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<p>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 &gt; 400,000/µL (OR: 3.4, 95% CI: 2.1–5.8), D-dimer &gt; 1000ng/mL (OR: 3.0, 95% CI: 2.0-4.8), prolonged immobility &gt; 48&#xa0;h (OR: 2.7, 95% CI: 1.6–4.4), tumor size &gt; 4&#xa0;cm (OR: 2.3, 95% CI: 1.5–3.7), and extended surgical duration &gt; 180&#xa0;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.</p>

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

  • 期刊论文

  • 发表日期：

    2025年4月24日

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  • Dragan Nikolić,
  • Djula Djilvesi,
  • Vladimir Manojlović,
  • Nebojša Lasica,
  • Marijana Basta Nikolić,
  • Jagoš Golubović

摘要

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.