Prediction of moderate to severe bleeding risk in pediatric immune thrombocytopenia using machine learning.

Journal: European journal of pediatrics
PMID: 40195151

Abstract

UNLABELLED: This study aimed to develop and validate a risk prediction model for moderate to severe bleeding in children with immune thrombocytopenia (ITP). Data from 286 ITP patients were prospectively collected and randomly split into training (80%) and test (20%) sets. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Among seven machine learning algorithms, the eXtreme Gradient Boosting (XGBoost) model demonstrated the best performance (AUC = 0.886, 95% CI: 0.790-0.982) and was selected as the optimal model. Shapley Additive Explanations (SHAP) were used for model interpretation, identifying child age, age at diagnosis, and initial platelet count as key predictors of moderate to severe bleeding risk.

Authors

  • Xuelan Shen
    Department of Hematology and Oncology Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Rare Diseases in Infection and Immunity, Chongqing, People's Republic of China.
  • Xiaoli Guo
    College of Mathematics and Information Science, Zhengzhou University of Light Industry, Zhengzhou, China.
  • Yang Liu
    Department of Computer Science, Hong Kong Baptist University, Hong Kong, China.
  • Xiaorong Pan
    Department of Hematology and Oncology Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Rare Diseases in Infection and Immunity, Chongqing, People's Republic of China.
  • Haisu Li
    Department of Anesthesiology, Children's Hospital of Chongqing Medical University, Chongqing, People's Republic of China.
  • Jianwen Xiao
    Department of Hematology and Oncology Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Rare Diseases in Infection and Immunity, Chongqing, People's Republic of China.
  • Liping Wu
    Department of Gastroenterology, The Third People's Hospital of Chengdu, Chengdu 610031, Sichuan Province, China.

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