分析免疫性血小板减少症患者血栓形成的风险因素并建立预测模型

Hui Liang, Lingxue Duan, Manyu Long, Songyuan Tie, Changyan Sun, Sha Ma, Jing Wang, Shuya Wang
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摘要

目的 探讨免疫性血小板减少症(ITP)患者血栓形成的风险因素,并建立风险预测模型,以更好地预测ITP患者血栓形成的风险。方法 我们对2020年1月至2024年6月期间在云南省第一人民医院住院治疗的350名ITP患者进行了回顾性分析。我们记录了所有患者的人口统计学特征和临床数据,分析了ITP患者血栓形成的风险因素,并建立了风险预测模型。结果 逐步逻辑回归分析表明,高补体D-二聚体水平、低PLT和高Padua评分是ITP患者血栓形成的独立危险因素。根据多变量分析,成功建立了血栓风险预测模型;ROC 曲线下面积(AUC)为 0.673(95% CI:0.615-0.730),最大 Youden 指数、敏感性和特异性分别为 0.272、47.0% 和 80.2%。结论 高补体D-二聚体水平、低PLT水平和高帕多瓦评分被证明是ITP患者血栓形成的独立风险因素。我们根据这三个风险因素建立了一个风险预测模型,可在一定程度上预测 ITP 患者血栓形成的风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Risk Factors and the Establishment of a Predictive Model for Thrombosis in Patients with immune thrombocytopenia
Objectives To explore the risk factors for thrombi occurring in patients with immune thrombocytopenia (ITP) and establish a risk prediction model to better predict the risk of thrombosis in patients with ITP. Methods We retrospectively analyzed 350 ITP patients who had been hospitalized in The First People's Hospital of Yunnan Province between January 2020 and June 2024. For all patients, we recorded demographic characteristics and clinical data, analyzed the risk factors for thrombosis in ITP patients and then developed a risk prediction model. Results Stepwise logistic regression analysis indicated that a high complement D- dimer level, a low PLT and a high Padua score were independent risk factors for thrombosis in ITP patients. According to multivariate analysis, a predictive model for thrombus risk was successfully established; the area under the ROC curve(AUC) was 0.673 (95% CI: 0.615-0.730) and the maximum Youden index, sensitivity and specificity were 0.272, 47.0% and 80.2%, respectively. Conclusion A high complement D-dimer level, low PLT level, and a high Padua score were shown to be independent risk factors for thrombosis in ITP patients. We developed a risk prediction model based on these three risk factors that could predict the risk of thrombosis in ITP patients to some extent.
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