ArticleInfection and drug resistance2025
Clinical Diagnostic Prediction Model For Mycoplasma pneumoniae Pneumonia in Children.
Article in Infection and drug resistance, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Clinical characteristics, risk factors, and pathogen spectrum of mixed infections in children withMicrobiology spectrum · 2026Article
- Machine learning-driven risk assessment of severeFrontiers in medicine · 2026Article
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Authors and funding
9 authors.
Funding
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Abstract
Background: The aim of this research is to ascertain the risk determinants associated with Mycoplasma pneumoniae pneumonia (MPP) in pediatric patients diagnosed with community-acquired pneumonia (CAP), as well as to construct predictive models to forecast the incidence of MPP. Methods: This study was conducted at Xindu District People's Hospital of Chengdu from August 2023 to March 2024. A total of 1030 children aged 0 to 14 years with CAP were enrolled and divided into MPP ( Results: The results of prediction model showed that four models had good performance. The area under the ROC curve revealed good predictive ability (AUC > 0.8 in both Logistic model and Experience model), the results of calibration curves indicated a good consistency consistency. Logistic+Lasso model selected 9 key variables for further analysis. Conclusion: We have developed and validated a clinical prediction model in children with Mycoplasma pneumoniae pneumonia (MPP). The model identifies NEUT%, EOS%, HSCRP, ADA, Crea, Urea, HDL, P, and ESR as significant independent predictors. It demonstrated robust discriminative ability and good calibration, offering a practical tool for clinicians to stratify risk and guide early intervention in pediatric patients.
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Registered trials
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