Abstract
Study DesignRetrospective cohort study.ObjectivesDeep venous thrombosis (DVT) is a common complication following lumbar spine surgery, which can lead to adverse consequences such as venous thromboembolism and pulmonary embolism. This study aimed to investigate whether predictors of DVT can improve clinical interventions.MethodsThe study included patients who underwent posterior lumbar fusion between 2012 and 2022. In the training cohort, stepwise logistic regression, based on the Akaike information criterion minimum, was used to identify variables for constructing the nomogram. The nomogram was evaluated and validated using calibration curves, Brier scores, receiver operating characteristic (ROC) curves, C-index, decision curve analyses (DCAs), clinical impact curves (CICs), and risk stratification analyses.ResultsA total of 9216 patients were enrolled after screening. The nomogram included seven variables: cerebrovascular disease, diabetes, body mass index, age, pedicular screw quantity, D-dimer, and hypertension. Calibration plots demonstrated favorable agreement between predicted and observed probabilities. The C-index indicated satisfactory discriminatory ability of the nomogram (0.772 for the training cohort and 0.792 for the validation cohort). Additionally, the DCA and CIC revealed that the nomogram could provide clinical benefits for patients.ConclusionsThis study successfully developed and validated a nomogram that can assess the risk of DVT following posterior lumbar fusion. The nomogram will assist surgeons in making informed clinical decisions.