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International Journal of Rheumatology
Volume 2016, Article ID 6019268, 5 pages
http://dx.doi.org/10.1155/2016/6019268
Research Article

The Reliability of a Novel Automated System for ANA Immunofluorescence Analysis in Daily Clinical Practice

1Department of Rheumatology and Clinical Immunology, Asklepios Medical Center Bad Abbach, Kaiser-Karl-V-Allee 3, 93077 Bad Abbach, Germany
2Department of Internal Medicine I, University Medical Center Regensburg, 93042 Regensburg, Germany

Received 21 February 2016; Accepted 13 April 2016

Academic Editor: Barri J. Fessler

Copyright © 2016 Mohammed Alsuwaidi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Automated interpretation (AI) systems for antinuclear antibody (ANA) analysis have been introduced based on assessment of indirect immunofluorescence (IIF) patterns. The diagnostic performance of a novel automated IIF reading system was compared with visual interpretation (VI) of IIF in daily clinical practice to evaluate the reduction of workload. ANA-IIF tests of consecutive serum samples from patients with suspected connective tissue disease were carried out using HEp-2 cells according to routine clinical care. AI was performed using a visual analyser (Zenit G-Sight, Menarini, Germany). Agreement rates between ANA results by AI and VI were calculated. Of the 336 samples investigated, VI yielded 205 (61%) negative, 42 (13%) ambiguous, and 89 (26%) positive results, whereas 82 (24%) were determined to be negative, 176 (52%) ambiguous, and 78 (24%) positive by AI. AI displayed a diagnostic accuracy of 175/336 samples (52%) with a kappa coefficient of 0.34 compared to VI being the gold standard. Solely relying on AI, with VI only performed for all ambiguous samples by AI, would have missed 1 of 89 (1%) positive results by VI and misclassified 2 of 205 (1%) negative results by VI as positive. The use of AI in daily clinical practice resulted only in a moderate reduction of the VI workload (82 of 336 samples: 24%).