Dataset Information

Informing Antibiotic Treatment Decisions: Evaluating Rapid Molecular Diagnostics To Identify Susceptibility and Resistance to Carbapenems against Acinetobacter spp. in PRIMERS III.

ABSTRACT: The widespread dissemination of carbapenem-resistant Acinetobacter spp. has created significant therapeutic challenges. At present, rapid molecular diagnostics (RMDs) that can identify this phenotype are not commercially available. Two RMD platforms, PCR combined with electrospray ionization mass spectrometry (PCR/ESI-MS) and molecular beacons (MB), for detecting genes conferring resistance/susceptibility to carbapenems in Acinetobacter spp. were evaluated. An archived collection of 200 clinical Acinetobacter sp. isolates was tested. Predictive values for susceptibility and resistance were estimated as a function of susceptibility prevalence and were based on the absence or presence of beta-lactamase (bla) NDM, VIM, IMP, KPC, and OXA carbapenemase genes (e.g., bla_OXA-23, bla_OXA-24/40, and bla_OXA-58 found in this study) against the reference standard of MIC determinations. According to the interpretation of MICs, 49% (n = 98) of the isolates were carbapenem resistant (as defined by either resistance or intermediate resistance to imipenem). The susceptibility sensitivities (95% confidence interval [CI]) for imipenem were 82% (74%, 89%) and 92% (85%, 97%) for PCR/ESI-MS and MB, respectively. Resistance sensitivities (95% CI) for imipenem were 95% (88%, 98%) and 88% (80%, 94%) for PCR/ESI-MS and MB, respectively. PRIMERS III establishes that RMDs can discriminate between carbapenem resistance and susceptibility in Acinetobacter spp. In the context of a known prevalence of resistance, SPVs and RPVs can inform clinicians regarding the best choice for empiric antimicrobial therapy against this multidrug-resistant pathogen.

SUBMITTER: Evans SR

PROVIDER: S-EPMC5228224 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Informing Antibiotic Treatment Decisions: Evaluating Rapid Molecular Diagnostics To Identify Susceptibility and Resistance to Carbapenems against Acinetobacter spp. in PRIMERS III.

Evans Scott R SR Hujer Andrea M AM Jiang Hongyu H Hill Carol B CB Hujer Kristine M KM Mediavilla Jose R JR Manca Claudia C Tran Thuy Tien T TT Domitrovic T Nicholas TN Higgins Paul G PG Seifert Harald H Kreiswirth Barry N BN Patel Robin R Jacobs Michael R MR Chen Liang L Sampath Rangarajan R Hall Thomas T Marzan Christine C Fowler Vance G VG Chambers Henry F HF Bonomo Robert A RA

Journal of clinical microbiology 20161228 1

The widespread dissemination of carbapenem-resistant Acinetobacter spp. has created significant therapeutic challenges. At present, rapid molecular diagnostics (RMDs) that can identify this phenotype are not commercially available. Two RMD platforms, PCR combined with electrospray ionization mass spectrometry (PCR/ESI-MS) and molecular beacons (MB), for detecting genes conferring resistance/susceptibility to carbapenems in Acinetobacter spp. were evaluated. An archived collection of 200 clinical ...[more]

PMID: 27795336

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Project description:Background: Antibiotics are often prescribed empirically to treat infection syndromes before causative bacteria and their susceptibility to antibiotics are identified. Guidelines on empiric antibiotic prescribing are key to effective treatment of infection syndromes, and need to be informed by likely bacterial aetiology and antibiotic resistance patterns. We aimed to create a clinically-relevant composite index of antibiotic resistance for common infection syndromes to inform recommendations at the national level. Methods: To create our index, we used open-access antimicrobial resistance (AMR) surveillance datasets, including the ECDC Surveillance Atlas, CDDEP ResistanceMap, WHO GLASS and the newly-available Pfizer ATLAS dataset. We integrated these with data on aetiology of common infection syndromes, existing empiric prescribing guidelines, and pricing and availability of antibiotics. Results: The ATLAS dataset covered many more bacterial species (287) and antibiotics (52) than other datasets (ranges = 8-11 and 16-32 respectively), but had a similar number of samples per country per year. Using these data, we were able to make empiric prescribing recommendations for bloodstream infection, pneumonia and cellulitis/skin abscess in up to 44 countries. There was insufficient data to make national-level recommendations for the other six syndromes investigated. Results are presented in an interactive web app, where users can visualise underlying resistance proportions to first-line empiric antibiotics for infection syndromes and countries of interest. Conclusions: We found that whilst the creation of a composite resistance index for empiric antibiotic therapy was technically feasible, the ATLAS dataset in its current form can only inform on a limited number of infection syndromes. Other open-access AMR surveillance datasets are largely limited to bloodstream infection specimens and cannot directly inform treatment of other syndromes. With improving availability of international AMR data and better understanding of infection aetiology, this approach may prove useful for informing empiric prescribing decisions in settings with limited local AMR surveillance data.

Dataset Information

Informing Antibiotic Treatment Decisions: Evaluating Rapid Molecular Diagnostics To Identify Susceptibility and Resistance to Carbapenems against Acinetobacter spp. in PRIMERS III.

Publications

Informing Antibiotic Treatment Decisions: Evaluating Rapid Molecular Diagnostics To Identify Susceptibility and Resistance to Carbapenems against Acinetobacter spp. in PRIMERS III.

Similar Datasets

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