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)

Pan-immune-inflammation value and its association with all-cause and cause-specific mortality in the general population: a nationwide cohort study

Introduction

The Pan-Immune-Inflammation Value (PIV) is a novel biomarker derived from counts of neutrophils, platelets, monocytes, and lymphocytes, providing a comprehensive measure of systemic immune and inflammatory status. While it has shown prognostic value in specific disease settings, its association with mortality in the general population remains unclear. This study aims to evaluate the predictive value of PIV for all-cause and cause-specific mortality, including cardiovascular, cancer, and diabetes-related deaths, within a general adult population.

Methods

Data were obtained from the NHANES cohort, with 48,662 participants aged 20 and older. Participants were followed for an average of 117.44 months, with PIV quartiles calculated at baseline. Cox proportional hazard models were used to assess mortality risk across PIV quartiles, while restricted cubic spline models examined nonlinear dose-response relationships. Subgroup and sensitivity analyses further explored the robustness of PIV's associations.

Results

Higher PIV levels were significantly associated with increased risks of all-cause, cardiovascular, cancer, and diabetes mortality. Nonlinear relationships were observed between PIV and all-cause, cardiovascular, and cancer mortality, with a risk threshold at PIV values above 254.07. Subgroup analyses supported these findings, and sensitivity analyses confirmed the consistency of PIV's prognostic value.

Conclusion

Elevated PIV serves as an independent risk factor for multiple mortality outcomes in the general population. This study underscores the potential of PIV as a predictive biomarker for mortality risk, with implications for its use in clinical and epidemiological settings. Further studies are needed to confirm PIV's clinical utility across diverse populations and conditions.

The Protective Effect of Bilirubin on MAFLD May Be Mediated by Improving Insulin Re-Sistance and Alleviating Chronic Inflammation

Background

Bilirubin, as a potent endogenous antioxidant, has demonstrated protective effects in various metabolic and inflammatory diseases. However, the precise role and underlying mechanisms of bilirubin in metabolic-associated fatty liver disease (MAFLD) remain unclear.

Methods

This study involved 3000 participants, categorized into non-MAFLD and MAFLD groups. Using weighted multiple linear regression and mediation effect analysis, this study examined the protective impact of total bilirubin (TBIL), direct bilirubin (DBIL), and indirect bilirubin (IBIL) on MAFLD risk. Additionally, potential mediators-inflammation and insulin resistance (IR) through which bilirubin exerts its protective effects were explored.

Results

TBIL and DBIL levels in the MAFLD group were significantly lower than those in the non-MAFLD group. Multiple linear regression analysis, adjusted for confounding variables, revealed that compared to the lowest tertile group (TBIL < 14.6), the odds ratios (ORs) for the middle tertile (TBIL 14.6-19.2) and the highest tertile (TBIL ≥ 19.3) groups were 0.735 and 0.615. Similarly, compared to the lowest tertile group (DBIL < 3.4), the ORs for the middle tertile (DBIL 3.4-4.4) and the highest tertile (DBIL ≥ 4.5) groups were 0.613 and 0.367. Mediation analysis revealed significant indirect effects of SIRI, PIV, TyG, TyGBMI, METS-IR, and AIP on the relationship between TBIL, DBIL, and MAFLD risk. Specifically, SIRI mediated 4.07% and 1.55% of the TBIL-MAFLD and DBIL-MAFLD associations, respectively; PIV mediated 9.56% and 4.22%; TyG mediated 69.27% and 81.91%; TyGBMI mediated 100% and 78.34%; METS-IR mediated 100% and 81.41%; and AIP mediated 100% for both TBIL-MAFLD and DBIL-MAFLD associations.

Conclusion

Our findings suggest that increased serum levels of TBIL and DBIL are significantly inversely correlated with MAFLD risk, with both serving as independent protective factors against MAFLD occurrence. Further mediation analysis indicates that this protective effect is likely mediated by improvements in IR and the alleviation of systemic chronic inflammation.

