Frequency of MCR-1-mediated colistin resistance among Escherichia coli clinical isolates obtained from patients in Canadian hospitals (CANWARD 2008-2015)
Bibliographic record
Abstract
Background: Colistin is often used as an antimicrobial of last resort for the treatment of infections caused by multidrug-resistant gram-negative bacilli. In 2015, plasmid-mediated colistin resistance in Escherichia coli due to MCR-1 was described. The purpose of this study was to evaluate the frequency of colistin resistance among E. coli clinical isolates obtained from patients in Canadian hospitals as part of the Canadian Ward Surveillance Study (CANWARD) and to determine how often the mcr-1 gene is detected among the colistin-resistant subset. Methods: From January 2008 to December 2015 (excluding 2011), 10 to 15 sentinel hospitals submitted consecutive clinical isolates (1 per patient per infection site) from blood (100-240), respiratory (100-150), urine (25-100) and wound (25-100) infections. We performed susceptibility testing using Clinical and Laboratory Standards Institute broth microdilution methods. Isolates that showed resistance to colistin as defined by European Committee on Antimicrobial Susceptibility Testing breakpoints (minimum inhibitory concentration ≥ 4 µg/mL) were evaluated for the mcr-1 gene by polymerase chain reaction. Results: In total, 5571 E. coli clinical isolates were obtained over the study years. Twelve isolates (0.2%) were resistant to colistin. The proportion of colistin-resistant isolates varied from 0.0% to 0.5% depending on the study year, and there was no clear trend toward increasing resistance over time. Typically the colistin-resistant isolates remained susceptible to antimicrobials from several other classes. Two colistin-resistant isolates (0.04%) were found to harbour the mcr-1 gene. Interpretation: The results suggest that colistin resistance among E. coli human clinical isolates, including resistance mediated by the mcr-1 gene, remains rare in 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".