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Feasibility of the TBDx automated digital microscopy system for the diagnosis of pulmonary tuberculosis

  • Pamela Nabeta
  • , Joshua Havumaki
  • , Dang Thi Minh Ha
  • , Tatiana Caceres
  • , Pham Thu Hang
  • , Jimena Collantes
  • , Nguyen Thi Ngoc Lan
  • , Eduardo Gotuzzo
  • , Claudia M. Denkinger
  • FIND
  • Pham NgocThach Hospital
  • Universidad Peruana Cayetano Heredia, Instituto de Medicina Tropical Alexander von Humboldt

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Background: Improved and affordable diagnostic or triage tests are urgently needed at the microscopy centre level. Automated digital microscopy has the potential to overcome issues related to conventional microscopy, including training time requirement and inconsistencies in results interpretation. Methods: For this blinded prospective study, sputum samples were collected from adults with presumptive pulmonary tuberculosis in Lima, Peru and Ho Chi Minh City, Vietnam. TBDx performance was evaluated as a stand-alone and as a triage test against conventional microscopy and Xpert, with culture as the reference standard. Xpert was used to confirm positive cases. Findings: A total of 613 subjects were enrolled between October 2014 and March 2015, with 539 included in the final analysis. The sensitivity of TBDx was 62-2% (95% CI 56-6-67-4) and specificity was 90-7% (95% CI 85-9-94-2) compared to culture. The algorithm assessing TBDx as a triage test achieved a specificity of 100% while maintaining sensitivity. Interpretation: While the diagnostic performance of TBDx did not reach the levels obtained by experienced microscopists in reference laboratories, it is conceivable that it would exceed the performance of less experienced microscopists. In the absence of highly sensitive and specific molecular tests at the microscopy centre level, TBDx in a triage-testing algorithm would optimize specificity and limit overall cost without compromising the number of patients receiving up-front drug susceptibility testing for rifampicin. However, the algorithm would miss over one third of patients compared to Xpert alone.

Original languageEnglish
Article numbere0173092
JournalPLoS ONE
Volume12
Issue number3
DOIs
StatePublished - Mar 2017

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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