Risk Factors and Nomogram Prediction Model for Isolated Distal Deep Vein Thrombosis After Endovascular Treatment in Acute Ischemic Stroke Patients

Abstract

Objective: To identify independent risk factors for isolated distal deep vein thrombosis (IDDVT) following endovascular treatment (EVT) in patients with acute ischemic stroke (AIS), and to establish a practical and accurate nomogram-based prediction model. Methods: A retrospective review was performed on 263 AIS patients who underwent EVT at the First Affiliated Hospital of Ningbo University between September 2022 and September 2024. Patients were divided into IDDVT and non-IDDVT groups based on postoperative ultrasound findings. Baseline characteristics were compared, and univariate and multivariate logistic regression analyses were conducted to determine independent predictors of IDDVT. A nomogram was constructed based on regression results. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA). Results: Among 263 patients, 45 (17.1%) developed IDDVT. Multivariate logistic regression revealed that elevated D-dimer levels, decreased lower limb muscle strength, prior stroke history, and intracranial hemorrhagic transformation after EVT were independent risk factors (all P < 0.05). The nomogram incorporating these predictors demonstrated excellent discrimination, with an AUC of 0.903 (95% CI: 0.856–0.950), sensitivity of 86.7%, and specificity of 87.2%. Calibration and DCA confirmed good accuracy and clinical applicability. Conclusion: Elevated D-dimer levels, reduced lower limb strength, history of stroke, and postoperative hemorrhagic transformation serve as critical warning indicators for IDDVT after EVT in AIS patients. The nomogram developed in this study provides a high-precision tool for individualized risk prediction, supporting early risk stratification and preventive decision-making in clinical practice.