切开复位钢板内固定治疗胫腓骨骨折后下肢深静脉血栓形成的危险因素分析
易媛 , 古洪基 , 李孟泽
中国现代医学杂志 ›› 2026, Vol. 36 ›› Issue (08) : 103 -109.
切开复位钢板内固定治疗胫腓骨骨折后下肢深静脉血栓形成的危险因素分析
Analysis of risk factors for deep vein thrombosis after open reduction and plate internal fixation in the treatment of tibiofibular fractures
目的 探讨切开复位钢板内固定治疗胫腓骨骨折后下肢深静脉血栓(DVT)形成的危险因素。 方法 选取2022年1月—2025年1月泸州市中医医院收治的127例胫腓骨骨折患者,患者均接受切开复位钢板内固定治疗,根据术后是否出现下肢DVT分为DVT组(36例)和非DVT组(91例)。收集两组患者一般资料,术前取患者外周静脉血,检测生化指标、C反应蛋白(CRP)、纤维蛋白原、活化部分凝血活酶时间(APTT)、D-二聚体。通过多因素逐步Logistic回归模型分析筛选患者术后发生下肢DVT的影响因素,构建列线图预测模型,并评估模型的拟合效果。 结果 DVT组年龄大于非DVT组(P <0.05),受伤至手术时间、术后首次下床活动时间均长于非DVT组(P <0.05),红细胞压积、CRP和D-二聚体水平均高于非DVT组(P <0.05),APTT水平低于非DVT组(P <0.05)。多因素逐步Logistic回归分析结果显示:年龄大[O^R=1.177(95% CI:1.038,1.335)],D-二聚体水平高[O^R=1.032(95% CI:1.020,1.044)]、高红细胞压积[O^R=1.213(95% CI:1.051,1.401)]和术后首次下床活动时间晚[O^R=1.272(95% CI:1.058,1.530)]均为患者术后DVT发生的危险因素(P <0.05),APTT水平高[O^R=0.809(95% CI:0.686,0.953)]为患者术后下肢DVT发生的保护因素(P <0.05)。Bootstrap法表明列线图模型的预测效能良好,平均绝对误差为0.039,该模型的C-index为0.853(95% CI:0.791,0.913),表明其具有较好的判别性能。 结论 该研究构建了包含高龄、术前D-二聚体升高、高红细胞压积及术后首次下床时间延迟等关键因素的列线图预测模型,为临床早期识别高危患者、针对性开展下肢血管超声检查及制订个体化预防策略提供重要工具。
Objective This study aimed to analyze the risk factors for lower extremity deep vein thrombosis (DVT) in patients with tibiofibular fractures after treatment with open reduction and plate internal fixation. Methods The study subjects were 127 patients with tibiofibular fractures admitted to our hospital from January 2022 to January 2025. All patients underwent open reduction and plate internal fixation, and were divided into the DVT group (36 cases) and non-DVT group (91 cases) based on the presence or absence of postoperative lower extremity DVT. General data of patients in both groups were collected. Peripheral venous blood samples were taken before surgery to detect biochemical indicators, C-reactive protein (CRP), fibrinogen (FIB), activated partial thromboplastin time (APTT), and D-dimer. Logistic regression analysis was used to screen for risk factors of postoperative DVT, a nomogram prediction model was constructed, and the fitting effect of the model was evaluated. Results Patients in the DVT group were older than those in the non-DVT group (P < 0.05). The time from injury to surgery and the time to first postoperative ambulation were both longer in the DVT group (P < 0.05). Hematocrit, CRP, and D-dimer levels were higher, while APTT levels were lower in the DVT group compared with the non-DVT group (all P < 0.05). Multivariable stepwise logistic regression analysis showed that older age [O^R = 1.177 (95% CI: 1.038, 1.335) ], higher preoperative D-dimer level [O^R = 1.032 (95% CI: 1.020, 1.044)], higher hematocrit [O^R = 1.213 (95% CI: 1.051, 1.401) ], and delayed first postoperative ambulation [O^R = 1.272 (95% CI: 1.058, 1.530) ] were independent risk factors for postoperative DVT (P < 0.05), whereas higher APTT level [O^R = 0.809 (95% CI: 0.686, 0.953) ] was a protective factor (P < 0.05). Bootstrap validation demonstrated good predictive performance of the nomogram model, with a mean absolute error of 0.039 and a C-index of 0.853 (95% CI: 0.791, 0.913), indicating good discrimination ability. Conclusion A nomogram prediction model incorporating key factors, including advanced age, elevated preoperative D-dimer, increased hematocrit, and delayed first postoperative ambulation, was developed in this study. This model provides an important tool for early identification of high-risk patients, targeted use of lower extremity vascular ultrasound, and the formulation of individualized preventive strategies in clinical practice.
