Characterization of MRSA in Canada from 2007 to 2016
Bibliographic record
Abstract
OBJECTIVES: This study assessed the demographic and molecular characteristics of community-associated (CA) and healthcare-associated (HA) MRSA genotypes in Canadian hospitals between 2007 and 2016. METHODS: A total of 1963 MRSA were identified among 9103 Staphylococcus aureus isolates collected from inpatients and outpatients presenting to tertiary-care medical centres across Canada. Antimicrobial susceptibility testing was performed by broth microdilution in accordance with CLSI standards (M7 11th edition, 2018). PCR was performed to detect the Panton-Valentine leucocidin (PVL) genes and molecular analysis was performed by spa typing. RESULTS: Between 2007 and 2016, the annual proportion of S. aureus that were MRSA decreased from 26.1% to 16.9% (P < 0.0001). The proportion of CA-MRSA genotypes increased significantly from 20.8% in 2007 to 56.3% in 2016 (P < 0.0001) while HA-MRSA genotypes decreased from 79.2% to 43.8% throughout the study period (P < 0.0001). Predominant genotypes included HA genotype CMRSA2 (USA100/800) (53.6%) and CA genotype CMRSA10 (USA300) (24.9%). PVL was present in 30.1% of all MRSA isolates, including 78.4% of CA-MRSA and 1.7% of HA-MRSA genotypes. Resistance to clarithromycin, clindamycin, trimethoprim/sulfamethoxazole and fluoroquinolones decreased significantly over time (P < 0.0001). CONCLUSIONS: The proportion of MRSA in Canada declined between 2007 and 2016. In contrast, the proportion of CA-MRSA strain types, particularly CMRSA10 (USA300), continues to increase. In 2016, CA-MRSA genotypes surpassed HA-MRSA as the most common cause of MRSA infections in Canadian hospitals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".