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.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".