Spatial distribution of <i>Escherichia coli</i> ST131 C subclades in a centralized Canadian urban region
Bibliographic record
Abstract
INTRODUCTION: Escherichia coli ST131 is the most common multidrug-resistant (MDR) E. coli clone causing bloodstream infections (BSIs) in Calgary. This study describes patient characteristics and spatial distribution of ST131 subclades C1 and C2 causing BSIs in Calgary. METHODS: E. coli from blood (n = 685) obtained in Calgary, Canada, (2016) were PCR screened for ST131 and positives (n = 141) underwent whole genome sequencing. Patient characteristics were analysed using Fisher's Exact/t-tests and spatial analysis was used to identify clusters. RESULTS: Overall, 21% of E. coli was identified as ST131 and clade C dominated the population. ST131-C2 was associated with blaCTX-M-15 and significantly more MDR than ST131-C1. The spatial distribution in Calgary showed that ST131-C1 was mainly present in long-term care (LTC) residents whereas ST131-C2 clustered in a specific North East (NE) Calgary sector comprising of six neighbourhoods without LTC centres. This NE sector has high immigration and travel rates from the Indian subcontinent. CONCLUSIONS: This study showed that ST131 C subclades have different geographical distribution patterns in Calgary. We believe that recent travel to and immigration from certain high-risk regions for antimicrobial resistance are responsible for the ST131-C2 NE Calgary clustering pattern.
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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 | 0.002 | 0.004 |
| 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) | 0.002 | 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".