Serological markers are important for the diagnosis of hepatitis E virus (HEV) infection. This study aims to compare the diagnostic performance of the anti-HEV IgM and the HEV antigen (Ag) assays and establish a multifactorial model to improve the diagnosis of current HEV infection when HEV RNA detection is not available. A total of 809 serum samples, including 325 anti-HEV IgM-positive and 484 anti-HEV IgM-negative samples, were tested for HEV RNA. The anti-HEV IgM assay had very high sensitivity (99.4%) but moderate accuracy (79.2%) and specificity (74.3%). By retrospective follow-up of 58 patients with sequential samples (n = 143) tested for anti-HEV antibodies, we found anti-HEV IgM remained positive for more than 10 months in some HEV-infected patients, when HEV RNA was already undetectable; thus, decision solely based on anti-HEV IgM may lead to misdiagnosis. In contrast, the HEV Ag assay had very high specificity (100%). However, the detection efficiency of HEV Ag greatly diminished when the HEV RNA level was low or the anti-HEV IgG level was high. By logistic regression, a model integrating anti-HEV IgM, alanine aminotransferase, and HEV Ag was proposed, and the cutoff value was determined based on the testing results of the 143 sequential samples. The model was further evaluated with 67 randomly selected IgM-positive samples from single-visit patients. Overall, the model outperformed the anti-HEV IgM or the HEV Ag assay in the diagnosis of current HEV infection (sensitivity/specificity/accuracy, 89.5%/95.2%/91.9%). The area under the receiver operating characteristics curve of the model was greater than 0.97.

中文翻译：

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戊型肝炎病毒（HEV）抗体的动力学和建立多因素模型以改善资源受限环境中HEV感染的诊断

血清学标记对于戊型肝炎病毒（HEV）感染的诊断很重要。这项研究旨在比较抗HEV IgM和HEV抗原（Ag）检测方法的诊断性能，并建立多因素模型来改善当前无法获得HEV RNA检测的HEV感染的诊断。测试了总共809个血清样品，包括325个抗HEV IgM阳性和484个抗HEV IgM阴性样品。抗HEV IgM检测具有很高的灵敏度（99.4％），但具有中等准确性（79.2％）和特异性（74.3％）。通过回顾性随访58例连续样本（n= 143）对抗HEV抗体进行了测试，我们发现在某些HEV感染患者中，HEV RNA已经检测不到，抗HEV IgM保持阳性超过10个月。因此，仅基于抗HEV IgM的决定可能导致误诊。相反，HEV Ag测定具有很高的特异性（100％）。但是，当HEV RNA水平低或抗HEV IgG水平高时，HEV Ag的检测效率会大大降低。通过逻辑回归，提出了一个整合了抗HEV IgM，丙氨酸转氨酶和HEV Ag的模型，并根据143个连续样本的检测结果确定了临界值。使用来自单次就诊患者的67个随机选择的IgM阳性样品进一步评估该模型。总体，该模型在目前的戊型肝炎病毒感染的诊断中（敏感性/特异性/准确性为89.5％/ 95.2％/ 91.9％）优于抗HEV IgM或HEV Ag分析。该模型的接收器工作特性曲线下的面积大于0.97。