Department of Neurology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China.
Department of Neurology, Wenzhou Hospital of Traditional Chinese Medicine Affiliated to Zhejiang Chinese Medical University, Wenzhou, 325000, Zhejiang, China.
BMC Geriatr. 2021 Feb 25;21(1):140. doi: 10.1186/s12877-021-02088-y.
Although isolated distal deep vein thrombosis (IDDVT) is a clinical complication for acute ischemic stroke (AIS) patients, very few clinicians value it and few methods can predict early IDDVT. This study aimed to establish and validate an individualized predictive nomogram for the risk of early IDDVT in AIS patients.
This study enrolled 647 consecutive AIS patients who were randomly divided into a training cohort (n = 431) and a validation cohort (n = 216). Based on logistic analyses in training cohort, a nomogram was constructed to predict early IDDVT. The nomogram was then validated using area under the receiver operating characteristic curve (AUROC) and calibration plots.
The multivariate logistic regression analysis revealed that age, gender, lower limb paralysis, current pneumonia, atrial fibrillation and malignant tumor were independent risk factors of early IDDVT; these variables were integrated to construct the nomogram. Calibration plots revealed acceptable agreement between the predicted and actual IDDVT probabilities in both the training and validation cohorts. The nomogram had AUROC values of 0.767 (95% CI: 0.742-0.806) and 0.820 (95% CI: 0.762-0.869) in the training and validation cohorts, respectively. Additionally, in the validation cohort, the AUROC of the nomogram was higher than those of the other scores for predicting IDDVT.
The present nomogram provides clinicians with a novel and easy-to-use tool for the prediction of the individualized risk of IDDVT in the early stages of AIS, which would be helpful to initiate imaging examination and interventions timely.
尽管孤立性远端深静脉血栓形成（IDDVT）是急性缺血性脑卒中（AIS）患者的一种临床并发症，但很少有临床医生重视它，也很少有方法可以预测早期 IDDVT。本研究旨在建立和验证一种用于预测 AIS 患者早期 IDDVT 风险的个体化预测列线图。
本研究纳入了 647 例连续的 AIS 患者，他们被随机分为训练队列（n=431）和验证队列（n=216）。基于训练队列中的逻辑分析，构建了一个预测早期 IDDVT 的列线图。然后使用接受者操作特征曲线（AUROC）和校准图来验证该列线图。
多变量逻辑回归分析显示，年龄、性别、下肢瘫痪、现患肺炎、心房颤动和恶性肿瘤是早期 IDDVT 的独立危险因素；这些变量被整合到列线图中。校准图显示，在训练和验证队列中，预测和实际 IDDVT 概率之间存在可接受的一致性。该列线图在训练和验证队列中的 AUROC 值分别为 0.767（95%CI：0.742-0.806）和 0.820（95%CI：0.762-0.869）。此外，在验证队列中，该列线图预测 IDDVT 的 AUROC 高于其他评分。
本列线图为临床医生提供了一种新颖易用的工具，用于预测 AIS 早期 IDDVT 的个体化风险，这有助于及时进行影像学检查和干预。
