ArticleInfection and drug resistance2025
Integrated SIRI and Lipid Profile for Early Prediction of Bloodstream Infection in AML During Induction Chemotherapy.
Article in Infection and drug resistance, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Purpose: Bloodstream infections (BSIs), a frequent and life-threatening complication during acute myeloid leukemia (AML) induction chemotherapy, carry high mortality; however, current predictive models lack robust combined inflammatory-metabolic biomarkers. Patients and Methods: We conducted a retrospective analysis of 225 AML patients (2020-2024). The systemic inflammation response index (SIRI) and lipids measured at baseline. BSIs were confirmed according to Centers for Disease Control and Prevention/National Healthcare Safety Network (CDC/NHSN) criteria during neutropenia. Predictors selected via univariate analysis (P<0.05) and multivariable logistic regression using backward selection based on the Akaike information criterion (AIC). A nomogram was constructed. Model validation included receiver operating characteristic curve analysis and area under the curve (ROC-AUC), calibration curves (1,000× bootstrap), and decision curve analysis (DCA). Results: Among 225 AML patients, BSIs incidence was 24% (54/225). Patients with BSIs exhibited significantly elevated systemic inflammation (SIRI: 2.52 ± 0.38 vs 1.57 ± 0.29; P<0.001) and atherogenic dyslipidemia, characterized by higher low-density lipoprotein cholesterol (LDL-C: 3.43 ± 0.91 vs 2.56 ± 0.72 mmol/L; P<0.001) and lower high-density lipoprotein cholesterol (HDL-C: 0.61 ± 0.19 vs 0.92 ± 0.25 mmol/L; P<0.001). The SIRI-lipid nomogram incorporated six independent predictors, including SIRI (OR=3.36, 95% CI 2.00-6.07), LDL-C (OR=5.98, 95% CI 2.84-14.13) and HDL-C (OR=0.06, 95% CI 0.01-0.64). The nomogram achieved an AUC of 0.926 (95% CI 0.879-0.973) and demonstrated excellent calibration, with a mean absolute calibration error of 0.014 based on 1000 bootstrap samples. DCA showed clinical utility across decision thresholds. SIRI remained an independent predictor of BSIs after multivariable adjustment (OR=3.28) and correlated with prolonged hospitalization (P=0.007). Conclusion: The SIRI-lipid integrated nomogram provides clinically applicable prediction of BSIs risk in AML induction therapy, with validated clinical utility. Elevated SIRI combined with atherogenic dyslipidemia, characterized by high LDL-C and low HDL-C, represents actionable risk indicators enabling early clinical interventions.
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