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

摘要:

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。

Abstract:

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.