Impact of a Reduction in the Use of High-Risk Antibiotics on the Course of an Epidemic of Clostridium difficile-Associated Disease Caused by the Hypervirulent NAP1/027 Strain
Bibliographic record
Abstract
A series of measures were implemented, in a secondary/tertiary-care hospital in Quebec, to control an epidemic of nosocomial Clostridium difficile-associated disease (n-CDAD) caused by a virulent strain; these measures included the development of a nonrestrictive antimicrobial stewardship program. Interrupted time-series analysis was used to evaluate the impact of these measures on n-CDAD incidence. From 2003-2004 to 2005-2006, total and targeted antibiotic consumption, respectively, decreased by 23% and 54%, and the incidence of n-CDAD decreased by 60%. No change in n-CDAD incidence was noted after strengthening of infection control procedures (P=.63), but implementation of the antimicrobial stewardship program was followed by a marked reduction in incidence (P=.007). This suggests that nonrestrictive measures to optimize antibiotic usage can yield exceptional results when physicians are motivated and that such measures should be a mandatory component of n-CDAD control. The inefficacy of infection control measures targeting transmission through hospital personnel might be a result of their implementation late in the epidemic, when the environment was heavily contaminated with spores.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".