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Updated: Jan 13, 2026
Development and Assessment of Intracellular Infection Models for Staphylococcus aureus
Published on: January 17, 2025
Development and validation of a clinical nomogram for predicting methicillin-resistant Staphylococcus aureus in
Ting Ao1, Yingxiu Huang1, Ming Hu1
1Department of Infectious Diseases, Beijing Luhe Hospital, Capital Medical University, No. 82, Xinhua South Road, Tongzhou District, Beijing, 101100, China.
Background:
This study aimed to develop and validate a reliable nomogram based on clinical factors to predict the risk of methicillin-resistant Staphylococcus aureus (MRSA) bacteremia among patients with Staphylococcus aureus bacteremia, addressing the urgency surrounding its management.
Methods:
Adult patients with Staphylococcus aureus bacteremia diagnosed at Beijing Luhe Hospital affiliated with Capital Medical University between January 2019 and November 2024 were enrolled. Patients were randomly divided into training (70%) and validation (30%) cohorts. Clinical data were analyzed using best subset regression and multifactor logistic regression analyses to screen for risk factors. A model was constructed, and a nomogram was plotted. Model performance was evaluated and internally validated using the area under the curve (AUC), Hosmer-Lemeshow test, calibration curve, and decision curve analysis.
Results:
Of the 253 patients, 118 patients (46.6%) had MRSA bacteremia. The nomogram included Intensive Care Unit admission, long-term bedridden, central-venous catheter placement, and application of broad-spectrum antibiotics in the recent 3 months. The receiver-operating characteristic curve showed that the AUC of the nomogram was 0.868 (95%CI [confidence interval] 0.815-0.920) in the training cohort and 0.846 (95%CI 0.755-0.936) in the validation cohort. The calibration plot exhibited high consistency in prediction, and decision curve analysis showed excellent net benefits.
Conclusion:
Our nomogram demonstrates excellent discrimination, calibration, and clinical utility and may thus help clinicians accurately assess the risk of MRSA among patients with Staphylococcus aureus bacteremia.
