Scientific Calendar December 2025

The diagnosis of joint disorders relies on different observations and methods, such as clinical signs, findings in radiology, and laboratory analysis of synovial fluid [1]. Synovial fluid originates as an ultrafiltrate of plasma that passes through the synovial membrane into the joint cavity, where it becomes enriched with hyaluronic acid secreted by the synovial lining cells [1]. The laboratory analysis of synovial fluid comprises various tests ranging from microbiological examination, cell counts and differentials, to C-reactive protein (CRP), glucose, and evaluation of the presence of crystals. Patient management for joint infections is often based on white blood cell (WBC) count results; therefore, an accurate count and differentiation are important [2–4].

Cell counting in synovial fluid can be performed manually, using a counting chamber, or automatically, using a haematology analyser. Although the manual method is considered the gold standard, it comes with several limitations: long turnaround time, high imprecision, and interpersonal variability [1–2, 4]. These are reasons why automated methods have become standard practice for body fluid analysis [1, 2]. However, especially synovial samples should be validated with care, as studies have demonstrated that automated methods may yield falsely elevated counts, particularly in joint arthroplasty patients [2, 4–5].

Emphasis for laboratory personnel should be placed on detecting interferences resulting in falsely elevated WBC counts, particularly in synovial fluid analysis of patients with knee arthroplasty, to avoid reporting false results [2]. Vanrenterghem et al. (2024) have observed that the deposition of non-cellular particles in synovial fluid could be a reason for interferences in the WBC count obtained by automated analysers [2]. Pearson et al. (2021) describe metallosis, a rare complication occurring due to metallic erosion and release of metallic particles after arthroplasty, as a potential cause of spuriously high cell counts from automated analysers [4]. Both authors suspect that these non-cellular particles may be counted as nucleated cells, thus leading to a falsely high cell count [2, 4].

Vanrenterghem et al. (2024) therefore introduced a workflow based on scattergram interpretation. Recognising a distinct ‘banana-shape’ pattern in the WDF scattergram during visual scattergram inspection supported the laboratory in preventing overestimation of the WBC count. This allowed the continued use of the automated haematology analysers, even for patients with arthroplasty, while ensuring accurate cell count reporting [2].