Construction and validation of a prediction model for acute ischemic stroke patients with concomitant deep vein thrombosis

The aim was to investigate the independent risk factors for complications of deep vein thrombosis (DVT) in patients with acute ischemic stroke (AIS), and to establish a nomogram prediction model accordingly. The data of AIS patients in our hospital were collected from January 2021 to December 2023, and single-factor and multifactorial logistic regression analyses were used to determine the independent risk factors for the complication of DVT in patients with AIS and to establish the corresponding nomogram. The receiver operating characteristic curves were plotted the area under the curve was calculated, and the calibration and decision curves were plotted to evaluate the model performance. Five hundred twenty-seven AIS patients were included in the study, and 42 AIS patients were complicated with DVT, with an incidence rate of 7.97%. After univariate and multivariate logistic regression analyses, a total of 5 variables were identified as independent risk factors for the complication of DVT in patients with AIS: age > 70 years (OR, 1.551; 95% CI, 1.189-2.751), diabetes (OR, 2.543; 95% CI, 1.322-4.265), the national institutes of health stroke scale > 16 (OR, 3.124; 95% CI, 1.314-7.003), D-dimer > 0.5 mg/L (OR, 2.303; 95% CI, 1.250-3.645), and fibrinogen > 4 g/L (OR, 1.918; 95% CI, 1.532-6.369). The nomogram constructed in this study for AIS patients with concomitant DVT has good predictive accuracy and helps physicians to intervene in advance in patients at high risk of acute AIS patients with concomitant DVT.