Abstract:Objective To identify the influencing factors for the occurrence of lower extremity deep vein thrombosis (DVT) in patients recovering from cerebral infarction, and to construct a risk prediction model and validate its predictive effectiveness. Methods A retrospective analysis was conducted on the clinical data of 233 patients recovering from cerebral infarction admitted in the Suzhou Hospital of Anhui Medical University from June 2020 to December 2024. Based on the occurrence of lower extremity DVT, the patients were divided into the DVT group (n=33) and the non-DVT group (n=200). The relevant clinical data and laboratory indicators of the two groups were compared. Univariate and multivariate logistic analysis were used to analyze the influencing factors of lower extremity DVT in patients with cerebral infarction during the recovery period. Based on the independent risk factors screened above, a nomogram prediction model for lower extremity DVT in patients recovering from cerebral infarction was constructed. The receiver operating characteristic (ROC) curve was used to evaluate the discrimination of the nomogram prediction model. Calibration curves and decision curves were drawn to verify and evaluate the consistency and clinical benefits of the nomogram prediction model. Results Compared with the non-DVT group, the DVT group had an older age, a higher proportion of hypertension, elevated platelet-to-lymphocyte ratio (PLR) and mean platelet volume (MPV), lower Barthel index scores, and lower levels of hemoglobin and uric acid (P＜0.05). Multivariate regression analysis showed that high PLR (OR= 1.006, 95%CI: 1.000-1.012, P= 0.033), high MPV (OR= 2.107, 95%CI: 1.422-3.121, P＜0.001), low Barthel index score (OR= 0.954, 95%CI: 0.928-0.981, P= 0.001), and older age (OR= 1.057, 95%CI: 1.003-1.114, P= 0.040) were independent risk factors for the occurrence of lower extremity DVT in patients recovering from cerebral infarction. The area under ROC curve (AUC) of the nomogram prediction model for lower extremity DVT in patients recovering from cerebral infarction constructed based on the above independent risk factors was 0.854, with a sensitivity of 0.758 and a specificity of 0.835. The calibration curve demonstrated good consistency between the predicted value and the actual value of the prediction model (Brier=0.070, P= 0.804). Decision curve analysis showed that the risk threshold ranged from 0 to 0.98, with the nomogram model providing good clinical benefit. Conclusion The nomogram prediction model for lower extremity DVT in patients recovering from cerebral infarction based on PLR, age, MPV and Barthel score demonstrates good predictive performance.