<p>Deep vein thrombosis (DVT) in patients undergoing endoscopic endonasal surgery remains underexplored, despite its potential impact on postoperative recovery. This study aimed to develop and validate a predictive nomogram for assessing the risk of lower-limb DVT in such patients without chemoprophylaxis. A retrospective analysis was conducted on 935 patients with postoperative lower-limb vein ultrasonography. Clinical data, including potential risk factors, were used to construct a predictive model via multivariate logistic regression analysis. The resulting nomogram was validated using an independent cohort and evaluated through concordance index (C-index), calibration plots, and decision curve analysis. The incidence of postoperative DVT was 28.9%, with most cases being distal (27.2%). Significant predictors included older age, intraoperative bleeding, female gender, prolonged surgery duration, elevated postoperative APTT and D-dimer levels, and disturbance of consciousness. The nomogram demonstrated good predictive performance, with C-index values of 0.81 in the training cohort and 0.75 in the validation cohort. Calibration and decision curve analyses confirmed the model’s clinical applicability. This nomogram offers a practical tool for individualized DVT risk assessment in patients undergoing endoscopic endonasal surgery, facilitating more targeted prophylactic measures.</p>

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Predictive nomogram for postoperative lower-limb deep vein thrombosis in patients undergoing endoscopic endonasal surgery during hospitalization: a retrospective cohort study

  • Hai Peng,
  • Ruofei Yuan,
  • Zhe Zhang,
  • Ying Wang,
  • Xingchao Wang,
  • Bo Wang,
  • Peng Li

摘要

Deep vein thrombosis (DVT) in patients undergoing endoscopic endonasal surgery remains underexplored, despite its potential impact on postoperative recovery. This study aimed to develop and validate a predictive nomogram for assessing the risk of lower-limb DVT in such patients without chemoprophylaxis. A retrospective analysis was conducted on 935 patients with postoperative lower-limb vein ultrasonography. Clinical data, including potential risk factors, were used to construct a predictive model via multivariate logistic regression analysis. The resulting nomogram was validated using an independent cohort and evaluated through concordance index (C-index), calibration plots, and decision curve analysis. The incidence of postoperative DVT was 28.9%, with most cases being distal (27.2%). Significant predictors included older age, intraoperative bleeding, female gender, prolonged surgery duration, elevated postoperative APTT and D-dimer levels, and disturbance of consciousness. The nomogram demonstrated good predictive performance, with C-index values of 0.81 in the training cohort and 0.75 in the validation cohort. Calibration and decision curve analyses confirmed the model’s clinical applicability. This nomogram offers a practical tool for individualized DVT risk assessment in patients undergoing endoscopic endonasal surgery, facilitating more targeted prophylactic measures.