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Updated: May 8, 2025
Experimental Model to Evaluate Resolution of Pneumonia
Published on: February 17, 2023
Construction and validation of a nomogram model to predict bronchiolitis Mycoplasma pneumoniae pneumonia in children
Shuping Xiong1,2, Lihua Lin3,1, Qihong Chen3,1
1Department of Pediatrics, Pediatric Key Laboratory of Xiamen, the First Affiliated Hospital of Xiamen University, Xiamen, 361003, China.
Abstract:
After the cancellation of COVID-19 epidemic control measures in 2023, cases of pediatric bronchiolitis caused by Mycoplasma pneumoniae (MP) have been reported successively, with some children experiencing residual bronchiolitis obliterans (BO). Currently, the diagnosis of bronchiolitis Mycoplasma pneumoniae pneumonia (MPP) primarily relies on high-resolution computed tomography (HRCT). To establish a predictive model for bronchiolitis MPP, a retrospective analysis was conducted. The patients were randomly divided into a training cohort and a validation cohort. The nomogram model was constructed in the training cohort. Finally, the differential, calibration, and clinical applicability of the prediction model were evaluated using both the training and validation cohorts. Logistic stepwise regression analysis identified age, atopy, wheezing, hypoxemia, and pleural effusion as independent predictors of bronchiolitis MPP. These factors were used to construct a nomogram model. This nomogram model serves as a useful tool for predicting the risk of bronchiolitis MPP, which may facilitate individualized early intervention.
Insights
Pediatric bronchiolitis caused by Mycoplasma pneumoniae (MP) is increasing. Researchers developed a nomogram model using age, atopy, wheezing, hypoxemia, and pleural effusion to predict bronchiolitis Mycoplasma pneumoniae pneumonia (MPP) risk for early intervention.
Area of Science:
- Pediatric Pulmonology
- Infectious Diseases
- Medical Diagnostics
Background:
- Post-COVID-19, pediatric Mycoplasma pneumoniae (MP) infections, including bronchiolitis, have risen.
- Some children develop residual bronchiolitis obliterans (BO) after MP infection.
- Diagnosing bronchiolitis Mycoplasma pneumoniae pneumonia (MPP) typically relies on high-resolution computed tomography (HRCT).
Purpose of the Study:
- To develop and validate a predictive model for bronchiolitis MPP.
- To identify key clinical factors for predicting MPP risk.
- To facilitate early and individualized intervention for affected children.
Main Methods:
- Retrospective analysis of pediatric patients diagnosed with bronchiolitis MPP.
- Random division into training and validation cohorts.
- Construction of a nomogram model using logistic stepwise regression.
Main Results:
- Age, atopy, wheezing, hypoxemia, and pleural effusion were identified as independent predictors of bronchiolitis MPP.
- A nomogram model was successfully constructed and validated.
- The model demonstrated good differential, calibration, and clinical applicability.
Conclusions:
- The developed nomogram model is a valuable tool for predicting the risk of bronchiolitis MPP in children.
- Early risk prediction can aid in timely and personalized treatment strategies.
- Further research may refine predictive capabilities for pediatric respiratory infections.
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