Predictive value of cumulative SII for MACE in STEMI patients after PCI

The systemic immune-inflammation index (SII) has been used effectively to effectively assess the prognosis of patients with a variety of diseases. But few evidence on the relationship between SII and long-term prognosis of myocardial infarction. We thus aimed to evaluate the relationships of cumulative exposure to SII and its accumulation time course with major adverse cardiovascular events (MACE) events in patients with acute myocardial infarction after percutaneous coronary intervention. To evaluate the predictive value of SII in MACE events in patients with acute myocardial infarction. A total of 480 patients with acute ST-elevation myocardial infarction who underwent emergency coronary angiography at the Department of Cardiology, Affiliated Hospital of Hebei University from August 2022 to August 2023 were enrolled in this study. Eighteen patients were lost to follow-up, with a loss rate of 3.8%. Time-weighted cumulative SII was calculated as the weighted sum of the mean SII value for each time interval, then normalized by total exposure duration, the exposure duration was from hospitalization to 1-year follow-up. Duration of high SII exposure was defined as the duration with high SII and ranged from hospitalization to 1-year follow-up. The time course of SII accumulation was categorized by the combination of time-weighted cumulative SII < or ≥ median and SII slope. At 1-year follow-up, after adjusting for potential confounders, the time-weighted cumulative SII was divided into 2 groups. The S2 group which is above the median had a higher risk of MACE (hazard ratio, 1.090; 95% confidence interval 1.035-1.149), the high time-weighted cumulative SII group with a positive slope had a higher risk of MACE (hazard ratio, 4.096; 95% confidence interval 1.851-9.065). Long-term cumulative exposure to SII increases the risk of MACE in patients with acute ST-elevation myocardial infarction undergoing coronary angiography, and late high SII results in a higher risk of MACE events at the same time-weighted cumulative SII, underscoring the importance of late inflammation control.

Association of Inflammatory and Metabolic Markers with Mortality in Patients with Postoperative Femur Fractures in the Intensive Care Unit

Background and Objectives: Postoperative femur fracture in elderly patients is associated with high morbidity and mortality, especially in the intensive care unit (ICU). Various factors, including demographic and laboratory parameters, may influence mortality in this population. The aim of this study was to evaluate the association of inflammatory and metabolic markers with mortality in ICU patients with postoperative femur fractures and to identify key predictors to enhance risk stratification and improve patient outcomes. Materials and Methods: In this retrospective single-center study, we analyzed 121 patients aged over 65 years with postoperative femur fractures who were admitted to the ICU between January 2023 and January 2024. Demographic and clinical data, including comorbidities, Charlson Comorbidity Index (CCI), and Acute Physiology and Chronic Health Evaluation (APACHE II) score, were collected. Laboratory parameters such as white blood cell count (WBC), albumin, C-reactive protein (CRP), D-dimer, Pan-Immune-Inflammation Value (PIV), CRP-to-albumin ratio (CAR), neutrophil-to-lymphocyte ratio (NLR), and others were analyzed. Linear regression, logistic regression, and Receiver Operating Characteristic (ROC) analyses were performed to determine the predictive value of these markers for ICU mortality. Results: The mean age of the patients was 76.3 ± 9.6 years, and 52.1% were female. The most common comorbidities were hypertension (67.8%) and diabetes (49.6%). ICU mortality occurred in 24 patients (20%). Significant predictors of mortality included higher CRP (>62.8 mg/L), NLR (>10.0), PIV (>450), and APACHE II scores (>23) (p < 0.001 for all). Lower albumin levels (<2.5 g/dL) were strongly associated with increased mortality (p < 0.001). ROC analysis demonstrated that the APACHE II score had the highest predictive accuracy for mortality (AUC = 0.83), followed by albumin (AUC = 0.79) and PIV (AUC = 0.76). Extended ICU stay (>10 days) was also significantly correlated with increased mortality (p < 0.001). Conclusions: This study successfully demonstrates the utility of combining traditional clinical markers, such as APACHE II score, with novel inflammatory markers, such as PIV, CAR, and NLR, in predicting mortality in ICU patients following femur fracture surgery. The integration of emerging biomarkers with well-established scoring systems offers enhanced predictive accuracy and provides valuable insights into patient management.

