基于网络的预测儿童难治性肺炎支原体肺炎的动态列线图
A Web-Based Dynamic Nomogram for Predicting Refractory Mycoplasma pneumoniae Pneumonia in Children.
摘要(中文译文)
儿童难治性肺炎支原体肺炎（RMPP）与更强的炎症反应、更复杂的治疗管理及更高的肺部并发症风险相关。早期识别高危儿童可能有助于及时调整治疗。本回顾性研究纳入2022年11月至2023年11月期间500例住院的肺炎支原体肺炎患儿。队列被随机分为训练集（n = 375）和验证集（n = 125）。单因素和多因素logistic回归分析确定了RMPP的六个独立预测因素：入院前发热持续时间、峰值体温、乳酸脱氢酶水平、痰栓或胸腔积液、肺实变及低氧血症。利用这些变量构建了基于网络的动态列线图。该模型显示出良好的区分度，训练集受试者工作特征曲线下面积/C指数为0.840（95% CI，0.785-0.892），验证集为0.831（95% CI，0.743-0.906）。校准曲线显示预测风险与观察风险之间具有良好的一致性，决策曲线分析提示在大多数阈值概率下具有临床净获益。对于发热持续时间长、峰值体温高、乳酸脱氢酶升高、低氧血症以及CT证据显示肺实变或痰栓/胸腔积液的儿童，应认为其RMPP风险增加，可能需要更密切的监测和及时的治疗调整。
Abstract
Refractory Mycoplasma pneumoniae pneumonia (RMPP) in children is associated with stronger inflammatory responses, more complex management, and a higher risk of pulmonary complications. Early identification of high-risk children may support timely treatment adjustment. This retrospective study included 500 hospitalized children with Mycoplasma pneumoniae pneumonia from November 2022 to November 2023. The cohort was randomly divided into a training set (n = 375) and a validation set (n = 125). Univariable and multivariable logistic regression analyses identified six independent predictors of RMPP: fever duration before admission, peak body temperature, lactate dehydrogenase level, sputum plugs or pleural effusion, lung consolidation, and hypoxemia. A web-based dynamic nomogram was constructed using these variables. The model showed good discrimination, with an area under the receiver operating characteristic curve/C-index of 0.840 (95% CI, 0.785-0.892) in the training set and 0.831 (95% CI, 0.743-0.906) in the validation set. Calibration curves showed good agreement between predicted and observed risks, and decision curve analysis suggested clinical net benefit across most threshold probabilities. Children with prolonged fever, high peak temperature, elevated lactate dehydrogenase, hypoxemia, and CT evidence of lung consolidation or sputum plugs/pleural effusion should be considered at increased risk of RMPP and may require closer monitoring and timely treatment adjustment.
如何引用
AMA
Jiali Yang, Xin Yan. A Web-Based Dynamic Nomogram for Predicting Refractory Mycoplasma pneumoniae Pneumonia in Children.. Journal of visualized experiments : JoVE. 2026; doi:10.3791/71588.
APA
Jiali Yang, Xin Yan (2026). A Web-Based Dynamic Nomogram for Predicting Refractory Mycoplasma pneumoniae Pneumonia in Children.. Journal of visualized experiments : JoVE. https://doi.org/10.3791/71588
GB/T 7714
Jiali Yang, Xin Yan. A Web-Based Dynamic Nomogram for Predicting Refractory Mycoplasma pneumoniae Pneumonia in Children.[J]. Journal of visualized experiments : JoVE, 2026 doi:10.3791/71588.
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