A Nomogram Prediction Model Integrating TEG and Clinical Features for Postoperative Lower Extremity DVT in TF...

Area of Science:

• Orthopedic Surgery
• Vascular Surgery
• Trauma Surgery

Background:

• Postoperative deep vein thrombosis (DVT) is a significant complication in patients with traumatic lower extremity fractures (LETF).
• Accurate risk stratification is crucial for effective DVT prevention and management in this high-risk population.

Purpose of the Study:

• To identify independent risk factors for postoperative DVT in patients with LETF.
• To develop and validate a nomogram prediction model for assessing DVT risk in these patients.

Main Methods:

• A cohort of 136 LETF patients was analyzed.
• Patients were classified into DVT and non-DVT groups based on postoperative ultrasonography.
• Logistic regression and nomogram construction were employed, with validation using ROC curve, calibration curves, and decision curve analysis (DCA).

Main Results:

• Independent risk factors for DVT included hip fracture, Injury Severity Score (ISS) ≥ 25, elevated fibrinogen (FIB), elevated D-Dimer (D-D), higher Thromboelastography (TEG) maximum amplitude (MA), and lower TEG clot formation time (K).
• The developed nomogram demonstrated excellent predictive performance (AUC = 0.89) and good calibration.
• DCA confirmed the clinical utility of the nomogram for risk assessment.

Conclusions:

• A TEG-based nomogram integrating clinical factors effectively predicts postoperative DVT risk in traumatic fracture patients.
• This model facilitates early identification of high-risk individuals.
• Personalized prophylaxis strategies can be implemented to reduce DVT incidence and improve patient outcomes.