Predicting the occurrence of venous thromboembolism: construction and verification of risk warning model

被引:7
|
作者
Shen, Chen [1 ]
Ge, Binqian [2 ]
Liu, Xiaoqin [1 ]
Chen, Hao [3 ]
Qin, Yi [1 ]
Shen, Hongwu [1 ]
机构
[1] Nantong Univ, Dept Nursing, Affiliated Hosp, 20 Xisi Rd, Nantong City 226000, Jiangsu, Peoples R China
[2] Suzhou Vocat Hlth Coll, Sch Nursing, 28 Kehua Rd, Suzhou 215009, Jiangsu, Peoples R China
[3] Nantong Univ, Dept Informat, Affiliated Hosp, 20 Xisi Rd, Nantong City 226000, Jiangsu, Peoples R China
关键词
Venous thromboembolism; Risk factors; Caprini scale; Logistic regression analysis; Predictive model; DEEP-VEIN THROMBOSIS; PULMONARY-EMBOLISM; HOME TREATMENT; CANCER; TRENDS; EPIDEMIOLOGY; IMPROVE; BURDEN;
D O I
10.1186/s12872-020-01519-9
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
BackgroundThe onset of venous thromboembolism is insidious and the prognosis is poor. In this study, we aimed to construct a VTE risk warning model and testified its clinical application value.MethodsPreliminary construction of the VTE risk warning model was carried out according to the independent risk warning indicators of VTE screened by Logistic regression analysis. The truncated value of screening VTE was obtained and the model was evaluated. ROC curve analysis was used to compare the test of Caprini risk assessment scale and VTE risk warning model. The cut-off value of the VTE risk warning model was used to evaluate the test effectiveness of the model for VTE patients with validation data set.ResultsThe VTE risk warning model is p=e(x) / (1+ e(x)), x=-4.840+2.557 center dot X-10(1)+1.432 center dot X-14(1)+2.977 center dot X-15(1)+3.445 center dot X-18(1)+1.086 center dot X-25(1)+0.249 center dot X-34+0.282 center dot X-41. ROC curve results show that: AUC (95%CI), cutoff value, sensitivity, specificity, accuracy, Youden index, Caprini risk assessment scale is 0.596 (0.552, 0.638), 5, 26.07, 96.50, 61.3%, 0.226, VTE risk warning model is 0.960 (0.940, 0.976), 0.438, 92.61, 91.83, 92.2%, 0.844, respectively, with statistically significant differences (Z=14.521, P<0.0001). The accuracy and Youden index of VTE screening using VTE risk warning model were 81.8 and 62.5%, respectively.ConclusionsVTE risk warning model had high accuracy in predicting VTE occurrence in hospitalized patients. Its test performance was better than Caprini risk assessment scale. It also had high test performance in external population.
引用
收藏
页数:9
相关论文
共 50 条
  • [21] Predicting Venous Thromboembolism Recurrence Risk in Patients with Cancer: A Validation Study
    Louzada, Martha L.
    Bose, Gauruv
    Cheung, Andrew
    Chin-Yee, Benjamin H.
    Wells, Simon
    Wells, Philip S.
    BLOOD, 2012, 120 (21)
  • [22] A nomogram predicting the risk of venous thromboembolism in patients following urologic surgeries
    Wei, Mengchao
    Yang, Wenjie
    Qiao, Yi
    Ma, Lin
    Xu, Weifeng
    Dong, Jie
    SCIENTIFIC REPORTS, 2025, 15 (01):
  • [23] Predicting the Risk of Recurrent Venous Thromboembolism: Current Challenges and Future Opportunities
    Stevens, Hannah
    Peter, Karlheinz
    Tran, Huyen
    McFadyen, James
    JOURNAL OF CLINICAL MEDICINE, 2020, 9 (05)
  • [24] A nomogram predicting venous thromboembolism risk in primary liver cancer patients
    Lei, Haike
    Li, Xiaosheng
    Hu, Zuhai
    Xu, Qianjie
    Li, Qingdong
    Zhou, Rong
    Yu, Qianwen
    Xiao, Jing
    JOURNAL OF THROMBOSIS AND THROMBOLYSIS, 2025, 58 (01) : 145 - 156
  • [25] Predicting Risk of Venous Thromboembolism in Multiple Myeloma: The Impede VTE Score
    Sanfilippo, Kristen M.
    Luo, Suhong
    Wang, Tzu-Fei
    Wildes, Tanya
    Mikhael, Joseph
    Keller, Jesse W.
    Thomas, Theodore S.
    Carson, Kenneth R.
    Gage, Brian F.
    BLOOD, 2018, 132
  • [26] Predicting the risk of venous thromboembolism during neoadjuvant therapy for oesophagogastric cancer
    Calabrese, Michele
    Chmelo, Jakub
    Prasad, Pooja
    Brown, Joshua
    Wallace, Lauren
    Phillips, Alexander
    BRITISH JOURNAL OF SURGERY, 2021, 108
  • [27] Risk of Venous Thromboembolism
    Gundert-Remy, Ursula
    Stammschulte, Thomas
    DEUTSCHES ARZTEBLATT INTERNATIONAL, 2011, 108 (45): : 768 - 768
  • [28] 3D-PAST: Risk Assessment Model for Predicting Venous Thromboembolism in COVID-19
    Lee, Yi
    Jehangir, Qasim
    Lin, Chun-Hui
    Li, Pin
    Sule, Anupam A.
    Poisson, Laila
    Balijepally, Venugopal
    Halabi, Abdul R.
    Patel, Kiritkumar
    Krishnamoorthy, Geetha
    Nair, Girish B.
    JOURNAL OF CLINICAL MEDICINE, 2022, 11 (14)
  • [29] Predicting risk of venous thromboembolism in hospitalized cancer patients: Utility of a risk assessment tool
    Patell, Rushad
    Rybicki, Lisa
    McCrae, Keith R.
    Khorana, Alok A.
    AMERICAN JOURNAL OF HEMATOLOGY, 2017, 92 (06) : 501 - 507
  • [30] Construction of nomogram model for risk of venous thromboembolism after spine surgery based on thromboelastography and coagulation indices
    He, Yongtao
    Wang, Zhen
    Zheng, Xiang
    Zhang, Xunmeng
    Guo, Lianjin
    FRONTIERS IN MEDICINE, 2024, 11