Aggregate Index of Systemic Inflammation (AISI), Disease Severity, and Mortality in COVID-19: A Systematic Review and Meta-Analysis

The U-shape relationship between the aggregate index of systemic inflammation and depression in American adults: A cross-sectional study

BACKGROUND

This investigation aims to examine the connection between the aggregate index of systemic inflammation (AISI) and depression, using data from the National Health and Nutrition Examination Survey (NHANES) database.

METHODS

We conducted a cross-sectional study using data from the NHANES collected between 2005 and 2018. Depression was assessed via the patient health questionnaire-9. To investigate the connection between AISI and the prevalence of depression, we employed weighted multivariable logistic regression models as well as restricted cubic spline (RCS) models. This study also performed subgroup and interaction analyses to further explore these associations. Additionally, threshold effect and saturation effect analyses were conducted to identify potential inflection points for AISI and depression. Finally, we compared the area under the curve (AUC) values from receiver operating characteristic (ROC) analyses to assess the diagnostic capability of the optimal model for depression.

RESULTS

This study initially recruited 29,092 individuals, of whom 2596 had depression. After adjusting for potential confounders, we discovered a higher AISI was significantly linked with an higher risk of depression when comparing the highest to the lowest quantile of AISI (odds ratio: 1.205; 95 % confidence interval: 1.019-1.424; P = 0.032). Marital status interacted with AISI to influence the prevalence of depression (P for trend = 0.0275). The curve for participants was U-shaped, with an optimal AISI value of 828.8, and a non-linear relationship was found between AISI and depression (P for log-likelihood ratio test <0.001). ROC analysis indicated that AISI had a stronger discriminative ability and accuracy in predicting depression compared to other inflammatory biomarkers.

CONCLUSIONS

The AISI level exhibited a U-shaped association with depression, indicating that maintaining AISI within a reasonable range may help reduce the prevalence of depression.

Association of novel inflammatory markers with osteoporosis index in older spine osteoporosis patients: NHANES 1999-2018 cross-sectional study

This study aimed to examine the relationships of osteoporosis with Osteoporosis indices in elderly patients, and investigate the associations of novel inflammatory markers with variations of Osteoporosis indices. Senior citizens were recruited from the National Health and Nutrition Examination Survey (NHANES). Dual-energy X-ray absorptiometry was used to detect bone mineral density tests. Osteoporosis indices and diagnosis of osteoporosis were evaluated using multivariate weighted logistic regression models. Novel inflammatory markers were calculated based on lymphocyte, neutrophil, monocyte, platelet, and albumin counts. The relationships between the Osteoporosis indices and novel inflammatory markers were evaluated with multivariate weighted logistic regression models. Totally 837 elderly patients were enrolled, including 494 men and 343 women, and their weighted average age was 68.28 ± 7.60 years. Our results indicated that the osteoporosis indices were positively correlated with the presence of osteoporosis and that these three indices measured the severity of osteoporosis. After multivariate weighted logistic regression model analysis of the novel inflammatory markers and osteoporosis index, AIRI, SIRI, and SII were significantly correlated with the osteoporosis indices. There may be a close relationship between inflammation and senile osteoporosis. The novel inflammatory markers are convenient and objective for predicting low BMD or osteoporosis risk in older patients. Among these markers, elderly patients with high levels of AISI, SIRI, and SII should focus on the risk of osteoporosis. However, this study has some limitations. It is essential to expand the sample size to a wider population to investigate the relationship between inflammation and osteoporosis.

Examination of Pan-Immune-Inflammation Value and Lymphocyte-Monocyte Ratio in Sudden Sensorineural Hearing Loss

BACKGROUND

Studies about inflammation indices are becoming increasingly common. Inflammation is thought to play an important role in the aetiopathogenesis of sudden sensorineural hearing loss.

AIM

In this study, we aimed to compare sudden sensorineural hearing loss patients and patients in a control group in terms of pan-immune-inflammation value and lymphocyte-monocyte ratio and to determine the relationship of these indices with sudden sensorineural hearing loss.

METHODS

The research was designed as a retrospective, case-control study. The archival records of patients diagnosed with sudden sensorineural hearing loss between 1 January 2018 and 1 May 2023 were scanned. Within the scope of the study, age, gender, amount of hearing loss, hearing loss accompanied by vertiginous symptoms, hearing loss accompanied by tinnitus, full blood count results, pan-immune-inflammation value and lymphocyte-monocyte ratio were analysed between the groups. Statistical analyses were performed using the independent samples t-test, Chi-square test and Pearson correlation analysis.

