| 李政阳,洪春波,黄 栋,刘永涛,辛 兵.Caprini血栓风险评分及血清D-D、VEGF、PDGF-B对创伤性骨折患者术后深静脉血栓形成的预测价值及模型构建[J].,2024,(8):1571-1576 |
| Caprini血栓风险评分及血清D-D、VEGF、PDGF-B对创伤性骨折患者术后深静脉血栓形成的预测价值及模型构建 |
| Predictive Value and Model Construction of Caprini Thrombosis Risk Score and Serum D-D, VEGF and PDGF-B for Postoperative Deep Vein Thrombosis in Patients with Traumatic Fracture |
| 投稿时间：2023-10-06 修订日期：2023-10-31 |
| DOI：10.13241/j.cnki.pmb.2024.08.033 |
| 中文关键词: 创伤性骨折 Caprini血栓风险评分 D-D VEGF PDGF-B 深静脉血栓形成 模型构建 |
| 英文关键词: Traumatic fracture Caprini thrombosis risk score D-D VEGF PDGF-B Deep vein thrombosis Model construction |
| 基金项目:江苏省科技厅自然科学基金面上项目（BK20201154） |
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| 中文摘要: |
| 摘要 目的：探讨Caprini血栓风险评分及血清D-二聚体（D-D）、血管内皮生长因子（VEGF）、血小板衍生生长因子B（PDGF-B）对创伤性骨折患者术后深静脉血栓形成（DVT）的预测价值，并构建风险预测模型。方法：选取2019年6月至2022年5月徐州医科大学附属医院收治的216例创伤性骨折住院患者为研究对象，依据术后DVT发生情况分为DVT组（62例）和非DVT组（154例），对比两组Caprini血栓风险评分、血清D-D、VEGF、PDGF-B及临床资料的差异，多因素Logistic回归分析明确DVT的危险因素，建立预测模型，并进行模型的验证，绘制受试者工作特征曲线（ROC）进行效能评估。结果：创伤性骨折患者术后DVT发生率为28.70%。DVT组骨折至入院时间＞24 h患者占比多于非DVT组，凝血酶原时间（PT）、活化部分凝血活酶时间（APTT）、D-D、VEGF、PDGF-B、Caprini血栓风险评分均高于非DVT组（P＜0.05）。多因素Logistic回归分析显示，骨折至入院时间>24 h、血清D-D、VEGF、PDGF-B高水平及Caprini血栓风险评分升高是创伤性骨折患者术后发生DVT的独立危险因素（P＜0.05）。以Logistic回归分析筛选的创伤性骨折患者术后发生DVT的5个独立危险因素，建立预测模型方程：Logit（P）=-0.171 +1.170×骨折至入院时间 +1.041×血清D-D +0.046×血清VEGF +0.100×血清PDGF-B +0.080×Caprini血栓风险评分，内部验证结果显示C-index指数为0.825（95%CI：0.740~0.892），Calibration曲线显示校正曲线与理想曲线趋近重合（P＞0.05）。使用本研究样本进行外部验证：曲线下面积AUC为0.901、灵敏度为0.887、特异度为0.870，显示该模型具有很高的预测效能，明显高于D-D、VEGF、PDGF-B、Caprini血栓风险评分单独应用的预测效能。结论：骨折至入院时间、血清D-D、VEGF、PDG及Caprini血栓风险评分均是创伤性骨折患者术后发生DVT的影响因素，构建的预测模型对DVT的发生具有较好的预测效能。 |
| 英文摘要: |
| ABSTRACT Objective: To explore the predictive value of Caprini thrombosis risk score and serum D-dimer (D-D), vascular endothelial growth factor (VEGF), platelet-derived growth factor B (PDGF-B) for postoperative deep vein thrombosis (DVT) in patients with traumatic fracture, and to construct risk prediction model. Methods: 216 hospitalized patients with traumatic fracture admitted to The Affiliated Hospital of Xuzhou Medical University from June 2019 to May 2022 were selected as the research objects. According to the occurrence of postoperative DVT, they were divided into DVT group (62 cases) and non-DVT group (154 cases). The differences of Caprini thrombosis risk score, serum D-D, VEGF, PDGF-B and clinical data between the two groups were compared. Multivariate Logistic regression analysis was used to identify the risk factors of DVT, the prediction model was established, and the model was validated, and the receiver operating characteristic (ROC) curve was drawn for efficacy evaluation. Results: The occurrence rate of postoperative DVT in patients with traumatic fracture was 28.70%. The proportion of patients in the DVT group with the time from fracture to admission greater than 24 hours were more than those in the non-DVT group, and the prothrombin time (PT), activated partial thromboplastin time (APTT), D-D, VEGF, PDGF-B and Caprini thrombosis risk score were higher than those in the non-DVT group (P<0.05). Multivariate Logistic regression analysis showed that the time from fracture to admission greater than 24 hours, high levels of serum D-D, VEGF, PDGF-B and increased Caprini thrombosis risk score were independent risk factors for the occurrence of postoperative DVT in patients with traumatic fracture (P<0.05). Logistic regression analysis was used to analyze the 5 independent risk factors of the occurrence of postoperative DVT in patients with traumatic fracture, and the prediction model equation was established as follows: Logit (P) =-0.171 +1.170×time from fracture to admission +1.041×serum D-D +0.046×serum VEGF +0.100×serum PDGF-B +0.080×Caprini thrombosis risk score, the internal verification results showed that the C-index count was 0.825 (95%CI: 0.740~0.892), and the Calibration curve showed that the Calibration curve was close to the ideal curve (P>0.05). External validation used this study sample: the area under curve (AUC) was 0.901, the sensitivity was 0.887, and the specificity was 0.870, which showed that the model had high predictive efficiency, it was significantly higher than the predictive efficacy of D-D, VEGF, PDGF-B and caprini thrombus risk score alone. Conclusion: The time from fracture to admission, serum D-D, VEGF, PDG and Caprini thrombosis risk score were the influencing factors of the occurrence of postoperative DVT in patients with traumatic fracture, the constructed prediction model had good predictive efficiency for the occurrence of DVT. |
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