Development and internal validation of a nomogram for estimating concurrent superficial vein thrombosis at presentation in patients with lower extremity varicose veins.

Background: Superficial vein thrombosis (SVT) is a clinically relevant complication of lower extremity varicose veins. This study aimed to develop and internally validate a parsimonious nomogram for estimating the probability of concurrent SVT at presentation. Methods: This single-center retrospective study included 423 patients with lower extremity varicose veins, including 91 with SVT. Twenty-four candidate variables were evaluated using LASSO regression, the Boruta algorithm, and a genetic algorithm for feature selection. Variables retained by all three methods were entered into multivariable logistic regression to construct the full model, and a reduced model excluding fibrinogen (FIB) was assessed for parsimony. Model performance was compared with the Caprini score and internally validated using 1,000 bootstrap resamples. Results: Age, interleukin-6, C-reactive protein, D-dimer, and FIB were identified as consensus-selected variables. The full model had an AUC of 0.844 (95% CI, 0.797-0.891). Removing FIB produced minimal changes in discrimination ( Conclusion: A nomogram based on age, interleukin-6, C-reactive protein, and D-dimer showed good internally validated performance for estimating the probability of concurrent SVT at presentation. Because validation was limited to bootstrap resampling within a single-center cohort, independent external validation is required before clinical application.