A Novel Nomogram Integrating Clinical, Radiological, and Immunological Indicators for Early Prediction of Severe Mycoplasma pneumoniae Pneumonia in Children

Objective: This study aimed to develop a preliminary nomogram model for early prediction of severe Mycoplasma pneumoniae pneumonia (SMPP) in children. Methods: A retrospective analysis was conducted on children with MPP, classifying them into general MPP (GMPP) and severe MPP (SMPP) groups. The risk factors for SMPP were identified using Logistic Stepwise Regression Analysis, followed by Multivariate Regression Analysis to construct the nomogram model. The model’s discrimination was evaluated using the receiver operating characteristic (ROC) curve and area under the curve (AUC), its calibration with a calibration curve, and the results were visualized using the Hosmer–Lemeshow goodness-of-fit test. Results: No statistically significant differences were observed in gender or age between the two groups (all p > 0.05). Compared with the GMPP group, the SMPP group had a longer duration of fever ( p < 0.05), and significantly higher rates of extrapulmonary complications, pulmonary consolidation, large lesions, refractory MPP (RMPP), as well as glucocorticoid and bronchoscopy usage (all p < 0.05). Concurrently, levels of CRP, LDH, IFN-γ, CD64, and D-dimer were also significantly elevated in the SMPP group (all p < 0.05). Multivariate logistic regression analysis identified the duration of fever (OR = 1.557, 95% CI: 1.154– 2.103), pulmonary consolidation (OR = 13.812, 95% CI: 2.674– 71.337), CD64 (OR = 2.076, 95% CI: 1.106– 3.899), and LDH (OR = 1.022, 95% CI: 1.011– 1.032) as independent risk factors for SMPP (all p < 0.05). The nomogram model constructed based on these factors demonstrated a concordance index (C-index) of 0.910 upon internal validation. The model showed good calibration, supported by the Hosmer-Lemeshow test indicating a good fit ( p = 0.823). ROC curve analysis revealed that the model predicted SMPP with an area under the curve (AUC) of 0.910, a sensitivity of 73.1%, and a specificity of 94.7%. Conclusion: Fever duration, pulmonary consolidation, CD64, and LDH are independent risk factors for SMPP in children. The nomogram integrating these four factors shows good preliminary predictive performance but requires external validation in larger, multi-center cohorts before clinical application. Keywords: children, Mycoplasma pneumoniae pneumonia, severe, CD64, nomogram, prediction model