Diagnostic Value of Combined Biomarkers and the Shock Index for Predicting Febrile Neutropenia and Clinical Outcomes in the Emergency Department: A Multivariate Regression Analysis
- 1Department of Emergency Medicine, Faculty of Medicine, Başkent University, Ankara 06490, Türkiye
- 2Department of Physiology, Faculty of Medicine, Yüksek İhtisas University, Ankara 06530, Türkiye
Abstract
Background: Early risk stratification of febrile neutropenia (FN) in the emergency department (ED) is vital to accelerate empirical antibiotic management. This study evaluates the independent diagnostic performance of combined blood-borne inflammatory indices and the Shock Index (SI) in predicting FN status and severe clinical outcomes. Methods: Medical records of 338 febrile oncology patients presenting to the ED between 2020 and 2026 were retrospectively evaluated. Patients were divided into the FN group (fever + ANC < 1000 cells/μL; n=213) and the control group (n=125). Advanced cell-line metrics and biochemical ratios were calculated at admission. Independent predictors were isolated using multivariable logistic regression analysis. Results: Multivariable regression analysis revealed that elevated core body temperature (aOR: 3.229, 95% CI: 1.845–5.652, p< 0.001), lower serum sodium levels (aOR: 0.843, 95% CI: 0.767–0.926, p< 0.001), a low Neutrophil-to-Lymphocyte Ratio (NLR) (aOR: 0.636, 95% CI: 0.549–0.736, p< 0.001), and an elevated Shock Index (aOR: 24.010, 95% CI: 2.258–255.360, p=0.008) were stable independent predictors of FN. The combined four-variable integrated model achieved an outstanding Area Under the Curve (AUC) of 0.906 (95% CI: 0.874–0.937) with a diagnostic sensitivity of 77.4% and a specificity of 87.0%. Conclusions: Integrating baseline core temperature, hyponatremia, low cellular NLR, and physiologic SI values creates a rapid, cost-effective, and highly accurate screening platform to optimize emergency triage workflows and prevent computational delivery latency in critical oncologic emergencies.
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BibTeX
@article{muratoglu2026diagnostic,
title = {{Diagnostic Value of Combined Biomarkers and the Shock Index for Predicting Febrile Neutropenia and Clinical Outcomes in the Emergency Department: A Multivariate Regression Analysis}},
author = {Murat Muratoglu and Busra Bulut and Saide Bakal Muratoglu and Mohammadsajad Cheraqi and Fatih Yıldırım},
journal = {Journal of Clinical Medicine},
year = {2026},
month = oct,
doi = {10.3390/jcm15218234},
url = {https://www.mdpi.com/2077-0383/15/21/8234},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Diagnostic Value of Combined Biomarkers and the Shock Index for Predicting Febrile Neutropenia and Clinical Outcomes in the Emergency Department: A Multivariate Regression Analysis
AU - Murat Muratoglu
AU - Busra Bulut
AU - Saide Bakal Muratoglu
AU - Mohammadsajad Cheraqi
AU - Fatih Yıldırım
PY - 2026
DA - 2026/10/22
JO - Journal of Clinical Medicine
DO - 10.3390/jcm15218234
UR - https://www.mdpi.com/2077-0383/15/21/8234
AB - Background: Early risk stratification of febrile neutropenia (FN) in the emergency department (ED) is vital to accelerate empirical antibiotic management. This study evaluates the independent diagnostic performance of combined blood-borne inflammatory indices and the Shock Index (SI) in predicting FN status and severe clinical outcomes. Methods: Medical records of 338 febrile oncology patients presenting to the ED between 2020 and 2026 were retrospectively evaluated. Patients were divided into the FN group (fever + ANC < 1000 cells/μL; n=213) and the control group (n=125). Advanced cell-line metrics and biochemical ratios were calculated at admission. Independent predictors were isolated using multivariable logistic regression analysis. Results: Multivariable regression analysis revealed that elevated core body temperature (aOR: 3.229, 95% CI: 1.845–5.652, p< 0.001), lower serum sodium levels (aOR: 0.843, 95% CI: 0.767–0.926, p< 0.001), a low Neutrophil-to-Lymphocyte Ratio (NLR) (aOR: 0.636, 95% CI: 0.549–0.736, p< 0.001), and an elevated Shock Index (aOR: 24.010, 95% CI: 2.258–255.360, p=0.008) were stable independent predictors of FN. The combined four-variable integrated model achieved an outstanding Area Under the Curve (AUC) of 0.906 (95% CI: 0.874–0.937) with a diagnostic sensitivity of 77.4% and a specificity of 87.0%. Conclusions: Integrating baseline core temperature, hyponatremia, low cellular NLR, and physiologic SI values creates a rapid, cost-effective, and highly accurate screening platform to optimize emergency triage workflows and prevent computational delivery latency in critical oncologic emergencies.
SN - 2077-0383
ER -