ArticleBMC infectious diseases2023
Optimization strategy for the early timing of bronchoalveolar lavage treatment for children with severe mycoplasma pneumoniae pneumonia.
Article in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed, 20 citations in OpenAlex.
- A machine learning-based early in-hospital risk stratification model for severe mycoplasma pneumoniae pneumonia in children.Translational pediatrics · 2026Article
- Methodological comparison of capillary and venous blood parameters in pediatricTranslational pediatrics · 2026Article
- Levels of Toll-Like Receptor 2, Myeloid Differentiation Primary Response 88 and Mucin 5AC, Oligomeric Mucus/Gel-Forming in Bronchoalveolar Lavage Fluid for Predicting SevereInfection and drug resistance · 2026Article
- Immunopathogenesis, molecular phenotyping, and host-directed interventions for severe pediatricFrontiers in cellular and infection microbiology · 2026Review
- Machine learning-driven risk assessment of severeFrontiers in medicine · 2026Article
- CT-based radiomics models for predicting the prognosis of children with mycoplasma pneumonia.Frontiers in cellular and infection microbiology · 2026Article
- Timing and efficacy of doxycycline in macrolide-resistantFrontiers in public health · 2026Article
- A fever-based therapeutic window for bronchoscopy to prevent bronchiolitis obliterans in children with Mycoplasma pneumoniae pneumonia.Frontiers in pediatrics · 2026Article
- Comparing differences in onset and clinical manifestations between children and adults withFrontiers in public health · 2026Article
- Development and Validation of a Nomogram Model to Predict the Risk of Severe Pneumonia in Children with Pneumococcal Infection.Infection and drug resistance · 2026Article
- A causal forest model integrating quantitative CT scores to predict benefit from flexible bronchoscopy in pediatric Mycoplasma pneumoniae pneumonia: a two-center retrospective study.Respiratory research · 2025Article
- Analysis of risk factors for plastic bronchitis induced by Streptococcus pneumoniae in children.BMC infectious diseases · 2025Article
- Risk factors analysis of airway mucus plugs in community-acquired refractory mycoplasma pneumoniae pneumonia: a case-control study.Italian journal of pediatrics · 2025Article
- Predictive value of an early comprehensive assessment model for refractory mycoplasma pneumoniae pneumonia and internal validation.BMC infectious diseases · 2025Article
- Case Report: A neonatal case of severe congenitalFrontiers in pediatrics · 2025Article
- Biomarkers associated with the diagnosis and prognosis ofFrontiers in cellular and infection microbiology · 2025Review
- Microbial and clinical disparities in pneumonia: insights from metagenomic next-generation sequencing in patients with community-acquired and severe pneumonia.Frontiers in microbiology · 2025Article
- Building a diagnostic prediction model for severeFrontiers in public health · 2025Article
- Lung consolidation absorption time in 238 pediatric cases of mycoplasma pneumoniae pneumonia.Frontiers in pediatrics · 2025Article
- The role of bronchoalveolar lavage fluid metagenomic next-generation sequencing in detecting pathogens and optimising antibiotic therapy in paediatric severe community-acquired pneumonia.Frontiers in cellular and infection microbiology · 2025Article
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundEarly evaluation of severe mycoplasma pneumoniae pneumonia (SMPP) and the prompt utilization of fiberoptic bronchoscopic manipulation can effectively alleviate complications and restrict the progression of sequelae. This study aim to establish a nomogram forecasting model for SMPP in children and explore an optimal early therapeutic bronchoalveolar lavage (TBAL) treatment strategy.
methodsThis retrospective study included children with mycoplasma pneumoniae pneumonia (MPP) from January 2019 to December 2021. Multivariate logistic regression analysis was used to screen independent risk factors for SMPP and establish a nomogram model. The bootstrap method was employed and a receiver operator characteristic (ROC) curve was drawn to evaluate the accuracy and robustness of the model. Kaplan-Meier analysis was used to assess the effect of lavage and hospitalization times.
resultsA total of 244 cases were enrolled in the study, among whom 68 with SMPP and 176 with non-SMPP (NSMPP). A prediction model with five independent risk factors: left upper lobe computed tomography (CT) score, sequential organ failure assessment (SOFA) score, acute physiology and chronic health assessment (APACHE) II score, bronchitis score (BS), and c-reactive protein (CRP) was established based on the multivariate logistic regression analysis. The ROC curve of the prediction model showed the area under ROC curve (AUC) was 0.985 (95% confidence interval (CI) 0.972-0.997). The Hosmer-Lemeshow goodness-of-fit test results showed that the nomogram model predicted the risk of SMPP well (χ2 = 2.127, P = 0.977). The log-rank result suggested that an early BAL treatment could shorten MPP hospitalization time (P = 0.0057).
conclusionThis nomogram model, based on the left upper lobe CT score, SOFA score, APACHE II score, BS, and CRP level, represents a valuable tool to predict the risk of SMPP in children and optimize the timing of TBAL.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.