Development and validation of a predictive model for postoperative deep vein thrombosis in elderly patients undergoing hip fracture surgery: A retrospective study

This study aimed to systematically examine the incidence of deep vein thrombosis (DVT) after hip surgery and identify its key determinants. The findings are intended to inform the refinement of postoperative risk assessment tools, the optimization of prevention strategies, and the development of personalized nursing protocols. This retrospective cohort study consecutively enrolled elderly patients aged ≥ 60 years who underwent hip fracture surgery at the First Affiliated Hospital of Nanchang University between January and September 2024 and had complete medical records. The primary outcome was postoperative DVT confirmed by imaging. Predictive factors were identified through univariate and multivariate logistic regression analyses, and a nomogram prediction model was constructed. A total of 710 patients were included, with a postoperative DVT incidence of 12.11% (86/710). Significant differences were observed between the DVT group and the non-DVT group in terms of 24-hour post-admission assessment and venous thromboembolism scores (P < .05).Multivariate logistic regression revealed that a specialized risk score within 24 hours of admission (OR = 4.326, 95% CI: 2.00-9.35, P < .001), elevated preoperative C-reactive protein levels (OR = 1.018, 95% CI: 1.01-1.03, P < .05), perioperative blood transfusion (OR = 0.212, 95% CI: 0.10-0.43, P < .001), Postoperative graded elevation in D-dimer levels (OR = 2.691, 95% CI: 1.08-6.37, P < .05), and preexisting DVT risk scores (OR = 1.711, 95% CI: 1.35-2.17, P < .001) were identified as independent predictors of postoperative DVT in elderly patients undergoing hip replacement surgery. The constructed nomogram model demonstrated excellent predictive performance (concordance index: 0.873). In elderly patients receiving hip replacement surgery, 5 independent predictors of postoperative DVT were identified. These factors were integrated into a bar-chart-based risk assessment tool, which quantifies individualized thrombotic risk through a visual scoring system. This model provides clinicians with a practical method for early risk stratification, supporting targeted prevention strategies and postoperative monitoring in routine care.