Association between a four-parameter inflammatory index and all-cause mortality in critical ill patients with non-traumatic subarachnoid hemorrhage: a retrospective analysis of the MIMIC-IV database (2012-2019)

Association of the systemic immune-inflammation index with all-cause and cardiovascular mortality in individuals with rheumatoid arthritis

The systemic immune-inflammation index (SII), a metric reflecting systemic inflammatory response and immune activation, remains underexplored concerning its correlation with mortality among rheumatoid arthritis (RA) patients. This study aimed to delineate the association between SII and both all-cause and cardiovascular mortality within the cohort of American adults diagnosed with RA, utilizing data from the National Health and Nutrition Examination Survey (NHANES) spanning 1999 to 2018. The investigation extracted data from NHANES cycles between 1999 and 2018, identifying RA patients through questionnaire responses. The SII was computed based on complete blood counts, employing the formula: (platelets × neutrophils) / lymphocytes. The optimal SII cutoff value for significant survival outcomes was determined using maximally selected rank statistics. Multivariable Cox proportional hazards models assessed the relationship between SII levels and mortality (all-cause and cardiovascular) among RA patients, with subgroup analyses examining potential modifications by clinical confounders. Additionally, restricted cubic spline (RCS) analyses were conducted to explore the linearity of the SII-mortality association. The study encompassed 2070 American adults with RA, among whom 287 exhibited a higher SII (≥ 919.75) and 1783 a lower SII (< 919.75). Over a median follow-up duration of 108 months, 602 participants died. After adjustments for demographic, socioeconomic, and lifestyle variables, a higher SII was associated with a 1.48-fold increased risk of all-cause mortality (hazard ratio [HR] = 1.48, 95% confidence interval [CI] 1.21-1.81, P < 0.001) and a 1.51-fold increased risk of cardiovascular mortality (HR = 1.51, 95% CI 1.04-2.18, P = 0.030) compared to a lower SII. Kaplan-Meier analyses corroborated significantly reduced survival rates within the higher SII cohort for both all-cause and cardiovascular mortality (Pall-cause mortality < 0.0001 and Pcardiovascular mortality = 0.0004). RCS analyses confirmed a positive nonlinear relationship between SII and mortality rates. In conclusion, the SII offers a straightforward indicator of the equilibrium between detrimental innate inflammation and beneficial adaptive immunity. Our investigation, utilizing a comprehensive and nationally representative sample, reveals that elevated SII levels independently forecast a greater risk of mortality from all causes, as well as cardiovascular-specific mortality, in individuals suffering from RA. These insights underscore the clinical relevance of the SII as an affordable and readily accessible biomarker. Its incorporation into regular clinical practice could significantly enhance the precision of risk assessment and forecasting for patients with RA, facilitating more tailored and effective management strategies. Specifically, patients with high SII levels could be identified for more stringent cardiovascular risk management, including closer monitoring, lifestyle interventions, and aggressive pharmacological treatments to mitigate their increased risk of mortality.

Pan-immune-inflammation value predict delayed cerebral ischemia in patients with aneurysmal subarachnoid hemorrhage

Inflammatory reaction and immune dysregulation are known as components contributing to delayed cerebral ischemia (DCI) in patients with following aneurysmal subarachnoid hemorrhage (aSAH). The objective of this study was to investigate the role of pan-immune-inflammation value (PIV) as a novel comprehensive inflammatory marker in predicting the DCI development following aSAH. A total of 1028 participants with aSAH were enrolled. There were 296 patients with DCI and 732 patients without DCI. Various inflammatory markers were analyzed using peripheral blood sample obtained at admission. Receiver operating characteristic (ROC) analysis was performed to identify the optimal cutoff value of PIV for distinguishing DCI. Multivariate analysis was used to determine independent predictors for DCI. Mean PIV was significantly higher in the DCI (+) group than in the DCI (-) group (437.6 ± 214.7 vs 242.1 ± 154.7, P = 0.007). In ROC analysis, the optimal cutoff value of PIV was 356.7 for predicting DCI (area under the curve [AUC] 0.772, 95 % confidence interval [CI] 0.718-0.816; P < 0.001). Multivariate analysis showed that high Hunt-Hess grade (odds ratio [OR] 1.70, 95 % CI 1.38-2.22; P = 0.007), thick SAH (OR 1.82, 95 % CI 1.44-2.32; P = 0.005), and elevated PIV (≥356.7) (OR 1.42, 95 % CI 1.10-1.74; P = 0.013) were independent predictors of DCI after aSAH. PIV is a potent predictor of DCI in patients with aSAH. Elevated PIV is associated with more DCI development. Thus, PIV has predictive value for DCI development.

Prognostic value of the systemic immune-inflammation index in patients with acute respiratory distress syndrome: A retrospective study

Background

Inflammation is critical in the etiology and progression of acute respiratory distress syndrome (ARDS). This study aims to rigorously assess the predictive capacity of systemic immune-inflammation index (SII) in determining the outcomes of patients with ARDS.

Methods

Patient data were extracted from version 2.2 of the Medical Information Mart for Intensive Care IV (MIMIC-IV). The Receiver Operating Characteristic (ROC) curve was deployed to determine the optimal cutoff value for the SII, facilitating the stratification of participants into distinct cohorts based on SII levels. The relationship between SII and survival outcomes was rigorously evaluated using Cox proportional hazards models. The association between SII and patient survival was rigorously examined using Cox proportional-hazard models. The impact of varying SII levels on mortality was quantitatively assessed through these models, with the results articulated as hazard ratios (HRs) and 95% confidence intervals (CIs). Three distinct models were formulated for this analysis: Model 1 employed univariate Cox regression to relate SII with mortality; Model 2 introduced adjustments for age and sex; and Model 3 extended these adjustments to include age, sex, race, SAPS II, APSIII, Hemoglobin, Albumin, Pneumonia, SpO2, and SBP.

Results

Post-application of the inclusion criteria, a cohort of 976 eligible patients was delineated for detailed examination. Univariate analysis focusing on 30-day mortality within the SII ≥1694, the hazard ratio (HR) was 1.42 (95% confidence interval (CI): 1.11, 1.81). However, after adjusting for confounding factors such as age, sex, race, Simplified Acute Physiology Score II (SAPS II), Acute Physiology Score (APS) III, Hemoglobin, Albumin, Pneumonia, SpO2, and Systolic Blood Pressure (SBP), an SII value of ≥1694 was identified as an independent and significant risk factor for mortality in patients with ARDS, with an HR of 1.38 (95% CI: 1.08-1.77, P = 0.0016). This trend was consistent for 90-day and one-year mortality rates.

Conclusions

SII surfaced as an autonomous determinant of mortality in ARDS patients, affirming its status as an accessible and dependable prognostic indicator for individuals newly diagnosed with this critical condition. Additional research is imperative to further elucidate the prognostic implications of SII in the therapeutic management of patients with ARDS.