ORIGINAL RESEARCH article
Front. Pediatr.
Sec. Pediatric Infectious Diseases
This article is part of the Research TopicNew Discoveries and Challenges in Pediatric Infectious Diseases: Epidemiological, Clinical, and Pathogenic AdvancesView all 21 articles
Screening of Early Predictive Serum Biomarkers and Construction of a Combined Predictive Model for Refractory Mycoplasma pneumoniae Infection in Children
Provisionally accepted
- 1Nanjing Jiangbei Hospital, Nanjing, China
- 2Nanjing Jiangbei Hospital, 830357, Nanjing, China
- 3Anhui Medical University Clinic Medical College, Hefei, China
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Background: Mycoplasma pneumoniae pneumonia (MPP) is a prevalent respiratory infection. Refractory MPP (RMPP) presents more severe symptoms and requires more intensive treatment compared to general MPP (GMPP). This study aimed to identify distinguishing clinical, laboratory, and radiological characteristics between RMPP and GMPP and develop an early predictive model for RMPP risk stratification. Methods: A total of 568 patients, including 130 RMPP cases and 438 GMPP cases, were enrolled. Clinical information, laboratory tests, and radiological features were compared. Univariate and multivariate logistic regression analyses identified serum biomarkers associated with RMPP. A combined predictive model using random forest approach was developed and externally validated. Results: RMPP patients showed significantly higher rates of older age, fever, tachypnea, chest tightness, wheezing, chills, extrapulmonary complications, decreased unilateral lung sounds, longer fever duration, hospital stay, antibiotic therapy, oxygenotherapy use, and Intensive Care Unit (ICU) admission (all P<0.05). Laboratory findings revealed elevated neutrophil percentage, C-reactive protein (CRP), lactate dehydrogenase (LDH), immunoglobulin A (IgA), interleukin (IL)- 6, IL-10, and interferon-gamma (IFN-γ), but lower prealbumin (PAB) concentrations in RMPP. Radiologically, RMPP exhibited more severe manifestations such as large lesions, pleural effusion, lobar atelectasis, pulmonary consolidation, and pleural thickening. Using the eight independently associated serum biomarkers, we developed a multi-factor random forest model that showed excellent discrimination between RMPP and GMPP (AUC=0.978 in the development cohort), which was confirmed in an external validation cohort (AUC=0.957). Conclusions: Significant differences in clinical, laboratory, and radiological characteristics were observed between RMPP and GMPP. The combined multi-marker model shows strong potential for early risk identification of RMPP and may support timely clinical decision-making; however, prospective validation is needed before routine implementation.
Keywords: Mycoplasma, Pneumonia, predictive model, respiratory infection, Serum biomarkers
Received: 06 Aug 2025; Accepted: 19 Jan 2026.
Copyright: © 2026 Zhu, Xu, Yuan, Li and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jinsheng Xu
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