张昊, 谢欣, 周章剑, 郝楠. 列线图预测恶性肿瘤患者PICC导管相关血栓风险的研究[J]. 中国肿瘤临床, 2018, 45(3): 137-141. DOI: 10.3969/j.issn.1000-8179.2018.03.877
引用本文: 张昊, 谢欣, 周章剑, 郝楠. 列线图预测恶性肿瘤患者PICC导管相关血栓风险的研究[J]. 中国肿瘤临床, 2018, 45(3): 137-141. DOI: 10.3969/j.issn.1000-8179.2018.03.877
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Zhang Hao, Xie Xin, Zhou Zhangjian, Hao Nan. Nomogram predicted the risk for peripherally inserted central catheter related thrombosis in cancer patients[J]. CHINESE JOURNAL OF CLINICAL ONCOLOGY, 2018, 45(3): 137-141. DOI: 10.3969/j.issn.1000-8179.2018.03.877
Citation: Zhang Hao, Xie Xin, Zhou Zhangjian, Hao Nan. Nomogram predicted the risk for peripherally inserted central catheter related thrombosis in cancer patients[J]. CHINESE JOURNAL OF CLINICAL ONCOLOGY, 2018, 45(3): 137-141. DOI: 10.3969/j.issn.1000-8179.2018.03.877
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列线图预测恶性肿瘤患者PICC导管相关血栓风险的研究

Nomogram predicted the risk for peripherally inserted central catheter related thrombosis in cancer patients

    摘要
  • 摘要:
      目的  经外周中心静脉置管（peripherally inserted central catheters，PICC）在恶性肿瘤化疗中的应用越来越广泛，其导管相关血栓的发生率也呈现上升的趋势，显著影响患者的治疗及生存质量。
      方法  回顾性分析2014年12月至2015年12月就诊于西安交通大学第一附属医院的286例进行PICC置管的恶性肿瘤患者相关临床资料，并对潜在的危险因素进行最小绝对收缩选择算子（least absolute shrinkage and selection operator，LASSO）回归分析，最终构建列线图模型。
      结果  286例PICC置管患者中，72例出现导管相关血栓。将研究所纳入的27个潜在的血栓相关危险因素进行LASSO回归分析，结果显示进行外周血管穿刺时是否应用超声引导、患者既往是否接受过经外周静脉化疗、置管期间是否存在其他合并症以及置管时的血浆D-二聚体含量为影响PICC置管患者发生导管相关血栓的危险因素，最终应用上述风险因素构建列线图预测模型，其C-index指数为0.688，拟合曲线和校正后地拟合曲线均位于10%的误差范围内。
      结论  结合穿刺技术、既往治疗，合并症以及D二聚体等因素所构建的列线图可以较准确的预测PICC相关血栓形成的风险，为临床诊疗工作的开展提供一定的理论基础和数据支持。

     

    Abstract:
      Objective  To explore the risk of incidence of catheter-related thrombosis in cancer patients receiving chemotherapy using nomogran.
      Methods  We retrospectively evaluated 286 patients with malignant tumor who needed PICC insertion at the First Affiliated Hospital of Xi'an Jiaotong University between December 2014 and December 2015. Potential risk factors were included in the least absolute shrinkage and selection operator (LASSO) regression analysis to finally build a nomogram to predict the risk of PICC-related thrombosis.
      Results  A total of 286 patients who needed PICC insertion were analyzed, among whom 72 experienced PICC-related thrombosis. Twenty-seven potential thrombosis-related risk factors were included in the LASSO regression analysis. The results indicated that the use of ultrasound guidance during insertion, previous chemotherapy, other catheter-related complications, and plasma Ddimer were the risk factors of PICC related thrombosis. Thus, these four risk factors were applied to the nomogram model. Further, the nomogram prediction model yielded a C-index of 0.688 and the adjusted fitting curve was located in the error range of 10%.
      Conclusions  Combined with puncture technology, previous chemotherapy history, complications, and D-dimer level constituted the nomogram prediction model for PICC-related thrombosis which had a good accuracy.

     

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