Related Experiment Video
Updated: Jun 5, 2025
Experimental Model to Evaluate Resolution of Pneumonia
Published on: February 17, 2023
Risk association model for atelectasis complication in Mycoplasma pneumoniae pneumonia patients following
Mingyi Xu1,2, Minhao Fan2, Huixia Wang3
1Department of Respiratory Medicine, The Affiliated Wuxi People's Hospital, Wuxi Children's Hospital of Nanjing Medical University, Wuxi, Jiangsu, China.
Background:
Mycoplasma pneumoniae pneumonia (MPP) is a common disease of childhood pneumonia, and atelectasis is a serious comorbidity. Traditional diagnostic methods for MPP are limited by low accuracy, emphasizing the need for improved diagnostic approaches. This study aimed to establish a predictive scoring model for early detection of MPP complicated with atelectasis following standardized treatment.
Methods:
A total of 572 children were retrospectively enrolled, including 40 patients with MPP complicated by atelectasis despite standardized treatment and 532 patients in the non-atelectasis group. Clinical, laboratory, and imaging data within 24 h of admission were collected, including demographic information and various biomarkers. Multivariate logistic regression analysis was employed to identify risk factors and construct a predictive model, evaluated using receiver operating characteristic (ROC) curve analysis.
Results:
Significant differences were observed between the MPP complicated with atelectasis group and the non-atelectasis group in terms of age, hospital admission time, fever duration, neutrophil percentage and count, CRP, ALT, and LDH levels (P < 0.05). According to the multivariate logistic regression analysis, length of fever, neutrophil ratio, platelet count, ALT, LDH, age were incorporated into the nomogram. The predictive model exhibited a sensitivity of 87.97% and specificity of 77.50% according to the ROC curve.
Conclusion:
Our study presents a preliminary risk association model incorporating clinical indicators such as fever duration, neutrophil ratio, platelet count, ALT value, LDH value, and age to aid in the early prediction of atelectasis in children with MPP. Given the methodological limitations, the generalizability of our findings is constrained, and this model should be viewed as an initial framework for clinical assessment rather than a definitive tool.
Insights
This study developed a scoring model to predict atelectasis in children with Mycoplasma pneumoniae pneumonia (MPP). The model uses clinical factors to aid early detection of this serious complication.
Area of Science:
- Pediatric Pulmonology
- Infectious Diseases
- Diagnostic Medicine
Background:
- Mycoplasma pneumoniae pneumonia (MPP) is a common childhood illness.
- Atelectasis is a frequent and serious complication of MPP.
- Current diagnostic methods for MPP lack accuracy, necessitating improved approaches.
Purpose of the Study:
- To develop a predictive scoring model for early detection of atelectasis in children with MPP.
- To identify key clinical indicators associated with atelectasis in MPP patients.
- To establish a tool for improved clinical assessment and management of complicated MPP.
Main Methods:
- Retrospective analysis of 572 children with MPP.
- Data collection included clinical, laboratory, and imaging findings within 24 hours of admission.
- Multivariate logistic regression and ROC curve analysis were used to build and evaluate the predictive model.
Main Results:
- Significant differences in age, fever duration, neutrophil counts, CRP, ALT, and LDH levels were found between groups.
- Fever duration, neutrophil ratio, platelet count, ALT, LDH, and age were identified as key predictors.
- The predictive model achieved 87.97% sensitivity and 77.50% specificity.
Conclusions:
- A preliminary predictive model incorporating clinical indicators was established for early atelectasis detection in pediatric MPP.
- The model serves as an initial framework for clinical assessment, requiring further validation.
- This tool aims to improve the early identification of atelectasis in children with MPP.
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