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Background  The establishment of therapeutic regimens for mycobacteriosis depends on the accurate identification of  Mycobacterium  species, and misdiagnosis can result in inappropriate treatment and increased mortality of patients. Differential diagnosis among  Mycobacterium  species has been made by conventional phenotypic and biochemical tests after a long culture period. Specialized molecular diagnostics of mycobacteria allows rapid detection and species identification; however, such tests are not available in public health programs. Our aim was to demonstrate the clinical implications of erroneous diagnosis by performing molecular genotyping of mycobacterial infections in patients that were diagnosed based on symptoms, culture and bacilloscopy.    Methods  Culture samples of mycobacterial infections from 55 patients clinically diagnosed as tuberculosis in 2013 and 2014, based on conventional methods, were identified by PCR -RFLP and results are discussed.    Results  We have confirmed 35 (63.6 %) positive samples as  M. tuberculosis , but 18 (32.7 %) were identified as non-tuberculous mycobacteria ( M. avium  type 1,  M. avium  type 2,  M. kansasii  type 1 type 1,  M. mucogenicum ,  M. chelonae , M. terrae type 3, and 1 unknown RFLP pattern) and two were negative. Regarding clinical diagnosis, 61.8 % (34/55) was classified as pulmonary tuberculosis. It is important to emphasize that 36.4 % (20/55) of samples were misdiagnosed by conventional methods, and 11 (61.1 %) of the HIV positive patients (18/55) were NTM-coinfected.    Conclusion  The identification of species in mycobacterial infections is essential for correct diagnosis and choice of treatment regimen, and misdiagnosis by conventional tools can lead to chronic disease, increased resistance and death.    Electronic supplementary material  The online version of this article (doi:10.1186/s12879-016-1474-6) contains supplementary material, which is available to authorized users.

Diagnosis of mycobacterial infections based on acid-fast bacilli test and bacterial growth time and implications on treatment and disease outcome