Predictive value of AFR and UCR for the Methicillin-resistant Staphylococcus aureus infection in children with bone and joint infections

Background: Methicillin-resistant Staphylococcus aureus (MRSA) infections present significant diagnostic and therapeutic challenges in pediatric bone and joint infections (BJIs). Therefore, this study aimed to evaluate the predictive value of the albumin-to-fibrinogen ratio (AFR) and the urea-to-creatinine ratio (UCR) at admission for MRSA infections in pediatric patients with BJIs. Methods: Patients were retrospectively categorized into MRSA ( n = 23) and methicillin-susceptible Staphylococcus aureus (MSSA, n = 54) groups based on microbiological culture results (MSSA group = 0, MRSA group = 1). Clinical data and laboratory parameters, including serum albumin, fibrinogen, urea, creatinine, white blood cell (WBC) count, C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR), were collected. Receiver operating characteristic (ROC) curves were employed to assess the predictive accuracy of AFR and UCR for MRSA infection. Logistic regression analyses were conducted to identify independent predictors of MRSA infection. Results: Compared to the MSSA group, the MRSA group demonstrated significantly lower values for both AFR and UCR values (both P < 0.05). ROC analysis indicated moderate diagnostic accuracy for AFR (AUC = 0.696) and UCR (AUC = 0.655) in predicting MRSA infections. Multivariate logistic regression analysis confirmed that higher levels of AFR > 6.73 and UCR > 23.91 served as independent protective factors against MRSA infection ( P = 0.016 and P = 0.024, respectively). Traditional inflammatory markers (WBC, CRP, and ESR) showed no significant differences between groups ( P > 0.05). Conclusions: In pediatric patients admitted with BJIs, AFR ≤ 6.73 and UCR ≤ 23.91 at admission may indicate an increased likelihood of MRSA infection. Both AFR and UCR exhibit moderate predictive value for early identification of MRSA-associated pediatric BJIs, thus they may facilitate optimization of empirical antimicrobial therapy.