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Risk Assessment of Deep‐Vein Thrombosis After Acute Stroke: a Prospective Study Using Clinical Factors

机译:急性中风后深静脉血栓形成的风险评估:一项使用临床因素的前瞻性研究

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Summary Aims Deep‐vein thrombosis ( DVT ) represents a serious complication in acute stroke patients with pulmonary embolus ( PE ) as a potential outcome. Prediction of DVT may help with formulating a proper prevention strategy. To assess of the risk of deep venous thrombosis ( DVT ) in acute stroke patients, we developed and validated a clinical score in a cohort study. Methods Incidence of Deep Venous Thrombosis after Acute Stroke in China ( INVENT ‐China) is a multicenter prospective cohort study. The potential predictive variables for DVT at baseline were collected, and the presence of DVT was evaluated using ultrasonography on the 14 ± 3 days. Data were randomly assigned to either a training data set or a test data set. Multivariate logistic regression analysis was used to develop risk scores to predict DVT in the training data set and the area under the receiver operating characteristic curve to validate the score in the test data set. Results From 2006–2007, 862 hospital‐based acute stroke patients were enrolled in China. The overall incidence of DVT after acute stroke within two weeks was 12.4% (95% CI 10.3–14.7%). A seven‐point score derived in the training data set (age [≥65 years = 1], sex [female gender = 1]), obesity [ BMI ≥ 25 kg/m2 = 1], active cancer [yes = 2], stroke subtype [cerebral hemorraghe = 1], muscle weakness [≥2 on Lower limb NIHSS score = 1] was highly predictive of 14‐day risk of DVT (c statistic = 0.70, 95% CI , 0.64–0.76, P Conclusions This clinical score may help identify acute stroke patients with high risk of DVT . In addition, it also serves as a platform to develop further models of DVT prediction in stroke patients based on clinical factors.
机译:总结目的深静脉血栓形成(DVT)代表急性卒中合并肺栓塞(PE)的严重并发症。 DVT的预测可能有助于制定适当的预防策略。为了评估急性中风患者深静脉血栓形成(DVT)的风险,我们在一项队列研究中制定并验证了临床评分。方法中国急性卒中后深静脉血栓的发生率是一项多中心的前瞻性队列研究。收集基线时DVT的潜在预测变量,并在14±3天使用超声检查评估DVT的存在。将数据随机分配给训练数据集或测试数据集。使用多元逻辑回归分析来制定风险评分,以预测训练数据集中的DVT,并通过接收器工作特性曲线下的面积来验证测试数据集中的评分。结果2006-2007年,中国共入院862例急性卒中患者。急性中风后两周内DVT的总发生率为12.4%(95%CI为10.3-14.7%)。训练数据集得出的七分得分(年龄[≥65岁= 1],性别[女性性别= 1]),肥胖症[BMI≥25 kg / m2 = 1],活动性癌症[是= 2],脑卒中亚型[脑出血= 1],肌肉无力[下肢NIHSS评分≥2= 1]可以高度预测DVT 14天的风险(c统计= 0.70,95%CI,0.64–0.76,P结论评分可以帮助识别具有DVT高风险的急性卒中患者,此外,它还可以作为一个平台,根据临床因素开发DVT预测模型。

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