Association of pan-immune inflammation value with mortality in patients with pulmonary embolism: a cohort study

Pan-immune inflammation value (PIV) is associated with prognosis in immune and inflammatory diseases, and inflammation is a hallmark of pulmonary embolism (PE). Nonetheless, the link between PIV and prognosis in PE remains unclear. However, few studies have specifically focused on critically ill patients with PE in ICUs. This study retrospectively analyzed electronic health data of patients with PE from the Medical Information Mart for Intensive Care (MIMIC-IV) database. The primary outcome was 28-day ACM; secondary outcomes were 90-day, 1-year, ICU, and in-hospital mortality. The study population included 213 patients with PE. Multivariate Cox proportional hazards regression showed that elevated PIV was significantly associated with ACM at 28 days (adjusted hazard ratio [aHR]: 1.93; 95% confidence interval [CI]: 1.02-3.63) and 90 days (aHR: 1.96; 95% CI: 1.10-3.47). Further, multivariate logistic regression analysis showed that PIV was significantly and positively associated with the risk of ACM. Kaplan-Meier survival curves showed that PIV was positively associated with ACM. Subgroup and interaction analyses corroborated this correlation. PIV was significantly correlated with ACM in critically ill ICU patients with PE. This correlation highlights the potential utility of PIV for stratifying patients with PE according to their risk of death.

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.

Relationship between systemic immune-inflammation index and long-term all-cause and cause-specific mortality among adult asthma patients: a population-based study

BACKGROUND

Persistent inflammation in the airways is a hallmark of asthma, and researchers have extensively explored various inflammatory indicators that contribute to the condition. Despite this, there is limited research on the relationship between the systemic immune-inflammation index (SII), a novel marker of inflammation, and overall mortality rates as well as mortality rates due to specific causes in individuals with asthma.

METHODS

We analyzed data from the National Health and Nutrition Examination Survey (NHANES) covering a 20-year period, from 1999 to 2018. To examine the association between SII and mortality rates in asthma patients, we used a combination of statistical methods, including weighted Kaplan-Meier analysis and multivariate-adjusted Cox analysis. Additionally, we applied restricted cubic spline (RCS) analysis to investigate the potential non-linear relationship between these variables. To further validate our findings, we performed subgroup and sensitivity analyses to ensure the reliability of the results.

RESULTS

This study analyzed data from 5,384 individuals with asthma, finding a link between increased SII levels and a higher risk of death from all-cause, cardiovascular disease and respiratory disease, but no association with cancer mortality. There were J-shaped non-linear relationships between SII and all-cause, cardiovascular and respiratory diseases mortality in asthma patients. The inflection points were 326, 350 and 355, respectively. Below these inflection points, each 100-unit increase in SII was associated with a decrease in mortality by 8%, 11% and 10%, while above these thresholds, mortality rates increased by 4%, 4%, and 3%, respectively. Subgroup analyses showed that SII was a significant predictor of all-cause mortality across various subgroups, and sensitivity analyses confirmed these findings, with the highest SII group consistently showing higher mortality rates for all-cause, cardiovascular, and respiratory disease mortality in the fully adjusted model.

CONCLUSIONS

Our study initially demonstrated a strong link between elevated SII levels and a higher risk of death from all-cause, cardiovascular disease, and respiratory disease in individuals with asthma. Furthermore, our analysis showed that the relationship between SII and mortality rates in asthma patients followed a non-linear, J-shaped pattern for all-cause, cardiovascular, and respiratory disease mortality.

CLINICAL TRIAL NUMBER

Clinical trial number not applicable.

The Roles of Vitamin D Levels, Gla-Rich Protein (GRP) and Matrix Gla Protein (MGP), and Inflammatory Markers in Predicting Mortality in Intensive Care Patients: A New Biomarker Link?

OBJECTIVES

Identifying reliable biomarkers to predict mortality in critically ill patients is crucial for optimizing management in intensive care units (ICUs). Inflammatory and metabolic markers are increasingly recognized for their prognostic value. This study aims to evaluate the association of various inflammatory and metabolic markers with ICU mortality.

METHODS

This prospective observational study was conducted from January 2023 to January 2024 in the City Hospital's ICU. A total of 160 critically ill patients were enrolled. Laboratory parameters, including white blood cell (WBC) count, red cell distribution width (RDW), platelet count, neutrophil count, mean platelet volume (MPV), monocyte count, lymphocyte count, procalcitonin (PCT), C-reactive protein (CRP), calcium (Ca++), and vitamin D levels, were analyzed. Additionally, ratios such as the platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), systemic inflammatory index (SII), and pan-immune-inflammation value (PIV) were calculated. Plasma levels of Gla-rich protein (GRP) and dephosphorylated uncarboxylated matrix Gla protein (dp-ucMGP) were measured using ELISA.

