Development and Validation of a Nomogram for Predicting Postoperative Lower Extremity Deep Vein Thrombosis in Patients with Traumatic Spinal Fractures
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Background
Patients undergoing surgery for traumatic spinal fractures face a substantially elevated risk of postoperative lower extremity deep vein thrombosis (DVT). While generic risk assessment tools exist, a purpose-built model integrating spine-specific and readily available preoperative predictors is lacking. This study aimed to develop and internally validate a novel predictive model for this specific complication.
Methods
This retrospective cohort study analyzed data from 1,676 patients who underwent surgery for traumatic spinal fractures at a single center. All patients received standardized DVT surveillance. The cohort was randomly split into training (70%) and testing (30%) sets. Univariate and multivariable logistic regression with stepwise selection were used to identify independent predictors from 29 candidate variables. Model performance was evaluated by its discriminative ability (area under the curve, AUC), calibration (calibration curves and Hosmer-Lemeshow test), and clinical utility (decision curve analysis, DCA). A nomogram was constructed for clinical use.
Results
The incidence of postoperative DVT was 14.26% (239/1,676). Six independent preoperative predictors were identified: prolonged bed rest > 72 hours (adjusted odds ratio [aOR] = 5.208), pre-existing lower extremity vascular disease (aOR = 2.938), elevated D-dimer (aOR = 1.582), elevated fibrinogen (aOR = 1.434), severe neurological impairment (ASIA grade A/B), and advanced age (aOR = 1.019). The model demonstrated robust discrimination (AUC: 0.891 training, 0.885 testing) and excellent calibration (Hosmer-Lemeshow p > 0.7), with high sensitivity (90.5– 91.2%) and moderate specificity (74.3–74.5%). Decision curve analysis confirmed its clinical utility across a wide range of threshold probabilities.
Conclusion
We developed and validated a parsimonious and clinically practical prediction model for postoperative DVT in traumatic spinal fracture patients. This tool, which leverages six preoperatively accessible variables, facilitates individualized risk stratification and could guide the implementation of targeted prophylactic strategies to improve patient outcomes.
