Hao-Ran Cheng1, Gui-Qian Huang1, Zi-Qian Wu2, Yue-Min Wu1, Gang-Qiang Lin1, Jia-Ying Song3, Yun-Tao Liu1, Xiao-Qian Luan1, Zheng-Zhong Yuan4, Wen-Zong Zhu5, Jin-Cai He6, Zhen Wang7. 1. Department of Neurology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China. 2. Department of Neurology, Wenzhou Hospital of Traditional Chinese Medicine Affiliated to Zhejiang Chinese Medical University, Wenzhou, 325000, Zhejiang, China. 3. School of Mental Health, Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China. 4. Department of Traditional Chinese Medicine, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China. 5. Department of Neurology, Wenzhou Hospital of Traditional Chinese Medicine Affiliated to Zhejiang Chinese Medical University, Wenzhou, 325000, Zhejiang, China. m15990703311@163.com. 6. Department of Neurology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China. hjc@wmu.edu.cn. 7. Department of Neurology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, Zhejiang, China. wangzhen@wzhospital.cn.
Abstract
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
BACKGROUND: 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 AISpatients. METHODS: This study enrolled 647 consecutive AISpatients 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. RESULTS: 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. CONCLUSIONS: 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.
Entities:
Keywords:
Deep vein thrombosis; Nomogram; Prediction; Stroke
Authors: J-P Galanaud; M-A Sevestre; G Pernod; C Genty; S Richelet; S R Kahn; C Boulon; H Terrisse; I Quéré; J-L Bosson Journal: J Thromb Haemost Date: 2017-04-21 Impact factor: 5.824
Authors: Martin Dennis; Peter Sandercock; John Reid; Catriona Graham; Gordon Murray; Graham Venables; Anthony Rudd; Gill Bowler Journal: J Neurol Neurosurg Psychiatry Date: 2011-02-28 Impact factor: 10.154