Admission-Based Prediction of Macrolide Resistance in Children Aged >28 Days and ≤8 Years with

Purpose: Macrolide-resistant Patients and Methods: This single-center retrospective prediction model study included hospitalized children with confirmed MPP at the First Affiliated Hospital of Jiamusi University from October 2023 to October 2024. Candidate predictors were restricted to demographic and laboratory variables available at admission or during early hospitalization. Univariable analyses were followed by multivariable logistic regression with stepwise selection. Model performance was assessed by receiver operating characteristic (ROC) analysis, calibration plots, decision curve analysis (DCA), and bootstrap internal validation. Results: A total of 724 children were included, of whom 146 (20.2%) were classified as having macrolide resistance. The final model included height, C-reactive protein (CRP), lactate dehydrogenase (LDH), and creatine kinase-MB (CK-MB). The model showed an apparent area under the ROC curve (AUC) of 0.752 (95% CI, 0.711-0.793), and the optimism-corrected AUC after internal validation was 0.746. At the selected cutoff, sensitivity was 0.719, specificity was 0.680, and the negative predictive value was 0.906. Calibration and DCA suggested acceptable agreement and potential clinical usefulness within the observed sample. Conclusion: An admission-based model using height, CRP, LDH, and CK-MB showed moderate discrimination for predicting macrolide resistance in children aged >28 days and ≤8 years with MPP. The model showed a high negative predictive value and may help identify children at lower risk of molecularly confirmed macrolide resistance; molecular testing remains necessary to confirm resistance in children at higher predicted risk, and external validation is required before routine clinical use.