Preparedness for <i>Candida auris</i> in Canadian Nosocomial Infection Surveillance Program (CNISP) hospitals, 2024
Bibliographic record
Abstract
Abstract Objective: To assess preparedness for Candida auris in Canadian hospitals. Design: Cross-sectional survey. Setting: Canadian Nosocomial Infection Surveillance Program (CNISP) hospitals. Methods: In June 2024, surveys were e-mailed to the infection prevention and control departments of 109 CNISP hospitals and their 33 microbiology laboratories. The surveys assessed policies for patient screening/management and laboratory processes supporting C. auris transmission prevention. Results were compared to a similar 2018 survey. Results: All 109 hospitals and 32/33 laboratories responded. Most hospitals had policies for admission screening (80%, 87/109) and policies/defined plans for post-exposure screening (95%, 104/109). Policy presence increased from 18% to 73% in 56 hospitals completing both 2018 and 2024 surveys ( P < 0.001). Among hospitals with admission screening policies, 69% (60/87) screened for recent out-of-country hospitalization. All but one hospital implemented transmission-based precautions for cases; 70% (76/109) continued precautions indefinitely. Overall, 94% (99/105; excluding hospitals with exclusively private rooms) and 55% (60/109) of hospitals screened roommates and wardmates, respectively. Frequency and timing of screening and policies regarding precautions for exposed patients varied. All hospitals used axilla and groin swabs, at minimum, for screening. Most (81%, 26/32) laboratories identified all clinically significant Candida isolates to species level, increasing from 48% to 85% ( P < 0.001) in the 27 laboratories completing both 2018 and 2024 surveys. Twenty-four laboratories (75%) had standard operating procedures for processing screening specimens; 96% (23/24) used direct plating onto chromogenic agar. Conclusions: Despite progress in C. auris preparedness, areas for improvement remain. Variability in practice may be related to evidence gaps and resource constraints.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".