Predicting Antibiotic Resistance in Gram-Negative Bacilli from Resistance Genes

We developed a rapid high-throughput PCR test and evaluated highly antibiotic-resistant clinical isolates of ( = 2,919), ( = 1,974), ( = 1,150), and ( = 1,484) for several antibiotic resistance genes for comparison with phenotypic resistance across penicillins, cephalosporins, carbapenems, amino...

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Published in:	Antimicrobial agents and chemotherapy Vol. 63; no. 4
Main Authors:	Walker, G Terrance, Quan, Julia, Higgins, Stephen G, Toraskar, Nikhil, Chang, Weizhong, Saeed, Alexander, Sapiro, Vadim, Pitzer, Kelsey, Whitfield, Natalie, Lopansri, Bert K, Motyl, Mary, Sahm, Daniel
Format:	Journal Article
Language:	English
Published:	United States American Society for Microbiology 01-04-2019
Subjects:	Africa Anti-Bacterial Agents Anti-Bacterial Agents - pharmacology Asia Cross Infection - drug therapy Cross Infection - microbiology Drug Resistance, Microbial Drug Resistance, Microbial - genetics Europe Gram-Negative Bacteria Gram-Negative Bacteria - drug effects Gram-Negative Bacteria - genetics Gram-Negative Bacterial Infections Gram-Negative Bacterial Infections - drug therapy Gram-Negative Bacterial Infections - microbiology Humans Mechanisms of Resistance North America Polymerase Chain Reaction - methods South America South America Asia North America Europe Africa antibiotic resistance resistance genes PCR
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Summary:	We developed a rapid high-throughput PCR test and evaluated highly antibiotic-resistant clinical isolates of ( = 2,919), ( = 1,974), ( = 1,150), and ( = 1,484) for several antibiotic resistance genes for comparison with phenotypic resistance across penicillins, cephalosporins, carbapenems, aminoglycosides, trimethoprim-sulfamethoxazole, fluoroquinolones, and macrolides. The isolates originated from hospitals in North America (34%), Europe (23%), Asia (13%), South America (12%), Africa (7%), or Oceania (1%) or were of unknown origin (9%). We developed statistical methods to predict phenotypic resistance from resistance genes for 49 antibiotic-organism combinations, including gentamicin, tobramycin, ciprofloxacin, levofloxacin, trimethoprim-sulfamethoxazole, ertapenem, imipenem, cefazolin, cefepime, cefotaxime, ceftazidime, ceftriaxone, ampicillin, and aztreonam. Average positive predictive values for genotypic prediction of phenotypic resistance were 91% for , 93% for , 87% for , and 92% for across the various antibiotics for this highly resistant cohort of bacterial isolates.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Present address: Natalie Whitfield, GenMark Diagnostics, Inc., Carlsbad, California, USA. Citation Walker GT, Quan J, Higgins SG, Toraskar N, Chang W, Saeed A, Sapiro V, Pitzer K, Whitfield N, Lopansri BK, Motyl M, Sahm D. 2019. Predicting antibiotic resistance in Gram-negative bacilli from resistance genes. Antimicrob Agents Chemother 63:e02462-18. https://doi.org/10.1128/AAC.02462-18.
ISSN:	0066-4804 1098-6596
DOI:	10.1128/AAC.02462-18