Establishment and validation of a predictive model for lower extremity deep vein thrombosis in patients with traumatic pelvic fractures.

Background: Patients with traumatic pelvic fracture (TPF) are at high risk for developing deep vein thrombosis (DVT). However, there is still no unified standard on how to distinguish high-risk groups for DVT in patients with TPF and how to accurately use anticoagulants at present.

Objectives: This observational study aimed to establish a DVT risk nomogram score (DRNS) model for TPF patients, and to explore the value of the DRNS model as a clinical guideline in the prevention of DVT with low molecular weight heparin (LMWH).

Methods: Independent risk factors of lower extremity DVT were screened through Lasso regression and logistic regression. A DRNS model was established per this.

Results: The independent risk factors of DVT included combined femoral fractures, age ≥ 40 years old, BMI (body mass index) ≥ 24 kg/m², ISS score, fibrinogen concentration, and the minimum concentration of ionized calcium within 48 h after admission. The optimal cutoff value for DRNS was 78.5. In the low-risk population of DVT (DRNS < 78.5), there was no statistical significance of variation about the incidence of DVT progression between the LMWH once a day (qd) group and the LMWH once every 12 h (q12h) group, with P = 0.323. In the high-risk population of DVT (DRNS ≥ 78.5), the incidence of DVT progression in the LMWH qd group was significantly higher than that in the LMWH q12h group, with P = 0.002.

Conclusions: The DRNS model based on independent risk factors of DVT could stratify the risk of DVT for TPF patients, and it was able to provide more precise DVT drug prevention plans for clinicians.