Title |
Automated Processing and Evaluation of Anti-Nuclear Antibody Indirect Immunofluorescence Testing
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Published in |
Frontiers in immunology, May 2018
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DOI | 10.3389/fimmu.2018.00927 |
Pubmed ID | |
Authors |
Vincent Ricchiuti, Joseph Adams, Donna J. Hardy, Alexander Katayev, James K. Fleming |
Abstract |
Indirect immunofluorescence (IIF) is considered by the American College of Rheumatology (ACR) and the international consensus on ANA patterns (ICAP) the gold standard for the screening of anti-nuclear antibodies (ANA). As conventional IIF is labor intensive, time-consuming, subjective, and poorly standardized, there have been ongoing efforts to improve the standardization of reagents and to develop automated platforms for assay incubation, microscopy, and evaluation. In this study, the workflow and performance characteristics of a fully automated ANA IIF system (Sprinter XL, EUROPattern Suite, IFA 40: HEp-20-10 cells) were compared to a manual approach using visual microscopy with a filter device for single-well titration and to technologist reading. The Sprinter/EUROPattern system enabled the processing of large daily workload cohorts in less than 8 h and the reduction of labor hands-on time by more than 4 h. Regarding the discrimination of positive from negative samples, the overall agreement of the EUROPattern software with technologist reading was higher (95.6%) than when compared to the current method (89.4%). Moreover, the software was consistent with technologist reading in 80.6-97.5% of patterns and 71.0-93.8% of titers. In conclusion, the Sprinter/EUROPattern system provides substantial labor savings and good concordance with technologist ANA IIF microscopy, thus increasing standardization, laboratory efficiency, and removing subjectivity. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 43 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 9 | 21% |
Other | 5 | 12% |
Researcher | 4 | 9% |
Student > Master | 4 | 9% |
Student > Ph. D. Student | 3 | 7% |
Other | 6 | 14% |
Unknown | 12 | 28% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 10 | 23% |
Medicine and Dentistry | 9 | 21% |
Immunology and Microbiology | 4 | 9% |
Agricultural and Biological Sciences | 3 | 7% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 2% |
Other | 4 | 9% |
Unknown | 12 | 28% |