BMC Geriatrics (Feb 2021)

Individualized predictions of early isolated distal deep vein thrombosis in patients with acute ischemic stroke: a retrospective study

  • Hao-Ran Cheng,
  • Gui-Qian Huang,
  • Zi-Qian Wu,
  • Yue-Min Wu,
  • Gang-Qiang Lin,
  • Jia-Ying Song,
  • Yun-Tao Liu,
  • Xiao-Qian Luan,
  • Zheng-Zhong Yuan,
  • Wen-Zong Zhu,
  • Jin-Cai He,
  • Zhen Wang

DOI
https://doi.org/10.1186/s12877-021-02088-y
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 12

Abstract

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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.

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