The evolving epidemiology of Carbapenemase-producing Enterobacterales in Canadian acute care facilities, 2010–2023
Bibliographic record
Abstract
Abstract Background Carbapenemase-producing Enterobacterales (CPE) are associated with substantial morbidity and mortality with limited treatment options and have an ability to spread rapidly in healthcare settings. We analyzed surveillance data from the Canadian Nosocomial Infection Surveillance Program to describe trends and the epidemiology of CPE from 2010 to 2023. Methods Participating acute-care hospitals submitted eligible isolates to the National Microbiology Laboratory for detection of carbapenemase genes. Trained infection control professionals applied standardized definitions to collect epidemiological data by chart review from 30–97 hospitals from 2010 to 2023. Results The national incidence of CPE infection (0.03 to 0.14 per 10,000 patient days; R2 = 0.76) and colonization (0.02 to 0.78 per 10,000 patient days; R2 = 0.83) increased exponentially from 2010 to 2023. We identified rapidly rising rates of healthcare-associated (HA) CPE infections from 2019 to 2023 (0.05 to 0.09 per 10,000 patient-days, p = 0.04), attributed to select hospitals (7/97) which accounted for half (53%) of all HA-CPE infections in 2023. Similarly, we identified that 2023 HA-CPE colonization rates were highest in medium (201–499 beds) and large (≥500 beds) hospitals in the Central region. Most patients did not report international travel (66%) nor receipt of medical care abroad (74%). Travel and receipt of medical care were less commonly reported among blaKPC associated cases (7.1% and 5.3% respectively) compared to blaNDM (55% and 45% respectively) and blaOXA-48 (57% and 39%) associated cases. Furthermore, blaKPC was the predominant carbapenemase among all HA-CPE isolates (62%, 950/1,534). Conclusions Surveillance data from a national network of Canadian acute care hospitals indicates that while the incidence of CPE in Canada remains low, it is accelerating at an exponential rate. Our findings suggest that nosocomial transmission is driving the recent increase in CPE incidence in Canada. Improved infection control measures and antimicrobial stewardship as well as access to newer antimicrobials are all urgently needed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".