Performance of a novel algorithm using automated digital microscopy for diagnosing tuberculosis

Show simple item record Ismail, Nazir Ahmed Omar, S.V. (Shaheed Vally) Lewis, James J. Dowdy, David W. Dreyer, Andries W. Van der Meulen, Hermina Nconjana, George Clark, David A. Churchyard, Gavin J. 2015-08-21T10:28:10Z 2015-08-21T10:28:10Z 2015-06
dc.description.abstract RATIONALE : TBDx automated microscopy is a novel technology that processes digital microscopic images to identify acid-fast bacilli (AFB). Use of TBDx as part of a diagnostic algorithm could improve the diagnosis of tuberculosis (TB), but its performance characteristics have not yet been formally tested. OBJECTIVES : To evaluate the performance of the TBDx automated microscopy system in algorithms for diagnosis of TB. METHODS : Prospective samples from patients with presumed TB were processed in parallel with conventional smear microscopy, TBDx microscopy, and liquid culture. All TBDx-positive specimens were also tested with the Xpert MTB/RIF (GXP) assay. We evaluated the sensitivity and specificity of two algorithms-(1) TBDx-GXP (TBDx with positive specimens tested by Xpert MTB/RIF) and (2) TBDx alone-against the gold standard liquid media culture. MEASUREMENTS AND MAIN RESULTS : Of 1,210 samples, 1,009 were eligible for evaluation, of which 109 were culture positive for Mycobacterium tuberculosis. The TBDx system identified 70 specimens (68 culture positive) as having 10 or more putative AFB (high positive) and 207 (19 culture positive) as having 1-9 putative AFB (low positive). An algorithm in which "low-positive" results on TBDx were confirmed by GXP had 78% sensitivity (85 of 109) and 99.8% specificity (889 of 900), requiring 21% (207 of 1,009) specimens to be processed by GXP. As a stand-alone test, a "high-positive" result on TBDx had 62% sensitivity and 99.7% specificity. CONCLUSIONS : TBDx used in diagnostic algorithms with GXP provided reasonable sensitivity and high specificity for active TB while dramatically reducing the number GXP tests performed. As a stand-alone microscopy system, its performance was equivalent to that of a highly experienced TB microscopist. en_ZA
dc.description.embargo 2016-06-30 en_ZA
dc.description.librarian hb2015 en_ZA
dc.description.uri en_ZA
dc.identifier.citation Ismail, NA, Omar, SV, Lewis, JJ, Dowdy, DW, Dreyer, AW, Van der Meulen, H, Nconjana, G, Clark, DA & Churchyard, GJ 2015, 'Performance of a novel algorithm using automated digital microscopy for diagnosing tuberculosis', American Journal of Respiratory and Critical Care Medicine, vol. 191, no. 12, pp. 1443-1449. en_ZA
dc.identifier.issn 1073-449X (print)
dc.identifier.issn 1535-4970 (online)
dc.identifier.other 10.1164/rccm.201502-0390OC
dc.language.iso en en_ZA
dc.publisher American Thoracic Society en_ZA
dc.rights © 2015 American Thoracic Society. en_ZA
dc.subject TBDx en_ZA
dc.subject Xpert en_ZA
dc.subject Microscopy en_ZA
dc.subject Triage en_ZA
dc.subject Tuberculosis (TB) en_ZA
dc.subject Acid-fast bacilli (AFB) en_ZA
dc.title Performance of a novel algorithm using automated digital microscopy for diagnosing tuberculosis en_ZA
dc.type Postprint Article en_ZA

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