ArticleInfection and drug resistance2015
Discrepancy in MALDI-TOF MS identification of uncommon Gram-negative bacteria from lower respiratory secretions in patients with cystic fibrosis.
Article in Infection and drug resistance, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 28 citations in OpenAlex.
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- Approaching two decades of cystic fibrosis research in Qatar: a historical perspective and future directions.Multidisciplinary respiratory medicine · 2019Review
- Molecular Typing and Carbapenem Resistance Mechanisms ofFrontiers in microbiology · 2018Article
- Clinical and microbiological profile of chronic Burkholderia cepacia complex infections in a cystic fibrosis reference hospital in Brazil.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2017Article
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6 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
introductionEarly identification of microbial organisms from respiratory secretions of patients with cystic fibrosis (CF) is important to guide therapeutic decisions. The objective was to compare the accuracy of matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) relative to the conventional phenotypic method in identifying common bacterial isolates, including nonfermenting Gram-negative bacteria, in a cohort of patients with CF.
methodsA total of 123 isolates from 50 patients with CF representing 14 bacterial species from respiratory specimens were identified using MALDI-TOF MS in parallel with conventional phenotypic methods. Discrepancies were confirmed by 16S ribosomal RNA (rRNA) gene sequencing in five Gram-negative isolates.
resultsThe MALDI-TOF MS managed to identify 122/123 (99.2%) bacterial isolates to the genus level and 118/123 (95.9%) were identified to the species level. The MALDI-TOF MS results were 100% consistent to the species level with conventional phenotypic identification for isolates of Staphylococcus aureus, Pseudomonas aeruginosa, Haemophilus influenzae, Streptococcus pyogenes, Achromobacter xylosoxidans, Stenotrophomonas maltophilia, and other uncommon organisms such as Chryseobacterium gleum and Enterobacter cloacae. The 5/123 (4.6%) isolates misidentified were all Gram-negative bacteria. The isolation of E. cloacae and Haemophilus paraphrohaemolyticus may extend the potentially pathogenic list of organisms isolated from patients with CF.
conclusionAlthough the technique provides an early identification and antimicrobial therapy approach in patients with CF, limitation in the diagnosis of uncommon Gram-negative bacteria may exist.
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