Polyclonal Outbreak of Vancomycin-resistant Enterococcus faecium in a Pediatric Oncology Department
Bibliographic record
Abstract
We present a polyclonal outbreak of vancomycin-resistant enterococci (VRE) colonization in a pediatric oncology department and the role of a bundle of actions. After the occurrence of VRE bloodstream infections in 2 patients, an active surveillance of VRE colonization was started. Enhanced infection control measures and closure of the department to new admissions for the first 3 months were implemented. Among 32 patients screened for VRE, 21 were found colonized. Daily prevalence of VRE colonization among hospitalized patients ranged from 40% to 75%, but no new VRE infections occurred. Monthly incidence of VRE colonization decreased from 2.5 to 0.6 cases per 100 occupied bed-days at the end of this outbreak by the implementation of the above-mentioned measures. All VRE isolates tested were Enterococcus faecium carrying VanA gene. Pulsed field gel electrophoresis showed a polyclonal outbreak. A case-control study did not show any particular risk factors for colonization. High use of glycopeptide was noted before study outbreak that was drastically decreased during the study but only temporarily. Control of VRE in pediatric oncology departments with high colonization rates is challenging and requires a multifaceted strategy. Polyclonal spread of VRE found in this study suggests a possible effect of prior antimicrobial overuse and the critical need for antimicrobial stewardship especially in the era of multidrug-resistant bacteria.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".