多发伤患者深静脉血栓形成风险预测模型的构建及验证研究

doi:10.3761/j.issn.2096-7446.2025.09.007

摘要/Abstract

摘要：

目的探讨多发伤患者深静脉血栓（deep vein thrombosis，DVT）形成的独立危险因素，构建风险预测模型并进行验证研究。方法回顾性选取2022年—2023年北京市某三级甲等医院创伤救治中心收治的425例多发伤患者为研究对象，根据超声结果分为DVT组和非DVT组，通过单因素和二元Logistic回归筛选变量，并通过R软件构建可视化列线图，应用Bootstrap法对模型性能进行内部验证和调整。结果多发伤患者DVT发生率为26.82%，Logistic回归分析显示年龄、合并骨盆髋臼骨折、合并下肢骨折、输血、24~48 h纤维蛋白降解产物>5 μg/ml是DVT发生的独立危险因素。基于以上因素构建预测模型并进行验证，AUC为0.777，Brier评分为0.049，灵敏度为0.728，特异度为0.704。验证集中预测DVT的AUC为0.749，Brier评分为0.070，灵敏度为0.553，特异度为0.826。结论该研究提供了多发伤患者DVT风险预测工具，指标可通过信息系统自动提取，可为早期筛查多发伤DVT高危患者提供依据。

关键词: 多发伤, 深静脉血栓, 风险预测模型, 危险因素

Abstract:

Objective To explore the independent risk factors for deep vein thrombosis（DVT） in patients with multiple injuries，develop a risk prediction model for DVT and evaluate the effect. Methods By retrospective analysis method，425 multiple trauma patients from a tertiary hospital trauma center in Beijing from 2022 to 2023 were collected，and the patients were divided into DVT and non-DVT groups according to ultrasound results，and the variables were screened by univariate and binary logistic regression analysis. An visualized nomogram was constructed by R software，and the Bootstrap method was applied for the internal validation and model adjustment. Results The incidence of DVT in patients with multiple injuries in this study was as high as 26.82%. Logistic regression analysis showed that age，combined pelvic and acetabular fracture，combined lower extremity fracture，blood transfusion，and fibrinogen degradation products（FDP）>5 ug/ml within 24~48 h of admission were the independent risk factors for the occurrence of DVT. A risk prediction model for DVT in patients with multiple trauma was constructed and evaluated based on the above five factors，which predicted DVT with an AUC of 0.777，a Brier score of 0.049，a sensitivity of 0.728，and a specificity of 0.704. In the validation set，the AUC for predicting DVT was 0.749，the Brier score was0.070，the sensitivity was 0.553，and specificity was 0.826. Conclusion The model constructed in this study provides a simple method to calculate the DVT risk of patients with multiple trauma，and the indicators can be automatically extracted through the information system，providing a reference for early clinical screening of high-risk DVT patients with multiple trauma.

Key words: Multiple Trauma, Deep Vein Thrombosis, Risk Prediction Modeling, Risk Factors

祖路比亚·阿布都, 李婷, 孙丽冰, 陈慧娟. 多发伤患者深静脉血栓形成风险预测模型的构建及验证研究[J]. 中华急危重症护理杂志, 2025, 6(9): 1067-1073.

ABUDU·Zulubiya , LI Ting, SUN Libing, CHEN Huijuan. Development and validation of a predictive model for deep vein thrombosis in patients with multiple trauma[J]. Chinese Journal of Emergency and Critical Care Nursing, 2025, 6(9): 1067-1073.

