Li Zongxuan, Liu Xiangdong, Li Liang, Cao Pengkai, Zhang Guanyu, Jiao Zhipeng, Wang Fengkai, Hao Qingchun, Li Yunsong, Zhang Yanrong
Department of Vascular Surgery, the Third Hospital of Hebei Medical University, Shijiazhuang, China.
Front Surg. 2023 Mar 31;10:1148024. doi: 10.3389/fsurg.2023.1148024. eCollection 2023.
To analyze the risk factors of lower extremity deep venous thrombosis (DVT) detachment in orthopedic patients, and to establish a risk nomogram prediction model.
The clinical data of 334 patients with orthopedic DVT admitted to the Third Hospital of Hebei Medical University from January 2020 to July 2021 were retrospectively analyzed. General statistics included gender, age, BMI, thrombus detachment, inferior vena cava filter window type, filter implantation time, medical history, trauma history, operation, use of tourniquet, thrombectomy, anesthesia mode, anesthesia grade, operative position, blood loss during operation, blood transfusion, immobilization, use of anticoagulants, thrombus side, thrombus range, D-dimer content before filter implantation and during removal of inferior vena cava filter. Logistic regression was used to perform univariate and multivariate analysis on the possible factors of thrombosis detachment, screen out independent risk factors, establish a risk nomogram prediction model by variables, and internally verify the predictability and accuracy of the model.
Binary logistic regression analysis showed that Short time window filter (OR = 5.401, 95% CI = 2.338-12.478), lower extremity operation (OR = 3.565, 95% CI = 1.553-8.184), use of tourniquet (OR = 3.871, 95% CI = 1.733-8.651), non-strict immobilization (OR = 3.207, 95% CI = 1.387-7.413), non-standardized anticoagulation (OR = 4.406, 95% CI = 1.868-10.390), distal deep vein thrombosis (OR = 2.212, 95% CI = 1.047-4.671) were independent risk factors for lower extremity DVT detachment in orthopedic patients ( < 0.05). Based on these six factors, a prediction model for the risk of lower extremity DVT detachment in orthopedic patients was established, and the risk prediction ability of the model was verified. The C-index of the nomogram model was 0.870 (95% CI: 0.822-0.919). The results indicate that the risk nomogram model has good accuracy in predicting the loss of deep venous thrombosis in orthopedic patients.
The nomogram risk prediction model based on six clinical factors, including filter window type, operation condition, tourniquet use, braking condition, anticoagulation condition, and thrombosis range, has good predictive performance.
分析骨科患者下肢深静脉血栓（DVT）脱落的危险因素，并建立风险列线图预测模型。
回顾性分析2020年1月至2021年7月在河北医科大学第三医院收治的334例骨科DVT患者的临床资料。一般统计指标包括性别、年龄、BMI、血栓脱落情况、下腔静脉滤器窗口类型、滤器植入时间、病史、外伤史、手术、止血带使用情况、取栓术、麻醉方式、麻醉分级、手术体位、术中出血量、输血情况、制动情况、抗凝剂使用情况、血栓部位、血栓范围、滤器植入前及取出下腔静脉滤器时的D-二聚体含量。采用Logistic回归对血栓脱落的可能因素进行单因素和多因素分析，筛选出独立危险因素，通过变量建立风险列线图预测模型，并对模型的预测性和准确性进行内部验证。
二元Logistic回归分析显示，短时间窗口滤器（OR = 5.401，95%CI = 2.338 - 12.478）、下肢手术（OR = 3.565，95%CI = 1.553 - 8.184）、止血带使用（OR = 3.871，95%CI = 1.733 - 8.651）、制动不严格（OR = 3.207，95%CI = 1.387 - 7.413）、抗凝不规范（OR = 4.406，95%CI = 1.868 - 10.390）、远端深静脉血栓（OR = 2.212，95%CI = 1.047 - 4.671）是骨科患者下肢DVT脱落的独立危险因素（P < 0.05）。基于这六个因素，建立了骨科患者下肢DVT脱落风险预测模型，并验证了模型的风险预测能力。列线图模型的C指数为0.870（95%CI：0.822 - 0.919）。结果表明，风险列线图模型在预测骨科患者深静脉血栓脱落方面具有良好的准确性。
基于滤器窗口类型、手术情况、止血带使用、制动情况、抗凝情况和血栓范围六个临床因素的列线图风险预测模型具有良好的预测性能。