RESULTS

The mean age of the patients included in the study was 60.5 ± 15.8 years. Cardiovascular disease was present in 72 patients (45%), respiratory system disease in 58 (36%), and chronic kidney disease (CKD) in 38 (24%). Additionally, 61 patients (38%) had diabetes, and 68 (42%) had hypertension. Inflammatory markers, including PLR, NLR, and PIV, were all significantly higher in non-survivors, while calcium and vitamin D levels were lower (p < 0.05). Higher WBC, RDW, neutrophil count, PLR, NLR, PIV, CRP, procalcitonin, GRP, and dp-ucMGP levels were positively correlated with longer hospital stays and increased mortality. In contrast, platelet and lymphocyte counts were negatively correlated with both outcomes (p < 0.05). Vitamin D levels showed an inverse relationship with both hospital stay and mortality, indicating that lower levels were associated with worse outcomes (p < 0.05). In multiple logistic regression analysis, elevated WBC count (OR = 1.20, p = 0.02), RDW (OR = 1.35, p = 0.01), neutrophil count (OR = 1.25, p = 0.01), MPV (OR = 1.20, p = 0.02), PLR (OR = 1.30, p = 0.01), NLR (OR = 1.40, p = 0.001), PIV (OR = 1.50, p = 0.001), CRP (OR = 1.32, p = 0.01), procalcitonin (OR = 1.45, p = 0.001), GRP (OR = 1.40, p = 0.001), and dp-ucMGP (OR = 1.30, p = 0.001) levels were significantly associated with increased mortality.

CONCLUSIONS

Inflammatory and metabolic markers, particularly NLR, PLR, PIV, GRP, and dp-ucMGP, are strong predictors of mortality in ICU patients. These markers provide valuable insights for risk stratification and early identification of high-risk patients, potentially guiding more targeted interventions to improve outcomes.

The association between pan-immune-inflammation value and chronic obstructive pulmonary disease: data from NHANES 1999-2018

Background

The pan-immune-inflammation value (PIV) is an emerging biomarker quantitatively reflecting the systemic immune-inflammatory status. The predictive value of PIV has been well-established across various clinical settings. However, its role in chronic obstructive pulmonary disease (COPD) remains unclear and necessitates further investigation.

Methods

Data from NHANES 1999-2018 were filtered. Logistic regression analyses were used to assess the correlation between COPD prevalence and PIV in all participants. COX regression analyses and Kaplan-Meier survival curves were used to investigate the relationship between COPD all-cause mortality and PIV in COPD patients. Restricted cubic spline (RCS) analyses and piecewise linear regression analyses were additionally employed to explore the correlation between PIV and COPD. Subgroup analyses were performed to further clarify the effects of other covariates on the associations. Sensitivity analyses were employed to assess the robustness of the results.

Results

A total of 28,485 participants aged 40 years and older were recruited for this study. After fully adjusting for covariates, higher PIV levels were independently associated with increased COPD prevalence (OR = 1.67; 95% CI: 1.39-2.01) and all-cause mortality (HR = 2.04; 95% CI: 1.41-2.95). The COPD prevalence curve exhibited an inflection point at Log10-PIV of 2.24, showing no significant correlation on the left side (OR = 0.86; 95% CI: 0.45-1.64) but a positive correlation on the right side (OR = 2.00; 95% CI: 1.57-2.55). The COPD all-cause mortality curve displayed an inflection point at Log10-PIV of 2.38, indicating a negative correlation on the left side (HR = 0.23; 95% CI: 0.12-0.44) and a positive correlation on the right side (HR = 4.12; 95% CI: 2.62-6.48). Subgroup analyses with interaction tests showed that the strength of the correlation between PIV and COPD prevalence was influenced by race, smoking status, and BMI (all p for interaction <0.05). The relationship between PIV and COPD all-cause mortality was unaffected by any covariates (all p for interaction >0.05).

Conclusion

Elevated PIV levels are associated with increased COPD prevalence. COPD patients with either elevated or reduced PIV levels experience higher all-cause mortality. Further large-scale, longitudinal studies are required to corroborate these findings.

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.