The present investigation assessed the Liaison® diagnostic performance in detecting Epstein-Barr (EBV) IgM-VCA in a large patient cohort, considering age and symptomatology. VIDAS® were employed as a benchmark for acute EBV infection. The study also probed other coexisting conditions and potential cross-reactivity for error sources. A total of 1311 samples were analyzed, with notable associations found only among paediatric (kappa=0.75) and young adult (kappa=0.58) populations with compatible symptoms. ROC analysis revealed varying optimal cutoff values based on age and symptom categorizations. Logistic regression models identified age and patients from Oncology or Infectious Disease as significant factors for false positives. Potential interferences emerged with RF, ANCA, cytomegalovirus-IgM and VHS-IgM. Notably, Liaison® couldn´t distinguish EBV patients from Oncology, Haemathology or Internal Medicine. This study provides valuable insights, such as implementing ageand symptom-specific thresholds or reviewing test requests, for optimizing EBV serology in microbiology laboratories, leading to faster and more reliable responses.

本研究评估了 Liaison® 在大型患者队列中检测 Epstein-Barr (EBV) IgM-VCA 的诊断性能，同时考虑了年龄和症状。VIDAS® 被用作急性 EBV 感染的基准。该研究还探讨了其他共存条件和错误源的潜在交叉反应。总共分析了 1311 个样本，仅在具有相容症状的儿童（kappa=0.75）和年轻人（kappa=0.58）人群中发现显着关联。ROC 分析揭示了基于年龄和症状分类的不同最佳截止值。逻辑回归模型将年龄和肿瘤或传染病患者确定为误报的重要因素。RF、ANCA、巨细胞病毒-IgM 和 VHS-IgM 出现了潜在干扰。值得注意的是，Liaison® 无法将 EBV 患者与肿瘤科、血液科或内科科患者区分开来。这项研究提供了宝贵的见解，例如实施年龄和症状特定阈值或审查测试请求，以优化微生物实验室的 EBV 血清学，从而实现更快、更可靠的响应。