Dissemination of Verona Integron-encoded Metallo-β-lactamase among clinical and environmental Enterobacteriaceae isolates in Ontario, Canada
Bibliographic record
Abstract
Abstract Surveillance data from Southern Ontario show that a majority of Verona Integron-encoded Metallo-β-lactamase (VIM)-producing Enterobacteriaceae are locally acquired. To better understand the local epidemiology, we analysed clinical and environmental bla VIM -positive Enterobacteriaceae from the area. Clinical samples were collected within the Toronto Invasive Bacterial Diseases Network (2010–2016); environmental water samples were collected in 2015. We gathered patient information on place of residence and hospital admissions prior to the diagnosis. Patients with and without plausible source of acquisition were compared regarding risk exposures. Microbiological isolates underwent whole-genome sequencing (WGS); bla VIM carrying plasmids were characterized. We identified 15 patients, thereof 11 with bla VIM-1 -positive Enterobacter hormaechei within two genetic clusters based on WGS. Whereas no obvious epidemiologic link was identified among cluster I patients, those in cluster II were connected to a hospital outbreak. Except for patients with probable acquisition abroad, we did not identify any further risk exposures. Two bla VIM-1 -positive E. hormaechei from environmental waters matched with the clinical clusters; plasmid sequencing suggested a common ancestor plasmid for the two clusters. These data show that both clonal spread and horizontal gene transfer are drivers of the dissemination of bla VIM-1 -carrying Enterobacter hormaechei in hospitals and the aquatic environment in Southern Ontario, Canada.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".