RESULTS

Leukocyte, neutrophil, platelet and pan-immune-inflammation values were found to be significantly higher in patients with sudden sensorineural hearing loss (P values: 0.023, <0.001, 0.010, <0.001, respectively). Lymphocyte and monocyte values were significantly lower (P values: <0.001, 0.006, respectively). There was no significant difference in terms of lymphocyte-monocyte ratio (P = 0.455). There was no relationship between tinnitus, vertiginous symptoms and blood parameters. There was a positive correlation between neutrophil value and the amount of hearing loss (P = 0.036).

CONCLUSION

In our study, the pan-immune-inflammation value was significantly higher in sudden sensorineural hearing loss patients. A statistically significant relationship was detected between high neutrophil values and the amount of hearing loss. These results can be evaluated on the basis of the inflammation-ischaemia relationship in the aetiopathogenesis of sudden sensorineural hearing loss.

Aggregate index of systemic inflammation: A novel systemic inflammatory index for prediction of neonatal outcomes and chorioamnionitis in women with preterm premature rupture of membranes

OBJECTIVE

To determine the value of the Aggregate index of systemic inflammation (AISI) in predicting admission to neonatal intensive care unit (NICU) and chorioamnionitis.

METHODS

The present retrospective cohort study with pregnant women who were diagnosed with preterm premature rupture of membranes (PPROM) in the Department of Perinatology, Ministry of Health Ankara City Hospital between January 1, 2021, and June 1, 2023 (n = 357). The patients were categorized into subgroups: (1) cases with (n = 27) or without (n = 330) chorioamnionitis, (2) admission (n = 182) or no admission (n = 175) to NICU; (3) gestational age at birth <28 weeks or 28 weeks or longer; and (4) gestational age at birth <34 weeks or 34 weeks or longer. AISI values were compared between the subgroups, and cut-off values for AISI were determined to predict adverse outcomes.

RESULTS

AISI values were significantly higher in the admission to NICU group compared with the no admission to NICU group (707.0 vs 551.2) (P < 0.05). AISI values were also significantly higher in the chorioamnionitis group compared with those without chorioamnionitis (850.3 vs 609.4) (P < 0.05). AISI levels were significantly higher in cases delivered before 28 weeks of gestation compared with the cases delivered at 28 weeks of gestation or later (945.6 vs 604.9) (P < 0.05), and were also significantly higher in cases delivered before 34 weeks of gestation compared with the cases delivered at 34 weeks of gestation or later (715.5 vs 550.1) (P < 0.05). Optimal cut-off values of AISI were found to be 626.19 (74.1% sensitivity, 52.8% specificity), 506.09 (68.9% sensitivity and, 47.7% specificity), and 555.1 (69.8% sensitivity, 48.1% specificity) in predicting NICU admission, chorioamnionitis, and delivery before 28 weeks, respectively.

CONCLUSION

The novel inflammatory marker AISI may be used in the prediction of chorioamnionitis and NICU admission in PPROM cases.

SYNOPSIS

Aggregate index of systemic inflammation may be used as a novel marker in predicting high-risk for chorioamnionitis and neonatal intensive care unit admission in women with preterm premature rupture of membranes.

Association of First-Trimester Combined Inflammatory Markers (NLR, SII, SIRI, and AISI) With Poor Obstetric Outcomes in Pregnancies With Ulcerative Colitis

AIM

To compare the first-trimester combined inflammatory markers between pregnant women diagnosed with ulcerative colitis (UC) and healthy pregnant women. Furthermore, to investigate the predictive value of these markers for adverse obstetric outcomes in pregnant women affected by UC.

METHODS

In this retrospective study, data were collected from pregnant women with UC who gave birth at our hospital between January 2021 and May 2024 and from a control group of healthy pregnant women. A comparison was made between the two groups in terms of their demographic characteristics, neonatal outcomes, and the values of the first-trimester neutrophil-to-lymphocyte ratio (NLR), systemic inflammation index (SII), systemic inflammatory response index (SIRI), and aggregated index of systemic inflammation (AISI). Furthermore, the relationship between these combined inflammatory markers and adverse obstetric outcomes in pregnant women with UC was investigated.

RESULTS

No notable discrepancy was observed between the UC group and the control group with respect to SIRI and AISI. The first-trimester NLR and SII values were observed to be higher in the UC group in comparison to the control group. The data indicated that pregnant women with UC who experienced poor obstetric outcomes exhibited elevated levels of NLR, SII, SIRI, and AISI during the first trimester. In the ROC analysis, the predictive capacity of all four parameters for poor obstetric outcomes in UC patients was statistically significant.

