The PJI-TNM Classification as Predictor for Revision-Free Implant Survival Rates in Patients with Periprosthetic Joint Infection of the Hip or Knee Joint.
Frank Sebastian Fröschen, Lisa Greber, Ernst Molitor, Gunnar Thorben Rembert Hischebeth, Alexander Franz, Thomas Martin Randau
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Abstract
Background: Periprosthetic joint infections (PJIs) remain a major challenge in arthroplasty. This study tries to evaluate the PJI-TNM classification as predictor for the revision-free implant survival in patients with PJI of the hip or knee joint.
Methods: To this end, we perform a retrospective study of all consecutive patients with PJI of an inlying hip or knee arthroplasty between January 2015 and December 2019.
Results: A total of 443 cases (hip: n = 247; knee n = 196) were identified. In total, 439 patients underwent surgery (DAIR: n = 138 cases (31%), explantation: n = 272 (61%), irrigation with debridement without exchange of implant components: n = 29 (6.5%)). Four patients refused surgical treatment and 39.5% were lost to follow-up. In total, 78 patients died during follow-up and 27 deaths were directly related to PJI/complications during treatment. Patients with inlying "standard"-implants (p < 0.001) and without previous history of PJI (p = 0.002) displayed a significantly higher postoperative revision-free implant survival. In terms of the PJI-TNM subclassification, patients with loosened implants but without soft-tissue defects (T1) displayed the highest revision-free implant survival. In contrast, patients classified as M3 (no surgical treatment possible) displayed an inferior outcome compared to M0, M1, or M2. Patients with different N-subclassifications ("non-human cells"/causative pathogen) did not display differences in revision-free implant survival.
Conclusions: The PJI-TNM classification is well suited to classify PJIs. Its complexity allows for more than 500 different combinations of classifications. Further validation data are needed, but to us, the PJI-TNM classification seems to offer the possibility of comparing patients with PJIs. It may, therefore, be a very valuable tool in order to compare cohorts with PJIs and provide individual data for patient specific outcomes.
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