A causal forest model integrating quantitative CT scores to predict benefit from flexible bronchoscopy in pediatric Mycoplasma pneumoniae pneumonia: a two-center retrospective study.
Authors
Affiliations (13)
Affiliations (13)
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, People's Republic of China.
- 4+4 Medical Doctor Program, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.
- National Clinical Research Center for Child Health, National Children's Regional Medical Center, Children's Hospital, Zhejiang University School of Medicine, Sino-Finland Joint AI Laboratory for Child Health of Zhejiang Province, No. 3333 Binsheng Road, Binjiang District, Hangzhou, 310000, People's Republic Of China.
- Sino-Finland Joint AI Laboratory for Child Health of Zhejiang Province, Hangzhou, 310052, People's Republic of China.
- Department of Data and Information, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, 310052, People's Republic of China.
- Theranostics and Translational Research Center, National Infrastructures for Translational Medicine, Institute of Clinical Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.
- Department of CT, Rizhao Hospital of Traditional Chinese Medicine, Rizhao, People's Republic of China.
- Department of Epidemiology and Health Statistics, Institute of Basic Medicine Sciences, School of Basic Medicine, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, People's Republic of China.
- Department of Pediatrics, Rizhao Hospital of Traditional Chinese Medicine, Rizhao, People's Republic of China.
- Deepwise AI Lab, Beijing Deepwise & League of PhD Technology Co.Ltd, Beijing, People's Republic of China.
- Department of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, People's Republic of China. [email protected].
- National Clinical Research Center for Child Health, National Children's Regional Medical Center, Children's Hospital, Zhejiang University School of Medicine, Sino-Finland Joint AI Laboratory for Child Health of Zhejiang Province, No. 3333 Binsheng Road, Binjiang District, Hangzhou, 310000, People's Republic Of China. [email protected].
- Sino-Finland Joint AI Laboratory for Child Health of Zhejiang Province, Hangzhou, 310052, People's Republic of China. [email protected].
Abstract
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. 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. 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. 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.