[PJI-TNM as new classification system for periprosthetic joint infections : An evaluation of 20 cases]

Current classifications for periprosthetic joint infections (PJIs) often lack a detailed description of the overall underlying situation of a patient. The PJI-TNM classification uses the principles of the TNM classification from oncology for the description of critical parameters in PJIs: affected joint, type of implant and implant stability, soft tissue conditions, maturity of biofilm formation, causative microorganism, comorbidities of the patient and recurrence of infection. The aim of the current work is to evaluate the feasibility of this new PJI-TNM classification in clinical practice.

The PJI-TNM classification was used in 20 patients with hip, knee and shoulder PJIs. Based on a retrospective chart review, the respective parameters T (tissue and implants), N (non-eukaryotic cells and fungi), M (morbidity) and r (reinfection) were classified for each case.

All 20 cases (12 male, 8 female, average age 72.2 (40-88 years)) with 13 hip, 6 knee and 1 shoulder PJIs were to be classified with the new TNM-PJI classification system. There was a considerable heterogeneity among the cases: 12 protheses were fixed (T0), 6 were loosened (T1) and 2 were associated with a soft tissue defect (T2). Biofilm formation was considered immature in 7 cases (N0). Out of the PJIs, 13 were considered to be associated with mature biofilm formation. Out of the patients, 9 were systemically not or only mildly compromised (M0), 7 patients moderately (M1) and 3 patients (M2) severely compromised. One patient refused surgical treatment (M3a). Recurrent infections (r) were diagnosed in three cases.

The principles of the TNM classification from oncology can also be used for the classification of PJIs. Despite the limited number of cases in this study, a considerable heterogeneity of the evaluated PJIs is shown, which is a phenomenon that is also known from clinical practice. This heterogeneity can be adequately addressed by this new classification, which might be beneficial in decision-making in the future.