Independent Predictors of 28-Day Mortality and the Critical Role of Source Control in Stenotrophomonas maltophilia Bacteremia in the ICU

重症监护室中嗜麦芽窄食单胞菌菌血症28天死亡率的独立预测因素及感染源控制的关键作用

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Abstract

Stenotrophomonas maltophilia bacteremia is an opportunistic infection associated with high mortality among intensive care unit (ICU) patients, largely due to intrinsic antimicrobial resistance and the severe underlying conditions of affected hosts. This study aimed to identify independent predictors of 28-day mortality, evaluate the prognostic value of laboratory biomarkers, and assess the impact of source control in ICU patients with S. maltophilia bacteremia. A retrospective single-center case–control study was conducted over a five-year period, including 148 ICU patients with S. maltophilia bacteremia and 1:1 matched non-S. maltophilia controls. Demographic, clinical, and laboratory data were analyzed using multivariate logistic regression to determine independent predictors of mortality, while receiver operating characteristic (ROC) analysis assessed the prognostic performance of selected biomarkers. Multivariate analysis identified shock (OR = 6.01; 95% CI: 3.13–11.56; p < 0.001), underlying malignancy (OR = 4.31; 95% CI: 1.44–12.96; p = 0.009), higher Sequential Organ Failure Assessment (SOFA) score (OR = 1.28; 95% CI: 1.16–1.41; p < 0.001), and elevated procalcitonin levels (OR = 1.014; 95% CI: 1.002–1.026; p = 0.019) as independent predictors of mortality. A multivariable prediction model incorporating age, SOFA score, shock, malignancy, procalcitonin, and lactate demonstrated good discriminative performance for predicting 28-day mortality (AUC = 0.817; p < 0.001). Source control was significantly associated with improved survival. These findings suggest that hemodynamic instability, malignancy, and severe organ dysfunction are major determinants of mortality in ICU patients with S. maltophilia bacteremia, and that multidimensional risk assessment models integrating clinical severity scores and biomarkers may facilitate early identification of high-risk patients and support targeted clinical management.

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