The Performance of Diagnostic Tests for Identifying Periprosthetic Joint Infection After Failed Partial Knee Arthroplasty

Differential synovial fluid white blood cell count for the diagnosis of chronic peri-prosthetic joint infection - a systematic review and meta-analysis

Introduction: Peri-prosthetic joint infection (PJI) is a significant complication of arthroplasty, lacking a single gold standard diagnostic test. Synovial fluid white blood cell (WBC) count and polymorphonuclear neutrophil (PMN) proportion are widely used diagnostic tools, but their optimal cutoffs remain unclear, particularly for chronic PJI. Material and methods: This systematic review and meta-analysis included 74 studies published between 2000 and 2024. Data on diagnostic performance (sensitivity, specificity, and diagnostic odds ratios - DORs) of WBC count and PMN proportions were analysed. Sub-group analyses and heterogeneity assessments were performed, and optimal cutoffs for diagnostic accuracy were identified. Results: The meta-analysis revealed a WBC count summary DOR of 58.38 (95 % CI - confidence interval: 48.48-70.32) with an area under the curve (AUC) of the summarized receiver operating characteristic curve of 0.952. The PMN proportion showed a DOR of 43.17 (95 % CI: 35.31-52.79) and an AUC of 0.941. Optimal diagnostic thresholds for chronic PJI were WBC count > 2600 cells per microlitre and PMN > 70 %. Rule-in thresholds (specificity > 95 %) were WBC count ≥ 3000 cells per microlitre and PMN ≥ 75 %, while rule-out thresholds (sensitivity > 95 %) were WBC count ≤ 1500 cells per microlitre and PMN ≤ 65 %. Confounding conditions such as fractures, inflammatory arthritis, and metal-related reactions reduced test accuracy. Conclusions: Synovial fluid analysis remains a critical diagnostic tool for chronic PJI. Thresholds of WBC count < 1500 and > 3000  cells per microlitre and PMN < 65 % and > 75 % provide reliable negative and positive predictive values. A standardized diagnostic framework is essential for addressing remaining controversies and ensuring consistent interpretation across clinical settings.

[Dealing with early complications in unicondylar knee arthroplasty-what works, what does not?]

Complications in the early postoperative period following the implantation of a unicondylar knee arthroplasty (UKA) are both rare and rarely described in the literature. Often, only small case series or individual case reports are available. In this article, the most common complications of periprosthetic infection, periprosthetic tibial fracture, inlay dislocation and intra-articular cement residue in (loose bone cement body) are described and recommendations for conservative and surgical treatment are presented, including case examples. Ideally, surgical errors or an infection should be recognized at an early stage and revised as soon as possible.

The superiority of immune-inflammation summary index for diagnosing periprosthetic joint infection

BACKGROUND

Accurate and rapid diagnosis of periprosthetic joint infections (PJI) is particularly challenging. This study aimed to evaluate the diagnostic value of a newly developed immune-inflammation summary index (IISI) for PJI.

METHODS

Our study enrolled 171 aseptic loosening (AL) and 172 PJI cases. Based on a biological-driven approach, the IISI was formulated as C-reaction protein (CRP) × globulin × neutrophil / [lymphocyte × albumin]. Receiver operating characteristic (ROC) curves were constructed to compare the diagnostic performance of IISI with other known serum markers. Subgroup analysis was also performed to explore the robustness of IISI. Restricted cubic splines were used to evaluate the dose-response association. Additionally, changes in IISI levels prior to reimplantation were investigated.

RESULTS

The levels of all tested biomarkers were significantly different between the PJI and AL groups (all P < 0.05). ROC analysis revealed that IISI outperformed any other marker in diagnosing PJI with an area under the curve (AUC) value of 0.890. The diagnostic performance of IISI was also optimal in the hip (0.898), knee (0.903), low-grade infection (0.841), and culture-negative (0.919) subgroups. The optimal cut-off value is stabilized at around 1.6. The nonlinear association between IISI scores and PJI was also confirmed (P < 0.001). The levels of IISI before reimplantation demonstrated a significant decrease (P < 0.001) and were comparable to those of the AL group (P = 0.143).

CONCLUSION

IISI can improve the utilization of serum indicators and is superior to other well-known biomarkers in diagnosing PJI. Further studies should evaluate its specific role in different infectious and inflammatory diseases.