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The Systemic Inflammation Response Index (SIRI) for Stratifying Mortality Risk in Multidrug-Resistant Lower
Background:
Timely risk assessment is important in the management of patients with multidrug-resistant (MDR) hospital-acquired lower respiratory tract infections (LRTI). The Systemic Inflammation Response Index (SIRI), an inflammatory biomarker derived from peripheral neutrophil, monocyte, and lymphocyte counts, has shown prognostic potential across several clinical settings. However, its prognostic value and clinically interpretable threshold in patients with MDR hospital-acquired LRTI remain uncertain. This study aimed to evaluate the association between SIRI and in-hospital mortality in this population.
Methods:
This single-center retrospective cohort study included 214 patients diagnosed with MDR hospital-acquired LRTI, with all-cause in-hospital mortality as the primary outcome. Cox proportional hazards models were used to assess the prognostic value of SIRI. Restricted cubic splines were applied to examine potential nonlinear associations. A data-driven cutoff was evaluated using Kaplan-Meier survival analysis and stratified receiver operating characteristic (ROC) analysis.
Results:
When analyzed as a dichotomized variable using the data-driven cutoff, high SIRI was associated with increased in-hospital mortality (hazard ratio [HR] = 2.93, 95% confidence interval [CI]: 1.66-5.14, p < 0.001). Restricted cubic spline analysis suggested a nonlinear relationship, with risk increasing around a SIRI value of 3 and then approaching a high-risk plateau. Kaplan-Meier analysis showed lower survival among patients with SIRI > 3 (log-rank p < 0.001). However, stratified ROC analyses showed only modest discrimination when SIRI was treated as a continuous variable within the low-risk (SIRI ≤ 3, area under the curve [AUC] = 0.556) and high-risk (SIRI > 3, AUC = 0.567) subgroups.
Conclusion:
SIRI may help identify a subgroup of patients with MDR hospital-acquired LRTI who have a higher mortality risk, particularly when interpreted using a threshold of approximately 3.0. Given the modest ROC performance and retrospective single-center design, this cutoff should be regarded as an exploratory risk-stratification signal rather than a stand-alone clinical decision tool. External prospective validation is required before clinical implementation.