图/表 6

表1

表2

表3

图1

图2

图3

参考文献 22

[1]	He W, Fu XH, Chen S. Advancing polytrauma care:developing and validating machine learning models for early mortality prediction[J]. J Transl Med, 2023, 21(1):664.
[2]	Wang YH, Wang C, Hu P, et al. China trauma treatment statistics 2019:a national retrospective study based on hospitalized cases[J]. Front Public Health, 2023, 11:1116828.
[3]	黄伟, 许庭珉, 王天兵, 等. 创伤中心医疗质量控制指标专家共识[J]. 北京大学学报(医学版), 2024, 56(3):551-555. doi: 10.19723/j.issn.1671-167X.2024.03.025
	Huang W, Xu TM, Wang TB, et al. Expert consensus on key indicators for quality control in trauma medicine center[J]. J Peking Univ Health Sci, 2024, 56(3):551-555.
[4]	Liu T, Bai XJ. Trauma care system in China[J]. Chin J Traumatol, 2018, 21(2):80-83. doi: S1008-1275(17)30174-8 pmid: 29246656
[5]	Chen HJ, Sun LB, Kong XY. Risk assessment scales to predict risk of lower extremity deep vein thrombosis among multiple trauma patients:a prospective cohort study[J]. BMC Emerg Med, 2023, 23(1):144.
[6]	Roberts L, Rozen T, Murphy D, et al. A preliminary study of intensivist-performed DVT ultrasound screening in trauma ICU patients(APSIT Study)[J]. Ann Intensive Care, 2020, 10(1):122. doi: 10.1186/s13613-020-00739-8 pmid: 32926245
[7]	Peng N, Su L. Progresses in understanding trauma-induced coagulopathy and the underlying mechanism[J]. Chin J Traumatol, 2017, 20(3):133-136. doi: S1008-1275(16)30324-8 pmid: 28554592
[8]	Peng GX, Wang Q, Sun H, et al. Development and prospective validation of a novel risk score for predicting the risk of lower extremity deep vein thrombosis among multiple trauma patients[J]. Thromb Res, 2021, 201:116-122. doi: 10.1016/j.thromres.2021.02.020 pmid: 33662798
[9]	李阳, 李辉, 陈驾君, 等. 多发伤病历与诊断:专家共识(2023版)[J]. 创伤外科杂志, 2023, 25(8):561-568.
	Li Y, Li H, Chen JJ, et al. Chinese expert consensus on medical documentation and diagnosis for multiple trauma (2023 edition)[J]. J Trauma Surg, 2023, 25(8):561-568.
[10]	Riley RD, Snell KI, Ensor J, et al. Minimum sample size for developing a multivariable prediction model:PART Ⅱ- binary and time-to-event outcomes[J]. Stat Med, 2019, 38(7):1276-1296.
[11]	Bassa B, Little E, Ryan D, et al. VTE rates and risk factors in major trauma patients[J]. Injury, 2024, 55(12):111964.
[12]	孙健平, 王鹏飞, 薛汉中, 等. 多发伤患者围手术期深静脉血栓形成的发生及危险因素[J]. 中华创伤骨科杂志, 2019, 21(1):39-43.
	Sun JP, Wang PF, Xue HZ, et al. Incidence and risk factors of intraoperative deep venous thrombosis in patients with multiple injuries[J]. Chin J Orthop Trauma, 2019, 21(1):39-43.
[13]	傅一牧, 荆尧, 李冬冬, 等. 多发伤患者急性下肢深静脉血栓形成的危险因素分析[J]. 上海交通大学学报(医学版), 2019, 39(3):278-281. doi: 10.3969/j.issn.1674-8115.2019.03.010
	Fu YM, Jing Y, Li DD, et al. Risk factors analysis for acute lower deep venous thrombosis in multiple injury patients[J]. J Shanghai Jiao Tong Univ Med Sci, 2019, 39(3):278-281.
[14]	朱晓光, 王石冲, 高婧, 等. 多发伤患者静脉血栓栓塞症列线图预测模型建立的研究[J]. 国际骨科学杂志, 2021, 42(4):241-246.
	Zhu XG, Wang SC, Gao J, et al. A prognostic nomogram model to predict venous thromboembolism in multiple trauma patients[J]. Int J Orthop, 2021, 42(4):241-246.
[15]	Chowdhury S, Alrawaji F, Leenen LPH. Incidence and nature of lower-limb deep vein thrombosis in patients with polytrauma on thromboprophylaxis:a prospective cohort study[J]. Vasc Health Risk Manag, 2021, 17:395-405.
[16]	Wang T, Guo JF, Long YB, et al. Risk factors for preoperative deep venous thrombosis in hip fracture patients:a meta-analysis[J]. J Orthop Traumatol, 2022, 23(1):19. doi: 10.1186/s10195-022-00639-6 pmid: 35391566
[17]	Lee SY, Ro DH, Chung CY, et al. Incidence of deep vein thrombosis after major lower limb orthopedic surgery:analysis of a nationwide claim registry[J]. Yonsei Med J, 2015, 56(1):139-145.
[18]	Qian XL, Ge YP, Luo J. Risk factors for deep vein thrombosis after traumatic lower extremity fracture:a systematic review and meta-analysis[J]. Medicine, 2024, 103(23):e38439.
[19]	吴林沁. 股骨和骨盆骨折患者围术期深静脉血栓形成的危险因素分析[D]. 重庆: 重庆医科大学, 2021.
	Wu LQ. Analysis of risk factors for deep vein thrombosis in Patients with femoral and pelvic fractures during the perioperative period[D]. Chongqing: Chongqing Medical University, 2021.
[20]	王聪, 房延儒, 王兴义, 等. 老年多发伤患者下肢深静脉血栓形成的危险因素研究[J]. 重庆医学, 2024, 53(5):796-800.
	Wang C, Fang YR, Wang XY, et al. Study on risk factors of deep vein thrombosis in the lower extremities of elderly patients with multiple injuries[J]. Chongqing Med J, 2024, 53(5):796-800.
[21]	任飞, 刘锋卫, 李刚. 四肢骨折患儿外周血FIB、FDP、D-二聚体水平与DVT发生的关系[J]. 分子诊断与治疗杂志, 2023, 15(1):124-127.
	Ren F, Liu FW, Li G. Relationship between peripheral blood FIB,FDP,D-dimer levels and occurrence of DVT in children with limb fractures[J]. J Mol Diagn Ther, 2023, 15(1):124-127.
[22]	田丰, 杨家赵, 徐玮, 等. 创伤性四肢骨折患者血清FIB、FDP、D-D和TAT水平与血栓形成的关系[J]. 分子诊断与治疗杂志, 2020, 12(11):1535-1538,1543.
	Tian F, Yang JZ, Xu W, et al. Relationship between serum FIB,FDP,D-D and TAT levels and thrombosis in patients with traumatic limbs fractures[J]. J Mol Diagn Ther, 2020, 12(11):1535-1538,1543.