CONCLUSION

There is an association between elevated combined inflammatory markers in the first trimester and poor obstetric outcomes in pregnant women with UC.

Association of the panimmune-inflammatory value (PIV) with all-cause and cardiovascular mortality in maintenance hemodialysis patients: a propensity score matching retrospective study

PURPOSE

The panimmune-inflammatory value (PIV) is a novel inflammatory indicator. However, its role in maintenance hemodialysis (MHD) remains unclear. Our goal was to explore the predictive value of PIV for cardiovascular and all-cause mortality in MHD patients.

METHODS

In this retrospective cohort study, 507 patients receiving MHD between November 2017 and December 2022 were enrolled. The PIV value was calculated as follows: neutrophil count × monocyte count × platelet count/lymphocyte count. Patients were divided into two groups on the basis of the median PIV. Propensity score matching (PSM) was used to adjust for imbalances in baseline information between groups. Kaplan‒Meier curves, Cox regression, the Fine‒Gray competing risk model, and restricted cubic spline (RCS) curves were used to analyze the relationship between PIV and mortality.

RESULTS

By the end of follow-up, 126 deaths had occurred, 91 of which were due to cardiovascular disease. The Kaplan‒Meier curves demonstrated that MHD patients with higher PIV levels had a poorer prognosis for all-cause death (p = 0.019). PIV levels were linked to all-cause death in multivariate Cox proportional risk regression (HR = 1.76; 95% CI 1.14, 2.72; p = 0.011). The Fine‒Gray model revealed a greater cumulative incidence of cardiovascular death in the higher PIV group (p = 0.035). PIV levels were linked to cardiovascular mortality in the Fine‒Gray competing risk model (HR = 2.06; 95% CI 1.25, 3.42; p = 0.005). The RCS revealed a nonlinear relationship between PIV and mortality risk (p < 0.05). Using 63 years of age as the threshold, we observed a multiplicative interaction effect between age and PIV for all-cause mortality (p = 0.006).

CONCLUSION

In MHD patients, PIV is an independent hazard factor for cardiovascular-related mortality and all-cause mortality.

Development and validation of a prognostic model for critically ill type 2 diabetes patients in ICU based on composite inflammatory indicators

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder, and critically ill patients with T2DM in intensive care unit (ICU) have an increased risk of mortality. In this study, we investigated the relationship between nine inflammatory indicators and prognosis in critically ill patients with T2DM to provide a clinical reference for assessing the prognosis of patients admitted to the ICU. Critically ill patients with T2DM were extracted from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and divided into training and testing sets (7:3 ratio). An external validation cohort was collected from a single center in China using identical criteria. Logistic and Cox regression analyses were used to evaluate the relationship between nine inflammatory indicators and ICU, 30-day, and 90-day mortality rates. Significant predictive variables were chosen using least absolute shrinkage selection operator (LASSO) regression from logistic regression results, and a prognostic prediction model was built with multivariate logistic regression. The model was validated in both test and external validation sets. A total of 4,783 patients were included for model development and testing; an additional 204 served as the external validation set. The levels of eight inflammatory indicators were significantly correlated with short-term prognosis in critically ill patients with T2DM (P < 0.05 for all). The prediction model showed excellent discrimination performance, with AUC values of 0.825 (95% CI, 0.785-0.864) in the test set and 0.741 (95% CI, 0.630-0.851) in the external validation set. Calibration curves demonstrated strong consistency in both sets. In addition, decision curve analysis showed a net clinical benefit within 1-60% threshold probability in the test set and 10-41% threshold probability in the external validation set. Eight inflammatory indicators were identified as independent risk factors for prognosis in critically ill patients with T2DM. The prediction model showed promising performance in both internal and external validation cohorts, highlighting its potential as a valuable tool for early risk stratification and prediction of the outcomes of personalized treatment strategies in ICU settings.

Association of healthy lifestyles with risk of all-cause and cause-specific mortality among individuals with metabolic dysfunction-associated steatotic liver disease: results from the DFTJ cohort

AIM

To examine the associations of healthy lifestyles with risk of all-cause and cause-specific mortality among adults with metabolic dysfunction-associated steatotic liver disease (MASLD), and whether the association was mediated by systemic immune-inflammatory biomarkers (SIIBs).

