Decrease in the prevalence of antimicrobial resistance in Escherichia coli isolates of Canadian turkey flocks driven by the implementation of an antimicrobial stewardship program
Bibliographic record
Abstract
The emergence of antimicrobial-resistant organisms at the human-animal-environment interface has raised global concern prompting governments and various stakeholders to take action. As a part of the stewardship initiative, Canadian turkey producers have implemented an antimicrobial use (AMU) strategy to manage antimicrobial resistance (AMR) in their sector. This study evaluated farm-level AMU and AMR data collected between 2016 and 2021 in major turkey-producing provinces/regions through the Canadian Integrated Program for Antimicrobial Resistance Surveillance to assess the progress of the strategy by characterizing the prevalence of homologous and multidrug resistance (MDR) in Escherichia coli isolated from turkeys. Multivariable mixed-effect logistic regression models assessed temporal and provincial/regional variations in AMR and MDR. Negative binomial regression models examined the temporal and regional variations in the total AMU. The total AMU (measured in mg/kg turkey biomass) significantly decreased in all provinces/regions in 2020 and 2021. Escherichia coli isolates from turkey flocks showed a significant decrease in resistance to gentamicin, sulfisoxazole, and tetracyclines during the six-year study period, consistent with the timing of the AMU reduction strategy. The prevalence of MDR isolates was significantly lower in 2020 and 2021 compared to 2016. Higher prevalence was observed in the Western region compared to Québec and Ontario. Two common AMR patterns were identified: ampicillin-streptomycin-tetracyclines and streptomycin-sulfisoxazole-tetracyclines. These AMR patterns indicate possible cross-resistances (same class), co-selection (unrelated classes) for resistance, or potential carryover of resistance determinants from previous production cycles. The decreasing prevalence of resistance to homologous antimicrobials, MDR, and AMU quantity are suggestive that the turkey sector's AMU strategy is achieving its desired impact. However, antimicrobials previously eliminated for preventive use in turkey flocks and the use of highly important antimicrobials in human medicine suggest that the AMU reduction strategy should be monitored and re-evaluated periodically to mitigate the emergence of MDR bacteria and safeguard animal and public health.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".