Jiao Lian, Xiyao Si, Xiaolong Li, Tao Xue, Zhenying Liu
Background Mycoplasma pneumoniae pneumonia (MPP) remains a leading cause of community-acquired pneumonia in children, with respiratory failure occurring in 15%–20% of hospitalized cases. Despite advances in understanding MPP pathogenesis, validated tools for early prediction of respiratory failure are lacking. This study aimed to develop and validate a nomogram based on Clinical Pulmonary Infection Score (CPIS) for individualized risk stratification in pediatric MPP. Methods We conducted a retrospective cohort study of 305 children with confirmed MPP admitted to our hospital between July 2020 and December 2024. Patients were categorized into respiratory failure ( n = 62) and non-respiratory failure ( n = 243) groups. Demographics, clinical features, laboratory parameters, chest imaging findings, and CPIS were collected. Independent risk factors were identified through multivariate logistic regression, and a nomogram was constructed and validated using ROC curve analysis, calibration plots, and decision curve analysis. Results Respiratory failure was associated with significantly higher rates of tachypnea (91.9% vs. 16.5%), interstitial changes (87.1% vs. 25.5%), and pleural effusion (74.2% vs. 24.7%) (all P < 0.001). The respiratory failure group exhibited elevated NLR (5.2 vs. 3.7), CRP, D-dimer, and CPIS (7.4 vs. 5.3), with lower SpO 2 (89.6% vs. 94.3%) (all P < 0.001). Multivariate logistic analysis identified interstitial changes (OR = 2.522, P = 0.001), NLR (OR = 2.716, P < 0.001), and CPIS (OR = 1.932, P < 0.001) as independent risk factors, while older age (OR = 0.467, P < 0.001) and higher SpO 2 (OR = 0.772, P < 0.001) were protective. The nomogram demonstrated exceptional discriminative ability (AUC = 0.918, 95% CI: 0.880–0.956), good calibration (Hosmer-Lemeshow P = 0.71), and positive net benefit across threshold probabilities of 5%–40%. Conclusions This CPIS-based nomogram provides a highly accurate, clinically practical tool for predicting respiratory failure in pediatric MPP. By integrating radiographic, inflammatory, and physiological parameters, it enables early identification of high-risk patients for enhanced monitoring and preemptive respiratory support, potentially improving outcomes in severe MPP.