To develop and validate a nomogram to predict the probability of distal deep venous thrombosis (DVT) within first 14 days of stroke onset in patients by using easily obtainable parameters.
This is a retrospective study. The presence of distal DVT was evaluated using ultrasonography within the first 14 days. Data were randomly assigned to either a modelling data set or a validation data set. Univariable and multivariate logistic regression analysis was used to determine risk scores to predict distal DVT in the modelling data set, and nomogram and calibration curve were constructed by R project.
A total of 1620 patients with acute stroke were enrolled in the study. The multivariate analysis revealed that the old age, female gender, haemorrhagic stroke, coronary heart disease, lower limb weakness, a low serum albumin level, and a high D-dimer level are highly predictive of 14-day risk of distal DVT. The AUC of the nomogram to predict the 14-day risk of distal DVT was 0.785 (95% CI, 0.742-0.827) and 0.813 (0.766-0.860) for the modelling cohort and external validation cohort, respectively. Moreover, the calibration of the nomogram showed a nonsignificant Hosmer-Lemeshow test statistic in the modelling (P = 0.876) and validation (P = 0.802) sets. With respect to decision curve analyses, the nomogram exhibited preferable net benefit gains than the staging system across a wide range of threshold probabilities.
The established nomogram displayed a superior performance in terms of predictive accuracy, discrimination capability, and clinical utility, may be helpful for clinicians to identify high-risk groups of distal DVT.

Copyright © 2021. Published by Elsevier B.V.