Nomogram for predicting venous thromboembolism after spinal surgery

Abstract Purpose This study aimed to establish a nomogram to predict the risk of venous thromboembolism (VTE), identifying potential risk factors, and providing theoretical basis for prevention of VTE after spinal surgery. Methods A retrospective analysis was conducted on 2754 patients who underwent spinal surgery. The general characteristics of the training group were initially screened using univariate logistic analysis, and the LASSO method was used for optimal prediction. Subsequently, multivariate logistic regression analysis was performed to identify independent risk factors for postoperative VTE in the training group, and a nomogram for predict risk of VTE was established. The discrimination, calibration, and clinical usefulness of the nomogram were separately evaluated using the C-index, receiver operating characteristic curve, calibration plot and clinical decision curve, and was validated using data from the validation group finally. Results Multivariate logistic regression analysis identified 10 independent risk factors for VTE after spinal surgery. A nomogram was established based on these independent risk factors. The C-index for the training and validation groups indicating high accuracy and stability of the model. The area under the receiver operating characteristic curve indicating excellent discrimination ability; the calibration curves showed outstanding calibration for both the training and validation groups. Decision curve analysis showed the clinical net benefit of using the nomogram could be maximized in the probability threshold range of 0.01–1. Conclusion Patients undergoing spinal surgery with elevated D-dimer levels, prolonger surgical, and cervical surgery have higher risk of VTE. The nomogram can provide a theoretical basis for clinicians to prevent VTE.