Clostridium difficile-Associated Diarrhea Outbreaks: The Name of the Game Is Isolation and Cleaning
Bibliographic record
Abstract
Sir—We read with interest the article by Pépin et al. [1], which reports that use of quinolones is a major risk factor for illness during an outbreak of Clostridium difficile—associated diarrhea (CDAD). These results confirm previous observations that quinolones and other antibiotics, such as third-generation cephalosporins, macrolides, broad-spectrum β-lactams, and aminoglycosides, are important risk factors for CDAD [2, 3]. However, in addition to instating and/or following policies regarding antibiotic use, other infection-control procedures—including environmental hygiene, washing hands with soap and water, and isolating patients who have CDAD—are critical to the prevention of the spread of this disease [4, 5]. This outbreak has also been affecting our institution and has even forced medical units to be closed for varying lengths of time [6]. Interestingly, our institution does not have any respiratory quinolones on formulary and only uses ciprofloxacin. The fact that most patients are naive to treatment with respiratory quinolones leads us to believe that other factors have played a role in this outbreak.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.055 | 0.028 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".