JCNRJournal of Clinical and Nursing Research2208-36852208-3693Bio-Byword Scientific Publishing Pty. Ltd.10.26689/JCNR.v10i9.15817ArticleAnalysis of Influencing Factors for Pulmonary Consolidation in Children with Mycoplasma Pneumoniae Pneumonia and Construction‑Validation of a Nomogram Modelhttps://artdesignp.com/journal/JCNR/10/9/10.26689/JCNR.v10i9.15817SuLanlan,YinGuanghui,LiangPeishan,WeiYanping,LiChunlin,LinKun20261092026-10-23Objective: To explore the independent influencing factors for pulmonary consolidation complicated by mycoplasma pneumoniae pneumonia (MPP) in children, and construct a nomogram prediction model capable of individualised quantitative risk assessment, so as to provide evidence for early clinical identification of high‑risk children and formulation of precise intervention strategies. Methods: A retrospective cohort design was adopted in this study. A total of 316 children diagnosed with MPP at Wuming Hospital Affiliated to Guangxi Medical University from June 2023 to June 2024 were enrolled as research subjects. According to imaging findings, the children were divided into pulmonary‑consolidation group (n = 177) and non‑pulmonary‑consolidation group (n = 139). Baseline clinical data and laboratory indicators of the two groups were compared via univariate analysis. Variables with statistical differences in univariate analysis were included in multivariate binary Logistic regression analysis to screen independent risk factors for pulmonary consolidation among children with MPP. A nomogram prediction model was constructed based on screened results, and internal validation was performed using the Bootstrap method (1 000 repeated samplings). The discrimination, calibration and predictive performance of the model were comprehensively evaluated by calculating the concordance index (C‑index), plotting calibration curves and receiver operating characteristic (ROC) curves. Results: Univariate analysis showed that peripheral white blood cell count (WBC), high‑sensitivity C‑reactive protein (hs‑CRP), erythrocyte sedimentation rate (ESR) and fibrinogen (FIB) levels in the pulmonary‑consolidation group were significantly higher than those in the non‑pulmonary‑consolidation group (all p < 0.05). Multivariate Logistic regression analysis further confirmed that elevated WBC (OR = 1.054, 95%CI: 1.001–1.111), elevated hs‑CRP (OR = 1.044, 95% CI: 1.018–1.070) and elevated FIB (OR = 1.492, 95% CI: 1.007–2.212) were independent risk factors for pulmonary consolidation in children with MPP (all p < 0.05). For the nomogram prediction model constructed based on the above three indicators, the C‑index from internal validation was 0.718 (95% CI: 0.659–0.802), suggesting acceptable discrimination capacity of the model. The calibration curve indicated high consistency between predicted probabilities and actually‑observed probabilities. ROC‑curve analysis yielded an area under curve (AUC) of 0.731 for the model to predict pulmonary consolidation, with a sensitivity of 61.4 % and specificity of 75.2 %. Clinical decision‑curve analysis further verified positive net clinical benefit of the model across a wide range of threshold probabilities. In summary, this nomogram model achieves a sensitivity of 61.4 % and specificity of 75.2 %, with acceptable discrimination and calibration, and possesses certain clinical practical value. Conclusion: WBC, hs‑CRP and FIB are independent risk factors for pulmonary consolidation complicated by paediatric MPP. This study successfully constructed and validated a nomogram prediction model based on these three indicators. With favourable predictive performance and clinical practicality, the model can serve as clinical reference. It facilitates early individualised risk assessment of pulmonary consolidation for children with MPP and provides an intuitive, quantitative decision‑supporting tool for prospective clinical interventions.Mycoplasma pneumoniae, Pulmonary consolidation, Influencing factors, Nomogram model

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