Early-Outcome Differences between Acute and Chronic Periprosthetic Joint Infections—A Retrospective Single-Center Study

Abstract

Periprosthetic joint infections (PJI) are serious complications after arthroplasty, associated with high morbidity, mortality, and complex treatment processes. The outcomes of different PJI entities are largely unknown. The aim of this study was to access the early outcomes of different PJI entities. A retrospective, single-center study was conducted. The characteristics and outcomes of patients with PJI treated between 2018 and 2019 were evaluated 12 months after the completion of treatment. Primary endpoints were mortality, relapse free survival (RFS) and postoperative complications (kidney failure, sepsis, admission to ICU). A total of 115 cases were included [19.1% early (EI), 33.0% acute late (ALI), and 47.8% chronic infections (CI)]. Patients with ALI were older (p = 0.023), had higher ASA scores (p = 0.031), preoperative CRP concentrations (p = 0.011), incidence of kidney failure (p = 0.002) and sepsis (p = 0.026). They also tended towards higher in-house mortality (ALI 21.1%, 13.6% EI, 5.5% CI) and admission to ICU (ALI 50.0%, 22.7% EI, 30.9% CI). At 12 months, 15.4% of patients with EI had a relapse, compared to 38.1% in ALI and 36.4% in CI. There are differences in patient characteristics and early outcomes between PJI entities. Patients with EI have better early clinical outcomes. Patients with ALI require special attention during follow-up because they have higher occurrences of relapses and postoperative complications than patients with EI and CI.

Impact of a Novel Antiseptic Lavage Solution on Acute Periprosthetic Joint Infection in Hip and Knee Arthroplasty

“…This extension is predicated on the premise that early intervention, particularly within the acute phase, offers a higher likelihood of treatment success, as supported by the findings of Youssef et al [ 31 ]. Moreover, this study underscores the importance of integrating diagnostic criteria and treatment protocols to optimize patient care, as evidenced by the work of Parvizi et al and Tande et al [ 19 , 32 ].…”