METHODS

The study included 10,347 subjects with MASLD, who were enrolled in the Dongfeng-Tongji cohort study. The healthy lifestyles referred to non-smoking, being physically active (≥7.5 metabolic equivalents-hours/week), low-risk alcohol consumption (1-14 g/day for women and 1-28 g/day for men), and optimal sleep duration (≥6 to ≤8 h/day). Cox proportional hazard models were used to examine the relationship between each lifestyle and SIIBs with the risk of all-cause and cause-specific mortality. A mediation analysis was conducted to investigate the role of SIIBs on the association between healthy lifestyles and mortality.

RESULTS

There were 418 MASLD subjects dead till the follow-up of 2018, including 259 deaths from cardiovascular disease (CVD). Compared to MASLD participants with 0-1 healthy lifestyle score (HLS), those with 3-4 HLS had the lowest risk of all-cause mortality [hazard ratio (HR), 0.46; 95% CI, (0.36-0.60)], and CVD mortality [HR (95%CI), 0.41 (0.29-0.58)]. Mediation analyses indicated that SIIBs mediated the association between healthy lifestyles and mortality, with proportions ranging from 2.5% to 6.1%.

CONCLUSIONS

These findings suggest that adherence to healthy lifestyles can significantly reduce mortality for MASLD patients, and the decreased SIIBs may partially explain the protection mechanism of healthy lifestyles.

Machine Learning-Based Prediction of In-Stent Restenosis Risk Using Systemic Inflammation Aggregation Index Following Coronary Stent Placement

Introduction

Coronary artery disease (CAD) remains a significant global health challenge, with percutaneous coronary intervention (PCI) being a primary revascularization method. In-stent restenosis (ISR) post-PCI, although reduced, continues to impact patient outcomes. Inflammation and platelet activation play key roles in ISR development, emphasizing the need for accurate risk assessment tools. The systemic inflammation aggregation index (AISI) has shown promise in predicting adverse outcomes in various conditions but has not been studied in relation to ISR.

Methods

A retrospective observational study included 1712 patients post-drug-eluting stent (DES) implantation. Data collected encompassed demographics, medical history, medication use, laboratory parameters, and angiographic details. AISI, calculated from specific blood cell counts, was evaluated alongside other variables using machine learning models, including random forest, Xgboost, elastic networks, logistic regression, and multilayer perceptron. The optimal model was selected based on performance metrics and further interpreted using variable importance analysis and the SHAP method.

Results

Our study revealed that ISR occurred in 25.8% of patients, with a range of demographic and clinical factors influencing the risk of its development. The random forest model emerged as the most adept in predicting ISR, and AISI featured prominently among the top variables affecting ISR prediction. Notably, higher AISI values were positively correlated with an elevated probability of ISR occurrence. Comparative evaluation and visual analysis of model performance, the random forest model demonstrates high reliability in predicting ISR, with specific metrics including an AUC of 0.9569, accuracy of 0.911, sensitivity of 0.855, PPV of 0.81, and NPV of 0.948.

Conclusion

AISI demonstrated itself as a significant independent risk factor for ISR following DES implantation, with an escalation in AISI levels indicating a heightened risk of ISR occurrence.

Inflammatory Profile Assessment in a Highly Selected Athyreotic Population Undergoing Controlled and Standardized Hypothyroidism

Background: Hypothyroidism (hT) presents heterogeneous symptoms and findings. Evidence on this topic comes mainly from heterogeneous populations in terms of disease duration, residual thyroid function, and comorbidities. Therefore, it would be useful to assess systemic inflammation in a homogeneous hT population. The aim of this study was to investigate inflammation in a population that underwent standardized controlled hT. Methods: We recruited thyroidectomized patients diagnosed with thyroid cancer who were otherwise fit and healthy, showing hypothyroidism before I131 treatment using a standard protocol of LT4 withdrawal. The blood inflammatory indexes (BIIXs) (i.e., NLR, PLR, MLR, SII, SIRI, and AISI) were calculated using the blood tests collected just before I131 administration. Patients were divided according to sex, BMI, and thyroglobulin. The relationships between the BIIXs, age, and thyroid hormones were also investigated. Results: We included 143 patients. The median age of the sample was 43 years. The BIIX median values showed significant differences based on sex, BMI, and thyroglobulin levels (p < 0.05). No significant correlations were found between the BIIXs and age, TSH, FT4, and FT3. Conclusions: This study shows the BIIX median values of a population which underwent standardized hT. It suggests a role for some BIIXs in the evaluation of hypothyroidism in obese people and as hypothetical prognostic markers for thyroid cancer.