Background: Here, we report on a head-to-head comparison of the fully-automated Elecsys® Anti-SARS-CoV-2 immunoassay with the EDI TM enzyme linked immunosorbent assays (ELISA) for the detection of SARS-CoV-2 antibodies in human plasma. Methods: SARS-CoV-2 antibodies were measured with the Elecsys® assay and the EDI TM ELISAs (IgM and IgG) in 64 SARS-CoV-2 RT-PCR confirmed COVID-19 patients with serial blood samples (n = 104) collected at different time points from symptom onset. Blood samples from 200 healthy blood donors and 256 intensive care unit (ICU) patients collected before the COVID-19 outbreak were also used. Results: In COVID-19 patients, the percentage of positive results rose with time from symptom onset, peaking to positivity rates after 15-22 days of 100% for the Elecsys® assay, of 94% for the EDI TM IgM-ELISA and of 100% for the EDI TM IgG ELISA. In the 104 blood samples, the agreement between positive/negative classifications of the Elecsys® assay and the EDI TM ELISAs (IgM or IgG) was 90%. The false positivity rates in the healthy blood donors and the ICU patients were < 1% for the Elecsys® assay and < 3% for the EDI TM ELISAs. Conclusions: Our results indicate a high sensitivity and specificity for the Elecsys® assay and an acceptable agreement with the EDI TM ELISAs.

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Variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are replacing the initial wild-type strain, jeopardizing current efforts to contain the pandemic. Amino acid exchanges in the spike protein are of particular concern as they can render the virus more transmissible or reduce vaccine efficacy. Here, we conducted whole genome sequencing of SARS-CoV 2 positive samples from the Rhine-Neckar district in Germany during January-March 2021. We detected a total of 166 samples positive for a variant with a distinct mutational pattern in the spike gene comprising L18F, L452R, N501Y, A653V, H655Y, D796Y and G1219V with a later gain of A222V. This variant was designated A.27.RN according to its phylogenetic clade classification. It emerged in parallel with the B.1.1.7 variant, increased to >50% of all SARS-CoV-2 variants by week five. Subsequently it decreased to <10% of all variants by calendar week eight when B.1.1.7 had become the dominant strain. Antibodies induced by BNT162b2 vaccination neutralized A.27.RN but with a two-to-threefold reduced efficacy as compared to the wild-type and B.1.1.7 strains. These observations strongly argue for continuous and comprehensive monitoring of SARS CoV 2 evolution on a population level.

Throughout the SARS‐CoV‐2 pandemic, limited diagnostic capacities prevented sentinel testing, demonstrating the need for novel testing infrastructures. Here, we describe the setup of a cost‐effective platform that can be employed in a high‐throughput manner, which allows surveillance testing as an acute pandemic control and preparedness tool, exemplified by SARS‐CoV‐2 diagnostics in an academic environment. The strategy involves self‐sampling based on gargling saline, pseudonymized sample handling, automated RNA extraction, and viral RNA detection using a semiquantitative multiplexed colorimetric reverse transcription loop‐mediated isothermal amplification (RT‐LAMP) assay with an analytical sensitivity comparable with RT‐qPCR. We provide standard operating procedures and an integrated software solution for all workflows, including sample logistics, analysis by colorimetry or sequencing, and communication of results. We evaluated factors affecting the viral load and the stability of gargling samples as well as the diagnostic sensitivity of the RT‐LAMP assay. In parallel, we estimated the economic costs of setting up and running the test station. We performed > 35,000 tests, with an average turnover time of < 6 h from sample arrival to result announcement. Altogether, our work provides a blueprint for fast, sensitive, scalable, cost‐ and labor‐efficient RT‐LAMP diagnostics, which is independent of potentially limiting clinical diagnostics supply chains.

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Throughout the current SARS-CoV-2 pandemic, limited diagnostic testing capacity prevented sentinel testing of the population, demonstrating the need for novel testing strategies and infrastructures. Here, we describe the set-up of an alternative testing platform, which allows scalable surveillance testing as an acute pandemic response tool and for pandemic preparedness purposes, exemplified by SARS-CoV-2 diagnostics in an academic environment. The testing strategy involves self-sampling based on gargling saline, pseudonymized sample handling, automated 96-well plate-based RNA extraction, and viral RNA detection using a semi-quantitative multiplexed colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay with an analytical sensitivity comparable to RT-quantitative polymerase chain reaction (RT-qPCR). We provide standard operating procedures and an integrated software solution for all workflows, including sample logistics, LAMP assay analysis by colorimetry or by sequencing (LAMP-seq), and communication of results to participants and the health authorities. Using large sample sets including longitudinal sample series we evaluated factors affecting the viral load and the stability of gargling samples as well as the diagnostic sensitivity of the RT-LAMP assay. We performed >35,000 tests during the pandemic, with an average turnover time of fewer than 6 hours from sample arrival at the test station to result announcement. Altogether, our work provides a blueprint for fast, sensitive, scalable, cost- and labor-efficient RT-LAMP diagnostics. As RT-LAMP-based testing requires advanced, but non-specialized laboratory equipment, it is independent of potentially limiting clinical diagnostics supply chains.

Background The aim of our study was to evaluate the long-term prognostic value of blood-based biomarkers in comparison to the established National Institute of Health stroke scale (NIHSS) score in patients with acute ischemic stroke. Methods We measured plasma concentrations of IL-6, NT-proBNP, D-dimer, hs-cTnT, sST2, MR-proADM, MR-proANP, CT-proET-1, Copeptin, and Procalcitonin in 721 consecutive acute ischemic stroke patients within 24 h after admission to our stroke unit. Endpoint was all-cause mortality at 3 years. Results During follow-up, 199 patients died (28%). In univariate Cox proportional hazards regression analyses using a dichotomized approach according to median values, all blood-based biomarkers were associated with prognosis. However, in the multivariate analysis after adjustment for several clinical variables, only IL-6 &gt;7 pg/mL (risk ratio, 3.00; 95% CI, 2.03–4.44; P&lt;0.001), NT-proBNP &gt;447 ng/L (risk ratio, 2.67; 95% CI, 1.81–3.92; P&lt;0.001), NIHSS score &gt;3 (risk ratio, 2.24; 95% CI, 1.63–3.07; P&lt;0.001), Copeptin &gt;13 pmol/L (risk ratio, 1.87; 95% CI, 1.34–2.61; P&lt;0.001), and hs-cTnT &gt;14 ng/L (risk ratio, 1.74; 95% CI, 1.21–2.49; P=0.001) remained independent predictors. ROC curve analysis for mortality prediction demonstrated a higher area under the curve (AUC) for IL-6 and NT-proBNP, respectively, when compared to the NIHSS score (IL-6 AUC 0.81 vs. NIHSS AUC 0.75; P=0.016 and NT-proBNP AUC 0.80 vs. NIHSS AUC 0.75; P=0.039) and similar AUCs when comparing the NIHSS with hs-TnT (hs-TnT AUC 0.77) and Copeptin (Copeptin AUC 0.72). Conclusions In this large cohort of patients with acute ischemic stroke the blood-based biomarkers IL-6, NT-proBNP, hs-cTnT, and Copeptin were strong and independent prognostic markers for 3-year all-cause mortality. IL-6 and NT-proBNP even outperformed the NIHSS score for long-term mortality prediction. ROC plots for 3-year all-cause mortality Funding Acknowledgement Type of funding source: None