Risk stratification of in-hospital VTE associated with urinary cancer

Zhaoyang li, Huitang Yang, Yandong Cai,Zhan Jiang, Guoju Fan, Kaiqiang Wang, Bo Chen,Hongwei Zhang,Hailong Hu, Yankui Li

crossref(2024)

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摘要
Abstract Objective:The aim of this study is to establish a risk prediction model for VTE in patients with urologic cancer by retrospectively analyzing the clinical data of patients with urologic cancer, and to provide a clinical basis for formulating a risk stratification method for in-hospital VTE in accordance with the characteristics of patients with urologic cancer. Methods:The hospitalized patients with urologic malignancies who met the inclusion criteria in the Department of Urology, from September 2022 to October 2023 were summarized and analyzed. Among them, 51 patients were in the VTE group, and 153 patients without VTE were in the control group. The clinical data of all patients were collected, including general information of patients, laboratory tests on admission, imaging data and surgical data. SPSS25.0 was used to conduct Logistic regression analysis of the data to determine the risk factors of VTE in patients with urologic malignant tumors. According to the results of multivariate Logistic regression analysis, the risk prediction model of VTE in patients with malignant tumors was established, the Receiver Operating Characteristic curve (ROC) was drawn, and its predictive value was evaluated. Results:A total of 204 patients were included in this study, including 29 patients with kidney cancer (14.23%), 10 patients with renal pelvis and ureter cancer (4.90%), 128 patients with bladder cancer (62.75%), and 37 patients with prostate cancer (18.14%). Univariate Logistic regression results showed that, There were significant differences in age, gender, BMI, Caprini grade, history of varicose veins, surgical treatment, plasma D-Dimmer, activated partial thromboplastin time (APTT), prothrombin time (PT), and hemoglobin (Hb) between the VTE group and the non-VTE group (P < 0.05). The results of multivariate Logistic regression showed that Caprini grade, plasma D-dimer, prothrombin, hemoglobin, and surgical treatment were confirmed by statistical analysis as independent risk factors for lower extremity deep venous thrombosis in patients with urinary system malignant tumors. Based on the results, the corresponding prediction model can be proposed to evaluate the risk of in-hospital VTE in patients with urinary system cancer: Y=8.548+0.243×X1-0.419×X2+0.682×X3-0.05×X4+1.41×X5 (X1= D-dimer, X2= prothrombin time, X3=Caprini score, X4 = hemoglobin level (g/L), X5= surgical treatment). The area under the curve of the risk prediction model was 0.913 (P < 0.01), with a sensitivity of 0.745 and a specificity of 0.96. Conclusions: (1) High Caprini score, elevated plasma D-dimer level, shortened prothrombin time, anemia and surgical treatment are independent risk factors for VTE in patients with urologic cancer. When such conditions are found, high attention should be paid to the possibility of VTE and preventive measures should be taken in time. (2) On the basis of Caprini risk assessment model, the levels of plasma D-dimer, prothrombin, hemoglobin and surgical conditions were added to further improve the performance of Caprini risk assessment model, so as to prevent the occurrence of in-hospital VTE in urological malignant tumors early and accurately and reduce the incidence of VTE and mortality.
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