Clinical value of a five-predictor nomogram for lower-extremity deep vein thrombosis after orthopaedic surgery in ICU patients
Xiaomin Zhang, Min Yu, Haimeng Lu, Ping LuObjective
To evaluate the predictive value of a five-predictor nomogram for postoperative lower-extremity deep vein thrombosis (DVT) in orthopedic patients admitted to the intensive care unit (ICU).
Methods
Clinical data from 224 postoperative orthopedic ICU patients admitted between March 2022 and March 2025 were retrospectively analyzed. Patients were divided into a DVT group (n = 73) and a non-DVT group (n = 151). Logistic regression analysis was used to identify independent risk factors, and a predictive nomogram was constructed based on these variables. The performance of the model was evaluated using receiver operating characteristic (ROC) curve analysis.
Results
The incidence of postoperative DVT was 32.59%. Patients in the DVT group had significantly higher age, D-dimer, prothrombin time (PT), activated partial thromboplastin time (APTT), and a higher prevalence of diabetes, preoperative heart failure, and postoperative infection compared with the non-DVT group (P < 0.05). Multivariate logistic regression identified age, diabetes, preoperative heart failure, PT, and APTT as independent risk factors for DVT. The nomogram demonstrated good predictive performance, with an area under the curve (AUC) of 0.877. The sensitivity and specificity were 82.47% and 76.68%, respectively.
Conclusion
The five-predictor nomogram provides individualized estimates of postoperative DVT probability in orthopedic ICU patients and may support risk stratification and targeted prevention.