A prediction model for bronchoalveolar lavage in children with Mycoplasma pneumoniae pneumonia and consolidation

支气管肺泡灌洗预测模型在患有肺炎支原体肺炎和肺实变的儿童中的应用

阅读:1

Abstract

To identify risk factors associated with the necessity of bronchoalveolar lavage (BAL) in children with Mycoplasma pneumoniae pneumonia (MPP) and pulmonary consolidation, and to develop and validate a predictive model to support clinical decision-making. A retrospective study was conducted on 323 children diagnosed with MPP and pulmonary consolidation at our hospital from September 2020 to October 2023. Patients were divided into BAL group (n = 163) and non-BAL group (n = 160). Clinical data, laboratory findings, and imaging features (including quantified pulmonary consolidation volume) were collected. Univariate and multivariate logistic regression analyses were employed to identify independent predictors for BAL intervention. A nomogram was constructed based on significant factors. The model's performance was assessed using the receiver operating characteristic (ROC) curve, concordance index (C-index), calibration plot, and internal validation via bootstrap resampling. Multivariate logistic regression identified lung atelectasis, older age, greater pulmonary consolidation volume (percentage of total lung volume), and longer hospital stay as independent risk factors for BAL. Corticosteroid treatment emerged as a protective factor. The nomogram developed from these variables yielded an area under the ROC curve (AUC) of 0.87 (95% CI: 0.83-0.91), with good calibration. Internal validation confirmed the robustness of the model. Lung atelectasis, pulmonary consolidation extent, length of hospitalization, age, and corticosteroid therapy are key determinants for BAL necessity in MPP children with consolidation. The proposed nomogram demonstrates strong discrimination, calibration, and clinical applicability, facilitating personalized evaluation of BAL indication.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。