Predicting 30-Day Venous Thromboembolism Following Total Joint Arthroplasty: Adjusting for Trends in Annual Length of Stay.

Background: Venous thromboembolism (VTE) following total hip arthroplasty and total knee arthroplasty (TKA) is linked to immobility, and preoperative prediction remains difficult. We aimed to evaluate whether annual mean length of stay (LOS) is associated with the incidence of VTE and develop a generalizable machine learning model to preoperatively predict the incidence of symptomatic VTE following total hip and TKA using National Surgical Quality Improvement Program. Methods: Annual incidence of 30-day postoperative VTE, deep vein thrombosis, and pulmonary embolism was calculated over 6 years and tested for trend. Correlation between annual VTE rates and mean LOS was calculated. Predictive models (logistic regression, random forest, and XGBoost) were trained and tested based on year of surgery with different oversampling algorithms used to address data imbalance. Results: A total of 498,314 patients were included, with 0.88% developing a VTE within 30 days. VTE rates decreased from 1.11% in 2014 to 0.76% in 2019 ( Conclusions: This study revealed declining VTE rates strongly correlated to decreasing postoperative LOS and identified patient and surgery-specific factors associated with VTE risk. Development of more accurate machine learning models for VTE prediction may improve risk stratification, prevention, and monitoring for arthroplasty patients.