Clinical and microbiological characteristics of bloodstream infections due to AmpC β-lactamase producing Enterobacteriaceae: an active surveillance cohort in a large centralized Canadian region
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to describe the clinical and microbiological characteristics of bloodstream infections (BSIs) due to AmpC producing Enterobacteriaceae (AE) in a large centralized Canadian region over a 9-year period. METHODS: An active surveillance cohort design in Calgary, Canada. RESULTS: A cohort of 458 episodes of BSIs caused by AE was assembled for analysis. The majority of infections were of nosocomial origin with unknown sources. Enterobacter spp. was the most common species while BSIs due to Serratia spp. had a significant higher mortality when compared to other AE. Delays in empiric or definitive antibiotic therapy were not associated with a difference in outcome. However, patients that did not receive any empiric antimicrobial therapy had increased mortality (3/5; 60% vs. 57/453; 13%; p = 0.018) as did those that did not receive definitive therapy (6/17; 35% vs. 54/441; 12%; p = 0.015). CONCLUSIONS: Delays in therapy were not associated with adverse outcomes although lack of active therapy was associated with increased mortality. A strategy for BSIs due to AE where β-lactam antibiotics (including oxyimino-cephalosporins) are used initially followed by a switch to non-β-lactam antibiotics once susceptibility results are available is effective.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 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".