| [1] |
MISHRA J, KUMAR DAS T, GUGLANI K, et al. Single-incision direct lateral approach versus dual-incision approach for distal tibial and fibular fractures[J]. Cureus, 2024, 16(9): e69516. |
| [2] |
FU Y H, LIU P, XU X, et al. Deep vein thrombosis in the lower extremities after femoral neck fracture: a retrospective observational study[J]. J Orthop Surg (Hong Kong), 2020, 28(1): 2309499019901172. |
| [3] |
郑楚荣, 古鹏, 吴文正, 下肢骨折深静脉血栓防治的研究进展[J]. 广州中医药大学学报, 2024, 41(6): 1647-1652. |
| [4] |
ZHANG J N, SHAO Y, ZHOU H M, et al. Prediction model of deep vein thrombosis risk after lower extremity orthopedic surgery[J]. Heliyon, 2024, 10(9): e29517. |
| [5] |
李陶陶, 张雨露, 马丽, 基于XGBoost模型预测下肢骨折患者术后深静脉血栓形成风险的临床研究[J]. 中国骨与关节杂志, 2025, 14(4): 337-342. |
| [6] |
WEI C H, WANG J L, YU P F, et al. Comparison of different machine learning classification models for predicting deep vein thrombosis in lower extremity fractures[J]. Sci Rep, 2024, 14(1): 6901. |
| [7] |
中华医学会外科学分会血管外科学组. 深静脉血栓形成的诊断和治疗指南(第三版)[J]. 中国血管外科杂志(电子版), 2017, 9(4): 250-257. |
| [8] |
郭刚. 小腿前外侧单切口切开复位钢板内固定治疗胫腓骨中下段双骨折[J]. 实用手外科杂志, 2020, 34(2): 217-218. |
| [9] |
ZHENG X, LU X L, CHEN Y B, et al. Ultrasonographic features and risk factors of postoperative lower limb deep venous thrombosis in patients with lower limb fractures[J]. Acta Orthop Belg, 2024, 90(4): 665-671. |
| [10] |
ZHANG H, LI X Y, XIA S B, et al. The effect of different frames filters on the prevention of pulmonary embolism in fracture patients subsequent with deep venous thrombosis on a multicenter prospective observational study[J]. J Vasc Surg Venous Lymphat Disord, 2023, 11(2): 351-356.e1. |
| [11] |
张永政, 王荷晴, 崔立敏. 胫腓骨骨折患者下肢深静脉血栓形成危险因素的Meta分析[J]. 中国老年保健医学, 2024, 22(6): 30-34. |
| [12] |
WANG H, KANDEMIR U, LIU P, et al. Perioperative incidence and locations of deep vein thrombosis following specific isolated lower extremity fractures[J]. Injury, 2018, 49(7): 1353-1357. |
| [13] |
刘瑞婷, 谢素丽, 王珂, 基于梯度提升决策树构建下肢创伤骨折患者术后深静脉血栓风险预测模型[J]. 创伤外科杂志, 2025, 27(7): 523-531. |
| [14] |
LI C, XIE X, ZHENG H T, et al. The effect of intermittent pneumatic compression device combined with low-molecular-weight heparin on the prevention of deep vein thrombosis in elderly patients after femoral neck fracture surgery[J]. Br J Hosp Med (Lond), 2024, 85(10): 1-12. |
| [15] |
唐茁栋, 王明友, 王洪平, 胫骨平台骨折术前下肢深静脉血栓形成列线图预测模型构建与验证[J]. 创伤外科杂志, 2025, 27(1): 43-49. |
| [16] |
WATANABE-KUSUNOKI K, NAKAZAWA D, ISHIZU A, et al. Thrombomodulin as a physiological modulator of intravascular injury[J]. Front Immunol, 2020, 11: 575890. |
| [17] |
CHANG W J, WANG B, LI Q W, et al. Study on the risk factors of preoperative deep vein thrombosis (DVT) in patients with lower extremity fracture[J]. Clin Appl Thromb Hemost, 2021, 27: 10760296211002900. |
| [18] |
JACOBS J W, SHARMA D, STEPHENS L D, et al. Thrombosis risk with haemoglobin C trait and haemoglobin C disease: a systematic review[J]. Br J Haematol, 2024, 204(4): 1500-1506. |
| [19] |
GHORBANZADEH A, ABUD A, LIEDL D, et al. Reduced calf muscle pump function is not explained by handgrip strength measurements[J]. J Vasc Surg Venous Lymphat Disord, 2024, 12(4): 101869. |
| [20] |
高飞, 王根, 王大伟, 胫腓骨骨折下肢深静脉血栓形成的特点与危险因素[J]. 中国矫形外科杂志, 2020, 28(12): 1085-1088. |
| [21] |
洪丽荣, 陈雨佳, 江庆来, 新型血栓四项联合常规凝血指标预测抗磷脂综合征患者血栓形成的价值[J]. 北京大学学报(医学版), 2023, 55(6): 1033-1038. |
| [22] |
董卫兵, 明海武, 任国强, 外周血CRP、ACA、FM联合检测对下肢创伤骨折患者深静脉血栓的预测价值[J]. 中国卫生检验杂志, 2023, 33(13): 1625-1628. |
| [23] |
张利鹏, 屈福锋, 翟英杰, 血小板平均体积/淋巴细胞比值对下肢创伤骨折患者术后发生深静脉血栓的预测价值[J]. 保健医学研究与实践, 2025, 22(3): 68-74. |
| [24] |
苏艳艳, 李娜, 田轩. 股骨颈骨折后下肢深静脉血栓形成的列线图风险预测模型构建[J]. 血管与腔内血管外科杂志, 2025, 11(5): 608-613. |
四川省科技计划项目(2023YFS0137)
/
| 〈 |
|
〉 |