| 刘要先,李博,孟杨海,等.下肢动脉硬化闭塞病人介入术后并发 DVT的风险预测列线图模型构建及验证[J].安徽医药,2024,28(1):100-104. |
| 下肢动脉硬化闭塞病人介入术后并发 DVT的风险预测列线图模型构建及验证 |
| Construction and validation of a nomogram model for the risk prediction of DVT after interventional therapy in patients with lower limb arteriosclerotic occlusion |
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| DOI：10.3969/j.issn.1009-6469.2024.01.021 |
| 中文关键词: 血管成形术 手术后并发症 静脉血栓形成 闭塞性动脉硬化 下肢 风险因素 列线图模型 |
| 英文关键词: Angioplasty Postoperative complications Venous thrombosis Arteriosclerosis occlusive Lower extremity Risk factors Nomogram model |
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| 中文摘要: |
| 目的探讨下肢动脉硬化闭塞病人介入术后并发深静脉血栓( DVT)的风险因素，并构建 DVT风险预测列线图模型及进行验证。方法回顾性分析 2018年 6月至 2022年 5月在漯河市中心医院进行经皮腔内介入术治疗的 374例下肢动脉硬化闭塞病人的临床资料，根据术后是否并发 DVT而将病人分为并发 DVT组与未并发 DVT组。对比两组一般资料，采用多因素 lo- gistic回归分析法分析下肢动脉硬化闭塞介入术后并发 DVT的危险因素，并利用 R软件与 rms程序构建 DVT风险预测列线图模型，且应用 caret程序包通过 Bootstrap法对其进行内部验证，计算模型一致性指数( C-index)，并绘制受试者操作特征( ROC)曲线评价该模型的预测效能。结果 374例下肢动脉硬化闭塞病人介入术后 3个月内， DVT并发率为 9.63%(36/374)；并发 DVT组年龄 ≥60岁占比、完全闭塞占比、术后卧床时间 ≥3 d占比及总胆固醇( TC)、三酰甘油( TG)、低密度脂蛋白胆固醇( LDLC)、纤维蛋白原( FIB)、 D-二聚体( D-D)、血小板计数( PLT)均高于未并发 DVT组［ 69.44%(25/36)比 50.59%(171/338)、 41.67%(15/36)比 25.44%(86/338)、 58.33%(21/36)比 22.19%(75/338)、(4.96±1.02)mmol/L比( 4.63±0.94)mmol/L、(2.09±0.26)mmol/L比( 1.81±0.31)mmol/L、(3.65±0.54)mmol/L比( 3.47±0.51)mmol/L、(3.45±0.62)g/L比( 3.11±0.54)g/L、(0.67±0.11)mg/L比( 0.38±0.06)mg/L、(246.85±42.74)×109/L比( 205.16±39.68)×109/L］(P<0.05)凝血酶时间( TT)低于未并发 DVT组［( 15.16±3.11)s比(16.33±3.14)s］(P<0.05)；多因素 logistic回归分析结果显示年龄 ≥60术后卧床时间 ≥3 d、TG、FIB、D-D、PLT均是下肢动脉硬化闭塞介入术后并发 DVT的危险因素( P<0.05)；基于多因素 logistic回归分析结果而构建下肢动脉硬化闭塞介入术后并发 DVT的风险预测列线图模型，其校正曲线结果显示标准曲线与校准预测曲线具有良好的贴合度；该模型 C-index为 0.88(0.81~ 岁、0.89)ROC曲线下面积为 0.85［95%CI:(0.78，0.91)Z=9.54，P<0.001］。结论基于年龄、术后卧床时间、 TG、FIB、D-D、PLT构动脉硬化闭塞病人介入术后并发 DVT风测列线图模型具有较好的预测能力与区分能力，对临床筛选高风险人建的下肢，险预，群具有较高的指导价值。 |
| 英文摘要: |
| Objective To investigate the risk factors for deep venous thrombosis (DVT) after interventional surgery in patients withlower limb arteriosclerotic occlusion and to construct and verify a risk prediction nomogram model for DVT.Methods The clinical da- ta of 374 patients with lower limb arteriosclerotic occlusion who underwent percutaneous transluminal interventional therapy at LuoheCentral Hospital from June 2018 to May 2022 were retrospectively analyzed, and the patients were divided into the DVT group and non-DVT group according to whether the DVT was concomitant after surgery. The general data of the two groups were compared, and therisk factors for DVT after interventional surgery with lower limb arteriosclerotic occlusion were analyzed by multivariate logistic regres-sion analysis. R software and the rms program were used to construct a nomogram model for DVT risk prediction, and the caret package was used to verify the model by the bootstrap method, calculate the model consistency index (c-index), and plot the receiver operating characteristic (ROC) curve to evaluate the prediction efficiency of the model.Results The complication rate of DVT was 9.63% (36/374) in 374 patients with lower limb arteriosclerotic occlusion within 3 months of interventional surgery. The proportion of age ≥ 60years, the proportion of total occlusion, the proportion of postoperative bed-rest time ≥ 3 d, and the total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), fibrinogen (FIB), D-dimer (D-D), and platelet count (PLT) in the DVT group were higher than those in the non DVT group [69.44% (25/36) vs.50.59% (171/338), 41.67% (15/36) vs. 25.44% (86/338), 58.33% (21/36) vs. 22.19% (75/338), (4.96±1.02) mmol/L vs. (4.63±0.94) mmol/L, (2.09±0.26) mmol/L vs. (1.81±0.31) mmol/L, (3.65±0.54) mmol/L vs. (3.47±0.51) mmol/L, (3.45±±0.62) g/L vs. (3.11±0.54) g/L, (0.67±0.11) mg/L vs. (0.38±0.06) mg/L, (246.85±42.74) ×109/L vs. (205.16± 39.68) ×109/L] (P < 0.05), and thrombin time (TT) was lower than that in the non-DVT group [(15.16±3.11) s vs. (16.33±3.14) s] (P < 0.05). Multivariate logistic regression analysis showed that age ≥ 60 years, postoperative bed-rest time ≥ 3 d, TG, FIB, D-D and PLT were risk factors for DVT after intervention for lower limb arteriosclerosis occlusion (P < 0.05). Based on the results of multivariate lo-gistic regression analysis, the nomogram model for risk predicting the complication of DVT after lower extremity arteriosclerosis occlu-sion intervention was constructed, and the result of the calibration curve showed that the standard curve and the calibration predictioncurve had a good fit, and the C-index of the model was 0.88 (0.81-0.89), and the area under the ROC curve was 0.85 [95%CI: (0.78, 0.91), Z=9.54, P < 0.001].Conclusion The nomogram model for predicting the risk of DVT after interventional surgery in patientswith lower limb arteriosclerotic occlusion based on age, postoperative bed-time, TG, FIB, D-D and PLT has good prediction and differ- entiation abilities, and has high guiding value for the clinical screening of high-risk groups. |
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