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<p>Early identification of high-risk patients is crucial for preventing peripherally intravenous central catheter (PICC)-related thrombosis in children with hematological malignancies. This study aims to develop and validate a clinical risk prediction tool for PICC-related thrombosis. A retrospective analysis was conducted on 519 children with hematological malignancies who underwent PICC catheterization at Tongji Hospital between January 2018 and December 2023. Among these children, 98 (18.9%) developed PICC-related thrombosis. A total of 54 potential predictor variables were analyzed, and six independent risk factors were identified: leukemia, number of catheters, history of catheterization, total parenteral nutrition, post-catheterization D-dimer, and post-catheterization fibrinogen. The prediction model constructed based on these factors demonstrated good predictive performance with the area under the curve of 0.844 (95% CI 0.787–0.900) for the training set and 0.794 (95% CI 0.698–0.890) for the validation set. The calibration curve and decision curve analysis further validated the good calibration and utility of the model. Through the visualization of nomogram, the model can provide strong support for the early prediction of PICC-related thrombosis in children with hematological malignancies and holds significant clinical application value.</p>

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Development and validation of a nomogram risk prediction model for PICC-related thrombosis in children with hematological malignancies

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年6月10日

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  • Maoling Fu,
  • Qiaoyue Yang,
  • Xiao Wu,
  • Xinyu Li,
  • Lexue Jiang,
  • Huiping Yan,
  • Genzhen Yu

摘要

Early identification of high-risk patients is crucial for preventing peripherally intravenous central catheter (PICC)-related thrombosis in children with hematological malignancies. This study aims to develop and validate a clinical risk prediction tool for PICC-related thrombosis. A retrospective analysis was conducted on 519 children with hematological malignancies who underwent PICC catheterization at Tongji Hospital between January 2018 and December 2023. Among these children, 98 (18.9%) developed PICC-related thrombosis. A total of 54 potential predictor variables were analyzed, and six independent risk factors were identified: leukemia, number of catheters, history of catheterization, total parenteral nutrition, post-catheterization D-dimer, and post-catheterization fibrinogen. The prediction model constructed based on these factors demonstrated good predictive performance with the area under the curve of 0.844 (95% CI 0.787–0.900) for the training set and 0.794 (95% CI 0.698–0.890) for the validation set. The calibration curve and decision curve analysis further validated the good calibration and utility of the model. Through the visualization of nomogram, the model can provide strong support for the early prediction of PICC-related thrombosis in children with hematological malignancies and holds significant clinical application value.