Soluble transferrin receptor (sTfR) and ferritin concentrations were measured in a variety of clinical settings to compare the ability of these two tests to identify iron deficiency. Among 62 anemic patients who either had a bone marrow aspirate performed or had a documented response to iron therapy, the diagnostic sensitivity and specificity of sTfR (at a diagnostic cutoff of >2.8 mg/L) were 92% and 84%, respectively, with a positive predictive value of 42% in this population. Ferritin (≤12 μg/L) had a sensitivity of 25% and a specificity of 98%. However, the sensitivity and specificity of ferritin could be improved to 92% and 98%, respectively, by using a diagnostic cutoff value of ≤30 μg/L, resulting in a positive predictive value of 92%. Ferritin and sTfR were also measured in 267 outpatient samples and 112 medical students. In the outpatient group, the two tests agreed in 73% of the samples; however, 25% of the samples had ferritin values >12 μg/L and increased sTfR. Among the medical students, there was 91% agreement between the two tests, but 7% of the samples had ferritin ≤12 μg/L and normal sTfR. Together, these data suggest that measurement of sTfR does not provide sufficient additional information to ferritin to warrant routine use. However, sTfR may be useful as an adjunct in the evaluation of anemic patients, whose ferritin values may be increased as the result of an acute-phase reaction.

Background The recent emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in a rapid proliferation of serologic assays. However, little is known about their clinical performance. Here, we compared two commercial SARS-CoV-2 IgG assays. Methods 103 specimens from 48 patients with PCR-confirmed SARS-CoV-2 infections and 153 control specimens were analyzed using SARS-CoV-2 serologic assays by Abbott and EUROIMMUN (EI). Duration from symptom onset was determined by medical record review. Diagnostic sensitivity, specificity, and concordance were calculated. Results The Abbott SARS-CoV-2 assay had a diagnostic specificity of 99.4% (95% CI; 96.41–99.98%), and sensitivity of 0.0% (95% CI; 0.00–26.47%) at <3 days post symptom onset, 30.0% (95% CI; 11.89–54.28) at 3–7d, 47.8% (95% CI; 26.82–69.41) at 8–13d and 93.8% (95% CI; 82.80–98.69) at ≥14d. Diagnostic specificity on the EI assay was 94.8% (95% CI; 89.96–97.72) if borderline results were considered positive and 96.7% (95% CI; 92.54–98.93) if borderline results were considered negative. The diagnostic sensitivity was 0.0% (95% CI; 0.00–26.47%) at <3d, 25.0% (95% CI; 8.66–49.10) at 3–7d, 56.5% (95% CI; 34.49–76.81) at 3–7d and 85.4% (95% CI; 72.24–93.93) at ≥14d if borderline results were considered positive. The qualitative concordance between the assays was 0.83 (95% CI; 0.75–0.91). Conclusion The Abbott SARS-CoV-2 assay had fewer false positive and false negative results than the EI assay. However, diagnostic sensitivity was poor in both assays during the first 14 days of symptoms.

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Diagnosis of Epstein-Barr virus (EBV) infection is based on clinical symptoms and serological markers, including the following: immunoglobulin G (IgG)and IgM antibodies to the viral capsid antigen (VCA), heterophile antibodies, and IgG antibodies to the EBV early antigen-diffuse (EA-D) and nuclear antigen (EBNA-1). The use of all five markers results in 32 possible serological patterns. As a result, interpretation of EBV serologies remains a challenge. The purpose of this study was to use a large population of patients to develop evidence-based tools for interpreting EBV results. This study utilized 1,846 serum specimens sent to the laboratory for physician-ordered EBV testing. Chart review was performed for more than 800 patients, and diagnoses were assigned based on physician-ordered testing, clinical presentation, and patient history. Testing for all five EBV antibodies was performed separately on all serum samples using the Bio-Rad BioPlex 2200 system. Presumed EBV diagnosis (based on previous publications) was compared to EBV diagnosis based on a medical record review for each serological pattern. Interestingly, of the 32 possible serological patterns, only 12 occurred in >10 patients. The remaining 20 patterns were uninterpretable because they occurred with such infrequency. Two easy-to-use tables were created to interpret EBV serological patterns based on whether three (EBV VCA IgG, IgM, and heterophile) or five markers are utilized. The use of these two tables allows for interpretation of >95% of BioPlex serological results. This is the first evidence-based study of its kind for EBV serology.

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