Larkin Hald (yamweapon54)

Preoperative calculation of treatment failure risk in patients undergoing surgery for periprosthetic joint infection (PJI) is imperative to allow for medical optimization and targeted prevention. A preoperative prognostic model for PJI treatment failure was previously developed, and this study sought to externally validate the model. A retrospective review was performed of 380 PJIs treated at two institutions. The model was used to calculate the risk of treatment failure, and receiver operating characteristic curves were generated to calculate the area under the curve (AUC) for each institution. When applying this model to institution 1, an AUC of 0.795 (95% confidence interval [CI] 0.693-0.897) was found, whereas institution 2 had an AUC of 0.592 (95% CI 0.502-0.683). Comparing all institutions in which the model had been applied to, we found institution 2 represented a significantly sicker population and different infection profile. In this cohort study, we externally validated the prior published model for institution 1. However, institution 2 had a decreased AUC using the prior model and represented a sicker and less homogenous cohort compared with institution 1. When matching for chronicity of the infection, the AUC of the model was not affected. This study highlights the impact of comorbidities and their distributions on PJI prognosis and brings to question the clinical utility of the algorithm which requires further external validation. In this cohort study, we externally validated the prior published model for institution 1. However, institution 2 had a decreased AUC using the prior model and represented a sicker and less homogenous cohort compared with institution 1. When matching for chronicity of the infection, the AUC of the model was not affected. This study highlights the impact of comorbidities and their distributions on PJI prognosis and brings to question the clinical utility of the algorithm which requires further external validation. Well-powered studies investigating the relationship of emergency department (ED) visits and total knee arthroplasty (TKA) are limited. Therefore, the specific aims of this study were to 1) compare patient demographics of patients who did and did not have an ED visit; and for the visits, identified 2) leading reasons; and 3) risk factors for ED visits (prearthroplasty/postarthroplasty). Patients undergoing primary TKA who had an ED visit within 90 days after their index procedure were identified from a nationwide database. The query yielded 1,364,655 patients who did (n= 5689) and did not have (n= 1,358,966) an ED visit. Baseline demographics such as age, sex, and comorbidity prevalence between the two cohorts; reasons for ED visits; and prearthroplasty and postarthroplasty risk factors were analyzed. Odds ratios (ORs) of ED visits were assessed using multivariate binomial logistic regression analyses. A P-value less than 0.001 was considered statistically significant. Patients who did and did not have ED visits differed with respect to age (P < .0001) and mean Elixhauser Comorbidity Index scores (9 vs 6, P < .0001). Musculoskeletal etiologies were the most common reason for ED visits. Hypertension was the greatest contributor to ED visits prearthroplasty and postarthroplasty. Comorbid conditions associated with ED visits postarthroplasty included peripheral vascular disease (OR 1.61, P < .0001), coagulopathy (OR 1.58, P < .0001), and rheumatoid arthritis (OR 1.56, P < .0001). By identifying demographic patterns of patients, reasons, and risk factors, the information found from this study can help identify targets for quality improvement to potentially reduce the incidence of ED visits after primary TKA. By identifying demographic patterns of patients, reasons, and risk factors, the information found from this study can help identify targets for quality improvement to potentia