Diagnosis of nontuberculous mycobacterial infections.

Link to article at PubMed

Diagnosis of nontuberculous mycobacterial infections.

Semin Respir Crit Care Med. 2013 Feb;34(1):103-9

Authors: van Ingen J

Abstract
The nontuberculous mycobacteria (NTM) are typically environmental organisms residing in soil and water. Although generally of low pathogenicity to humans, NTM can cause a wide array of clinical diseases; pulmonary disease is most frequent, followed by lymphadenitis in children, skin disease by M. marinum (particularly in fish tank fanciers), and other extrapulmonary or disseminated infections in severely immunocompromised patients. Of the >140 NTM species reported in the literature, 25 species have been strongly associated with NTM diseases; the remainder are environmental organisms rarely encountered in clinical samples. Correct species identification is very important because NTM species differ in their clinical relevance. Further, NTM differ strongly in their growth rate, temperature tolerance, and drug susceptibility. The diagnosis of NTM disease is complex and requires good communication between clinicians, radiologists, and microbiologists. Isolation of M. kansasii and (in northwestern Europe) M. malmoense from pulmonary specimens usually indicates disease, whereas Mycobacterium gordonae and, to a lesser extent, M. simiae or M. chelonae are typically contaminants rather than causative agents of true disease. Mycobacterium avium complex (MAC), M. xenopi, and M. abscessus form an intermediate category between these two extremes. This review covers the clinical and laboratory diagnosis of NTM diseases and particularities for the different disease types and patient populations. Because of limited sensitivity and specificity of symptoms, radiology, and direct microscopy of clinical samples, culture remains the gold standard. Yet culture is time consuming and demands the use of multiple media types and incubation temperatures to optimize the yield. Outside of reference centers, such elaborate culture algorithms are scarce.

PMID: 23460010 [PubMed - in process]

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