Declining Trends in Septic Revision Following Total Knee Arthroplasty From 2010 to 2019: A National Cohort Analysis

Background: Periprosthetic joint infections (PJIs) following total knee arthroplasty (TKA) are associated with high patient morbidity, mortality, and health care costs. Methods to reduce the burden of PJI have been shown to be efficacious on a small scale. On a national scale, it is unknown whether these methods have reduced PJI rates. Methods: A retrospective trend analysis was conducted using a national database. The incidence of 2year septic revision was observed for the entire cohort in patients who had high-risk comorbidities from 2010 to 2019. A multivariable logistic regression was performed to compare the odds ratios of 2year septic revision rates from 2011 to 2019 to the reference year of 2010. Linear regression was used to compare the change in the overall and high-risk subanalysis groups. Results: Among the 860,185 patients, 5,589 underwent septic revision within 2 years. The 2-year septic revision rate decreased from 0.75% in 2010 to 0.69% in 2019 (compounded annual growth rate = -0.94%, P = 0.049). Multivariable logistic regressions demonstrated that the odds of septic revision in 2019 were significantly lower than those in 2010 (odds ratio: 0.83, 95% CI [confidence interval]: [0.70 to 0.96], P = 0.017). In high-risk patients, the septic revision rate decreased from 1.04 to 0.80% (compounded annual growth rate = -2.80%, P = 0.004), specifically in those who had a history of psychoses, Medicaid insurance, anemia, heart failure, obesity, liver disease, tobacco use, and drug abuse (P < 0.05 for all). Conclusions: This study demonstrated a national reduction in the 2-year septic revision rate in all TKA patients, including patients considered at high risk for PJI. This suggests that current preventative methods may be efficacious on a national scale in TKA. Further research is needed to identify more modalities to reduce the national incidence of this morbid and costly complication. (c) 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.