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Record W2571505402 · doi:10.1093/ofid/ofw194.126

Characterization of Clinical Methicillin-Resistant Staphylococcus aureus (MRSA) Isolates From Canadian Hospitals, 2010–2015

2016· article· en· W2571505402 on OpenAlexaffabout
Ana Cabrera, George R. Golding, Jennifer Campbell, Linda Pelude, Elizabeth Bryce, Charles Frenette, Denise Gravel, Kevin Katz, Allison McGeer, Stephanie Smith, Karl Weiss, Andrew E. Simor

Bibliographic record

VenueOpen Forum Infectious Diseases · 2016
Typearticle
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsHôpital Maisonneuve-RosemontHealth Sciences CentreAlberta Hospital EdmontonMcGill UniversityUniversity of Alberta HospitalPublic Health Agency of CanadaVancouver Coastal HealthSunnybrook Health Science CentreNorth York General HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineMethicillin-resistant Staphylococcus aureusStaphylococcus aureusMicrobiologyStaphylococcal infectionsBacteriaBiology

Abstract

fetched live from OpenAlex

Background. The Canadian Nosocomial Infection Surveillance Program (CNISP) has been performing prospective laboratory-based surveillance for MRSA infections since 1995. In this study we investigated the changes in MRSA genotypes and antimicrobial susceptibilities from 2010 to 2015. Methods. Clinical (non-screening) MRSA isolates from patients in 59 acute-care Canadian hospitals were included in the study. Pulsed-field gel electrophoresis (PFGE) epidemic type was assigned using spa typing. Spa types t002 and t008 correspond to CMRSA2 (USA100/800) and CMRSA10 (USA300), respectively. Antibiotic susceptibilities were determined by broth microdilution in accordance with CLSI guidelines. Results. A total of 3589 MRSA isolates were submitted: 49.1% were CMRSA2 and 35.5% CMRSA10. Infection sites were as follows: 48.4% bloodstream infections, 18.6% skin/soft tissue, 11.3% respiratory, 9.2% surgical site, 7.9% urine and 4.5% other sites. CMRSA10 was more likely to be recovered from skin/soft tissue, while CAMRSA2 from all other sites. The proportion of CMRSA10 isolates increased from 28.1% in 2010 to 42.2% in 2015 (p < 0.001), whereas CMRSA2 decreased (Figure 1A). Regional differences in genotype distribution were noted: CMRSA10 was predominant in western Canada (Figure 1A). Antimicrobial resistance profiles are shown in Figure 1B. Resistance to clindamycin decreased (from 93.1% in 2010 to 58.8% 2015; p < 0.001), whereas resistance to fusidic acid and high-level resistance to mupirocin increased (6.8% to 12.3%, p < 0.001; and 0.9% to 5.6%, p = 0.001; respectively). Figure 1. A. PFGE type per year/region (CMRSA2 blue; CMRSA10 red). B. CMRSA2/CMRSA10 antibiogram. CLD, clindamycin; ERY, erythromycin; CIP, ciprofloxacin; GEN, gentamicin; LIN, linezolid; RIF, rifampin; TET, tetracycline; SXT, trimethoprim-sulfamethoxazole; VAN, vancomycin; TIG, tigecycline; FUS, fusidic acid; MUP, mupirocin; DAP, daptomycin. Overall resistance rate is shown (blue line). Conclusion. There has been a change in genotypes over the past few years with an increased incidence of CMRSA10 as a cause of infection in Canadian hospitals. This has been associated with increased susceptibility to clindamycin. Resistance to trimethoprim-sulfamethoxazole and tetracycline remains stable and low. Disclosures. All authors: No reported disclosures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.319
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2016
Admission routes2
Has abstractyes

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