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September 10, 2025African Health SciencesOpen Access

Establishment and validation of a predictive model for severe pneumonia in children

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Authors

WYWenhua YeJWJinyan WuMCMi Cao

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Overview

This study develops a predictive model to identify severe pneumonia in children, indicating prompt treatment may be necessary.

Key Points

  • The predictive model accurately identifies children at risk for severe pneumonia, enabling timely intervention.
  • Children with high body temperature and respiratory rate are recognized as independent risk factors for severe pneumonia.
  • Observational analysis of children aged 1 month to 14 years diagnosed with pneumonia reveals critical differences in clinical indicators.
  • The model may reduce family burden and enhance overall patient outcomes in pediatric pneumonia cases.

Cite This Study

Ye et al. (2025) studied this question.

synapsesocial.com/papers/68c23e02b210217d6479050bhttps://doi.org/10.4314/ahs.v25i1.14
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Construction of a prediction model for pneumonia in children undergoing neurosurgery based on regular clinical laboratory tests and baseline information2025
  2. 2Management of severe pneumonia in respiratory non-intensive care unit: a retrospective study from a single center experience2025
  3. 3Building a diagnostic prediction model for severe Mycoplasma pneumoniae pneumonia in children using machine learning2025 · 10 citations
  4. 4Risk factors for mortality and development of a predictive model in pediatric sepsis2025
  5. 5A clinical prediction model for rapidly differentiating pulmonary tuberculosis from community acquired pneumonia in children2025