with PMF, and 22 healthy male volunteers (HC) as controls not exposed to ES dust, were recruited. The following circulating levels of biomarkers like lactate dehydrogenase (LDH), angiotensin-converting-enzyme (ACE), protein C reactive (PCR), rheumatoid factor, alkaline phosphatase and fibrinogen were obtained from clinical reports after being measured from blood samples. As biochemical markers, only LDH (HC = 262 ± 48.1; SS = 315.4 ± 65.4; PMF = 337.6 ± 79.3 U/L), ACE (HC = 43.1 ± 18.4; SS = 78.2 ± 27.2; PMF = 86.1 ± 23.7 U/L) and fibrinogen (HC = 182.3 ± 49.1; SS = 212.2 ± 43.5; PMF = 256 ± 77.3 U/L) levels showed a significant sequential increase, not been observed for the rest of biomarkers, in the HC → SS → PMF direction. Moreover, several systemic inflammation indices neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), systemic inflammation response index (SIRI), systemic immune-inflammation index (SII), aggregate index of systemic inflammation (AISI) derived from whole blood cell counts showed significant differences between the HC, SS and PMF groups. All these biomarkers were analyzed using receiver operating characteristic (ROC) curves, and the results provided moderately high sensitivity and specificity for discriminating between ES silicosis patient groups and healthy controls. Our study reveals that some inflammatory biomarkers, easily available from routine blood analysis, are present in ES silicosis patients even several years after cessation of exposure to ES silica dust and they could help to know the progression of the disease.

Machine Learning-Based Approaches for Prediction of Patients’ Functional Outcome and Mortality after Spontaneous Intracerebral Hemorrhage

Spontaneous intracerebral hemorrhage (SICH) has been common in China with high morbidity and mortality rates. This study aims to develop a machine learning (ML)-based predictive model for the 90-day evaluation after SICH. We retrospectively reviewed 751 patients with SICH diagnosis and analyzed clinical, radiographic, and laboratory data. A modified Rankin scale (mRS) of 0–2 was defined as a favorable functional outcome, while an mRS of 3–6 was defined as an unfavorable functional outcome. We evaluated 90-day functional outcome and mortality to develop six ML-based predictive models and compared their efficacy with a traditional risk stratification scale, the intracerebral hemorrhage (ICH) score. The predictive performance was evaluated by the areas under the receiver operating characteristic curves (AUC). A total of 553 patients (73.6%) reached the functional outcome at the 3rd month, with the 90-day mortality rate of 10.2%. Logistic regression (LR) and logistic regression CV (LRCV) showed the best predictive performance for functional outcome (AUC = 0.890 and 0.887, respectively), and category boosting presented the best predictive performance for the mortality (AUC = 0.841). Therefore, ML might be of potential assistance in the prediction of the prognosis of SICH.