The State of Antimicrobial Resistance of Gram-Negative Bacilli in Canada
Bibliographic record
Abstract
In the last two decades, there has been an increase in resistance among Gram-negative bacteria in Canada. From 2007 to 2016, the proportion of ESBL-producing isolates among Escherichia coli and Klebsiella pneumoniae isolates increased from 3.5% to 11.1%. There has also been an increase in carbapenem use over this time period, which may be contributing to the increasing prevalence of carbapenemase-producing Enterobacterales (CPE) in Canada. CPE, which were historically associated with travel, are now mostly acquired domestically. The prevalence of multi-drug resistant (MDR) Pseudomonas aeruginosa has decreased slightly, possibly due to decreasing use of fluoroquinolones and aminoglycosides. Many of the most effective antimicrobials for the treatment of infections with resistant Gram-negative organisms, including many of the novel β-lactam/β-lactamase inhibitors (βL/βLIs), are not marketed in Canada. A coordinated focus on antimicrobial stewardship and infection control is necessary to slow the spread of resistance and to preserve the efficacy of our current antimicrobials for future generations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".