Prescribing antibiotics to hospitalised patients increases the risk of <i>Clostridium difficile</i> infection for the next bed occupant
Bibliographic record
Abstract
Commentary on: Freedberg DE, Salmasian H, Cohen B, et al . Receipt of antibiotics in hospitalized patients and risk for Clostridium difficile infection in subsequent patients who occupy the same bed . JAMA Intern Med 2016;176:1801–8. Patients are at heightened risk of Clostridium difficile- associated disease when they are exposed to both the organism and to antibiotic treatments, which deplete their normal, diverse, protective gastrointestinal flora. Both of these factors are prevalent in healthcare facilities, and thus C. difficile is the most common and most burdensome hospital-acquired pathogen.1 The hazards of antibiotic use may extend beyond the individual patient. As ward-level antibiotic use increases, so too does an individual patient’s risk of C. difficile infection, even when he or she has not directly received antibiotics.2 In this study, Freedberg et al aim to provide perhaps the most direct evidence of the indirect hazards of antibiotic use on the risk of C. difficile —by testing whether antibiotic receipt by a …
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Observational | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".