Comprehensive DVT risk assessment model for meningioma surgery: development, validation and clinical implementation

Deep vein thrombosis (DVT) represents a significant complication in meningioma surgery, with reported incidence rates of 10-30%. Current predictive models demonstrate limited accuracy in this specific population, necessitating the development of more precise risk assessment tools. In this single-center retrospective cohort study (2019-2024), we analyzed 126 patients who underwent meningioma surgery, equally distributed between DVT and control groups. Multiple regression analysis was used to develop a predictive model incorporating clinical, laboratory, and surgical parameters. The model was validated using bootstrap resampling with 1000 iterations. Primary outcome was ultrasonography-confirmed DVT. The model achieved superior discrimination (derivation cohort: AUC = 0.83, 95% CI: 0.78-0.89; validation cohort: AUC = 0.81, 95% CI: 0.75-0.87) compared to existing risk assessment tools. Independent predictors included preoperative platelet count > 400,000/µL (OR: 3.4, 95% CI: 2.1-5.8), D-dimer > 1000ng/mL (OR: 3.0, 95% CI: 2.0-4.8), prolonged immobility > 48 h (OR: 2.7, 95% CI: 1.6-4.4), tumor size > 4 cm (OR: 2.3, 95% CI: 1.5-3.7), and extended surgical duration > 180 min (OR: 2.1, 95% CI: 1.4-3.5). Model implementation resulted in significant reductions in unnecessary screening (28%) and prophylactic anticoagulation use (35%), with demonstrated overall cost savings of 42% per patient. This comprehensive risk assessment model demonstrates robust predictive accuracy for post-operative DVT in meningioma patients, offering significant improvements in risk stratification and resource utilization. The model's strong discrimination and successful validation support its implementation in clinical practice.