No abstract

Venous thromboembolism (VTE) and major bleeding (MBE) are feared complications that are influenced by numerous host and surgical related factors. Using machine learning on contemporary data, our aim was to develop and validate a practical, easy-to-use algorithm to predict risk for VTE and MBE following total joint arthroplasty (TJA). This was a single institutional study of 35,963 primary and revision total hip (THA) and knee arthroplasty (TKA) patients operated between 2009 and 2020. Fifty-six variables related to demographics, comorbidities, operative factors as well as chemoprophylaxis were included in the analysis. The cohort was divided to training (70%) and test (30%) sets. Four machine learning models were developed for each of the outcomes assessed (VTE and MBE). Models were created for all VTE grouped together as well as for pulmonary emboli (PE) and deep vein thrombosis (DVT) individually to examine the need for distinct algorithms. For each outcome, the model that best performed using repeated cross validation was chosen for algorithm development, and predicted versus observed incidences were evaluated. Of the 35,963 patients included, 308 (0.86%) developed VTE (170 PE’s, 176 DVT’s) and 293 (0.81%) developed MBE. Separate models were created for PE and DVT as they were found to outperform the prediction of VTE. Gradient boosting trees had the highest performance for both PE (AUC-ROC 0.774 [SD 0.055]) and DVT (AUC-ROC 0.759 [SD 0.039]). For MBE, least absolute shrinkage and selection operator (Lasso) analysis had the highest AUC (AUC-ROC 0.803 [SD 0.035]). An algorithm that provides the probability for PE, DVT and MBE for each specific patient was created. All 3 algorithms had good discriminatory capability and cross-validation showed similar probabilities comparing predicted and observed failures indicating high accuracy of the model. We successfully developed and validated an easy-to-use algorithm that accurately predicts VTE and MBE following TJA. This tool can be used in every-day clinical decision making and patient counseling.

The association between blood transfusions and thromboembolic events (VTE) following total joint arthroplasty (TJA) remains debatable. Using contemporary institutional data, this study aimed to determine whether blood transfusions increase the risk of VTE following primary and revision TJA. This was a single institution, retrospective cohort study. The clinical records of all patients (n = 34,824) undergoing primary and revision TJA between 2009 and 2020 were reviewed. Demographic variables, co-morbidities, type of chemoprophylaxis and intraoperative factors such as use of tranexamic acid were collected. Clinical notes, hospital orders, and discharge summaries were reviewed to determine if a patient received a blood transfusion. Comprehensive queries utilizing keywords for VTE were conducted in clinical notes, physician dictations, and patient-provider phone-call logs. Propensity score matching as well as adjusted mixed models were performed. After adjusting for various confounders, results from regression analysis showed a significant association between allogenic blood transfusions and risk for developing VTE following primary and revision TJA (OR 4.11, 95% CI 2.53–6.69 and OR 2.15, 95% CI 1.12–4.13, respectively). While this strong association remained significant for PE in both primary (p < 0.001) and revision (p < 0.001) matched cohorts, it was no longer statistically significant for DVT (p = 0.802 and p = 0.65, respectively). These findings suggest that the risk of VTE is increased by approximately three-folds when blood transfusions are prescribed. This association was mainly due to higher symptomatic PE events which makes it even more worrisome. Surgeons should be aware of this association, revisit criteria for blood transfusions and use all means available in the perioperative period to optimize the patients and avoid transfusion.