Clinical Diagnostic Prediction Model For Mycoplasma pneumoniae Pneumonia in Children
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.
Authors
- Mingjun Zhang (ORCID: https://orcid.org/0009-0001-0708-5874)
- Fan Zhong (ORCID: https://orcid.org/0000-0002-5127-6707)
- Ying Xu (ORCID: https://orcid.org/0000-0001-9570-8666)
- Linyan Zhang (ORCID: https://orcid.org/0000-0002-4713-8977)
- Xiaohua Liu (ORCID: https://orcid.org/0000-0001-9555-0555)
- Yu Yang (ORCID: https://orcid.org/0000-0001-9863-253X)
- Hongfei Du
- Huacui Huang
- Guijie Wang (ORCID: https://orcid.org/0009-0005-1660-994X)
Institutions
- Chengdu Medical College (CN)
- First Affiliated Hospital of Chengdu Medical College (CN)
- Chengdu Second People's Hospital (CN)
- Chongqing Jiulongpo People's Hospital (CN)
Publication Details
- Journal
- Infection and Drug Resistance
- Published
- 2025-10-01
- DOI
- https://doi.org/10.2147/idr.s541396
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00