Transmission of carbapenemase-producing Enterobacter in Ontario, Canada: a retrospective genomic analysis
Bibliographic record
Abstract
Carbapenemase-producing Enterobacter (CP-Ent) are the third most prevalent species of CP-Enterobacteriaceae worldwide and exhibit greater strain diversity than other CP-species. This study aimed to describe the genomic epidemiology of CP-Ent in south-central Ontario, Canada. CP-Ent isolates collected from colonised/infected patients identified by population-based surveillance in Toronto/Peel Region, Canada (2007-2020), sink/shower drains in 12 regional hospitals (2016-2019), and five municipal wastewater treatment plants (2015, 2017) were analysed to assess relationships between patient and environmental CP-Ent. Clinical data were collected by chart review/patient interview. CP-Ent isolates were sequenced by Illumina. Genomic analysis included Snippy, IQ-Tree, and ClonalFrameML; ≤ 20 single-nucleotide variant differences defined strains. CP-Ent colonisation/infection incidence increased from 2007-2020. Overall, 3.5% of sink/shower drains and 22% of municipal wastewater cultures yielded CP-Ent. Patient and sink/shower drain isolates were similar in species and carbapenemases produced; municipal wastewater isolates were distinct. Forty-one of 116 patients (35%) belonged to 15 transmission clusters: 5/15 (33%) included drain isolates, and 32/41 (78%) patients were linked to others in the same hospital, including 22 (54%) linked by stays in the same ward. Patients were more likely to be linked by ward exposure at different times versus the same time in wards with sink/shower drains yielding CP-Ent versus those without (13/19 vs 2/23, p=<.001). Despite transmission control efforts, a significant proportion of CP-Ent are part of hospital transmission clusters; sink/shower drains may be implicated in transmission. It is likely that undetected patients, drains and/or other reservoirs contribute to CP-Ent transmission in the studied population.
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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) | 0.000 | 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) | 0.000 | 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".