ABSTRACT
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.
ABSTRACT
BACKGROUND: The study aimed at evaluating the prognostic utility of the prognostic nutritional index (PNI) for patients with sepsis. METHODS: Data in the present study were obtained from the Multiparameter Intelligent Monitoring in Intensive Care Database III. The calculation for PNI was as follows: serum albumin concentration (g/L) +0.005 × total lymphocyte count. 30-day mortality was considered as the primary outcome, while 90-day mortality and one-year mortality were the secondary outcomes. Cox proportional risk models and propensity score matching (PSM) analyses were used to analyze the association between PNI and clinical outcomes in patients with sepsis. To assess the predictive value of PNI for 30-day mortality, receiver operator characteristic (ROC) curve analysis was performed. RESULTS: A total of 2669 patients were in the study. After the confounding factors were adjusted, PNI ≥ 29.3 was identified as an independent predictive prognostic factor for the 30-day all-cause mortality (hazard ratio [HR]: 0.65; 95% confidence interval [CI]: 0.56-0.76; p < 0.00001). Moreover, PSM analysis further validated the prognostic predictive value of PNI for patients with sepsis. The AUC of the PNI was 0.6436 (95% CI: 0.6204-0.6625) which was significantly high than the AUC of NLR (0.5962, 95% CI: 0.5717-0.6206) (p = 0.0031), the RDW (0.5878, 95% CI: 0.5629-0.6127) (p < 0.0001), and PLR (0.4979, 95% CI: 0.4722-0.5235) (p < 0.0001). CONCLUSION: The findings suggested that PNI was also a significant risk factor for sepsis.
