Risk Factors for the Transmission of Methicillin‐Resistant<i>Staphylococcus aureus</i>in an Adult Intensive Care Unit: Fitting a Model to the Data
Bibliographic record
Abstract
Little is known about the amount of cross-transmission, the risk factors for infection, and the relative effectiveness of infection control procedures when methicillin-resistant Staphylococcus aureus (MRSA) infection occurs at highly endemic levels in intensive care units. A cohort study was done to identify exposures associated with cases that likely were the result of cross-transmission (i.e., occurring in clusters and with indistinguishable MRSA macrorestriction profiles). Fitting a simple stochastic model to the ascertained data allowed prediction of the effectiveness of infection control measures. Exposure to relative staff deficit (adjusted rate ratio, 1.05 independent; 95% confidence interval, 1.02-1.09) was the only factor significantly associated with potential transmission (P =.001). It was predicted that a 12% improvement in adherence to hand-hygiene policies might have compensated for staff shortage and prevented transmission during periods of overcrowding, shared care, and high workload but that this would be hard to achieve.
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".