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Jornal Brasileiro de Patologia e Medicina Laboratorial

On-line version ISSN 1678-4774


OPLUSTIL, Carmen Paz; TEIXEIRA, Sonia Regina; OSUGUI, Silvia Kimie  and  MENDES, Caio F.. Impact of automation in the diagnosis of mycobacterial infection. J. Bras. Patol. Med. Lab. [online]. 2002, vol.38, n.3, pp.167-173. ISSN 1678-4774.

Tuberculosis is a disease of worldwide importance and several years ago in many countries the disease was almost eradicated. With the advent of Aids infection, new cases of the disease started to emerge with the appearance of multiple drug resistant strains. Together with the increase in tuberculosis cases, diagnostic methodologies showed an advance and nowadays there are several manual and automated methodologies for the diagnosis of these infections. The Bactec 460 (Becton Dickinson Diagnostic Systems, Sparks, MD) system is used for the direct detection of mycobacteria in clinical specimens, for susceptibility testing against tuberculostatic drugs and differentiation of Mycobacterium tuberculosis complex from other species not of the complex, shortening the process in several days. In this study we evaluated the impact of the introduction of an automated system. In the period of January to June 1995, 326 specimens were processed using the traditional methodology of culture in Lowenstein-Jensen (LJ). Thirty-nine (12%) were positive being 77% of these identified as M. tuberculosis. Of the total of 39 positive cultures for M. tuberculosis, 29 (74.3%) showed a time for detection greater than 30 days. In the same period in the year of 1997 with the introduction of the semiautomated system, 340 specimens were processed of which 50 (14.7%) were positive being 46% of these M. tuberculosis. The mean time for detection of positive cultures for M. tuberculosis was 12 days. The use of the automated system for culture of mycobacteria showed an increase in the number of different species isolated from different specimens, decreasing the time for detection and allowing a better and safe condition for technicians while executing theses procedures.

Keywords : Mycobacteria ; Laboratory diagnostic ; Automated detection.

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