Comparison and screening of different risk assessment models for deep vein thrombosis in patients with solid tumors

被引:0
作者
Meng-meng Wang
Xiao-juan Qin
Xiao-xiao He
Meng-jun Qiu
Gang Peng
Sheng-li Yang
机构
[1] Huazhong University of Science and Technology,Division of Gastroenterology, Liyuan Hospital, Tongji Medical College
[2] Huazhong University of Science and Technology,Department of Ultrasound, Union Hospital, Tongji Medical College
[3] Hubei Province Key Laboratory of Molecular Imaging,Cancer Center, Union Hospital, Tongji Medical College
[4] Huazhong University of Science and Technology,undefined
来源
Journal of Thrombosis and Thrombolysis | 2019年 / 48卷
关键词
DVT; Pauda; Khorana; Solid tumor; Risk prediction;
D O I
暂无
中图分类号
学科分类号
摘要
To increase the detection rate of deep vein thrombosis (DVT) and to compare the predictive value of four different risk assessment scales (Caprini, Autar, Pauda, and Khorana scales) for DVT in patients with solid tumors by the receiver operating curve (ROC). A total of 361 patients with all kinds of malignant solid tumors, who accepted anti-tumor therapy in the cancer center between March 3, 2015 to April 13, 2018, were assigned to a group of 230 cases diagnosed with DVT and a control group of 131 cases without DVT. Data were recorded and summarized, and the predictive value of the above four risk assessment scales for DVT in solid tumor patients was compared based on the area under the ROC curve (AUC). The AUC values determined for the Caprini, Autar, Pauda, and Khorana scales were (0.631 ± 0.030), (0.686 ± 0.028), (0.654 ± 0.029), and (0.599 ± 0.032), respectively; maximum sensitivity, specificity, and Youden index were 80.9% for Khorana, 86.3% for Caprini, and 29.6% for Autar scale, respectively. We found no statistically significant differences in the AUC values between Autar and Caprini, Autar and Khorana, as well as Khorana and Pauda (p > 0.05). However, the AUC differences between Autar and Pauda, Caprini and Khorana, as well as Caprini and Pauda were statistically significant (p < 0.05). All four risk assessment models showed some value in the risk prediction of DVT in patients with solid tumors, but every model also exhibited its own restrictions; maximum sensitivity, specificity, and Youden index were 80.9% for Khorana, 86.3% for Caprini, and 29.6% for Autar scale, respectively. We confirmed that the detection rate can be improved by modifying the BMI cut-off value of the scale or by combining appropriate scales.
引用
收藏
页码:292 / 298
页数:6
相关论文
共 50 条
  • [1] Comparison and screening of different risk assessment models for deep vein thrombosis in patients with solid tumors
    Wang, Meng-meng
    Qin, Xiao-juan
    He, Xiao-xiao
    Qiu, Meng-jun
    Peng, Gang
    Yang, Sheng-li
    JOURNAL OF THROMBOSIS AND THROMBOLYSIS, 2019, 48 (02) : 292 - 298
  • [2] Deep vein thrombosis screening and risk factors in a high-risk trauma population
    Michetti, Christopher P.
    Franco, Elizabeth
    Coleman, Jonathan
    Bradford, Anna
    Trickey, Amber W.
    JOURNAL OF SURGICAL RESEARCH, 2015, 199 (02) : 545 - 551
  • [3] The Risk Factors for Preoperative and Postoperative Deep Vein Thrombosis in Surgical Patients
    Irmak, Burcin
    Karadag, Mevlude
    Emre, Nihal Yildiz
    CLINICAL AND EXPERIMENTAL HEALTH SCIENCES, 2022, 12 (01): : 120 - 127
  • [4] DETERMINATION OF DEEP VEIN THROMBOSIS RISK IN PATIENTS STAYING IN AN ORTHOPEDICS AND TRAUMATOLOGY CLINIC
    Kaya, Cigdem
    Bilik, Ozlem
    Solmaz, Perihan
    JOURNAL OF BASIC AND CLINICAL HEALTH SCIENCES, 2023, 7 (01): : 235 - 244
  • [5] Comparative study of two models predicting the risk of deep vein thrombosis progression in spinal trauma patients after operation
    Lai, Jiaxin
    Wu, Shiyang
    Fan, Ziwei
    Jia, Mengxian
    Yuan, Zongjie
    Yan, Xin
    Teng, Honglin
    Zhuge, Linmin
    CLINICAL NEUROLOGY AND NEUROSURGERY, 2024, 236
  • [6] The necessity of routine screening for deep vein thrombosis before surgery
    Endoh, Hideki
    Shiratori, Kazuaki
    Horigome, Miki
    Uematsu, Dai
    Takehana, Takuo
    Sakamoto, Taro
    Fukushima, Kazuyuki
    Ishige, Hiroyuki
    Watanabe, Hitoshi
    Yazaki, Yoshikazu
    ANNALS OF MEDICINE AND SURGERY, 2022, 77
  • [7] Correlation of Inflammation and Coagulation Markers with the Incidence of Deep Vein Thrombosis in Cancer Patients with High Risk of Thrombosis
    Setiawan, Budi
    Budianto, Widi
    Sukarnowati, Tri Wahyu
    Rizky, Daniel
    Pangarsa, Eko Adhi
    Santosa, Damai
    Setiabudy, Rahajuningsih Dharma
    Suharti, Catharina
    INTERNATIONAL JOURNAL OF GENERAL MEDICINE, 2022, 15 : 6215 - 6226
  • [8] Risk Factors and Impact on Outcomes of Lung Cancer Patients Concurrent with Deep Vein Thrombosis
    Jin, Yi-fan
    Ye, Ye-qiu
    Jin, Yu-jia
    Zhu, Xin-yun
    Sha, Min
    Liu, Rui
    Chen, Cheng
    CANCER CONTROL, 2022, 29
  • [9] Preoperative incidence and risk factors of deep vein thrombosis in patients with an isolated patellar fracture
    Weijie Yang
    Haicheng Wang
    Qun Wei
    Kai Ding
    Yuxuan Jia
    Chao Li
    Yanbin Zhu
    Wei Chen
    BMC Musculoskeletal Disorders, 23
  • [10] The risk factor of preoperative deep vein thrombosis in patients undergoing total knee arthroplasty
    Wakabayashi, Hiroki
    Hasegawa, Masahiro
    Niimi, Rui
    Yamaguchi, Toshio
    Naito, Yohei
    Sudo, Akihiro
    JOURNAL OF ORTHOPAEDIC SCIENCE, 2017, 22 (04) : 698 - 702