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1000 Titel
  • Evaluation of accuracy, exclusivity, limit-of-detection and ease-of-use of LumiraDx™: An antigen-detecting point-of-care device for SARS-CoV-2
1000 Autor/in
  1. Krüger, Lisa J. |
  2. Klein, Julian A. F. |
  3. Tobian, Frank |
  4. Gaeddert, Mary |
  5. Lainati, Federica |
  6. Klemm, Sarah |
  7. Schnitzler, Paul |
  8. Bartenschlager, Ralf |
  9. Cerikan, Berati |
  10. Neufeldt, Christopher J. |
  11. Nikolai, Olga |
  12. Lindner, Andreas K. |
  13. Mockenhaupt, Frank P. |
  14. Seybold, Joachim |
  15. Jones, Terry C. |
  16. Corman, Victor M. |
  17. Pollock, Nira R. |
  18. Knorr, Britta |
  19. Welker, Andreas |
  20. de Vos, Margaretha |
  21. Sacks, Jilian A. |
  22. Denkinger, Claudia |
  23. Assaad, K. |
  24. Fuhs, A. |
  25. Harter, C. |
  26. Schulze, C. |
  27. Schmitt, G. |
  28. Klemmer, Anja |
  29. Müller, Rico |
  30. Fink, Martina |
  31. Fougereau, Mathilde |
  32. Schirmer, Maximilian |
  33. Small, Annika |
  34. Meinlschmidt, Matthias |
  35. Dürr, Valerie |
  36. Schuckert, Alina |
  37. Backes, Ann-Kathrin |
  38. Steinke, Salome |
  39. Ellinghaus, Henrik |
  40. Abutaima, Loai |
  41. Kollatzsch, Mandy |
  42. Wintel, Mia |
  43. Kausch, Franka |
  44. Hommes, Franziska |
  45. Bölke, Alisa |
  46. Bernhard, Julian |
  47. Hülso, Claudia |
  48. Linzbach, Elisabeth |
  49. Rössig, Heike |
  50. Gertler, Maximilian |
  51. Burock, Susen |
  52. von dem Busche, Katja |
  53. Patberg, Stephanie |
1000 Erscheinungsjahr 2021
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-08-12
1000 Erschienen in
1000 Quellenangabe
  • 50(2):395-406
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1007/s15010-021-01681-y |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8358901/ |
1000 Publikationsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Purpose!#!Rapid antigen-detecting tests (Ag-RDTs) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can transform pandemic control. Thus far, sensitivity (≤ 85%) of lateral-flow assays has limited scale-up. Conceivably, microfluidic immunofluorescence Ag-RDTs could increase sensitivity for SARS-CoV-2 detection.!##!Methods!#!This multi-centre diagnostic accuracy study investigated performance of the microfluidic immunofluorescence LumiraDx™ assay, enrolling symptomatic and asymptomatic participants with suspected SARS-CoV-2 infection. Participants collected a supervised nasal mid-turbinate (NMT) self-swab for Ag-RDT testing, in addition to a professionally collected nasopharyngeal (NP) swab for routine testing with reverse transcriptase polymerase chain reaction (RT-PCR). Results were compared to calculate sensitivity and specificity. Sub-analyses investigated the results by viral load, symptom presence and duration. An analytical study assessed exclusivity and limit-of-detection (LOD). In addition, we evaluated ease-of-use.!##!Results!#!The study was conducted between November 2nd 2020 and 4th of December 2020. 761 participants were enrolled, with 486 participants reporting symptoms on testing day. 120 out of 146 RT-PCR positive cases were detected positive by LumiraDx™, resulting in a sensitivity of 82.2% (95% CI 75.2-87.5%). Specificity was 99.3% (CI 98.3-99.7%). Sensitivity was increased in individuals with viral load ≥ 7 log10 SARS-CoV2 RNA copies/ml (93.8%; CI 86.2-97.3%). Testing against common respiratory commensals and pathogens showed no cross-reactivity and LOD was estimated to be 2-56 PFU/mL. The ease-of-use-assessment was favourable for lower throughput settings.!##!Conclusion!#!The LumiraDx™ assay showed excellent analytical sensitivity, exclusivity and clinical specificity with good clinical sensitivity using supervised NMT self-sampling.!##!Trial registration number and registration date!#!DRKS00021220 and 01.04.2020.
1000 Sacherschließung
lokal
lokal COVID-19/diagnosis [MeSH]
lokal Diagnostic accuracy
gnd 1206347392 COVID-19
lokal Point-of-Care Systems [MeSH]
lokal Antigen-detecting diagnostics
lokal Humans [MeSH]
lokal RNA, Viral [MeSH]
lokal Point-of-care
lokal COVID-19 / SARS-CoV-2
lokal Covid-19
lokal Pandemics [MeSH]
lokal Sensitivity and Specificity [MeSH]
lokal Original Paper
lokal SARS-CoV-2 [MeSH]
1000 Liste der Beteiligten
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