AUTHOR=Zhuang ShuYuan , Wang Jing , Du Peng , Dong SiHong , Wu Jiao , Li DeLong , Zang YuanTong , Li Li 

TITLE=A clinical risk prediction model for perioperative lower extremity DVT in patients undergoing spinal fracture surgery

JOURNAL=Frontiers in Surgery

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/surgery/articles/10.3389/fsurg.2025.1597101

DOI=10.3389/fsurg.2025.1597101

ISSN=2296-875X

ABSTRACT=ObjectiveTo develop a perioperative lower-extremity deep vein thrombosis (DVT) risk prediction model for spinal fracture surgery patients using logistic regression, supporting clinical prevention strategies.MethodsClinical data from 249 patients undergoing spinal fracture surgery (July 2019–October 2024) were retrospectively analyzed. Participants were divided into a model group (n = 166) and a validation group (n = 83) in a 2:1 ratio. Univariate and multivariate logistic regression identified independent risk factors for perioperative DVT, and a predictive model was established. Model fit was evaluated using the Hosmer-Lemeshow test, and predictive performance was assessed via receiver operating characteristic (ROC) curve analysis.ResultsIndependent risk factors included perioperative blood transfusion, elevated C-reactive protein, D-dimer >500 μg/L, hypertension, age ≥60 years, and prolonged bed rest. The model [P = 1/(1 + e^−Z)] demonstrated a good fit (Hosmer-Lemeshow χ2 = 12.139, P = 0.807). ROC analysis showed AUC values of 0.75 (95% CI: 0.80–0.92) for the model group and 0.81 (95% CI: 0.64–0.98) for the validation group, indicating robust predictive performance.ConclusionThe identified risk factors are critical predictors of perioperative DVT in spinal fracture patients. The proposed model exhibits strong clinical utility for early risk stratification and intervention guidance.