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A causal forest model integrating quantitative CT scores to predict benefit from flexible bronchoscopy in pediatric Mycoplasma pneumoniae pneumonia: a two-center retrospective study

Respir Res. 2025 Dec 16. doi: 10.1186/s12931-025-03447-8. Online ahead of print.

ABSTRACT

BACKGROUND: Flexible bronchoscopy (FB) is recommended for pediatric Mycoplasma pneumoniae pneumonia (MPP) with persistent consolidation or atelectasis, though substantial heterogeneity in treatment effects exists. This study aimed to develop a causal forest-based predictive model to identify pediatric MPP patients most likely to benefit from FB.

METHODS: This retrospective two-center study enrolled pediatric MPP patients in derivation (n = 753) and validation (n = 139) cohorts. Clinical, laboratory, and AI-quantified computed tomography (CT) data were analyzed. Individual treatment effects (ITEs) were estimated using causal forest algorithms. FB-beneficial subgroups were defined using receiver operating characteristic (ROC) analysis of ITEs, with the varying treatment effect across the subgroups validated via multivariable linear regression. Subgroup characteristics, feature importance, and heatmap-based feature interactions were also analyzed.

RESULTS: FB treatment significantly reduced total fever duration in identified FB-beneficial subgroups in both derivation (β = – 1.16, p < 0.001) and validation (β = – 0.68, p = 0.04) cohorts. These beneficial subgroups exhibited significantly higher consolidation/atelectasis volume (CAV), pneumonia attenuation (PA), and consolidation-to-pneumonia ratio (CAR) compared to non-beneficial groups (all p < 0.001). Heatmap analyses confirmed that increased CAV combined with elevated PA or lymphocyte counts could improve FB efficacy.

CONCLUSIONS: This study developed and validated an individualized prediction model to identify pediatric MPP patients most likely to benefit from FB treatment. Our model may serve as a tool to support clinicians in optimizing FB utilization, potentially reducing unnecessary interventions and associated risks. An accessible online tool of this model facilitates practical clinical implementation.

PMID:41402819 | DOI:10.1186/s12931-025-03447-8

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